A meteorologically driven grain sorghum stress indicator model

NASA Technical Reports Server (NTRS)

Taylor, T. W.; Ravet, F. W. (Principal Investigator)

1981-01-01

A grain sorghum soil moisture and temperature stress model is described. It was developed to serve as a meteorological data filter to alert commodity analysts to potential stress conditions and crop phenology in selected grain sorghum production areas. The model also identifies optimum conditions on a daily basis and planting/harvest problems associated with poor tractability.

The phenology of leaf quality and its within-canopy variation is essential for accurate modeling of photosynthesis in tropical evergreen forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Jin; Serbin, Shawn P.; Xu, Xiangtao

Leaf quantity (i.e., canopy leaf area index, LAI), quality (i.e., per-area photosynthetic capacity), and longevity all influence the photosynthetic seasonality of tropical evergreen forests. However, these components of tropical leaf phenology are poorly represented in most terrestrial biosphere models (TBMs). Here in this paper, we explored alternative options for the representation of leaf phenology effects in TBMs that employ the Farquahar, von Caemmerer & Berry (FvCB) representation of CO 2 assimilation. We developed a two-fraction leaf (sun and shade), two-layer canopy (upper and lower) photosynthesis model to evaluate different modeling approaches and assessed three components of phenological variations (i.e., leafmore » quantity, quality, and within-canopy variation in leaf longevity). Our model was driven by the prescribed seasonality of leaf quantity and quality derived from ground-based measurements within an Amazonian evergreen forest. Modeled photosynthetic seasonality was not sensitive to leaf quantity, but was highly sensitive to leaf quality and its vertical distribution within the canopy, with markedly more sensitivity to upper canopy leaf quality. This is because light absorption in tropical canopies is near maximal for the entire year, implying that seasonal changes in LAI have little impact on total canopy light absorption; and because leaf quality has a greater effect on photosynthesis of sunlit leaves than light limited, shade leaves and sunlit foliage are more abundant in the upper canopy. Our two-fraction leaf, two-layer canopy model, which accounted for all three phenological components, was able to simulate photosynthetic seasonality, explaining ~90% of the average seasonal variation in eddy covariance-derived CO 2 assimilation. This work identifies a parsimonious approach for representing tropical evergreen forest photosynthetic seasonality in TBMs that utilize the FvCB model of CO 2 assimilation and highlights the importance of incorporating more realistic phenological mechanisms in models that seek to improve the projection of future carbon dynamics in tropical evergreen forests.« less

The phenology of leaf quality and its within-canopy variation is essential for accurate modeling of photosynthesis in tropical evergreen forests

DOE PAGES

Wu, Jin; Serbin, Shawn P.; Xu, Xiangtao; ...

2017-04-18

Leaf quantity (i.e., canopy leaf area index, LAI), quality (i.e., per-area photosynthetic capacity), and longevity all influence the photosynthetic seasonality of tropical evergreen forests. However, these components of tropical leaf phenology are poorly represented in most terrestrial biosphere models (TBMs). Here in this paper, we explored alternative options for the representation of leaf phenology effects in TBMs that employ the Farquahar, von Caemmerer & Berry (FvCB) representation of CO 2 assimilation. We developed a two-fraction leaf (sun and shade), two-layer canopy (upper and lower) photosynthesis model to evaluate different modeling approaches and assessed three components of phenological variations (i.e., leafmore » quantity, quality, and within-canopy variation in leaf longevity). Our model was driven by the prescribed seasonality of leaf quantity and quality derived from ground-based measurements within an Amazonian evergreen forest. Modeled photosynthetic seasonality was not sensitive to leaf quantity, but was highly sensitive to leaf quality and its vertical distribution within the canopy, with markedly more sensitivity to upper canopy leaf quality. This is because light absorption in tropical canopies is near maximal for the entire year, implying that seasonal changes in LAI have little impact on total canopy light absorption; and because leaf quality has a greater effect on photosynthesis of sunlit leaves than light limited, shade leaves and sunlit foliage are more abundant in the upper canopy. Our two-fraction leaf, two-layer canopy model, which accounted for all three phenological components, was able to simulate photosynthetic seasonality, explaining ~90% of the average seasonal variation in eddy covariance-derived CO 2 assimilation. This work identifies a parsimonious approach for representing tropical evergreen forest photosynthetic seasonality in TBMs that utilize the FvCB model of CO 2 assimilation and highlights the importance of incorporating more realistic phenological mechanisms in models that seek to improve the projection of future carbon dynamics in tropical evergreen forests.« less

Impacts of phenology on estimation of actual evapotranspiration with VegET model

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Henebry, G. M.

2009-12-01

The VegET model provides spatially explicit estimation of actual evapotranspiration (AET). Currently, it uses a climatology based on AVHRR NDVI image time series to modulate fluxes during growing seasons (Senay 2008). This step simplifies the model formulation, but it also introduces errors by ignoring the interannual variation in phenology. We report on a study to evaluate the effects of using an NDVI climatology in VegET rather than current season values. Using flux tower data from three sites across the US Corn Belt, we found that currently the model overestimates the duration of season. With the standard deviation of more than one week, the model results in an additional 50 to 70 mm of AET per season, which can account for about 10% of seasonal AET in drier western sites. The model showed only modest sensitivity to variation in growing season weather. This lack of sensitivity greatly decreased model accuracy during drought years: Pearson correlation coefficients between model estimates and observed values dropped from about 0.7 to 0.5, depending on vegetation type. We also evaluated an alternative approach to drive the canopy component of evapotranspiration, the Event Driven Phenology Model (EDPM). The parameterization of VegET with EDPM-simulated canopy dynamics improved the correlation by 0.1 or more and reduced the RMSE on daily AET estimates by 0.3 mm. By accounting for the progress of phenology during a particular growing season, the EDPM improves AET estimation over an NDVI climatology.

Phase-dependent outbreak dynamics of geometrid moth linked to host plant phenology.

PubMed

Jepsen, Jane U; Hagen, Snorre B; Karlsen, Stein-Rune; Ims, Rolf A

2009-12-07

Climatically driven Moran effects have often been invoked as the most likely cause of regionally synchronized outbreaks of insect herbivores without identifying the exact mechanism. However, the degree of match between host plant and larval phenology is crucial for the growth and survival of many spring-feeding pest insects, suggesting that a phenological match/mismatch-driven Moran effect may act as a synchronizing agent. We analyse the phase-dependent spatial dynamics of defoliation caused by cyclically outbreaking geometrid moths in northern boreal birch forest in Fennoscandia through the most recent massive outbreak (2000-2008). We use satellite-derived time series of the prevalence of moth defoliation and the onset of the growing season for the entire region to investigate the link between the patterns of defoliation and outbreak spread. In addition, we examine whether a phase-dependent coherence in the pattern of spatial synchrony exists between defoliation and onset of the growing season, in order to evaluate if the degree of matching phenology between the moth and their host plant could be the mechanism behind a Moran effect. The strength of regional spatial synchrony in defoliation and the pattern of defoliation spread were both highly phase-dependent. The incipient phase of the outbreak was characterized by high regional synchrony in defoliation and long spread distances, compared with the epidemic and crash phase. Defoliation spread was best described using a two-scale stratified spread model, suggesting that defoliation spread is governed by two processes operating at different spatial scale. The pattern of phase-dependent spatial synchrony was coherent in both defoliation and onset of the growing season. This suggests that the timing of spring phenology plays a role in the large-scale synchronization of birch forest moth outbreaks.

Phase-dependent outbreak dynamics of geometrid moth linked to host plant phenology

PubMed Central

Jepsen, Jane U.; Hagen, Snorre B.; Karlsen, Stein-Rune; Ims, Rolf A.

2009-01-01

Climatically driven Moran effects have often been invoked as the most likely cause of regionally synchronized outbreaks of insect herbivores without identifying the exact mechanism. However, the degree of match between host plant and larval phenology is crucial for the growth and survival of many spring-feeding pest insects, suggesting that a phenological match/mismatch-driven Moran effect may act as a synchronizing agent. We analyse the phase-dependent spatial dynamics of defoliation caused by cyclically outbreaking geometrid moths in northern boreal birch forest in Fennoscandia through the most recent massive outbreak (2000–2008). We use satellite-derived time series of the prevalence of moth defoliation and the onset of the growing season for the entire region to investigate the link between the patterns of defoliation and outbreak spread. In addition, we examine whether a phase-dependent coherence in the pattern of spatial synchrony exists between defoliation and onset of the growing season, in order to evaluate if the degree of matching phenology between the moth and their host plant could be the mechanism behind a Moran effect. The strength of regional spatial synchrony in defoliation and the pattern of defoliation spread were both highly phase-dependent. The incipient phase of the outbreak was characterized by high regional synchrony in defoliation and long spread distances, compared with the epidemic and crash phase. Defoliation spread was best described using a two-scale stratified spread model, suggesting that defoliation spread is governed by two processes operating at different spatial scale. The pattern of phase-dependent spatial synchrony was coherent in both defoliation and onset of the growing season. This suggests that the timing of spring phenology plays a role in the large-scale synchronization of birch forest moth outbreaks. PMID:19740876

Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006

USGS Publications Warehouse

White, M.A.; de Beurs, K. M.; Didan, K.; Inouye, D.W.; Richardson, A.D.; Jensen, O.P.; O'Keefe, J.; Zhang, G.; Nemani, R.R.; van, Leeuwen; Brown, Jesslyn F.; de Wit, A.; Schaepman, M.; Lin, X.; Dettinger, M.; Bailey, A.S.; Kimball, J.; Schwartz, M.D.; Baldocchi, D.D.; Lee, J.T.; Lauenroth, W.K.

2009-01-01

Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by ±60 days and in standard deviation by ±20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.

Modelling of the spring phenological phases of the Silver birch Betula pendula and Bird cherry Padus racemosa in Baltic region

NASA Astrophysics Data System (ADS)

Kalvāns, Andis; Kalvāne, Gunta; Bitāne, Māra; Cepīte-Frišfelde, Daiga; Sīle, Tija; Seņņikovs, Juris

2014-05-01

The air temperature is the strongest driving factor of the plant development during spring time in moderate climate conditions. However other factors such as the air temperature during the dormancy period and light conditions can play a role as well. The full potential of the recent and historical phenological observation data can be utilised by modelling tools. We have calibrated seven phenological models described in scientific literature to calculate the likely dates leaf unfolding and start of flowering of the Silver birch Betula pendula and bird cherry Padus racemosa (Kalvāns at al, accepted). Phenological observations are derived from voluntary observation network for period 1960-2009 in Latvia. The number of used observations for each phase range from 149 to 172. Air temperature data measured in meteorological stations closest to the corresponding phenological observation sites are obtained from Latvian Environment, Geology and Meteorology Centre. We used 33 random data subsamples for model calibration to produce a range of model coefficients enabling the estimation of the phenological model uncertainty. It is found that the best reproduction of the observational data are obtained using a simple linear degree day model considering daily minimum and maximum temperature and more complex sigmoidal model honouring the need for low temperatures for dormancy release (UniChill, Chuine, 2000). The median calibration base temperature in the degree day model for the silver birch leaf unfolding is 5.6°C and for start of the flowering 6.7°C; for the bird cherry the corresponding base temperatures are 3.2°C and 3.4°C. The calibrated models and air temperature archive data derived from the Danish Meteorological Institute is used to simulate the respective phase onset in the Estonia, Latvia and Lithuania in 2009. Significant regional differences between modelled phase onset times are observed. There is a wide regional variation of the model uncertainty as well, indicated by the confidence intervals calculated from the 33 model calibrations: in some regions all the coefficient sets give similar phase onset times (within two to three day interval) while on other cases the spread can be more than a weak. In the spring 2014 field campaign is planned to obtain considerable data set for leaf unfolding and start of flowering of the bird cherry in Estonia, Latvia and Lithuania. The data will be used to evaluate performance of phenological models driven by short, medium and long term air temperature forecasts. The research is supported by the European Union through the European Social Fund Mobilitas grant No MJD309. References Chuine, I. (2000). A unified model for budburst of trees. Journal of theoretical biology, 207 (3), 337-347 Kalvāns, A., Bitāne, M., Kalvāne, G., accepted. Forecasting plant phenology: evaluating the phenological models for Betula pendula and Padus racemosa spring phases, Latvia. International Journal of Biometeorology, accepted.

Moisture-driven xylogenesis in Pinus ponderosa from a Mojave Desert mountain reveals high phenological plasticity.

PubMed

Ziaco, Emanuele; Truettner, Charles; Biondi, Franco; Bullock, Sarah

2018-04-01

Future seasonal dynamics of wood formation in hyperarid environments are still unclear. Although temperature-driven extension of the growing season and increased forest productivity are expected for boreal and temperate biomes under global warming, a similar trend remains questionable in water-limited regions. We monitored cambial activity in a montane stand of ponderosa pine (Pinus ponderosa) from the Mojave Desert for 2 consecutive years (2015-2016) showing opposite-sign anomalies between warm- and cold-season precipitation. After the wet winter/spring of 2016, xylogenesis started 2 months earlier compared to 2015, characterized by abundant monsoonal (July-August) rainfall and hyperarid spring. Tree size did not influence the onset and ending of wood formation, highlighting a predominant climatic control over xylem phenological processes. Moisture conditions in the previous month, in particular soil water content and dew point, were the main drivers of cambial phenology. Latewood formation started roughly at the same time in both years; however, monsoonal precipitation triggered the formation of more false rings and density fluctuations in 2015. Because of uncertainties in future precipitation patterns simulated by global change models for the Southwestern United States, the dependency of P. ponderosa on seasonal moisture implies a greater conservation challenge than for species that respond mostly to temperature conditions. © 2018 John Wiley & Sons Ltd.

Contribution of Phenological and Physiological Variations on Northern Vegetation Productivity Changes over Last Three Decades

NASA Technical Reports Server (NTRS)

Ganguly, Sangram

2015-01-01

Plant phenology and maximum photosynthetic state determine spatiotemporal variability of gross primary productivity (GPP) of vegetation. Recent warming induced impacts accelerate shifts of phenology and physiological status over Northern vegetated land. Thus, understanding and quantifying these changes are very important. Here, we investigate 1) how vegetation phenology and physiological status (maximum photosynthesis) are evolved over last three decades and 2) how such components (phenology and physiological status) contribute on inter-annual variation of the GPP during the last three decades. We utilized both long-term remotely sensed (GIMMS (Global Inventory Modeling and Mapping Studies), NDVI3g (Normalized Difference Vegetation Index 3rd generation) and MODIS (Moderate Resolution Imaging Spectroradiometer)) to extract larger scale phenology metrics (growing season start, end and duration); and productivity (i.e., growing season integrated vegetation index, GSIVI) to answer these questions. For evaluation purpose, we also introduced field-measured phenology and productivity datasets (e.g., FLUXNET) and possible remotely-sensed and modeled metrics at continental and regional scales. From this investigation, we found that onset of the growing season has advanced by 1.61 days per decade and the growing season end has delayed by 0.67 days per decade over the circumpolar region. This asymmetric extension of growing season results in a longer growing-season trend (2.96 days per decade) and widespread increasing vegetation-productivity trend (2.96 GSIVI per decade) over Northern land. However, the regionally-diverged phenology shift and maximum photosynthetic state contribute differently characterized productivity, inter-annual variability and trend. We quantified that about 50 percent, 13 percent and 6.5 percent of Northern land's inter-annual variability are dominantly controlled by the onset of the growing season, the end of the growing season and the maximum photosynthetic state, respectively. Productivity characterization over the other approximately 30 percent region has been driven by these co-dominant drivers. Our study clearly shows that regionally different contribution of phenological and physiological components on characterizing vegetation production over the last three decades.

Shenandoah National Park Phenology Project-Weather data collection, description, and processing

USGS Publications Warehouse

Jones, John W.; Aiello, Danielle P.; Osborne, Jesse D.

2010-01-01

The weather data described in this document are being collected as part of a U.S. Geological Survey (USGS) study of changes in Shenandoah National Park (SNP) landscape phenology (Jones and Osbourne, 2008). Phenology is the study of the timing of biological events, such as annual plant flowering and seasonal bird migration. These events are partially driven by changes in temperature and precipitation; therefore, phenology studies how these events may reflect changes in climate. Landscape phenology is the study of changes in biological events over broad areas and assemblages of vegetation. To study climate-change relations over broad areas (at landscape scale), the timing and amount of annual tree leaf emergence, maximum foliage, and leaf fall for forested areas are of interest. To better link vegetation changes with climate, weather data are necessary. This report documents weather-station data collection and processing procedures used in the Shenandoah National Park Phenology Project.

Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests.

PubMed

Xu, Xiangtao; Medvigy, David; Powers, Jennifer S; Becknell, Justin M; Guan, Kaiyu

2016-10-01

We assessed whether diversity in plant hydraulic traits can explain the observed diversity in plant responses to water stress in seasonally dry tropical forests (SDTFs). The Ecosystem Demography model 2 (ED2) was updated with a trait-driven mechanistic plant hydraulic module, as well as novel drought-phenology and plant water stress schemes. Four plant functional types were parameterized on the basis of meta-analysis of plant hydraulic traits. Simulations from both the original and the updated ED2 were evaluated against 5 yr of field data from a Costa Rican SDTF site and remote-sensing data over Central America. The updated model generated realistic plant hydraulic dynamics, such as leaf water potential and stem sap flow. Compared with the original ED2, predictions from our novel trait-driven model matched better with observed growth, phenology and their variations among functional groups. Most notably, the original ED2 produced unrealistically small leaf area index (LAI) and underestimated cumulative leaf litter. Both of these biases were corrected by the updated model. The updated model was also better able to simulate spatial patterns of LAI dynamics in Central America. Plant hydraulic traits are intercorrelated in SDTFs. Mechanistic incorporation of plant hydraulic traits is necessary for the simulation of spatiotemporal patterns of vegetation dynamics in SDTFs in vegetation models. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Networked web-cameras monitor congruent seasonal development of birches with phenological field observations

NASA Astrophysics Data System (ADS)

Peltoniemi, Mikko; Aurela, Mika; Böttcher, Kristin; Kolari, Pasi; Loehr, John; Karhu, Jouni; Kubin, Eero; Linkosalmi, Maiju; Melih Tanis, Cemal; Nadir Arslan, Ali

2017-04-01

Ecosystems' potential to provide services, e.g. to sequester carbon is largely driven by the phenological cycle of vegetation. Timing of phenological events is required for understanding and predicting the influence of climate change on ecosystems and to support various analyses of ecosystem functioning. We established a network of cameras for automated monitoring of phenological activity of vegetation in boreal ecosystems of Finland. Cameras were mounted on 14 sites, each site having 1-3 cameras. In this study, we used cameras at 11 of these sites to investigate how well networked cameras detect phenological development of birches (Betula spp.) along the latitudinal gradient. Birches are interesting focal species for the analyses as they are common throughout Finland. In our cameras they often appear in smaller quantities within dominant species in the images. Here, we tested whether small scattered birch image elements allow reliable extraction of color indices and changes therein. We compared automatically derived phenological dates from these birch image elements to visually determined dates from the same image time series, and to independent observations recorded in the phenological monitoring network from the same region. Automatically extracted season start dates based on the change of green color fraction in the spring corresponded well with the visually interpreted start of season, and field observed budburst dates. During the declining season, red color fraction turned out to be superior over green color based indices in predicting leaf yellowing and fall. The latitudinal gradients derived using automated phenological date extraction corresponded well with gradients based on phenological field observations from the same region. We conclude that already small and scattered birch image elements allow reliable extraction of key phenological dates for birch species. Devising cameras for species specific analyses of phenological timing will be useful for explaining variation of time series of satellite based indices, and it will also benefit models describing ecosystem functioning at species or plant functional type level. With the contribution of the LIFE+ financial instrument of the European Union (LIFE12 ENV/FI/000409 Monimet, http://monimet.fmi.fi)

Effects of changing climate and cultivar on the phenology and yield of winter wheat in the North China Plain

NASA Astrophysics Data System (ADS)

Li, Kenan; Yang, Xiaoguang; Tian, Hanqin; Pan, Shufen; Liu, Zhijuan; Lu, Shuo

2016-01-01

Understanding how changing climate and cultivars influence crop phenology and potential yield is essential for crop adaptation to future climate change. In this study, crop and daily weather data collected from six sites across the North China Plain were used to drive a crop model to analyze the impacts of climate change and cultivar development on the phenology and production of winter wheat from 1981 to 2005. Results showed that both the growth period (GP) and the vegetative growth period (VGP) decreased during the study period, whereas changes in the reproductive growth period (RGP) either increased slightly or had no significant trend. Although new cultivars could prolong the winter wheat phenology (0.3˜3.8 days per decade for GP), climate warming impacts were more significant and mainly accounted for the changes. The harvest index and kernel number per stem weight have significantly increased. Model simulation indicated that the yield of winter wheat exhibited increases (5.0˜19.4 %) if new cultivars were applied. Climate change demonstrated a negative effect on winter wheat yield as suggested by the simulation driven by climate data only (-3.3 to -54.8 kg ha-1 year-1, except for Lushi). Results of this study also indicated that winter wheat cultivar development can compensate for the negative effects of future climatic change.

Effects of changing climate and cultivar on the phenology and yield of winter wheat in the North China Plain.

PubMed

Li, Kenan; Yang, Xiaoguang; Tian, Hanqin; Pan, Shufen; Liu, Zhijuan; Lu, Shuo

2016-01-01

Understanding how changing climate and cultivars influence crop phenology and potential yield is essential for crop adaptation to future climate change. In this study, crop and daily weather data collected from six sites across the North China Plain were used to drive a crop model to analyze the impacts of climate change and cultivar development on the phenology and production of winter wheat from 1981 to 2005. Results showed that both the growth period (GP) and the vegetative growth period (VGP) decreased during the study period, whereas changes in the reproductive growth period (RGP) either increased slightly or had no significant trend. Although new cultivars could prolong the winter wheat phenology (0.3∼3.8 days per decade for GP), climate warming impacts were more significant and mainly accounted for the changes. The harvest index and kernel number per stem weight have significantly increased. Model simulation indicated that the yield of winter wheat exhibited increases (5.0∼19.4%) if new cultivars were applied. Climate change demonstrated a negative effect on winter wheat yield as suggested by the simulation driven by climate data only (-3.3 to -54.8 kg ha(-1) year(-1), except for Lushi). Results of this study also indicated that winter wheat cultivar development can compensate for the negative effects of future climatic change.

First-year Progress and Future Directions of the USA National Phenology Network

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; Losleben, M. V.

2008-12-01

Background Periodic plant and animal cycles driven by seasonal variations in climate (i.e., phenology) set the stage for dynamics of ecosystem processes, determine land surface properties, control biosphere-atmosphere interactions, and affect food production, health, conservation, and recreation. Phenological data and models have applications related to scientific research, education and outreach, as well as to stakeholders interested in agriculture, tourism and recreation, human health, and natural resource conservation and management. The predictive potential of phenology requires a new data resource-a national network of integrated phenological observations and the tools to access and analyze them at multiple scales. The USA National Phenology Network (USA-NPN) is an emerging and exciting partnership between federal agencies, the academic community, and the general public to monitor and understand the influence of seasonal cycles on the Nation's resources. The USA-NPN will establish a wall-to-wall science and monitoring initiative focused on phenology as a tool to understand how plants, animals and landscapes respond to climate variation, and as a tool to facilitate human adaptation to ongoing and potential future climate change. Results The National Coordinating Office of the USA-NPN began operation in August 2007 at the University of Arizona, Tucson, AZ. This first year of operation produced many new phenology products and venues for phenology research and citizen involvement, as well as identification of future directions for the USA NPN. Products include a new web-site (www.usanpn.org) that went live in June 2008; the web-site includes a tool for on-line data entry, and serves as a clearinghouse for products and information to facilitate research and communication related to phenology. The new core Plant Phenology Program includes profiles for 185 vetted local, regional, and national plant species with descriptions and monitoring protocols, as well as templates for addition of new species. A partnership program describes how other monitoring networks can engage with USA-NPN to collect, manage or disseminate phenological information for science, health, education, management or predictive service applications. Project BudBurst, a USA-NPN field campaign for citizen scientists, went live in February 2008, and now includes over 3000 registered observers monitoring 4000 plants across the nation. For 2009 and beyond, we will initiate a new Wildlife Phenology Program, create an on-line clearing-house for phenology education and outreach, strengthen our national land surface phenology program, and improve tools for data entry, download and visualization.

Phenological shifts conserve thermal niches in North American birds and reshape expectations for climate-driven range shifts.

PubMed

Socolar, Jacob B; Epanchin, Peter N; Beissinger, Steven R; Tingley, Morgan W

2017-12-05

Species respond to climate change in two dominant ways: range shifts in latitude or elevation and phenological shifts of life-history events. Range shifts are widely viewed as the principal mechanism for thermal niche tracking, and phenological shifts in birds and other consumers are widely understood as the principal mechanism for tracking temporal peaks in biotic resources. However, phenological and range shifts each present simultaneous opportunities for temperature and resource tracking, although the possible role for phenological shifts in thermal niche tracking has been widely overlooked. Using a canonical dataset of Californian bird surveys and a detectability-based approach for quantifying phenological signal, we show that Californian bird communities advanced their breeding phenology by 5-12 d over the last century. This phenological shift might track shifting resource peaks, but it also reduces average temperatures during nesting by over 1 °C, approximately the same magnitude that average temperatures have warmed over the same period. We further show that early-summer temperature anomalies are correlated with nest success in a continental-scale database of bird nests, suggesting avian thermal niches might be broadly limited by temperatures during nesting. These findings outline an adaptation surface where geographic range and breeding phenology respond jointly to constraints imposed by temperature and resource phenology. By stabilizing temperatures during nesting, phenological shifts might mitigate the need for range shifts. Global change ecology will benefit from further exploring phenological adjustment as a potential mechanism for thermal niche tracking and vice versa.

Advances in the Use of In Situ Flux Tower Measures of Canopy Structure and Function for Evaluation of MODIS and VIIRS Vegetation Indices and Phenology

NASA Astrophysics Data System (ADS)

Huete, A. R.; Ma, X.; Devadas, R.; Miura, T.; Obata, K.; Restrepo-Coupe, N.; Kato, A.

2016-12-01

Prior studies have linked tower-based measures of ecosystem productivity (GEP) and satellite vegetation indices (VIs) over primarily phenologically driven ecosystems. In situ flux towers are advantageous for satellite product assessments due to their comparable footprints and finer temporal resolution measurements. However, weaker relationships have been reported in meteorological driven ecosystems in which satellite and flux tower measures of productivity are asynchronous. This suggests that satellite derived biophysical measures are not a measure of GEP, but rather a proxy for ecosystem structure (e.g. LAI) and function. Here we investigate the use of flux tower measures of photosynthetic infrastructure, including photosynthetic capacity and light use efficiency, as more appropriate measures for the evaluation of satellite VI products and phenology. We related MODIS and VIIRS VIs (NDVI, EVI, EVI2) and phenology over a series of flux tower sites located across a climatically-diverse north to south gradient in central Australia, encompassing wet and dry subtropcal savannas, semi-arid shrub/grass, and temperate broadleaf evergreen forests. These represented environmental conditions where phenology and meteorology are not always synchronized. Our objectives were to (1) advance the use of in situ tower data for more accurate evaluation of satellite products and assess challenges and limitations of in situ tower networks; (2) intercompare cross-sensor VI products and derived phenology with tower measures across biomes to assess consistencies; and (3) better understand satellite and tower relationships to improve upon interpretation of satellite VI and phenology data. Our results show, that in contrast to measures of GEP, our measures of photosynthetic infrastructure were much better related to satellite VIs; they removed strong hysteresis influences on VI- productivity relationships across phenologic green-up and brown-down phases; and thus were better related to satellite phenology profiles. We conclude that flux tower networks offer a valuable source of in situ and consistent data that can be used for satellite time series continuity and cross sensor studies. This can also bring forward the validation of vegetation indices beyond simple reflectance-based accuracy assessments.

Modeling winter wheat phenological responses to water deficits in the Unified Plant Growth Model (UPGM) component of the spatially distributed Agricultural Ecosystem Services (AgES) model

USDA-ARS?s Scientific Manuscript database

Accurately predicting phenology in crop simulation models is critical for correctly simulating crop production. While extensive work in modeling phenology has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses t...

Asynchrony in host and parasite phenology may decrease disease risk in livestock under climate warming: Nematodirus battus in lambs as a case study.

PubMed

Gethings, Owen J; Rose, Hannah; Mitchell, Siân; Van Dijk, Jan; Morgan, Eric R

2015-09-01

Mismatch in the phenology of trophically linked species as a result of climate warming has been shown to have far-reaching effects on animal communities, but implications for disease have so far received limited attention. This paper presents evidence suggestive of phenological asynchrony in a host-parasite system arising from climate change, with impacts on transmission. Diagnostic laboratory data on outbreaks of infection with the pathogenic nematode Nematodirus battus in sheep flocks in the UK were used to validate region-specific models of the effect of spring temperature on parasite transmission. The hatching of parasite eggs to produce infective larvae is driven by temperature, while the availability of susceptible hosts depends on lambing date, which is relatively insensitive to inter-annual variation in spring temperature. In southern areas and in warmer years, earlier emergence of infective larvae in spring was predicted, with decline through mortality before peak availability of susceptible lambs. Data confirmed model predictions, with fewer outbreaks recorded in those years and regions. Overlap between larval peaks and lamb availability was not reduced in northern areas, which experienced no decreases in the number of reported outbreaks. Results suggest that phenological asynchrony arising from climate warming may affect parasite transmission, with non-linear but predictable impacts on disease burden. Improved understanding of complex responses of host-parasite systems to climate change can contribute to effective adaptation of parasite control strategies.

A sub-canopy structure for simulating oil palm in the Community Land Model (CLM-Palm): phenology, allocation and yield

NASA Astrophysics Data System (ADS)

Fan, Y.; Roupsard, O.; Bernoux, M.; Le Maire, G.; Panferov, O.; Kotowska, M. M.; Knohl, A.

2015-11-01

In order to quantify the effects of forests to oil palm conversion occurring in the tropics on land-atmosphere carbon, water and energy fluxes, we develop a new perennial crop sub-model CLM-Palm for simulating a palm plant functional type (PFT) within the framework of the Community Land Model (CLM4.5). CLM-Palm is tested here on oil palm only but is meant of generic interest for other palm crops (e.g., coconut). The oil palm has monopodial morphology and sequential phenology of around 40 stacked phytomers, each carrying a large leaf and a fruit bunch, forming a multilayer canopy. A sub-canopy phenological and physiological parameterization is thus introduced so that each phytomer has its own prognostic leaf growth and fruit yield capacity but with shared stem and root components. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, separated by a thermal period. An important phenological phase is identified for the oil palm - the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization and leaf pruning are represented. Parameters introduced for the oil palm were calibrated and validated with field measurements of leaf area index (LAI), yield and net primary production (NPP) from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched notably well between simulation and observation (mean percentage error = 3 %). Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites and sufficiently represent the significant nitrogen- and age-related site-to-site variability in NPP and yield. Results also indicate that seasonal dynamics of yield and remaining small-scale site-to-site variability of NPP are driven by processes not yet implemented in the model or reflected in the input data. The new sub-canopy structure and phenology and allocation functions in CLM-Palm allow exploring the effects of tropical land-use change, from natural ecosystems to oil palm plantations, on carbon, water and energy cycles and regional climate.

Evaluation of the Event Driven Phenology Model Coupled with the VegET Evapotranspiration Model Through Comparisons with Reference Datasets in a Spatially Explicit Manner

NASA Technical Reports Server (NTRS)

Kovalskyy, V.; Henebry, G. M.; Adusei, B.; Hansen, M.; Roy, D. P.; Senay, G.; Mocko, D. M.

2011-01-01

A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and VegET coupling scheme, assuring its potential for spatially explicit applications.

Shorebird migration in the face of climate change: potential shifts in migration phenology and resource availability

USGS Publications Warehouse

Stutzman, Ryan J.; Fontaine, Joseph J

2015-01-01

Changes in temperature and seasonality resulting from climate change are heterogeneous, potentially altering important sources of natural selection acting on species phenology. Some species have apparently adapted to climate change but the ability of most species to adapt remains unknown. The life history strategies of migratory animals are dictated by seasonal factors, which makes these species particularly vulnerable to heterogeneous changes in climate and phenology. Here, we examine the phenology of migratory shorebirds, their habitats, and primary food resources, and we hypothesize how climate change may affect migrants through predicted changes in phenology. Daily abundance of shorebirds at stopover sites was correlated with local phenology and peaked immediately prior to peaks in invertebrate food resources. A close relationship between migrant and invertebrate phenology indicates that shorebirds may be vulnerable to changes in seasonality driven by climate change. It is possible that shifts in migrant and invertebrate phenology will be congruent in magnitude and direction, but because migration phenology is dependent on a suite of ecological factors, any response is likely to occur at a larger temporal scale and may lag behind the response of invertebrate food resources. The resulting lack of sufficient access to food at stopover habitats may cause migrants to extend migration and have cascading effects throughout their life cycle. If the heterogeneous nature of climate change results in uneven changes in phenology between migrants and their prey, it may threaten the long-term viability of migratory populations

Comparison of phenology models for predicting the onset of growing season over the Northern Hemisphere.

PubMed

Fu, Yang; Zhang, Haicheng; Dong, Wenjie; Yuan, Wenping

2014-01-01

Vegetation phenology models are important for examining the impact of climate change on the length of the growing season and carbon cycles in terrestrial ecosystems. However, large uncertainties in present phenology models make accurate assessment of the beginning of the growing season (BGS) a challenge. In this study, based on the satellite-based phenology product (i.e. the V005 MODIS Land Cover Dynamics (MCD12Q2) product), we calibrated four phenology models, compared their relative strength to predict vegetation phenology; and assessed the spatial pattern and interannual variability of BGS in the Northern Hemisphere. The results indicated that parameter calibration significantly influences the models' accuracy. All models showed good performance in cool regions but poor performance in warm regions. On average, they explained about 67% (the Growing Degree Day model), 79% (the Biome-BGC phenology model), 73% (the Number of Growing Days model) and 68% (the Number of Chilling Days-Growing Degree Day model) of the BGS variations over the Northern Hemisphere. There were substantial differences in BGS simulations among the four phenology models. Overall, the Biome-BGC phenology model performed best in predicting the BGS, and showed low biases in most boreal and cool regions. Compared with the other three models, the two-phase phenology model (NCD-GDD) showed the lowest correlation and largest biases with the MODIS phenology product, although it could catch the interannual variations well for some vegetation types. Our study highlights the need for further improvements by integrating the effects of water availability, especially for plants growing in low latitudes, and the physiological adaptation of plants into phenology models.

Comparison of Phenology Models for Predicting the Onset of Growing Season over the Northern Hemisphere

PubMed Central

Fu, Yang; Zhang, Haicheng; Dong, Wenjie; Yuan, Wenping

2014-01-01

Vegetation phenology models are important for examining the impact of climate change on the length of the growing season and carbon cycles in terrestrial ecosystems. However, large uncertainties in present phenology models make accurate assessment of the beginning of the growing season (BGS) a challenge. In this study, based on the satellite-based phenology product (i.e. the V005 MODIS Land Cover Dynamics (MCD12Q2) product), we calibrated four phenology models, compared their relative strength to predict vegetation phenology; and assessed the spatial pattern and interannual variability of BGS in the Northern Hemisphere. The results indicated that parameter calibration significantly influences the models' accuracy. All models showed good performance in cool regions but poor performance in warm regions. On average, they explained about 67% (the Growing Degree Day model), 79% (the Biome-BGC phenology model), 73% (the Number of Growing Days model) and 68% (the Number of Chilling Days-Growing Degree Day model) of the BGS variations over the Northern Hemisphere. There were substantial differences in BGS simulations among the four phenology models. Overall, the Biome-BGC phenology model performed best in predicting the BGS, and showed low biases in most boreal and cool regions. Compared with the other three models, the two-phase phenology model (NCD-GDD) showed the lowest correlation and largest biases with the MODIS phenology product, although it could catch the interannual variations well for some vegetation types. Our study highlights the need for further improvements by integrating the effects of water availability, especially for plants growing in low latitudes, and the physiological adaptation of plants into phenology models. PMID:25279567

Biases in simulation of the rice phenology models when applied in warmer climates

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, T.; Yang, X.; Simelton, E.

2015-12-01

The current model inter-comparison studies highlight the difference in projections between crop models when they are applied to warmer climates, but these studies do not provide results on how the accuracy of the models would change in these projections because the adequate observations under largely diverse growing season temperature (GST) are often unavailable. Here, we investigate the potential changes in the accuracy of rice phenology models when these models were applied to a significantly warmer climate. We collected phenology data from 775 trials with 19 cultivars in 5 Asian countries (China, India, Philippines, Bangladesh and Thailand). Each cultivar encompasses the phenology observations under diverse GST regimes. For a given rice cultivar in different trials, the GST difference reaches 2.2 to 8.2°C, which allows us to calibrate the models under lower GST and validate under higher GST (i.e., warmer climates). Four common phenology models representing major algorithms on simulations of rice phenology, and three model calibration experiments were conducted. The results suggest that the bilinear and beta models resulted in gradually increasing phenology bias (Figure) and double yield bias per percent increase in phenology bias, whereas the growing-degree-day (GDD) and exponential models maintained a comparatively constant bias when applied in warmer climates (Figure). Moreover, the bias of phenology estimated by the bilinear and beta models did not reduce with increase in GST when all data were used to calibrate models. These suggest that variations in phenology bias are primarily attributed to intrinsic properties of the respective phenology model rather than on the calibration dataset. Therefore we conclude that using the GDD and exponential models has more chances of predicting rice phenology correctly and thus, production under warmer climates, and result in effective agricultural strategic adaptation to and mitigation of climate change.

Photoperiod and temperature responses of bud swelling and bud burst in four temperate forest tree species.

PubMed

Basler, David; Körner, Christian

2014-04-01

Spring phenology of temperate forest trees is optimized to maximize the length of the growing season while minimizing the risk of freezing damage. The release from winter dormancy is environmentally mediated by species-specific responses to temperature and photoperiod. We investigated the response of early spring phenology to temperature and photoperiod at different stages of dormancy release in cuttings from four temperate tree species in controlled environments. By tracking bud development, we were able to identify the onset of bud swelling and bud growth in Acer pseudoplatanus L., Fagus sylvatica L., Quercus petraea (Mattuschka) Liebl. and Picea abies (L.) H. Karst. At a given early stage of dormancy release, the onset and duration of the bud swelling prior to bud burst are driven by concurrent temperature and photoperiod, while the maximum growth rate is temperature dependent only, except for Fagus, where long photoperiods also increased bud growth rates. Similarly, the later bud burst was controlled by temperature and photoperiod (in the photoperiod sensitive species Fagus, Quercus and Picea). We conclude that photoperiod is involved in the release of dormancy during the ecodormancy phase and may influence bud burst in trees that have experienced sufficient chilling. This study explored and documented the early bud swelling period that precedes and defines later phenological stages such as canopy greening in conventional phenological works. It is the early bud growth resumption that needs to be understood in order to arrive at a causal interpretation and modelling of tree phenology at a large scale. Classic spring phenology events mark visible endpoints of a cascade of processes as evidenced here.

Leaf Phenology of Amazonian Canopy Trees as Revealed by Spectral and Physiochemical Measurements

NASA Astrophysics Data System (ADS)

Chavana-Bryant, C.; Gerard, F. F.; Malhi, Y.; Enquist, B. J.; Asner, G. P.

2013-12-01

The phenological dynamics of terrestrial ecosystems reflect the response of the Earth's biosphere to inter- and intra-annual dynamics of climatic and hydrological regimes. Some Dynamic Global Vegetation Models (GDVMs) have predicted that by 2050 the Amazon rainforest will begin to dieback (Cox et al. 2000, Nature) or that the ecosystem will become unsustainable (Salazar et al. 2007, GRL). One major component in DGVMs is the simulation of vegetation phenology, however, modelers are challenged with the estimation of tropical phenology which is highly complex. Current modeled phenology is based on observations of temperate vegetation and accurate representation of tropical phenology is long overdue. Remote sensing (RS) data are a key tool in monitoring vegetation dynamics at regional and global scales. Of the many RS techniques available, time-series analysis of vegetation indices (VIs) has become the most common approach in monitoring vegetation phenology (Samanta et al. 2010, GRL; Bradley et al. 2011, GCB). Our research focuses on investigating the influence that age related variation in the spectral reflectance and physiochemical properties of leaves may have on VIs of tropical canopies. In order to do this, we collected a unique leaf and canopy phenological dataset at two different Amazonian sites: Inselberg, French Guyana (FG) and Tambopata, Peru (PE). Hyperspectral reflectance measurements were collected from 4,102 individual leaves sampled to represent different leaf ages and vertical canopy positions (top, mid and low canopy) from 20 different canopy tree species (8 in FG and 12 in PE). These leaf spectra were complemented with 1) leaf physical measurements: fresh and dry weight, area and thickness, LMA and LWC and 2) leaf chemical measurements: %N, %C, %P, C:N and d13C. Canopy level observations included top-of-canopy reflectance measurements obtained using a multispectral 16-band radiometer, leaf demography (tot. number and age distribution) and branch structural measurements (space between leaves, min. and max. season's growth and diameter) of two 1m branches harvested from each canopy level. Both leaf and canopy-level observations where collected monthly when trees where not in flush and weekly during the period of leaf flushing. Here, we present our leaf spectral and physiochemical results. Results show 1) changes in leaf spectral and physiochemical properties related to leaf age, 2) the most significant changes in the leaves' spectrum during different stages in their life cycle, and 3) how leaf spectral changes are related to changes in the chemical and physical properties of the leaves as they progress through their life cycle. Future work will involve the incorporation of leaf and canopy observations into a light canopy interaction model to investigate the possibility that seasonal variation in VIs may be driven by leaf aging as well as by the shedding or appearance of new leaves.

Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest.

PubMed

Wu, Jin; Kobayashi, Hideki; Stark, Scott C; Meng, Ran; Guan, Kaiyu; Tran, Ngoc Nguyen; Gao, Sicong; Yang, Wei; Restrepo-Coupe, Natalia; Miura, Tomoaki; Oliviera, Raimundo Cosme; Rogers, Alistair; Dye, Dennis G; Nelson, Bruce W; Serbin, Shawn P; Huete, Alfredo R; Saleska, Scott R

2018-03-01

Satellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun-sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite observations to study climate-phenology relationships in the tropics. No claim to original US Government works New Phytologist © 2017 New Phytologist Trust.

Disentangling climate change effects on species interactions: effects of temperature, phenological shifts, and body size.

PubMed

Rudolf, Volker H W; Singh, Manasvini

2013-11-01

Climate-mediated shifts in species' phenologies are expected to alter species interactions, but predicting the consequences of this is difficult because phenological shifts may be driven by different climate factors that may or may not be correlated. Temperature could be an important factor determining effects of phenological shifts by altering species' growth rates and thereby the relative size ratios of interacting species. We tested this hypothesis by independently manipulating temperature and the relative hatching phenologies of two competing amphibian species. Relative shifts in hatching time generally altered the strength of competition, but the presence and magnitude of this effect was temperature dependent and joint effects of temperature and hatching phenology were non-additive. Species that hatched relatively early or late performed significantly better or worse, respectively, but only at higher temperatures and not at lower temperatures. As a consequence, climate-mediated shifts in hatching phenology or temperature resulted in stronger or weaker effects than expected when both factors acted in concert. Furthermore, consequences of phenological shifts were asymmetric; arriving relatively early had disproportional stronger (or weaker) effects than arriving relatively late, and this varied with species identity. However, consistent with recent theory, these seemingly idiosyncratic effects of phenological shifts could be explained by species-specific differences in growth rates across temperatures and concordant shifts in relative body size of interacting species. Our results emphasize the need to account for environmental conditions when predicting the effects of phenological shifts, and suggest that shifts in size-structured interactions can mediate the impact of climate change on natural communities.

Phenological changes of the most commonly sampled ground beetle (Coleoptera: Carabidae) species in the UK environmental change network

NASA Astrophysics Data System (ADS)

Pozsgai, Gabor; Baird, John; Littlewood, Nick A.; Pakeman, Robin J.; Young, Mark R.

2018-03-01

Despite the important roles ground beetles (Coleoptera: Carabidae) play in ecosystems, the highly valued ecosystem services they provide, and ample descriptive documentation of their phenology, the relative impact of various environmental factors on carabid phenology is not well studied. Using the long-term pitfall trap capture data from 12 terrestrial Environmental Change Network (ECN) sites from the UK, we examined how changing climate influenced the phenology of common carabids, and the role particular climate components had on phenological parameters. Of the 28 species included in the analyses, 19 showed earlier start of their activity. This advance was particularly pronounced in the spring, supporting the view that early phenophases have a greater tendency to change and these changes are more directly controlled by temperature than later ones. Autumn activity extended only a few cases, suggesting a photoperiod-driven start of hibernation. No association was found between life-history traits and the ability of species to change their phenology. Air temperatures between April and June were the most important factors determining the start of activity of each species, whilst late season precipitation hastened the cessation of activity. The balance between the advantages and disadvantages of changing phenology on various levels is likely to depend on the species and even on local environmental criteria. The substantially changing phenology of Carabidae may influence their function in ecosystems and the ecosystem services they provide.

Phenological changes of the most commonly sampled ground beetle (Coleoptera: Carabidae) species in the UK environmental change network.

PubMed

Pozsgai, Gabor; Baird, John; Littlewood, Nick A; Pakeman, Robin J; Young, Mark R

2018-06-01

Despite the important roles ground beetles (Coleoptera: Carabidae) play in ecosystems, the highly valued ecosystem services they provide, and ample descriptive documentation of their phenology, the relative impact of various environmental factors on carabid phenology is not well studied. Using the long-term pitfall trap capture data from 12 terrestrial Environmental Change Network (ECN) sites from the UK, we examined how changing climate influenced the phenology of common carabids, and the role particular climate components had on phenological parameters. Of the 28 species included in the analyses, 19 showed earlier start of their activity. This advance was particularly pronounced in the spring, supporting the view that early phenophases have a greater tendency to change and these changes are more directly controlled by temperature than later ones. Autumn activity extended only a few cases, suggesting a photoperiod-driven start of hibernation. No association was found between life-history traits and the ability of species to change their phenology. Air temperatures between April and June were the most important factors determining the start of activity of each species, whilst late season precipitation hastened the cessation of activity. The balance between the advantages and disadvantages of changing phenology on various levels is likely to depend on the species and even on local environmental criteria. The substantially changing phenology of Carabidae may influence their function in ecosystems and the ecosystem services they provide.

Phenological changes of the most commonly sampled ground beetle (Coleoptera: Carabidae) species in the UK environmental change network

NASA Astrophysics Data System (ADS)

Pozsgai, Gabor; Baird, John; Littlewood, Nick A.; Pakeman, Robin J.; Young, Mark R.

2018-06-01

Despite the important roles ground beetles (Coleoptera: Carabidae) play in ecosystems, the highly valued ecosystem services they provide, and ample descriptive documentation of their phenology, the relative impact of various environmental factors on carabid phenology is not well studied. Using the long-term pitfall trap capture data from 12 terrestrial Environmental Change Network (ECN) sites from the UK, we examined how changing climate influenced the phenology of common carabids, and the role particular climate components had on phenological parameters. Of the 28 species included in the analyses, 19 showed earlier start of their activity. This advance was particularly pronounced in the spring, supporting the view that early phenophases have a greater tendency to change and these changes are more directly controlled by temperature than later ones. Autumn activity extended only a few cases, suggesting a photoperiod-driven start of hibernation. No association was found between life-history traits and the ability of species to change their phenology. Air temperatures between April and June were the most important factors determining the start of activity of each species, whilst late season precipitation hastened the cessation of activity. The balance between the advantages and disadvantages of changing phenology on various levels is likely to depend on the species and even on local environmental criteria. The substantially changing phenology of Carabidae may influence their function in ecosystems and the ecosystem services they provide.

Functional analysis of Normalized Difference Vegetation Index curves reveals overwinter mule deer survival is driven by both spring and autumn phenology

PubMed Central

Hurley, Mark A.; Hebblewhite, Mark; Gaillard, Jean-Michel; Dray, Stéphane; Taylor, Kyle A.; Smith, W. K.; Zager, Pete; Bonenfant, Christophe

2014-01-01

Large herbivore populations respond strongly to remotely sensed measures of primary productivity. Whereas most studies in seasonal environments have focused on the effects of spring plant phenology on juvenile survival, recent studies demonstrated that autumn nutrition also plays a crucial role. We tested for both direct and indirect (through body mass) effects of spring and autumn phenology on winter survival of 2315 mule deer fawns across a wide range of environmental conditions in Idaho, USA. We first performed a functional analysis that identified spring and autumn as the key periods for structuring the among-population and among-year variation of primary production (approximated from 1 km Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (NDVI)) along the growing season. A path analysis showed that early winter precipitation and direct and indirect effects of spring and autumn NDVI functional components accounted for 45% of observed variation in overwinter survival. The effect size of autumn phenology on body mass was about twice that of spring phenology, while direct effects of phenology on survival were similar between spring and autumn. We demonstrate that the effects of plant phenology vary across ecosystems, and that in semi-arid systems, autumn may be more important than spring for overwinter survival. PMID:24733951

Impact of vegetation feedback at subseasonal & seasonal timescales on precipitation over North America

NASA Astrophysics Data System (ADS)

Kim, Y.; Wang, G.

2006-05-01

Soil moisture-vegetation-precipitation feedbacks tend to enhance soil moisture memory in some areas of the globe, which contributes to the subseasonal and seasonal climate prediction skill. In this study, the impact of vegetation on precipitation over North America is investigated using a coupled land-atmosphere model CAM3- CLM3. The coupled model has been modified to include a predictive vegetation phenology scheme and validated against the MODIS data. Vegetation phenology is modeled by updating the leaf area index (LAI) daily in response to cumulative and concurrent hydrometeorological conditions. First, driven with the climatological SST, a large group of 5-member ensembles of simulations from the late spring and summer to the end of year are generated with the different initial conditions of soil moisture. The impact of initial soil moisture anomalies on subsequent precipitation is examined with the predictive vegetation phenology scheme disabled/enabled ("SM"/"SM_Veg" ensembles). The simulated climate differences between "SM" and "SM_Veg" ensembles represent the role of vegetation in soil moisture-vegetation- precipitation feedback. Experiments in this study focus on how the response of precipitation to initial soil moisture anomalies depends on their characteristics, including the timing, magnitude, spatial coverage and vertical depth, and further how it is modified by the interactive vegetation. Our results, for example, suggest that the impact of late spring soil moisture anomalies is not evident in subsequent precipitation until early summer when local convective precipitation dominates. With the summer wet soil moisture anomalies, vegetation tends to enhance the positive feedback between soil moisture and precipitation, while vegetation tends to suppress such positive feedback with the late spring anomalies. Second, the impact of vegetation feedback is investigated by driving the model with the inter-annually varying monthly SST (1983-1994). With the predictive vegetation phenology disabled/enabled ("SM"/"SM_Veg" ensembles), the simulated climates are compared with the observation. This will present the role of an interactive or predictive vegetation phenology scheme in subseasonal and seasonal climate prediction. Specifically, the extreme climate events such as drought in 1988 and flood in 1993 over the Midwestern United States will be the focus of results analyses.

Independent effects of warming and nitrogen addition on plant phenology in the Inner Mongolian steppe.

PubMed

Xia, Jianyang; Wan, Shiqiang

2013-06-01

Phenology is one of most sensitive traits of plants in response to regional climate warming. Better understanding of the interactive effects between warming and other environmental change factors, such as increasing atmosphere nitrogen (N) deposition, is critical for projection of future plant phenology. A 4-year field experiment manipulating temperature and N has been conducted in a temperate steppe in northern China. Phenology, including flowering and fruiting date as well as reproductive duration, of eight plant species was monitored and calculated from 2006 to 2009. Across all the species and years, warming significantly advanced flowering and fruiting time by 0·64 and 0·72 d per season, respectively, which were mainly driven by the earliest species (Potentilla acaulis). Although N addition showed no impact on phenological times across the eight species, it significantly delayed flowering time of Heteropappus altaicus and fruiting time of Agropyron cristatum. The responses of flowering and fruiting times to warming or N addition are coupled, leading to no response of reproductive duration to warming or N addition for most species. Warming shortened reproductive duration of Potentilla bifurca but extended that of Allium bidentatum, whereas N addition shortened that of A. bidentatum. No interactive effect between warming and N addition was found on any phenological event. Such additive effects could be ascribed to the species-specific responses of plant phenology to warming and N addition. The results suggest that the warming response of plant phenology is larger in earlier than later flowering species in temperate grassland systems. The effects of warming and N addition on plant phenology are independent of each other. These findings can help to better understand and predict the response of plant phenology to climate warming concurrent with other global change driving factors.

Dynamic Pulse-Driven Flowering Phenology in a Semiarid Shrubland

NASA Astrophysics Data System (ADS)

Krell, N.; Papuga, S. A.; Kipnis, E. L.; Nelson, K.

2014-12-01

Elevated springtime temperature has been convincingly linked to an increasingly earlier onset of phenological activity. Studies highlighting this phenomenon have generally been conducted in ecosystems where energy is the primary limiting factor. Importantly, phenological studies in semiarid ecosystems where water is the major limiting factor are rare. In semiarid ecosystems, the timing of phenological activity is also highly sensitive to discrete moisture pulses from infrequent precipitation events. The objective of this study is to identify the triggers of flowering phenology in a semiarid creosotebush-dominated ecosystem. Creosotebush (Larrea tridentata) is a repeat-flowering evergreen shrub that is the dominant species in three of the North American deserts. We present results from six years of daily meteorological and phenological data collected within the Santa Rita Experimental Range in southern Arizona. Our site is equipped with an eddy covariance tower providing estimates of water and carbon fluxes and associated meteorological variables including precipitation and soil moisture at multiple depths. Additionally, three digital cameras distributed within the footprint of the eddy provide daily images of phenological activity. Our results highlight substantial interannual variability in flowering phenology, both in spring and summer flowering. We show that spring flowering activity tends to be associated with energy triggers (e.g. temperature, growing degree days), whereas summer flowering activity tends to be associated with moisture triggers (e.g. large precipitation events, deep soil moisture). Our study suggests that changes in frequency and duration of precipitation events will impact timing of phenological activity resulting in important consequences for vegetation dynamics and pollinator behavior.

Incorporating variability in simulations of seasonally forced phenology using integral projection models

DOE PAGES

Goodsman, Devin W.; Aukema, Brian H.; McDowell, Nate G.; ...

2017-11-26

Phenology models are becoming increasingly important tools to accurately predict how climate change will impact the life histories of organisms. We propose a class of integral projection phenology models derived from stochastic individual-based models of insect development and demography. Our derivation, which is based on the rate summation concept, produces integral projection models that capture the effect of phenotypic rate variability on insect phenology, but which are typically more computationally frugal than equivalent individual-based phenology models. We demonstrate our approach using a temperature-dependent model of the demography of the mountain pine beetle (Dendroctonus ponderosae Hopkins), an insect that kills maturemore » pine trees. This work illustrates how a wide range of stochastic phenology models can be reformulated as integral projection models. Due to their computational efficiency, these integral projection models are suitable for deployment in large-scale simulations, such as studies of altered pest distributions under climate change.« less

Incorporating variability in simulations of seasonally forced phenology using integral projection models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goodsman, Devin W.; Aukema, Brian H.; McDowell, Nate G.

Phenology models are becoming increasingly important tools to accurately predict how climate change will impact the life histories of organisms. We propose a class of integral projection phenology models derived from stochastic individual-based models of insect development and demography. Our derivation, which is based on the rate summation concept, produces integral projection models that capture the effect of phenotypic rate variability on insect phenology, but which are typically more computationally frugal than equivalent individual-based phenology models. We demonstrate our approach using a temperature-dependent model of the demography of the mountain pine beetle (Dendroctonus ponderosae Hopkins), an insect that kills maturemore » pine trees. This work illustrates how a wide range of stochastic phenology models can be reformulated as integral projection models. Due to their computational efficiency, these integral projection models are suitable for deployment in large-scale simulations, such as studies of altered pest distributions under climate change.« less

Asynchronous vegetation phenology enhances winter body condition of a large mobile herbivore.

PubMed

Searle, Kate R; Rice, Mindy B; Anderson, Charles R; Bishop, Chad; Hobbs, N T

2015-10-01

Understanding how spatial and temporal heterogeneity influence ecological processes forms a central challenge in ecology. Individual responses to heterogeneity shape population dynamics, therefore understanding these responses is central to sustainable population management. Emerging evidence has shown that herbivores track heterogeneity in nutritional quality of vegetation by responding to phenological differences in plants. We quantified the benefits mule deer (Odocoileus hemionus) accrue from accessing habitats with asynchronous plant phenology in northwest Colorado over 3 years. Our analysis examined both the direct physiological and indirect environmental effects of weather and vegetation phenology on mule deer winter body condition. We identified several important effects of annual weather patterns and topographical variables on vegetation phenology in the home ranges of mule deer. Crucially, temporal patterns of vegetation phenology were linked with differences in body condition, with deer tending to show poorer body condition in areas with less asynchronous vegetation green-up and later vegetation onset. The direct physiological effect of previous winter precipitation on mule deer body condition was much less important than the indirect effect mediated by vegetation phenology. Additionally, the influence of vegetation phenology on body fat was much stronger than that of overall vegetation productivity. In summary, changing annual weather patterns, particularly in relation to seasonal precipitation, have the potential to alter body condition of this important ungulate species during the critical winter period. This finding highlights the importance of maintaining large contiguous areas of spatially and temporally variable resources to allow animals to compensate behaviourally for changing climate-driven resource patterns.

Linking patterns and processes of species diversification in the cone flies Strobilomyia (Diptera: Anthomyiidae).

PubMed

Sachet, Jean-Marie; Roques, Alain; Després, Laurence

2006-12-01

Phytophagous insects provide useful models for the study of ecological speciation. Much attention has been paid to host shifts, whereas situations where closely related lineages of insects use the same plant during different time periods have been relatively neglected in previous studies of insect diversification. Flies of the genus Strobilomyia are major pests of conifers in Eurasia and North America. They are specialized feeders in cones and seeds of Abies (fir), Larix (larch) ,and Picea (spruce). This close association is accompanied by a large number of sympatric Strobilomyia species coexisting within each tree genus. We constructed a molecular phylogeny with a 1320 base-pair fragment of mitochondrial DNA that demonstrated contrasting patterns of speciation in larch cone flies, as opposed to spruce and fir cone flies; this despite their comparable geographic distributions and similar resource quality of the host. Species diversity is the highest on larch, and speciation is primarily driven by within-host phenological shifts, followed by allopatric speciation during geographical expansion. By contrast, fewer species exploit spruce and fir, and within-host phenological shifts did not occur. This study illustrates within-host adaptive radiation through phenological shifts, a neglected mode of sympatric speciation.

Temperature fine-tunes Mediterranean Arabidopsis thaliana life-cycle phenology geographically.

PubMed

Marcer, A; Vidigal, D S; James, P M A; Fortin, M-J; Méndez-Vigo, B; Hilhorst, H W M; Bentsink, L; Alonso-Blanco, C; Picó, F X

2018-01-01

To understand how adaptive evolution in life-cycle phenology operates in plants, we need to unravel the effects of geographic variation in putative agents of natural selection on life-cycle phenology by considering all key developmental transitions and their co-variation patterns. We address this goal by quantifying the temperature-driven and geographically varying relationship between seed dormancy and flowering time in the annual Arabidopsis thaliana across the Iberian Peninsula. We used data on genetic variation in two major life-cycle traits, seed dormancy (DSDS50) and flowering time (FT), in a collection of 300 A. thaliana accessions from the Iberian Peninsula. The geographically varying relationship between life-cycle traits and minimum temperature, a major driver of variation in DSDS50 and FT, was explored with geographically weighted regressions (GWR). The environmentally varying correlation between DSDS50 and FT was analysed by means of sliding window analysis across a minimum temperature gradient. Maximum local adjustments between minimum temperature and life-cycle traits were obtained in the southwest Iberian Peninsula, an area with the highest minimum temperatures. In contrast, in off-southwest locations, the effects of minimum temperature on DSDS50 were rather constant across the region, whereas those of minimum temperature on FT were more variable, with peaks of strong local adjustments of GWR models in central and northwest Spain. Sliding window analysis identified a minimum temperature turning point in the relationship between DSDS50 and FT around a minimum temperature of 7.2 °C. Above this minimum temperature turning point, the variation in the FT/DSDS50 ratio became rapidly constrained and the negative correlation between FT and DSDS50 did not increase any further with increasing minimum temperatures. The southwest Iberian Peninsula emerges as an area where variation in life-cycle phenology appears to be restricted by the duration and severity of the hot summer drought. The temperature-driven varying relationship between DSDS50 and FT detected environmental boundaries for the co-evolution between FT and DSDS50 in A. thaliana. In the context of global warming, we conclude that A. thaliana phenology from the southwest Iberian Peninsula, determined by early flowering and deep seed dormancy, might become the most common life-cycle phenotype for this annual plant in the region. © 2017 German Botanical Society and The Royal Botanical Society of the Netherlands.

Characterizing phenological vegetation dynamics amidst extreme climate variability in Australia with MODIS VI data

NASA Astrophysics Data System (ADS)

Broich, M.; Huete, A. R.; Xuanlon, M.; Davies, K.; Restrepo-Coupe, N.; Ratana, P.

2012-12-01

Australia's climate is extremely variable with inter-annual rainfall at any given site varying by 5- or 6-fold or more, across the continent. In addition to such inter-annual variability, there can be significant intra-annual variability, especially in monsoonal Australia (e.g. the wet tropical savannas) and Mediterranean climates in SW Australia where prolonged dry seasons occur each year. This presents unique challenges to the characterization of seasonal dynamics with satellite datasets. In contrast to annual reoccurring temperature-driven phenology of northern hemisphere mid-latitudes, vegetation dynamics of the vast and dry Australian interior are poorly quantified by existing remote sensing products. For example, in the current global-based MODIS phenology product, central Australia is covered by ~30% fill values for any given year. Two challenges are specific to Australian landscapes: first, the difficulty of characterizing seasonality of rainfall-driven ecosystems in interior Australia where duration and magnitude of green-up and brown down cycles show high inter annual variability; second, modeling two phenologic layers, the trees and the grass in savannas were the trees are evergreen but the herbaceous understory varies with rainfall. Savannas cover >50% of Australia. Australia's vegetation and climate are different from other continents. A MODIS phenology product capable of characterizing vegetation dynamics across the continent is being developed in this research as part of the AusCover national expert network aiming to provide Australian biophysical remote sensing data time-series and continental-scale map products. These products aim to support the Terrestrial Ecosystem Research Network (TERN) serving ecosystem research in Australia. The MODIS land surface product for Australia first searches the entire time series of each Climate Modeling Grid pixel for low-high-low extreme point sequences. A double logistic function is then fit to each of these sequences allowing identification of growth periods with different magnitudes and durations anywhere in the time series. Results show that the highest absolute variability in peak greenness occurred in cropped areas while the highest relative variability (coefficient of variation) occurred in interior Australia particularly around Lake Eyre, the center of a closed drainage basin in the dry interior of the continent. Across the desert interior, the timing of the green-up onset and the peak greenness was correlated with the landfall of cyclones and the inland penetration and strength of the north Australian summer monsoon (represented by TRMM data). The variability of Australian land surface phenology magnitude and timing was found to be strongly correlated with the swings between La Nina and El Nino events. The information on vegetation dynamics represented here is critical for land surface, fuel accumulation, agricultural production, and permanent ecosystem change modeling in relation to climate trends. A unique research opportunity is provided by recent climate variability: in 2010 a persistent El Nino has given way to a strong two-year La Nina breaking a decade long drought that was followed by record-breaking rainfall across most of the continent and extensive flooding followed by sustained greening.

Similarities in butterfly emergence dates among populations suggest local adaptation to climate.

PubMed

Roy, David B; Oliver, Tom H; Botham, Marc S; Beckmann, Bjorn; Brereton, Tom; Dennis, Roger L H; Harrower, Colin; Phillimore, Albert B; Thomas, Jeremy A

2015-09-01

Phenology shifts are the most widely cited examples of the biological impact of climate change, yet there are few assessments of potential effects on the fitness of individual organisms or the persistence of populations. Despite extensive evidence of climate-driven advances in phenological events over recent decades, comparable patterns across species' geographic ranges have seldom been described. Even fewer studies have quantified concurrent spatial gradients and temporal trends between phenology and climate. Here we analyse a large data set (~129 000 phenology measures) over 37 years across the UK to provide the first phylogenetic comparative analysis of the relative roles of plasticity and local adaptation in generating spatial and temporal patterns in butterfly mean flight dates. Although populations of all species exhibit a plastic response to temperature, with adult emergence dates earlier in warmer years by an average of 6.4 days per °C, among-population differences are significantly lower on average, at 4.3 days per °C. Emergence dates of most species are more synchronised over their geographic range than is predicted by their relationship between mean flight date and temperature over time, suggesting local adaptation. Biological traits of species only weakly explained the variation in differences between space-temperature and time-temperature phenological responses, suggesting that multiple mechanisms may operate to maintain local adaptation. As niche models assume constant relationships between occurrence and environmental conditions across a species' entire range, an important implication of the temperature-mediated local adaptation detected here is that populations of insects are much more sensitive to future climate changes than current projections suggest. © 2015 The Authors. Global Change Biology published by John Wiley & Sons Ltd.

Comparison of Land Surface Phenology Detections from Geostationary (AHI) and Polar-orbiting (VIIRS) Sensors in Tropical Southeast Asia

NASA Astrophysics Data System (ADS)

Liu, L.; Zhang, X.

2017-12-01

Land surface phenology (LSP) is an important indicator of ecosystem response to global change and reflects the exchange of water, energy, and carbon between the land surface and the atmosphere. However, the extraction of LSP in tropical Southeast Asia is very challenging due to weak seasonal variation and frequent cloud commination during the vegetation growing season. The successful launch of Advanced Himawari Imager (AHI) onboard Himawari-8 geostationary satellite in October 2014 provides large opportunities to obtain cloud-free observations in daily time series data because it collects data every 10 minutes at a spatial resolution of 500m-2000 m. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard operational Suomi National Polar-orbiting Partnership (Suomi NPP) satellite provides global moderate-resolution (375-750 m) data once every day. To compare the capability of AHI and VIIRS observations to monitor LSP in frequently-cloud-covered tropical Southeast Asia, this research first extracted LSP metrics based on the time series of daily two-band enhanced vegetation index (EVI2) from AHI and VIIRS using a hybrid piecewise logistic model in 2015 and 2016. The daily AHI EVI2 was calculated from diurnal observations after EVI2 at every 10 minutes was angularly corrected using an empirical kernel-driven model to eliminate the effect caused by the varying sun-satellite geometry. Subsequently, we compared the phenological transition dates of greenup onset and dormancy onset retrieved from AHI and VIIRS data at both pixel level and country level. Finally, we assessed the influences of the quality of daily observation from AHI and VIIRS on the reconstruction of EVI2 time series and the retrievals of phenological dates.

Incorporating variability in simulations of seasonally forced phenology using integral projection models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goodsman, Devin W.; Aukema, Brian H.; McDowell, Nate G.

Phenology models are becoming increasingly important tools to accurately predict how climate change will impact the life histories of organisms. We propose a class of integral projection phenology models derived from stochastic individual-based models of insect development and demography.Our derivation, which is based on the rate-summation concept, produces integral projection models that capture the effect of phenotypic rate variability on insect phenology, but which are typically more computationally frugal than equivalent individual-based phenology models. We demonstrate our approach using a temperature-dependent model of the demography of the mountain pine beetle (Dendroctonus ponderosae Hopkins), an insect that kills mature pine trees.more » This work illustrates how a wide range of stochastic phenology models can be reformulated as integral projection models. Due to their computational efficiency, these integral projection models are suitable for deployment in large-scale simulations, such as studies of altered pest distributions under climate change.« less

PERPHECLIM ACCAF Project - Perennial fruit crops and forest phenology evolution facing climatic changes

NASA Astrophysics Data System (ADS)

Garcia de Cortazar-Atauri, Iñaki; Audergon, Jean Marc; Bertuzzi, Patrick; Anger, Christel; Bonhomme, Marc; Chuine, Isabelle; Davi, Hendrik; Delzon, Sylvain; Duchêne, Eric; Legave, Jean Michel; Raynal, Hélène; Pichot, Christian; Van Leeuwen, Cornelis; Perpheclim Team

2015-04-01

Phenology is a bio-indicator of climate evolutions. Measurements of phenological stages on perennial species provide actually significant illustrations and assessments of the impact of climate change. Phenology is also one of the main key characteristics of the capacity of adaptation of perennial species, generating questions about their consequences on plant growth and development or on fruit quality. Predicting phenology evolution and adaptative capacities of perennial species need to override three main methodological limitations: 1) existing observations and associated databases are scattered and sometimes incomplete, rendering difficult implementation of multi-site study of genotype-environment interaction analyses; 2) there are not common protocols to observe phenological stages; 3) access to generic phenological models platforms is still very limited. In this context, the PERPHECLIM project, which is funded by the Adapting Agriculture and Forestry to Climate Change Meta-Program (ACCAF) from INRA (French National Institute of Agronomic Research), has the objective to develop the necessary infrastructure at INRA level (observatories, information system, modeling tools) to enable partners to study the phenology of various perennial species (grapevine, fruit trees and forest trees). Currently the PERPHECLIM project involves 27 research units in France. The main activities currently developed are: define protocols and observation forms to observe phenology for various species of interest for the project; organizing observation training; develop generic modeling solutions to simulate phenology (Phenological Modelling Platform and modelling platform solutions); support in building research projects at national and international level; develop environment/genotype observation networks for fruit trees species; develop an information system managing data and documentation concerning phenology. Finally, PERPHECLIM project aims to build strong collaborations with public (Observatoire des Saisons) and private sector partners (technical institutes) in order to allow a more direct transfer of knowledge.

Why climate change will invariably alter selection pressures on phenology.

PubMed

Gienapp, Phillip; Reed, Thomas E; Visser, Marcel E

2014-10-22

The seasonal timing of lifecycle events is closely linked to individual fitness and hence, maladaptation in phenological traits may impact population dynamics. However, few studies have analysed whether and why climate change will alter selection pressures and hence possibly induce maladaptation in phenology. To fill this gap, we here use a theoretical modelling approach. In our models, the phenologies of consumer and resource are (potentially) environmentally sensitive and depend on two different but correlated environmental variables. Fitness of the consumer depends on the phenological match with the resource. Because we explicitly model the dependence of the phenologies on environmental variables, we can test how differential (heterogeneous) versus equal (homogeneous) rates of change in the environmental variables affect selection on consumer phenology. As expected, under heterogeneous change, phenotypic plasticity is insufficient and thus selection on consumer phenology arises. However, even homogeneous change leads to directional selection on consumer phenology. This is because the consumer reaction norm has historically evolved to be flatter than the resource reaction norm, owing to time lags and imperfect cue reliability. Climate change will therefore lead to increased selection on consumer phenology across a broad range of situations. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Examining spring and autumn phenology in a temperate deciduous urban woodlot

NASA Astrophysics Data System (ADS)

Yu, Rong

This dissertation is an intensive phenological study in a temperate deciduous urban woodlot over six consecutive years (2007-2012). It explores three important topics related to spring and autumn phenology, as well as ground and remote sensing phenology. First, it examines key climatic factors influencing spring and autumn phenology by conducting phenological observations four days a week and recording daily microclimate measurements. Second, it investigates the differences in phenological responses between an urban woodlot and a rural forest by employing comparative basswood phenological data. Finally, it bridges ground visual phenology and remote sensing derived phenological changes by using the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from the Moderate Resolution Imaging Spectro-radiometer (MODIS). The primary outcomes are as follows: 1) empirical spatial regression models for two dominant tree species - basswood and white ash - have been built and analyzed to detect spatial patterns and possible causes of phenological change; the results show that local urban settings significantly affect phenology; 2) empirical phenological progression models have been built for each species and the community as a whole to examine how phenology develops in spring and autumn; the results indicate that the critical factor influencing spring phenology is AGDD (accumulated growing degree-days) and for autumn phenology, ACDD (accumulated chilling degree-days) and day length; and 3) satellite derived phenological changes have been compared with ground visual community phenology in both spring and autumn seasons, and the results confirm that both NDVI and EVI depict vegetation dynamics well and therefore have corresponding phenological meanings.

Evaluation of land surface model representation of phenology: an analysis of model runs submitted to the NACP Interim Site Synthesis

NASA Astrophysics Data System (ADS)

Richardson, A. D.; Nacp Interim Site Synthesis Participants

2010-12-01

Phenology represents a critical intersection point between organisms and their growth environment. It is for this reason that phenology is a sensitive and robust integrator of the biological impacts of year-to-year climate variability and longer-term climate change on natural systems. However, it is perhaps equally important that phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating ecosystem processes, competitive interactions, and feedbacks to the climate system. Unfortunately, the phenological sub-models implemented in most state-of-the-art ecosystem models and land surface schemes are overly simplified. We quantified model errors in the representation of the seasonal cycles of leaf area index (LAI), gross ecosystem photosynthesis (GEP), and net ecosystem exchange of CO2. Our analysis was based on site-level model runs (14 different models) submitted to the North American Carbon Program (NACP) Interim Synthesis, and long-term measurements from 10 forested (5 evergreen conifer, 5 deciduous broadleaf) sites within the AmeriFlux and Fluxnet-Canada networks. Model predictions of the seasonality of LAI and GEP were unacceptable, particularly in spring, and especially for deciduous forests. This is despite an historical emphasis on deciduous forest phenology, and the perception that controls on spring phenology are better understood than autumn phenology. Errors of up to 25 days in predicting “spring onset” transition dates were common, and errors of up to 50 days were observed. For deciduous sites, virtually every model was biased towards spring onset being too early, and autumn senescence being too late. Thus, models predicted growing seasons that were far too long for deciduous forests. For most models, errors in the seasonal representation of deciduous forest LAI were highly correlated with errors in the seasonality of both GPP and NEE, indicating the importance of getting the underlying canopy dynamics correct. Most of the models in this comparison were unable to successfully predict the observed interannual variability in either spring or autumn transition dates. And, perhaps surprisingly, the seasonal cycles of models using phenology prescribed by remote sensing observations was, in general, no better than that that predicted by models with prognostic phenology. Reasons for the poor performance of both approaches will be discussed. These results highlight the need for improved understanding of the environmental controls on vegetation phenology. Existing models are unlikely to accurately predict future responses of phenology to climate change, and therefore will misrepresent the seasonality of key biosphere-atmosphere feedbacks and interactions in coupled model runs. New data sets, as for example from webcam-based monitoring networks (e.g. PhenoCam) or citizen science efforts (USA National Phenology Network) should prove valuable in this regard.

Independent effects of warming and nitrogen addition on plant phenology in the Inner Mongolian steppe

PubMed Central

Xia, Jianyang; Wan, Shiqiang

2013-01-01

Background and Aims Phenology is one of most sensitive traits of plants in response to regional climate warming. Better understanding of the interactive effects between warming and other environmental change factors, such as increasing atmosphere nitrogen (N) deposition, is critical for projection of future plant phenology. Methods A 4-year field experiment manipulating temperature and N has been conducted in a temperate steppe in northern China. Phenology, including flowering and fruiting date as well as reproductive duration, of eight plant species was monitored and calculated from 2006 to 2009. Key Results Across all the species and years, warming significantly advanced flowering and fruiting time by 0·64 and 0·72 d per season, respectively, which were mainly driven by the earliest species (Potentilla acaulis). Although N addition showed no impact on phenological times across the eight species, it significantly delayed flowering time of Heteropappus altaicus and fruiting time of Agropyron cristatum. The responses of flowering and fruiting times to warming or N addition are coupled, leading to no response of reproductive duration to warming or N addition for most species. Warming shortened reproductive duration of Potentilla bifurca but extended that of Allium bidentatum, whereas N addition shortened that of A. bidentatum. No interactive effect between warming and N addition was found on any phenological event. Such additive effects could be ascribed to the species-specific responses of plant phenology to warming and N addition. Conclusions The results suggest that the warming response of plant phenology is larger in earlier than later flowering species in temperate grassland systems. The effects of warming and N addition on plant phenology are independent of each other. These findings can help to better understand and predict the response of plant phenology to climate warming concurrent with other global change driving factors. PMID:23585496

Olive flowering phenology variation between different cultivars in Spain and Italy: modeling analysis

NASA Astrophysics Data System (ADS)

Garcia-Mozo, H.; Orlandi, F.; Galan, C.; Fornaciari, M.; Romano, B.; Ruiz, L.; Diaz de La Guardia, C.; Trigo, M. M.; Chuine, I.

2009-03-01

Phenology data are sensitive data to identify how plants are adapted to local climate and how they respond to climatic changes. Modeling flowering phenology allows us to identify the meteorological variables determining the reproductive cycle. Phenology of temperate of woody plants is assumed to be locally adapted to climate. Nevertheless, recent research shows that local adaptation may not be an important constraint in predicting phenological responses. We analyzed variations in flowering dates of Olea europaea L. at different sites of Spain and Italy, testing for a genetic differentiation of flowering phenology among olive varieties to estimate whether local modeling is necessary for olive or not. We build models for the onset and peak dates flowering in different sites of Andalusia and Puglia. Process-based phenological models using temperature as input variable and photoperiod as the threshold date to start temperature accumulation were developed to predict both dates. Our results confirm and update previous results that indicated an advance in olive onset dates. The results indicate that both internal and external validity were higher in the models that used the photoperiod as an indicator to start to cumulate temperature. The use of the unified model for modeling the start and peak dates in the different localities provides standardized results for the comparative study. The use of regional models grouping localities by varieties and climate similarities indicate that local adaptation would not be an important factor in predicting olive phenological responses face to the global temperature increase.

Wood phenology: from organ-scale processes to terrestrial ecosystem models

NASA Astrophysics Data System (ADS)

Delpierre, Nicolas; Guillemot, Joannès

2016-04-01

In temperate and boreal trees, a dormancy period prevents organ development during adverse climatic conditions. Whereas the phenology of leaves and flowers has received considerable attention, to date, little is known regarding the phenology of other tree organs such as wood, fine roots, fruits and reserve compounds. In this presentation, we review both the role of environmental drivers in determining the phenology of wood and the models used to predict its phenology in temperate and boreal forest trees. Temperature is a key driver of the resumption of wood activity in spring. There is no such clear dominant environmental cue involved in the cessation of wood formation in autumn, but temperature and water stress appear as prominent factors. We show that wood phenology is a key driver of the interannual variability of wood growth in temperate tree species. Incorporating representations of wood phenology in a terrestrial ecosystem model substantially improved the simulation of wood growth under current climate.

An integrated, indicator framework for assessing large-scale variations and change in seasonal timing and phenology (Invited)

NASA Astrophysics Data System (ADS)

Betancourt, J. L.; Weltzin, J. F.

2013-12-01

As part of an effort to develop an Indicator System for the National Climate Assessment (NCA), the Seasonality and Phenology Indicators Technical Team (SPITT) proposed an integrated, continental-scale framework for understanding and tracking seasonal timing in physical and biological systems. The framework shares several metrics with the EPA's National Climate Change Indicators. The SPITT framework includes a comprehensive suite of national indicators to track conditions, anticipate vulnerabilities, and facilitate intervention or adaptation to the extent possible. Observed, modeled, and forecasted seasonal timing metrics can inform a wide spectrum of decisions on federal, state, and private lands in the U.S., and will be pivotal for international efforts to mitigation and adaptation. Humans use calendars both to understand the natural world and to plan their lives. Although the seasons are familiar concepts, we lack a comprehensive understanding of how variability arises in the timing of seasonal transitions in the atmosphere, and how variability and change translate and propagate through hydrological, ecological and human systems. For example, the contributions of greenhouse warming and natural variability to secular trends in seasonal timing are difficult to disentangle, including earlier spring transitions from winter (strong westerlies) to summer (weak easterlies) patterns of atmospheric circulation; shifts in annual phasing of daily temperature means and extremes; advanced timing of snow and ice melt and soil thaw at higher latitudes and elevations; and earlier start and longer duration of the growing and fire seasons. The SPITT framework aims to relate spatiotemporal variability in surface climate to (1) large-scale modes of natural climate variability and greenhouse gas-driven climatic change, and (2) spatiotemporal variability in hydrological, ecological and human responses and impacts. The hierarchical framework relies on ground and satellite observations, and includes metrics of surface climate seasonality, seasonality of snow and ice, land surface phenology, ecosystem disturbance seasonality, and organismal phenology. Recommended metrics met the following requirements: (a) easily measured by day-of-year, number of days, or in the case of species migrations, by the latitude of the observation on a given date; (b) are observed or can be calculated across a high density of locations in many different regions of the U.S.; and (c) unambiguously describe both spatial and temporal variability and trends in seasonal timing that are climatically driven. The SPITT framework is meant to provide climatic and strategic guidance for the growth and application of seasonal timing and phenological monitoring efforts. The hope is that additional national indicators based on observed phenology, or evidence-based algorithms calibrated with observational data, will evolve with sustained and broad-scale monitoring of climatically sensitive species and ecological processes.

An Ecoinformatic Analysis of the Effect of Seasonal and Annual Variation in Temperature, Precipitation, and Solar Irradiance on Pollen Productivity in Two Neotropical Forests

NASA Astrophysics Data System (ADS)

Haselhorst, D. S.; Tcheng, D. K.; Moreno, J. E.; Punyasena, S. W.

2014-12-01

Observational data provide a powerful source of information for understanding the phenological response of tropical forests to a changing climate. Annual changes in mean temperature, precipitation, and solar irradiance, in part driven by ENSO cycles, provide a natural experiment. However, these time series are often relatively short (several years to several decades), the average climatic variability experienced in that timeframe is relatively small, and the corresponding response is therefore often very weak. As a result, standard statistical approaches may fail in detecting a biological response. We present an alternative ecoinformatic analysis that demonstrates the power of weak models in the discovery and interpretation of statistically significant signals in short, noisy, ecological time series. We developed a simple response prediction model that uses cross-validation to explore a landscape of models that correlate the phenological behavior of individual taxa (pollen production, flowering, fruiting) to seasonal and annual mean temperature, precipitation, and solar irradiance using multivariate linear regression. We use a sign slope sensitivity analysis of each linear model that tallies positive and negative slope counts of a taxon's phenological behavior to our environmental and null variables. We applied this analysis to pollen trap data collected from 1996 to 2006 from two lowland Panamanian forests, Barro Colorado Island and Parque National San Lorenzo. We also tested the performance of our predictive model using published data of annual flowering and fruiting from BCI to corroborate that our approach could reproduce previously published results on tropical phenology. Our results indicate that although the overall variation in temperature was 3.28 °C over the ten year period, pollen productivity at both sites was most consistently affected by changes in temperature. This result was replicated by the published BCI flower and fruit data, which also increased with increased temperatures, highlighting the significant influence of even subtle changes in temperature for tropical forest communities. We also observed that both pollen and fruit production were negatively correlated with precipitation, suggesting a mechanism for how climate may interfere with pollination success.

Connecting phenological predictions with population growth rates for mountain pine beetle, an outbreak insect

Treesearch

James A. Powell; Barbara J. Bentz

2009-01-01

It is expected that a significant impact of global warming will be disruption of phenology as environmental cues become disassociated from their selective impacts. However there are few, if any, models directly connecting phenology with population growth rates. In this paper we discuss connecting a distributional model describing mountain pine beetle phenology with a...

Nutrient status: a missing factor in phenological and pollen research?

PubMed Central

Jochner, Susanne; Höfler, Josef; Beck, Isabelle; Göttlein, Axel; Ankerst, Donna Pauler; Traidl-Hoffmann, Claudia; Menzel, Annette

2013-01-01

Phenology ranks among the best ecosystem processes for fingerprinting climate change since temperature explains a high percentage of the interannual or spatial variation in phenological onset dates. However, roles of other environmental variables, such as foliar nutrient concentrations, are far from adequately understood. This observational study examined the effects of air temperature and 11 nutrients on spring phenology of Betula pendula Roth (birch) along an urban–rural gradient in Munich, Germany, during the years 2010/2011. Moreover, the influence of temperature, nutrients, and air pollutants (NO2 and O3) on the amounts of pollen and catkin biomass in 2010 was evaluated. In addition to the influence of higher temperatures advancing phenological onset dates, higher foliar concentrations of potassium, boron, zinc, and calcium were statistically significantly linked to earlier onset dates. Since flushing of leaves is a turgor-driven process and all the influential nutrients are involved in cell extension, membrane function, and stability, there might be a reasonable physiological interpretation of the observed association. The amounts of pollen were negatively correlated with temperature, atmospheric NO2, and foliar iron concentration, suggesting that these variables restrict pollen production. The results of this study suggested an influence of nutritional status on both phenology and pollen production. The interaction of urbanization and climate change should be considered in the assessment of the impact of global warming on ecosystems and human health. PMID:23630329

Phase I of a National Phenological Assessment

NASA Astrophysics Data System (ADS)

Betancourt, J. L.; Henebry, G. M.

2009-12-01

Phenology is the gateway to climatic effects on both managed and unmanaged ecosystems. Adaptation to climatic variability and change will require integration of phenological data and models with climatic forecasts at seasonal to decadal timescales. We propose a scoping study to identify, formulate, and refine approaches to the first National Phenological Assessment (NPA) for the U.S. The NPA should be viewed as a data product of the USA-National Phenology Network that will help guide future phenological monitoring and research at the national level. We envision three main objectives for the first NPA: 1) Establish a suite of indicators of phenological change (IPCs) at regional to continental scales, following the Heinz Center model for such national assessments; 2) Using sufficiently long and broad-scale time series of IPCs and legacy phenological data, assess phenological responses to what many scientists are calling the early stages of anthropogenic climate change, specifically the abrupt advance in spring onset in the late 1970’s/early 1980’s 3) Project large-scale phenological changes into 21st Century using GCM and RCM model realizations. Toward this end we see the following tasks as critical preliminary work to plan the first NPA: a) Identify, evaluate, and refine IPCs based on indices developed from standard weather observations, streamflow and other hydrological observations (e.g., center of mass, lake freeze/thaw, etc.), plant and animal phenology observations from legacy datasets, remote sensing datastreams, flux tower observations, and GCM and RCM model realizations; b) Evaluate covariability between IPCs, legacy phenological data, and large-scale modes of climate variability to help detection and attribution of supposed secular trends and development of short and long-lead forecasts for phenological variations; c) identify, evaluate, and refine optimal methods for quantifying what constitutes significant statistical and ecological change in phenological indicators, given uncertainties in both data and methods and defined range of natural variability; d) identify, evaluate, and refine key questions of natural resource managers regarding phenological indicators for monitoring and adaptive management of habitats and wildlife, given the spectrum of management objectives on federal, state, and private lands.

On the uncertainty of phenological responses to climate change and its implication for terrestrial biosphere models

NASA Astrophysics Data System (ADS)

Migliavacca, M.; Sonnentag, O.; Keenan, T. F.; Cescatti, A.; O'Keefe, J.; Richardson, A. D.

2012-01-01

Phenology, the timing of recurring life cycle events, controls numerous land surface feedbacks to the climate systems through the regulation of exchanges of carbon, water and energy between the biosphere and atmosphere. Land surface models, however, are known to have systematic errors in the simulation of spring phenology, which potentially could propagate to uncertainty in modeled responses to future climate change. Here, we analyzed the Harvard Forest phenology record to investigate and characterize the sources of uncertainty in phenological forecasts and the subsequent impacts on model forecasts of carbon and water cycling in the future. Using a model-data fusion approach, we combined information from 20 yr of phenological observations of 11 North American woody species with 12 phenological models of different complexity to predict leaf bud-burst. The evaluation of different phenological models indicated support for spring warming models with photoperiod limitations and, though to a lesser extent, to chilling models based on the alternating model structure. We assessed three different sources of uncertainty in phenological forecasts: parameter uncertainty, model uncertainty, and driver uncertainty. The latter was characterized running the models to 2099 using 2 different IPCC climate scenarios (A1fi vs. B1, i.e. high CO2 emissions vs. low CO2 emissions scenario). Parameter uncertainty was the smallest (average 95% CI: 2.4 day century-1 for scenario B1 and 4.5 day century-1 for A1fi), whereas driver uncertainty was the largest (up to 8.4 day century-1 in the simulated trends). The uncertainty related to model structure is also large and the predicted bud-burst trends as well as the shape of the smoothed projections varied somewhat among models (±7.7 day century-1 for A1fi, ±3.6 day century-1 for B1). The forecast sensitivity of bud-burst to temperature (i.e. days bud-burst advanced per degree of warming) varied between 2.2 day °C-1 and 5.2 day °C-1 depending on model structure. We quantified the impact of uncertainties in bud-burst forecasts on simulated carbon and water fluxes using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of the seasonality of processes, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP) and evapotranspiration (ET) of 9.6% and 2.9% respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±2.0% for ET. For phenology models, differences among future climate scenarios represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, uncertainties related to model parameterization. The uncertainties we have quantified will affect the description of the seasonality of processes and in particular the simulation of carbon uptake by forest ecosystems, with a larger impact of uncertainties related to phenology model structure, followed by uncertainties related to phenological model parameterization.

Interannual Variations in Global Vegetation Phenology Derived from a Long Term AVHRR and MODIS Data Record

NASA Astrophysics Data System (ADS)

Zhang, X.; Friedl, M. A.; Yu, Y.

2013-12-01

Land surface phenology metrics are widely retrieved from satellite observations at regional and global scales, and have been shown to be valuable for monitoring terrestrial ecosystem dynamics in response to extreme climate events and predicting biological responses to future climate scenarios. While the response of spring vegetation greenup to climate warming at mid-to-high latitudes is well-documented, understanding of diverse phenological responses to climate change over entire growing cycles and at broad geographic scales is incomplete. Many studies assume that the timing of individual phenological indicators in responses to climate forcing is independent of phenological events that occur at other times during the growing season. In this paper we use a different strategy. Specifically, we hypothesize that integrating sequences of key phenological indicators across growing seasons provides a more effective way to capture long-term variation in phenology in response to climate change. To explore this hypothesis we use global land surface phenology metrics derived from the Version 3 Long Term Vegetation Index Products from Multiple Satellite Data Records data set to examine interannual variations and trends in global land surface phenology from 1982-2010. Using daily enhanced vegetation index (EVI) data at a spatial resolution of 0.05 degrees, we model the phenological trajectory for each individual pixel using piecewise logistic models. The modeled trajectories were then used to detect phenological indicators including the onset of greenness increase, the onset of greenness maximum, the onset of greenness decrease, the onset of greenness minimum, and the growing season length, among others at global scale. The quality of land surface phenology detection for individual pixels was calculated based on metrics that characterize the EVI quality and model fits in annual time series at each pixel. Phenological indicators characterized as having good quality were then used to detect interannual variation and long-term trends using linear and nonlinear trend analysis techniques.

Reverse engineering of legacy agricultural phenology modeling system

USDA-ARS?s Scientific Manuscript database

A program which implements predictive phenology modeling is a valuable tool for growers and scientists. Such a program was created in the late 1980's by the creators of general phenology modeling as proof of their techniques. However, this first program could not continue to meet the needs of the fi...

A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability

PubMed Central

Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.

2013-01-01

We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722

Divergent phenological and leaf gas exchange strategies of two competing tree species drive contrasting responses to drought at their altitudinal boundary.

PubMed

Fernández-de-Uña, Laura; Aranda, Ismael; Rossi, Sergio; Fonti, Patrick; Cañellas, Isabel; Gea-Izquierdo, Guillermo

2018-04-27

In Mediterranean mountains, Pinus sylvestris L. is expected to be displaced under a warming climate by more drought-tolerant species such as the sub-Mediterranean Quercus pyrenaica Willd. Understanding how environmental factors drive tree physiology and phenology is, therefore, essential to assess the effect of changing climatic conditions on the performance of these species and, ultimately, their distribution. We compared the cambial and leaf phenology and leaf gas exchange of Q. pyrenaica and P. sylvestris at their altitudinal boundary in Central Spain and assessed the environmental variables involved. Results indicate that P. sylvestris cambial phenology was more sensitive to weather conditions (temperature at the onset and water deficit at the end of the growing season) than Q. pyrenaica. On the other hand, Q. pyrenaica cambial and leaf phenology were synchronized and driven by photoperiod and temperatures. Pinus sylvestris showed lower photosynthetic nitrogen-use efficiency and higher intrinsic water-use efficiency than Q. pyrenaica as a result of a tighter stomatal control in response to summer dry conditions, despite its less negative midday leaf water potentials. These phenological and leaf gas exchange responses evidence a stronger sensitivity to drought of P. sylvestris than that of Q. pyrenaica, which may therefore hold a competitive advantage over P. sylvestris under the predicted increase in recurrence and intensity of drought events. On the other hand, both species could benefit from warmer springs through an advanced phenology, although this effect could be limited in Q. pyrenaica if it maintains a photoperiod control over the onset of xylogenesis.

[Comparison of the temperature-driven seasonality of campylobacteriosis and salmonellosis and the annual phenology of Eristalis tenax (Diptera: Syrphidae)].

PubMed

Trájer, Attila; Schoffhauzer, Judit

2016-04-03

Ambient temperature and the activity of Diptera species are the primary factors of the seasonality of bacterial enteral diseases. The authors analyzed the effect of the weekly mean ambient temperature on salmonellosis and campylobacteriosis incidence and the annual phenology of the potential vector Eristalis tenax. Weekly case number data of the period between 2004 and 2014 were derived from the Hungarian National Center for Epidemiology. European Climate Assessment Dataset was the source of the weekly mean temperature data for the grid overlapping Hungary. While in the case of campylobacteriosis weak correlation was found (r(2) = 0.39), salmonellosis showed strong correlation with mean temperature (r(2) = 0.71) using 8-weeks lag before the outbreak of the cases. Comparing the mean weekly incidence of campylobacteriosis and salmonellosis with the modeled weekly activity of Eristalis tenax it was found that vector Diptera species may influence the incidence of enteric diseases in late spring and summer, in July and August particularly.

Remote sensing data assimilation for a prognostic phenology model

Treesearch

R. Stockli; T. Rutishauser; D. Dragoni; J. O' Keefe; P. E. Thornton; M. Jolly; L. Lu; A. S. Denning

2008-01-01

Predicting the global carbon and water cycle requires a realistic representation of vegetation phenology in climate models. However most prognostic phenology models are not yet suited for global applications, and diagnostic satellite data can be uncertain and lack predictive power. We present a framework for data assimilation of Fraction of Photosynthetically Active...

Phenology of two interdependent traits in migratory birds in response to climate change.

PubMed

Kristensen, Nadiah Pardede; Johansson, Jacob; Ripa, Jörgen; Jonzén, Niclas

2015-05-22

In migratory birds, arrival date and hatching date are two key phenological markers that have responded to global warming. A body of knowledge exists relating these traits to evolutionary pressures. In this study, we formalize this knowledge into general mathematical assumptions, and use them in an ecoevolutionary model. In contrast to previous models, this study novelty accounts for both traits-arrival date and hatching date-and the interdependence between them, revealing when one, the other or both will respond to climate. For all models sharing the assumptions, the following phenological responses will occur. First, if the nestling-prey peak is late enough, hatching is synchronous with, and arrival date evolves independently of, prey phenology. Second, when resource availability constrains the length of the pre-laying period, hatching is adaptively asynchronous with prey phenology. Predictions for both traits compare well with empirical observations. In response to advancing prey phenology, arrival date may advance, remain unchanged, or even become delayed; the latter occurring when egg-laying resources are only available relatively late in the season. The model shows that asynchronous hatching and unresponsive arrival date are not sufficient evidence that phenological adaptation is constrained. The work provides a framework for exploring microevolution of interdependent phenological traits. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Modeling leaf phenology variation by groupings of species within and across ecosystems in northern Alaska

NASA Astrophysics Data System (ADS)

Euskirchen, E. S.; Carman, T. B.; McGuire, A. D.

2012-12-01

The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst and in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf-out, dynamic vegetation models simulated over a regional to global scale typically assume some average leaf-out for all of the species within an ecosystem. Here, we make use of air temperature records and observational data of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and ecotonal boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest. This implementation improves the timing of the onset of carbon uptake in the spring, permitting a more accurate assessment of the contribution of each grouping of species to ecosystem performance. Furthermore, this implementation provides a more nuanced perspective on light competition among species and across ecosystems. For example, in the shrub tundra, the sedges and grasses leaf-out before the shade-inducing willow and dwarf birch, thereby providing the sedges and grasses time to accumulate biomass before shading effects arise. Also in the shrub tundra, the forbs leaf-out last, and are therefore, more prone to shading impacts by the taller willow and dwarf birch shrubs. However, in the wet sedge and heath tundra ecosystems, the forbs leaf-out before the shrubs, and are therefore less prone to shading impacts early in the growing season. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape. These findings also demonstrate that high-latitude dynamic vegetation models should consider variation in leaf-out by groupings of species within and across ecosystems in order to provide more accurate projections of future plant distributions in Arctic regions.

Limited alpine climatic warming and modeled phenology advancement for three alpine species in the Northeast United States.

PubMed

Kimball, Kenneth D; Davis, Michael L; Weihrauch, Douglas M; Murray, Georgia L D; Rancourt, Kenneth

2014-09-01

• Most alpine plants in the Northeast United States are perennial and flower early in the growing season, extending their limited growing season. Concurrently, they risk the loss of reproductive efforts to late frosts. Quantifying long-term trends in northeastern alpine flower phenology and late-spring/early-summer frost risk is limited by a dearth of phenology and climate data, except for Mount Washington, New Hampshire (1916 m a.s.l.).• Logistic phenology models for three northeastern US alpine species (Diapensia lapponica, Carex bigelowii and Vaccinium vitis-idaea) were developed from 4 yr (2008-2011) of phenology and air temperature measurements from 12 plots proximate to Mount Washington's long-term summit meteorological station. Plot-level air temperature, the logistic phenology models, and Mount Washington's climate data were used to hindcast model yearly (1935-2011) floral phenology and frost damage risk for the focal species.• Day of year and air growing degree-days with threshold temperatures of -4°C (D. lapponica and C. bigelowii) and -2°C (V. vitis-idaea) best predicted flowering. Modeled historic flowering dates trended significantly earlier but the 77-yr change was small (1.2-2.1 d) and did not significantly increase early-flowering risk from late-spring/early-summer frost damage.• Modeled trends in phenological advancement and sensitivity for three northeastern alpine species are less pronounced compared with lower elevations in the region, and this small shift in flower timing did not increase risk of frost damage. Potential reasons for limited earlier phenological advancement at higher elevations include a slower warming trend and increased cloud exposure with elevation and/or inadequate chilling requirements. © 2014 Botanical Society of America, Inc.

Learning the Rhythm of the Seasons in the Face of Global Change: Phenological Research in the 21st Century

NASA Technical Reports Server (NTRS)

Morisette, Jeffrey T.; Richardson, Andrew D.; Knapp, Alan K.; Fisher, Jeremy I.; Graham, Eric A.; Abatzoglou, John; Wilson, Bruce E.; Breshears, David D.; Hanebry, Geoffrey M.; Hanes, Jonathan M.;

Ungulate reproductive parameters track satellite observations of plant phenology across latitude and climatological regimes

USGS Publications Warehouse

Stoner, David; Sexton, Joseph O.; Nagol, Jyoteshwar; Bernales, Heather H.; Edwards, Thomas C.

2016-01-01

The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primary productivity. Interannual variation in weather influences the quality and timing of forage availability, which can influence neonatal survival. Here, we evaluated macro-scale patterns in reproductive performance of a widely distributed ungulate (mule deer, Odocoileus hemionus) across contrasting climatological regimes using satellite-derived indices of primary productivity and plant phenology over eight degrees of latitude (890 km) in the American Southwest. The dataset comprised > 180,000 animal observations taken from 54 populations over eight years (2004–2011). Regionally, both the start and peak of growing season (“Start” and “Peak”, respectively) are negatively and significantly correlated with latitude, an unusual pattern stemming from a change in the dominance of spring snowmelt in the north to the influence of the North American Monsoon in the south. Corresponding to the timing and variation in both the Start and Peak, mule deer reproduction was latest, lowest, and most variable at lower latitudes where plant phenology is timed to the onset of monsoonal moisture. Parturition dates closely tracked the growing season across space, lagging behind the Start and preceding the Peak by 27 and 23 days, respectively. Mean juvenile production increased, and variation decreased, with increasing latitude. Temporally, juvenile production was best predicted by primary productivity during summer, which encompassed late pregnancy, parturition, and early lactation. Our findings offer a parsimonious explanation of two key reproductive parameters in ungulate demography, timing of parturition and mean annual production, across latitude and changing climatological regimes. Practically, this demonstrates the potential for broad-scale modeling of couplings between climate, plant phenology, and animal populations using space-borne observations.

Ungulate Reproductive Parameters Track Satellite Observations of Plant Phenology across Latitude and Climatological Regimes

PubMed Central

Stoner, David C.; Sexton, Joseph O.; Nagol, Jyoteshwar; Bernales, Heather H.; Edwards, Thomas C.

2016-01-01

The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primary productivity. Interannual variation in weather influences the quality and timing of forage availability, which can influence neonatal survival. Here, we evaluated macro-scale patterns in reproductive performance of a widely distributed ungulate (mule deer, Odocoileus hemionus) across contrasting climatological regimes using satellite-derived indices of primary productivity and plant phenology over eight degrees of latitude (890 km) in the American Southwest. The dataset comprised > 180,000 animal observations taken from 54 populations over eight years (2004–2011). Regionally, both the start and peak of growing season (“Start” and “Peak”, respectively) are negatively and significantly correlated with latitude, an unusual pattern stemming from a change in the dominance of spring snowmelt in the north to the influence of the North American Monsoon in the south. Corresponding to the timing and variation in both the Start and Peak, mule deer reproduction was latest, lowest, and most variable at lower latitudes where plant phenology is timed to the onset of monsoonal moisture. Parturition dates closely tracked the growing season across space, lagging behind the Start and preceding the Peak by 27 and 23 days, respectively. Mean juvenile production increased, and variation decreased, with increasing latitude. Temporally, juvenile production was best predicted by primary productivity during summer, which encompassed late pregnancy, parturition, and early lactation. Our findings offer a parsimonious explanation of two key reproductive parameters in ungulate demography, timing of parturition and mean annual production, across latitude and changing climatological regimes. Practically, this demonstrates the potential for broad-scale modeling of couplings between climate, plant phenology, and animal populations using space-borne observations. PMID:26849642

Ungulate Reproductive Parameters Track Satellite Observations of Plant Phenology across Latitude and Climatological Regimes.

PubMed

Stoner, David C; Sexton, Joseph O; Nagol, Jyoteshwar; Bernales, Heather H; Edwards, Thomas C

2016-01-01

The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primary productivity. Interannual variation in weather influences the quality and timing of forage availability, which can influence neonatal survival. Here, we evaluated macro-scale patterns in reproductive performance of a widely distributed ungulate (mule deer, Odocoileus hemionus) across contrasting climatological regimes using satellite-derived indices of primary productivity and plant phenology over eight degrees of latitude (890 km) in the American Southwest. The dataset comprised > 180,000 animal observations taken from 54 populations over eight years (2004-2011). Regionally, both the start and peak of growing season ("Start" and "Peak", respectively) are negatively and significantly correlated with latitude, an unusual pattern stemming from a change in the dominance of spring snowmelt in the north to the influence of the North American Monsoon in the south. Corresponding to the timing and variation in both the Start and Peak, mule deer reproduction was latest, lowest, and most variable at lower latitudes where plant phenology is timed to the onset of monsoonal moisture. Parturition dates closely tracked the growing season across space, lagging behind the Start and preceding the Peak by 27 and 23 days, respectively. Mean juvenile production increased, and variation decreased, with increasing latitude. Temporally, juvenile production was best predicted by primary productivity during summer, which encompassed late pregnancy, parturition, and early lactation. Our findings offer a parsimonious explanation of two key reproductive parameters in ungulate demography, timing of parturition and mean annual production, across latitude and changing climatological regimes. Practically, this demonstrates the potential for broad-scale modeling of couplings between climate, plant phenology, and animal populations using space-borne observations.

The influence of meteorological conditions on the progress and dynamics of pollen phenophases of selected species.

NASA Astrophysics Data System (ADS)

Jatczak, K.; Linkowska, J.; Rapiejko, P.

2010-09-01

In Poland phenological data is used mainly as a natural indicator of the influence of climate changes on environment. In relation to the growing interest of phenology in scientific research, we substantially extended observation ranges, concentrating mainly on phenophases of selected species that are important for allergology. Phenological data application in complex analysis together with meteorological and aerobiological data, give an opportunity for drawing conclusions on variability of the starting date of pollen season and its dynamics in a meteorological aspect. Species have their regional phenological characteristics, however the characteristics depends on meteorological conditions in a particular year. Therefore, the calculation of pheno-meteorological parameters is important for pollen release prediction. Availability of phenological database can also be useful in the field of preventive health care, through phenological data application in different atmospheric models (NWP models, phenological models, pollen release models) for numerical forecasting of pollen concentration in the air. Genetic conditions, industrial development, increase of air pollution are regarded as the main determinants of allergic diseases. The results of pheno - aero- meteorological analysis enable the estimation of the influence of natural environmental changes on the increasing prevalence of allergic diseases in Poland.

Uniform Temperature Dependency in the Phenology of a Keystone Herbivore in Lakes of the Northern Hemisphere

PubMed Central

Straile, Dietmar; Adrian, Rita; Schindler, Daniel E.

2012-01-01

Spring phenologies are advancing in many ecosystems associated with climate warming causing unpredictable changes in ecosystem functioning. Here we establish a phenological model for Daphnia, an aquatic keystone herbivore based on decadal data on water temperatures and the timing of Daphnia population maxima from Lake Constance, a large European lake. We tested this model with long-term time-series data from two lakes (Müggelsee, Germany; Lake Washington, USA), and with observations from a diverse set of 49 lakes/sites distributed widely across the Northern Hemisphere (NH). The model successfully captured the observed temporal variation of Daphnia phenology in the two case study sites (r2 = 0.25 and 0.39 for Müggelsee and Lake Washington, respectively) and large-scale spatial variation in the NH (R2 = 0.57). These results suggest that Daphnia phenology follows a uniform temperature dependency in NH lakes. Our approach – based on temperature phenologies – has large potential to study and predict phenologies of animal and plant populations across large latitudinal gradients in other ecosystems. PMID:23071520

Day length unlikely to constrain climate-driven shifts in leaf-out times of northern woody plants

NASA Astrophysics Data System (ADS)

Zohner, Constantin M.; Benito, Blas M.; Svenning, Jens-Christian; Renner, Susanne S.

2016-12-01

The relative roles of temperature and day length in driving spring leaf unfolding are known for few species, limiting our ability to predict phenology under climate warming. Using experimental data, we assess the importance of photoperiod as a leaf-out regulator in 173 woody species from throughout the Northern Hemisphere, and we also infer the influence of winter duration, temperature seasonality, and inter-annual temperature variability. We combine results from climate- and light-controlled chambers with species’ native climate niches inferred from georeferenced occurrences and range maps. Of the 173 species, only 35% relied on spring photoperiod as a leaf-out signal. Contrary to previous suggestions, these species come from lower latitudes, whereas species from high latitudes with long winters leafed out independent of photoperiod. The strong effect of species’ geographic-climatic history on phenological strategies complicates the prediction of community-wide phenological change.

Incorporating genetic variation into a model of budburst phenology of coast Douglas-fir (Pseudotsuga menziesii var

Treesearch

Peter J. Gould; Constance A. Harrington; Bradley J. St Clair

2011-01-01

Models to predict budburst and other phenological events in plants are needed to forecast how climate change may impact ecosystems and for the development of mitigation strategies. Differences among genotypes are important to predicting phenological events in species that show strong clinal variation in adaptive traits. We present a model that incorporates the effects...

Variations in global land surface phenology: a comparison of satellite optical and passive microwave data

NASA Astrophysics Data System (ADS)

Tong, X.; Tian, F.; Brandt, M.; Zhang, W.; Liu, Y.; Fensholt, R.

2017-12-01

Changes in vegetation phenological events are among the most sensitive biological responses to climate change. In last decades, facilitating by satellite remote sensing techniques, land surface phenology (LSP) have been monitored at global scale using proxy approaches as tracking the temporal change of a satellite-derived vegetation index. However, the existing global assessments of changes in LSP are all established on the basis of leaf phenology using NDVI derived from optical sensors, being responsive to vegetation canopy cover and greenness. Instead, the vegetation optical depth (VOD) parameter from passive microwave sensors, which is sensitive to the aboveground vegetation water content by including as well the woody components in the observations, provides an alternative, independent and comprehensive means for global vegetation phenology monitoring. We used the unique long-term global VOD record available for the period 1992-2012 to monitoring the dynamics of LSP metrics (length of season, start of season and end of season) in comparison with the dynamics of LSP metrics derived from the latest GIMMS NDVI3G V1. We evaluated the differences in the linear trends of LSP metrics between two datasets. Currently, our results suggest that the level of seasonality variation of vegetation water content is less than the vegetation greenness. We found significant phenological changes in vegetation water content in African woodlands, where has been reported with little leaf phenological change regardless of the delays in rainfall onset. Therefore, VOD might allow us to detect temporal shifts in the timing difference of vegetation water storage vs. leaf emergence and to see if some ecophysiological thresholds seem to be reached, that could cause species turnover as climate change-driven alterations to the African monsoon proceed.

From leaf longevity to canopy seasonality: a carbon optimality phenology model for tropical evergreen forests

NASA Astrophysics Data System (ADS)

Xu, X.; Medvigy, D.; Wu, J.; Wright, S. J.; Kitajima, K.; Pacala, S. W.

2016-12-01

Tropical evergreen forests play a key role in the global carbon, water and energy cycles. Despite apparent evergreenness, this biome shows strong seasonality in leaf litter and photosynthesis. Recent studies have suggested that this seasonality is not directly related to environmental variability but is dominated by seasonal changes of leaf development and senescence. Meanwhile, current terrestrial biosphere models (TBMs) can not capture this pattern because leaf life cycle is highly underrepresented. One challenge to model this leaf life cycle is the remarkable diversity in leaf longevity, ranging from several weeks to multiple years. Ecologists have proposed models where leaf longevity is regarded as a strategy to optimize carbon gain. However previous optimality models can not be readily integrated into TBMs because (i) there are still large biases in predicted leaf longevity and (ii) it is never tested whether the carbon optimality model can capture the observed seasonality in leaf demography and canopy photosynthesis. In this study, we develop a new carbon optimality model for leaf demography. The novelty of our approach is two-fold. First, we incorporate a mechanistic photosynthesis model that can better estimate leaf carbon gain. Second, we consider the interspecific variations in leaf senescence rate, which strongly influence the modelled optimal carbon gain. We test our model with a leaf trait database for Panamanian evergreen forests. Then, we apply the model at seasonal scale and compare simulated seasonality of leaf litter and canopy photosynthesis with in-situ observations from several Amazonian forest sites. We find that (i) compared with original optimality model, the regression slope between observed and predicted leaf longevity increases from 0.15 to 1.04 in our new model and (ii) that our new model can capture the observed seasonal variations of leaf demography and canopy photosynthesis. Our results suggest that the phenology in tropical evergreen forests might result from plant adaptation to optimize canopy carbon gain. Finally, this proposed trait-driven prognostic phenology model could potentially be incorporated into next generation TBMs to improve simulation of carbon and water fluxes in the tropics.

Genetic and physiological bases for phenological responses to current and predicted climates

PubMed Central

Wilczek, A. M.; Burghardt, L. T.; Cobb, A. R.; Cooper, M. D.; Welch, S. M.; Schmitt, J.

2010-01-01

We are now reaching the stage at which specific genetic factors with known physiological effects can be tied directly and quantitatively to variation in phenology. With such a mechanistic understanding, scientists can better predict phenological responses to novel seasonal climates. Using the widespread model species Arabidopsis thaliana, we explore how variation in different genetic pathways can be linked to phenology and life-history variation across geographical regions and seasons. We show that the expression of phenological traits including flowering depends critically on the growth season, and we outline an integrated life-history approach to phenology in which the timing of later life-history events can be contingent on the environmental cues regulating earlier life stages. As flowering time in many plants is determined by the integration of multiple environmentally sensitive gene pathways, the novel combinations of important seasonal cues in projected future climates will alter how phenology responds to variation in the flowering time gene network with important consequences for plant life history. We discuss how phenology models in other systems—both natural and agricultural—could employ a similar framework to explore the potential contribution of genetic variation to the physiological integration of cues determining phenology. PMID:20819808

Spring leaf phenology and the diurnal temperature range in a temperate maple forest.

PubMed

Hanes, Jonathan M

2014-03-01

Spring leaf phenology in temperate climates is intricately related to numerous aspects of the lower atmosphere [e.g., surface energy balance, carbon flux, humidity, the diurnal temperature range (DTR)]. To further develop and improve the accuracy of ecosystem and climate models, additional investigations of the specific nature of the relationships between spring leaf phenology and various ecosystem and climate processes are required in different environments. This study used visual observations of maple leaf phenology, below-canopy light intensities, and micrometeorological data collected during the spring seasons of 2008, 2009, and 2010 to examine the potential influence of leaf phenology on a seasonal transition in the trend of the DTR. The timing of a reversal in the DTR trend occurred near the time when the leaves were unfolding and expanding. The results suggest that the spring decline in the DTR can be attributed primarily to the effect of canopy closure on daily maximum temperature. These findings improve our understanding of the relationship between leaf phenology and the diurnal temperature range in temperate maple forests during the spring. They also demonstrate the necessity of incorporating accurate phenological data into ecosystem and climate models and warrant a careful examination of the extent to which canopy phenology is currently incorporated into existing models.

Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake

NASA Technical Reports Server (NTRS)

Koster, Randal Dean; Walker, Gregory K.; Collatz, George J.; Thornton, Peter E.

2013-01-01

Long-term, global offline (land-only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that: (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type, (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland, and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).

Rethinking "normal": The role of stochasticity in the phenology of a synchronously breeding seabird.

PubMed

Youngflesh, Casey; Jenouvrier, Stephanie; Hinke, Jefferson T; DuBois, Lauren; St Leger, Judy; Trivelpiece, Wayne Z; Trivelpiece, Susan G; Lynch, Heather J

2018-05-01

Phenological changes have been observed in a variety of systems over the past century. There is concern that, as a consequence, ecological interactions are becoming increasingly mismatched in time, with negative consequences for ecological function. Significant spatial heterogeneity (inter-site) and temporal variability (inter-annual) can make it difficult to separate intrinsic, extrinsic and stochastic drivers of phenological variability. The goal of this study was to understand the timing and variability in breeding phenology of Adélie penguins under fixed environmental conditions and to use those data to identify a "null model" appropriate for disentangling the sources of variation in wild populations. Data on clutch initiation were collected from both wild and captive populations of Adélie penguins. Clutch initiation in the captive population was modelled as a function of year, individual and age to better understand phenological patterns observed in the wild population. Captive populations displayed as much inter-annual variability in breeding phenology as wild populations, suggesting that variability in breeding phenology is the norm and thus may be an unreliable indicator of environmental forcing. The distribution of clutch initiation dates was found to be moderately asymmetric (right skewed) both in the wild and in captivity, consistent with the pattern expected under social facilitation. The role of stochasticity in phenological processes has heretofore been largely ignored. However, these results suggest that inter-annual variability in breeding phenology can arise independent of any environmental or demographic drivers and that synchronous breeding can enhance inherent stochasticity. This complicates efforts to relate phenological variation to environmental variability in the wild. Accordingly, we must be careful to consider random forcing in phenological processes, lest we fit models to data dominated by random noise. This is particularly true for colonial species where breeding synchrony may outweigh each individual's effort to time breeding with optimal environmental conditions. Our study highlights the importance of identifying appropriate null models for studying phenology. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Towards new approaches in phenological modelling

NASA Astrophysics Data System (ADS)

Chmielewski, Frank-M.; Götz, Klaus-P.; Rawel, Harshard M.; Homann, Thomas

2014-05-01

Modelling of phenological stages is based on temperature sums for many decades, describing both the chilling and the forcing requirement of woody plants until the beginning of leafing or flowering. Parts of this approach go back to Reaumur (1735), who originally proposed the concept of growing degree-days. Now, there is a growing body of opinion that asks for new methods in phenological modelling and more in-depth studies on dormancy release of woody plants. This requirement is easily understandable if we consider the wide application of phenological models, which can even affect the results of climate models. To this day, in phenological models still a number of parameters need to be optimised on observations, although some basic physiological knowledge of the chilling and forcing requirement of plants is already considered in these approaches (semi-mechanistic models). Limiting, for a fundamental improvement of these models, is the lack of knowledge about the course of dormancy in woody plants, which cannot be directly observed and which is also insufficiently described in the literature. Modern metabolomic methods provide a solution for this problem and allow both, the validation of currently used phenological models as well as the development of mechanistic approaches. In order to develop this kind of models, changes of metabolites (concentration, temporal course) must be set in relation to the variability of environmental (steering) parameters (weather, day length, etc.). This necessarily requires multi-year (3-5 yr.) and high-resolution (weekly probes between autumn and spring) data. The feasibility of this approach has already been tested in a 3-year pilot-study on sweet cherries. Our suggested methodology is not only limited to the flowering of fruit trees, it can be also applied to tree species of the natural vegetation, where even greater deficits in phenological modelling exist.

Toward a U.S. National Phenological Assessment

NASA Astrophysics Data System (ADS)

Henebry, Geoffrey M.; Betancourt, Julio L.

2010-01-01

Third USA National Phenology Network (USA-NPN) and Research Coordination Network (RCN) Annual Meeting; Milwaukee, Wisconsin, 5-9 October 2009; Directional climate change will have profound and lasting effects throughout society that are best understood through fundamental physical and biological processes. One such process is phenology: how the timing of recurring biological events is affected by biotic and abiotic forces. Phenology is an early and integrative indicator of climate change readily understood by nonspecialists. Phenology affects the planting, maturation, and harvesting of food and fiber; pollination; timing and magnitude of allergies and disease; recreation and tourism; water quantity and quality; and ecosystem function and resilience. Thus, phenology is the gateway to climatic effects on both managed and unmanaged ecosystems. Adaptation to climatic variability and change will require integration of phenological data and models with climatic forecasts at seasonal to decadal time scales. Changes in phenologies have already manifested myriad effects of directional climate change. As these changes continue, it is critical to establish a comprehensive suite of benchmarks that can be tracked and mapped at local to continental scales with observations and climate models.

Nature's Notebook Provides Phenology Observations for NASA Juniper Phenology and Pollen Transport Project

NASA Technical Reports Server (NTRS)

Luval, J. C.; Crimmins, T. M.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Prasad, A.; Vukovic, A.; VandeWater, P. K.; Budge, A. M.;

The timing of bud burst and its effect on tree growth.

PubMed

Rötzer, T; Grote, R; Pretzsch, H

2004-02-01

A phenology model for estimating the timings of bud burst--one of the most influential phenological phases for the simulation of tree growth--is presented in this study. The model calculates the timings of the leafing of beech (Fagus sylvatica L.) and oak (Quercus robur L.) and the May shoot of Norway spruce (Picea abies L.) and Scots pine (Pinus sylvestris L.) on the basis of the daily maximum temperature. The data for parameterisation and validation of the model have been taken from 40 climate and 120 phenological stations in southern Germany with time series for temperature and bud burst of up to 30 years. The validation of the phenology module by means of an independent data set showed correlation coefficients for comparisons between observed and simulated values of 54% (beech), 55% (oak), 59% (spruce) and 56% (pine) with mean absolute errors varying from 4.4 days (spruce) to 5.0 days (pine). These results correspond well with the results of other--often more complex--phenology models. After the phenology module had been implemented in the tree-growth model BALANCE, the growth of a mixed forest stand with the former static and the new dynamic timings for the bud burst was simulated. The results of the two simulation runs showed that phenology has to be taken into account when simulating forest growth, particularly in mixed stands.

Asynchronous response of tropical forest leaf phenology to seasonal and el Niño-driven drought.

PubMed

Pau, Stephanie; Okin, Gregory S; Gillespie, Thomas W

2010-06-25

The Hawaiian Islands are an ideal location to study the response of tropical forests to climate variability because of their extreme isolation in the middle of the Pacific, which makes them especially sensitive to El Niño-Southern Oscillation (ENSO). Most research examining the response of tropical forests to drought or El Niño have focused on rainforests, however, tropical dry forests cover a large area of the tropics and may respond very differently than rainforests. We use satellite-derived Normalized Difference Vegetation Index (NDVI) from February 2000-February 2009 to show that rainforests and dry forests in the Hawaiian Islands exhibit asynchronous responses in leaf phenology to seasonal and El Niño-driven drought. Dry forest NDVI was more tightly coupled with precipitation compared to rainforest NDVI. Rainforest cloud frequency was negatively correlated with the degree of asynchronicity (Delta(NDVI)) between forest types, most strongly at a 1-month lag. Rainforest green-up and dry forest brown-down was particularly apparent during the 2002-003 El Niño. The spatial pattern of NDVI response to the NINO 3.4 Sea Surface Temperature (SST) index during 2002-2003 showed that the leeward side exhibited significant negative correlations to increased SSTs, whereas the windward side exhibited significant positive correlations to increased SSTs, most evident at an 8 to 9-month lag. This study demonstrates that different tropical forest types exhibit asynchronous responses to seasonal and El Niño-driven drought, and suggests that mechanisms controlling dry forest leaf phenology are related to water-limitation, whereas rainforests are more light-limited.

Asynchronous Response of Tropical Forest Leaf Phenology to Seasonal and El Niño-Driven Drought

PubMed Central

Pau, Stephanie; Okin, Gregory S.; Gillespie, Thomas W.

2010-01-01

The Hawaiian Islands are an ideal location to study the response of tropical forests to climate variability because of their extreme isolation in the middle of the Pacific, which makes them especially sensitive to El Niño-Southern Oscillation (ENSO). Most research examining the response of tropical forests to drought or El Niño have focused on rainforests, however, tropical dry forests cover a large area of the tropics and may respond very differently than rainforests. We use satellite-derived Normalized Difference Vegetation Index (NDVI) from February 2000-February 2009 to show that rainforests and dry forests in the Hawaiian Islands exhibit asynchronous responses in leaf phenology to seasonal and El Niño-driven drought. Dry forest NDVI was more tightly coupled with precipitation compared to rainforest NDVI. Rainforest cloud frequency was negatively correlated with the degree of asynchronicity (ΔNDVI) between forest types, most strongly at a 1-month lag. Rainforest green-up and dry forest brown-down was particularly apparent during the 2002–003 El Niño. The spatial pattern of NDVI response to the NINO 3.4 Sea Surface Temperature (SST) index during 2002–2003 showed that the leeward side exhibited significant negative correlations to increased SSTs, whereas the windward side exhibited significant positive correlations to increased SSTs, most evident at an 8 to 9-month lag. This study demonstrates that different tropical forest types exhibit asynchronous responses to seasonal and El Niño-driven drought, and suggests that mechanisms controlling dry forest leaf phenology are related to water-limitation, whereas rainforests are more light-limited. PMID:20593034

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Transport

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; Van de Water, P. K.; Myers, O. B.; Budge, A. M.;

Use Of MODIS Satellite Images And An Atmospheric Dust Transport Model To Evaluate Juniperus Spp. Pollen Phenology And Transport

NASA Astrophysics Data System (ADS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A. R.; Nickovic, S.; Crimmins, T. M.; Van De Water, P. K.; Pejanovic, G.; Vukovic, A. J.; Myers, O.; Budge, A.; Zelicoff, A.; Bunderson, L.; Ponce-Campos, G.

2011-12-01

Pollen can be transported great distances. Van de Water et al., 2003 reported Juniperus spp. pollen, a significant aeroallergen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Direct detection of pollen via satellite is not practical. A practical alternative combines modeling and phenological observations using ground based sampling and satellite data. The DREAM (Dust REgional Atmospheric Model) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust (Nickovic et al. 2001). The use of satellite data products for studying phenology is well documented (White and Nemani 2006). In the current project MODIS data will provide critical input to the PREAM model providing pollen source location, timing of pollen release, and vegetation type. We are modifying the DREAM model (PREAM - Pollen REgional Atmospheric Model) to incorporate pollen transport. The linkages already exist with DREAM through PHAiRS (Public Health Applications in Remote Sensing) to the public health community. This linkage has the potential to fill this data gap so that the potential association of health effects of pollen can better be tracked for possible linkage with health outcome data which may be associated with asthma, respiratory effects, myocardial infarction, and lost workdays. Juniperus spp. pollen phenology may respond to a wide range of environmental factors such as day length, growing degree-days, precipitation patterns and soil moisture. Species differences are also important. These environmental factors vary over both time and spatial scales. Ground based networks such as the USA National Phenology Network have been established to provide national wide observations of vegetation phenology. However, the density of observers is not adequate to sufficiently document the phenology variability over large regions. Hence the use of satellite data is critical to observe Juniperus spp. pollen phenology. MODIS data was used to observe Juniperus spp. pollen phenology. The MODIS surface reflectance product(MOD09) provided information on the Juniper spp. cone formation and cone density. Ground based observational records of pollen release timing and quantities were used as verification. Techniques developed using MOD09 surface reflectance products will be directly applicable to the next generation sensors such as VIIRS.

A sub-canopy structure for simulating oil palm in the Community Land Model: phenology, allocation and yield

NASA Astrophysics Data System (ADS)

Fan, Y.; Roupsard, O.; Bernoux, M.; Le Maire, G.; Panferov, O.; Kotowska, M. M.; Knohl, A.

2015-06-01

Land surface modelling has been widely used to characterize the two-way interactions between climate and human activities in terrestrial ecosystems such as deforestation, agricultural expansion, and urbanization. Towards an effort to quantify the effects of forests to oil palm conversion occurring in the tropics on land-atmosphere carbon, water and energy fluxes, we introduce a new perennial crop plant functional type (PFT) for oil palm. Due to the modular and sequential nature of oil palm growth (around 40 stacked phytomers) and yield (fruit bunches axillated on each phytomer), we developed a specific sub-canopy structure for simulating palm's growth and yield within the framework of the Community Land Model (CLM4.5). In this structure each phytomer has its own prognostic leaf growth and fruit yield capacity like a PFT but with shared stem and root components among all phytomers. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, so that multiple fruit yields per annum are enabled in terms of carbon and nitrogen outputs. An important phenological phase is identified for the palm PFT - the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization, and leaf pruning are represented. Parameters introduced for the new PFT were calibrated and validated with field measurements of leaf area index (LAI) and yield from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched perfectly between simulation and observation (mean percentage error = 4 %). Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites but also indicates that seasonal dynamics and site-to-site variability of yield are driven by processes not yet implemented in the model. The new sub-canopy structure and phenology and allocation functions now allow exploring the effects of tropical land use change, from natural ecosystems to oil palm plantations, on carbon, water and energy cycles and regional climate.

On the uncertainty of phenological responses to climate change, and implications for a terrestrial biosphere model

NASA Astrophysics Data System (ADS)

Migliavacca, M.; Sonnentag, O.; Keenan, T. F.; Cescatti, A.; O'Keefe, J.; Richardson, A. D.

2012-06-01

Phenology, the timing of recurring life cycle events, controls numerous land surface feedbacks to the climate system through the regulation of exchanges of carbon, water and energy between the biosphere and atmosphere. Terrestrial biosphere models, however, are known to have systematic errors in the simulation of spring phenology, which potentially could propagate to uncertainty in modeled responses to future climate change. Here, we used the Harvard Forest phenology record to investigate and characterize sources of uncertainty in predicting phenology, and the subsequent impacts on model forecasts of carbon and water cycling. Using a model-data fusion approach, we combined information from 20 yr of phenological observations of 11 North American woody species, with 12 leaf bud-burst models that varied in complexity. Akaike's Information Criterion indicated support for spring warming models with photoperiod limitations and, to a lesser extent, models that included chilling requirements. We assessed three different sources of uncertainty in phenological forecasts: parameter uncertainty, model uncertainty, and driver uncertainty. The latter was characterized running the models to 2099 using 2 different IPCC climate scenarios (A1fi vs. B1, i.e. high CO2 emissions vs. low CO2 emissions scenario). Parameter uncertainty was the smallest (average 95% Confidence Interval - CI: 2.4 days century-1 for scenario B1 and 4.5 days century-1 for A1fi), whereas driver uncertainty was the largest (up to 8.4 days century-1 in the simulated trends). The uncertainty related to model structure is also large and the predicted bud-burst trends as well as the shape of the smoothed projections varied among models (±7.7 days century-1 for A1fi, ±3.6 days century-1 for B1). The forecast sensitivity of bud-burst to temperature (i.e. days bud-burst advanced per degree of warming) varied between 2.2 days °C-1 and 5.2 days °C-1 depending on model structure. We quantified the impact of uncertainties in bud-burst forecasts on simulated photosynthetic CO2 uptake and evapotranspiration (ET) using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of forest seasonality, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP) and ET of 9.6% and 2.9%, respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±2.0% for ET. For phenology models, differences among future climate scenarios (i.e. driver) represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, related to model parameterization. The uncertainties we have quantified will affect the description of the seasonality of ecosystem processes and in particular the simulation of carbon uptake by forest ecosystems, with a larger impact of uncertainties related to phenology model structure, followed by uncertainties related to phenological model parameterization.

Time-Dependent Trapping of Pollinators Driven by the Alignment of Floral Phenology with Insect Circadian Rhythms

PubMed Central

Lau, Jenny Y. Y.; Guo, Xing; Pang, Chun-Chiu; Tang, Chin Cheung; Thomas, Daniel C.; Saunders, Richard M. K.

2017-01-01

Several evolutionary lineages in the early divergent angiosperm family Annonaceae possess flowers with a distinctive pollinator trapping mechanism, in which floral phenological events are very precisely timed in relation with pollinator activity patterns. This contrasts with previously described angiosperm pollinator traps, which predominantly function as pitfall traps. We assess the circadian rhythms of pollinators independently of their interactions with flowers, and correlate these data with detailed assessments of floral phenology. We reveal a close temporal alignment between patterns of pollinator activity and the floral phenology driving the trapping mechanism (termed ‘circadian trapping’ here). Non-trapping species with anthesis of standard duration (c. 48 h) cannot be pollinated effectively by pollinators with a morning-unimodal activity pattern; non-trapping species with abbreviated anthesis (23–27 h) face limitations in utilizing pollinators with a bimodal circadian activity; whereas species that trap pollinators (all with short anthesis) can utilize a broader range of potential pollinators, including those with both unimodal and bimodal circadian rhythms. In addition to broadening the range of potential pollinators based on their activity patterns, circadian trapping endows other selective advantages, including the possibility of an extended staminate phase to promote pollen deposition, and enhanced interfloral movement of pollinators. The relevance of the alignment of floral phenological changes with peaks in pollinator activity is furthermore evaluated for pitfall trap pollination systems. PMID:28713403

Land surface phenology

USGS Publications Warehouse

Hanes, Jonathan M.; Liang, Liang; Morisette, Jeffrey T.

2013-01-01

Certain vegetation types (e.g., deciduous shrubs, deciduous trees, grasslands) have distinct life cycles marked by the growth and senescence of leaves and periods of enhanced photosynthetic activity. Where these types exist, recurring changes in foliage alter the reflectance of electromagnetic radiation from the land surface, which can be measured using remote sensors. The timing of these recurring changes in reflectance is called land surface phenology (LSP). During recent decades, a variety of methods have been used to derive LSP metrics from time series of reflectance measurements acquired by satellite-borne sensors. In contrast to conventional phenology observations, LSP metrics represent the timing of reflectance changes that are driven by the aggregate activity of vegetation within the areal unit measured by the satellite sensor and do not directly provide information about the phenology of individual plants, species, or their phenophases. Despite the generalized nature of satellite sensor-derived measurements, they have proven useful for studying changes in LSP associated with various phenomena. This chapter provides a detailed overview of the use of satellite remote sensing to monitor LSP. First, the theoretical basis for the application of satellite remote sensing to the study of vegetation phenology is presented. After establishing a theoretical foundation for LSP, methods of deriving and validating LSP metrics are discussed. This chapter concludes with a discussion of major research findings and current and future research directions.

Analysis of Accuracy of Modis BRDF Product (MCD43 C6) Based on Misr Land Surface Brf Product - a Case Study of the Central Part of Northeast Asia

NASA Astrophysics Data System (ADS)

Li, J.; Chen, S.; Qin, W.; Murefu, M.; Wang, Y.; Yu, Y.; Zhen, Z.

2018-04-01

EOS/MODIS land surface Bi-directional Reflectance Distribution Function (BRDF) product (MCD43), with the latest version C6, is one of the most important operational BRDF products with global coverage. The core sub-product MCD43A1 stores 3 parameters of the RossThick-LiSparseR semi-empirical kernel-driven BRDF model. It is important for confident use of the product to evaluate the accuracy of bi-directional reflectance factor (BRF) predicted by MCD43A1 BRDF model (mBRF). A typical region in the central part of Northeast Asia is selected as the study area. The performance of MCD43A1 BRDF model is analyzed in various observation geometries and phenological phases, using Multi-angle Imaging SpectroRadiometer (MISR) land-surface reflectance factor product (MILS_BRF) as the reference data. In addition, MODIS products MCD12Q1 and MOD/MYD10A1 are used to evaluate the impacts of land cover types and snow covers on the model accuracy, respectively. The results show an overall excellent performance of MCD43A1 in representing the anisotropic reflectance of land surface, with root mean square error (RMSE) of 0.0262 and correlation coefficient (R) of 0.9537, for all available comparable samples of MILS_BRF and mBRF pairs. The model accuracy varies in different months, which is related to the phenological phases of the study area. The accuracy for pixels labelled as `snow' by MCD43 is obviously low, with RMSE/R of 0.0903/0.8401. Ephemeral snowfall events further decrease the accuracy, with RMSE/R of 0.1001/0.7715. These results provide meaningful information to MCD43 users, especially those, whose study regions are subject to phenological cycles as well as snow cover and change.

Integrating models to investigate critical phenological overlaps in complex ecological interactions: the mountain pine beetle-fungus symbiosis.

PubMed

Addison, Audrey; Powell, James A; Bentz, Barbara J; Six, Diana L

2015-03-07

The fates of individual species are often tied to synchronization of phenology, however, few methods have been developed for integrating phenological models involving linked species. In this paper, we focus on mountain pine beetle (MPB, Dendroctonus ponderosae) and its two obligate mutualistic fungi, Grosmannia clavigera and Ophiostoma montium. Growth rates of all three partners are driven by temperature, and their idiosyncratic responses affect interactions at important life stage junctures. One critical phase for MPB-fungus symbiosis occurs just before dispersal of teneral (new) adult beetles, when fungi are acquired and transported in specialized structures (mycangia). Before dispersal, fungi must capture sufficient spatial resources within the tree to ensure contact with teneral adults and get packed into mycangia. Mycangial packing occurs at an unknown time during teneral feeding. We adapt thermal models predicting fungal growth and beetle development to predict overlap between the competing fungi and MPB teneral adult feeding windows and emergence. We consider a spectrum of mycangial packing strategies and describe them in terms of explicit functions with unknown parameters. Rates of growth are fixed by laboratory data, the unknown parameters describing various packing strategies, as well as the degree to which mycangial growth is slowed in woody tissues as compared to agar, are determined by maximum likelihood and two years of field observations. At the field location used, the most likely fungus acquisition strategy for MPB was packing mycangia just prior to emergence. Estimated model parameters suggested large differences in the relative growth rates of the two fungi in trees at the study site, with the most likely model estimating that G. clavigera grew approximately twenty-five times faster than O. montium under the bark, which is completely unexpected in comparison with observed fungal growth on agar. Copyright © 2014 Elsevier Ltd. All rights reserved.

Match and mismatch - comparing plant phenological metrics from ground-observations and from a prognostic model

NASA Astrophysics Data System (ADS)

Rutishauser, This; Stöckli, Reto; Jeanneret, François; Peñuelas, Josep

2010-05-01

Changes in the seasonality of life cycles of plants as recorded in phenological observations have been widely analysed at the species level with data available for many decades back in time. At the same time, seasonality changes in satellite-based observations and prognostic phenology models comprise information at the pixel-size or landscape scale. Change analysis of satellite-based records is restricted due to relatively short satellite records that further include gaps while model-based analyses are biased due to current model deficiencies., At 30 selected sites across Europe, we analysed three different sources of plant seasonality during the 1971-2000 period. Data consisted of (1) species-specific development stages of flowering and leave-out with different species observed at each site. (2) We used a synthetic phenological metric that integrates the common interannual phenological signal across all species at one site. (3) We estimated daily Leaf Area Index with a prognostic phenology model. The prior uncertainties of the model's empirical parameter space are constrained by assimilating the Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) and Leaf Area Index (LAI) from the MODerate Resolution Imaging Spectroradiometer (MODIS). We extracted the day of year when the 25%, 50% and 75% thresholds were passed each spring. The question arises how the three phenological signals compare and correlate across climate zones in Europe. Is there a match between single species observations, species-based ground-observed metrics and the landscape-scale prognostic model? Are there single key-species across Europe that best represent a landscape scale measure from the prognostic model? Can one source substitute another and serve as proxy-data? What can we learn from potential mismatches? Focusing on changes in spring this contribution presents first results of an ongoing comparison study from a number of European test sites that will be extended to the pan-European phenological database Cost725 and PEP725.

How Resource Phenology Affects Consumer Population Dynamics.

PubMed

Bewick, Sharon; Cantrell, R Stephen; Cosner, Chris; Fagan, William F

2016-02-01

Climate change drives uneven phenology shifts across taxa, and this can result in changes to the phenological match between interacting species. Shifts in the relative phenology of partner species are well documented, but few studies have addressed the effects of such changes on population dynamics. To explore this, we develop a phenologically explicit model describing consumer-resource interactions. Focusing on scenarios for univoltine insects, we show how changes in resource phenology can be reinterpreted as transformations in the year-to-year recursion relationships defining consumer population dynamics. This perspective provides a straightforward path for interpreting the long-term population consequences of phenology change. Specifically, by relating the outcome of phenological shifts to species traits governing recursion relationships (e.g., consumer fecundity or competitive scenario), we demonstrate how changes in relative phenology can force systems into different dynamical regimes, with major implications for resource management, conservation, and other areas of applied dynamics.

A modeling approach to investigate the sensitivity of plankton phenology to global change since the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Kretschmer, K.; Kucera, M.; Schulz, M.

2016-02-01

Plankton phenology is a key aspect of ecosystem dynamics. Up to now, it is not known how sensitive this parameter is to environmental perturbations and what magnitude of change is conceivable under extreme climate change scenarios. For example, one could argue that the phenology of the dominant Arctic planktonic foraminifera species Neogloboquadrina pachyderma will only shift slightly recording the more or less delayed onset of spring ocean warming. This assumption can be tested by examining the likely phenology of this species in the fossil record. Although phenology is difficult to derive directly from proxies, it can be estimated for past periods by models. Here we use an ecosystem modeling approach to investigate seasonal variations of N. pachyderma since the Last Glacial Maximum (LGM) in the North Atlantic. The model implies that the phenology of N. pachyderma during the LGM and the ensuing Heinrich Event 1 shifted by several months from the modern situation with a maximum seasonal production occurring later in the year (i.e. boreal summer). In comparison with the fossil records our model performs well in reproducing the observed abundance patterns and range shifts in the studied species during the last glacial period. Hence, the predicted large (and partly no-analog) shifts in the phenology of N. pachyderma are a plausible scenario. For instance, its maximum growth during Heinrich Event 1 in a region northeast of Newfoundland occurred during a part of the season where this species never peaks anywhere in the North Atlantic at present. Understanding the drivers of this change and knowing the potential adaptive space of phenology shifts are essential in predictions of plankton response to future global change scenarios.

Integrating models to investigate critical phenological overlaps in complex ecological interactions: The mountain pine beetle-fungus symbiosis

Treesearch

Audrey Addison; James A. Powell; Barbara J. Bentz; Diana L. Six

2015-01-01

The fates of individual species are often tied to synchronization of phenology, however, few methods have been developed for integrating phenological models involving linked species. In this paper, we focus on mountain pine beetle (MPB, Dendroctonus ponderosae) and its two obligate mutualistic fungi, Grosmannia clavigera and Ophiostoma montium. Growth rates of...

Unified phenology model with Bayesian calibration for several European species in Belgium

NASA Astrophysics Data System (ADS)

Fu, Y. S. H.; Demarée, G.; Hamdi, R.; Deckmyn, A.; Deckmyn, G.; Janssens, I. A.

2009-04-01

Plant phenology is a good bio-indicator for climate change, and this has brought a significant increase of interest. Many kinds of phenology models have been developed to analyze and predict the phenological response to climate change, and those models have been summarized into one kind of unified model, which could be applied to different species and environments. In our study, we selected seven European woody plant species (Betula verrucosa, Quercus robur pedunculata, Fagus sylvatica, Fraxinus excelsior, Symphoricarpus racemosus, Aesculus hippocastanum, Robinia pseudoacacia) occurring in five sites distributed across Belgium. For those sites and tree species, phenological observations such as bud burst were available for the period 1956 - 2002. We also obtained regional downscaled climatic data for each of these sites, and combined both data sets to test the unified model. We used a Bayesian approach to generate distributions of model parameters from the observation data. In this poster presentation, we compare parameter distributions between different species and between different sites for individual species. The results of the unified model show a good agreement with the observations, except for Fagus sylvatica. The failure to reproduce the bud burst data for Fagus sylvatica suggest that the other factors not included in the unified model affect the phenology of this species. The parameter series show differences among species as we expected. However, they also differed strongly for the same species among sites.Further work should elucidate the mechanism that explains why model parameters differ among species and sites.

Temperature variability is a key component in accurately forecasting the effects of climate change on pest phenology.

PubMed

Merrill, Scott C; Peairs, Frank B

2017-02-01

Models describing the effects of climate change on arthropod pest ecology are needed to help mitigate and adapt to forthcoming changes. Challenges arise because climate data are at resolutions that do not readily synchronize with arthropod biology. Here we explain how multiple sources of climate and weather data can be synthesized to quantify the effects of climate change on pest phenology. Predictions of phenological events differ substantially between models that incorporate scale-appropriate temperature variability and models that do not. As an illustrative example, we predicted adult emergence of a pest of sunflower, the sunflower stem weevil Cylindrocopturus adspersus (LeConte). Predictions of the timing of phenological events differed by an average of 11 days between models with different temperature variability inputs. Moreover, as temperature variability increases, developmental rates accelerate. Our work details a phenological modeling approach intended to help develop tools to plan for and mitigate the effects of climate change. Results show that selection of scale-appropriate temperature data is of more importance than selecting a climate change emission scenario. Predictions derived without appropriate temperature variability inputs will likely result in substantial phenological event miscalculations. Additionally, results suggest that increased temperature instability will lead to accelerated pest development. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

NASA Astrophysics Data System (ADS)

Jin, Z.; Azzari, G.; Lobell, D. B.

2016-12-01

Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

Testing hypotheses on distribution shifts and changes in phenology of imperfectly detectable species

USGS Publications Warehouse

Chambert, Thierry A.; Kendall, William L.; Hines, James E.; Nichols, James D.; Pedrini, Paolo; Waddle, J. Hardin; Tavecchia, Giacomo; Walls, Susan C.; Tenan, Simone

2015-01-01

With ongoing climate change, many species are expected to shift their spatial and temporal distributions. To document changes in species distribution and phenology, detection/non-detection data have proven very useful. Occupancy models provide a robust way to analyse such data, but inference is usually focused on species spatial distribution, not phenology.We present a multi-season extension of the staggered-entry occupancy model of Kendall et al. (2013, Ecology, 94, 610), which permits inference about the within-season patterns of species arrival and departure at sampling sites. The new model presented here allows investigation of species phenology and spatial distribution across years, as well as site extinction/colonization dynamics.We illustrate the model with two data sets on European migratory passerines and one data set on North American treefrogs. We show how to derive several additional phenological parameters, such as annual mean arrival and departure dates, from estimated arrival and departure probabilities.Given the extent of detection/non-detection data that are available, we believe that this modelling approach will prove very useful to further understand and predict species responses to climate change.

Improvement of Alternative Crop Phenology Detection Algorithms using MODIS NDVI Time Series Data in US Corn Belt Region

NASA Astrophysics Data System (ADS)

Lee, J.; Kang, S.; Seo, B.; Lee, K.

2017-12-01

Predicting crop phenology is important for understanding of crop development and growth processes and improving the accuracy of crop model. Remote sensing offers a feasible tool for monitoring spatio-temporal patterns of crop phenology in region and continental scales. Various methods have been developed to determine the timing of crop phenological stages using spectral vegetation indices (i.e. NDVI and EVI) derived from satellite data. In our study, it was compared four alternative detection methods to identify crop phenological stages (i.e. the emergence and harvesting date) using high quality NDVI time series data derived from MODIS. Also we investigated factors associated with crop development rate. Temperature and photoperiod are the two main factors which would influence the crop's growth pattern expressed in the VI data. Only the effect of temperature on crop development rate was considered. The temperature response function in the Wang-Engel (WE) model was used, which simulates crop development using nonlinear models with response functions that range from zero to one. It has attempted at the state level over 14 years (2003-2016) in Iowa and Illinois state of USA, where the estimated phenology date by using four methods for both corn and soybean. Weekly crop progress reports produced by the USDA NASS were used to validate phenology detection algorithms effected by temperature. All methods showed substantial uncertainty but the threshold method showed relatively better agreement with the State-level data for soybean phenology.

Plants and pixels: Comparing phenologies from the ground and from space (Invited)

NASA Astrophysics Data System (ADS)

Rutishauser, T.; Stoekli, R.; Jeanneret, F.; Peñuelas, J.

2010-12-01

Changes in the seasonality of life cycles of plants as recorded in phenological observations have been widely analysed at the species level with data available for many decades back in time. At the same time, seasonality changes in satellite-based observations and prognostic phenology models comprise information at the pixel-size or landscape scale. Change analysis of satellite-based records is restricted due to relatively short satellite records that further include gaps while model-based analyses are biased due to current model deficiencies. At 30 selected sites across Europe, we analysed three different sources of plant seasonality during the 1971-2000 period. Data consisted of (1) species-specific development stages of flowering and leave-out with different species observed at each site. (2) We used a synthetic phenological metric that integrates the common interannual phenological signal across all species at one site. (3) We estimated daily Leaf Area Index with a prognostic phenology model. The prior uncertainties of the model’s empirical parameter space are constrained by assimilating the Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) and Leaf Area Index (LAI) from the MODerate Resolution Imaging Spectroradiometer (MODIS). We extracted the day of year when the 25%, 50% and 75% thresholds were passed each spring. The question arises how the three phenological signals compare and correlate across climate zones in Europe. Is there a match between single species observations, species-based ground-observed metrics and the landscape-scale prognostic model? Are there single key-species across Europe that best represent a landscape scale measure from the prognostic model? Can one source substitute another and serve as proxy-data? What can we learn from potential mismatches? Focusing on changes in spring this contribution presents first results of an ongoing comparison study from a number of European test sites that will be extended to the pan-European phenological database Cost725 and PEP725.

Photoperiod- and Warming-driven Phenological Changes and Carbon and Nutrient Cycling. Remote Sensing Assessment

NASA Astrophysics Data System (ADS)

Penuelas, J.; Fu, Y.; Estiarte, M.; Gamon, J. A.; Filella, I.; Verger, A.; Jannssens, I.

2017-12-01

Ongoing spring warming allows the growing season to begin earlier in northern ecosystems, thus enhancing their carbon uptake. We will present data on atmospheric CO2 concentration measurements to show that this spring advancement of annual carbon intake in response to warming is decreasing. Reduced chilling during dormancy and the interactions between temperature and photoperiod in driving leaf-out may play a role. We will show that short photoperiod (in warm springs when leaf-out is early) significantly increases the heat requirement for leaf-out whereas long photoperiod (in cold springs when leaf-out is late) reduces the heat requirement for leaf-out. These two contrasting photoperiod effects illustrate a complicated temperature response of leaf-out phenology. We will also discuss how photoperiod exerts a strict control on leaf senescence at latitudes where winters are severe and temperature gains importance in the regulation as winters become less severe. On average, climatic warming will delay and drought will advance leaf senescence, but at varying degrees depending on the species. Warming and drought thus have opposite effects on the phenology of leaf senescence, and the impact of climate change will therefore depend on the relative importance of each factor in specific regions. We will then discuss the ecological effects of these phenological changes focusing, as an example, on the impacts of changes on the phenology of leaf senescence on carbon uptake and nutrient cycling. Finally, we will present recent advances on remote sensing monitoring of both the phenological changes and their ecological impacts. We will focus on advances derived from a close correspondence between seasonally changing foliar pigment levels, expressed as chlorophyll/carotenoid ratios, and evergreen photosynthetic activity.

Grapevine phenology and climate change in Georgia.

PubMed

Cola, G; Failla, O; Maghradze, D; Megrelidze, L; Mariani, L

2017-04-01

While the climate of Western Europe has been deeply affected by the abrupt climate change that took place in the late '1980s of the twentieth century, a similar signal is detected only few years later, in 1994, in Georgia. Grapevine phenology is deeply influenced by climate and this paper aimed to analyze how phenological timing changed before and after the climatic change of 1994. Availability of thermal resources in the two climatic phases for the five altitudinal belts in the 0-1250-m range was analyzed. A phenological dataset gathered in two experimental sites during the period 2012-2014, and a suitable thermal dataset was used to calibrate a phenological model based on the normal approach and able to describe BBCH phenological stages 61 (beginning of flowering), 71 (fruit set), and 81 (veraison). Calibration was performed for four relevant Georgian varieties (Mtsvane Kakhuri, Rkatsiteli, Ojaleshi, and Saperavi). The model validation was performed on an independent 3-year dataset gathered in Gorizia (Italy). Furthermore, in the case of variety Rkatsiteli, the model was applied to the 1974-2013 thermal time series in order to obtain phenological maps of the Georgian territory. Results show that after the climate change of 1994, Rkatsiteli showed an advance, more relevant at higher altitudes where the whole increase of thermal resource was effectively translated in phenological advance. For instance the average advance of veraison was 5.9 days for 250-500 m asl belt and 18.1 days for 750-1000 m asl). On the other hand, at lower altitudes, phenological advance was depleted by superoptimal temperatures. As a final result, some suggestions for the adaptation of viticultural practices to the current climatic phase are provided.

European larch phenology in the Alps: can we grasp the role of ecological factors by combining field observations and inverse modelling?

NASA Astrophysics Data System (ADS)

Migliavacca, M.; Cremonese, E.; Colombo, R.; Busetto, L.; Galvagno, M.; Ganis, L.; Meroni, M.; Pari, E.; Rossini, M.; Siniscalco, C.; Morra di Cella, U.

2008-09-01

Vegetation phenology is strongly influenced by climatic factors. Climate changes may cause phenological variations, especially in the Alps which are considered to be extremely vulnerable to global warming. The main goal of our study is to analyze European larch ( Larix decidua Mill.) phenology in alpine environments and the role of the ecological factors involved, using an integrated approach based on accurate field observations and modelling techniques. We present 2 years of field-collected larch phenological data, obtained following a specifically designed observation protocol. We observed that both spring and autumn larch phenology is strongly influenced by altitude. We propose an approach for the optimization of a spring warming model (SW) and the growing season index model (GSI) consisting of a model inversion technique, based on simulated look-up tables (LUTs), that provides robust parameter estimates. The optimized models showed excellent agreement between modelled and observed data: the SW model predicts the beginning of the growing season (BGS) with a mean RMSE of 4 days, while GSI gives a prediction of the growing season length (LGS) with a RMSE of 5 days. Moreover, we showed that the original GSI parameters led to consistent errors, while the optimized ones significantly increased model accuracy. Finally, we used GSI to investigate interactions of ecological factors during springtime development and autumn senescence. We found that temperature is the most effective factor during spring recovery while photoperiod plays an important role during autumn senescence: photoperiod shows a contrasting effect with altitude decreasing its influence with increasing altitude.

European larch phenology in the Alps: can we grasp the role of ecological factors by combining field observations and inverse modelling?

PubMed

Migliavacca, M; Cremonese, E; Colombo, R; Busetto, L; Galvagno, M; Ganis, L; Meroni, M; Pari, E; Rossini, M; Siniscalco, C; Morra di Cella, U

2008-09-01

Vegetation phenology is strongly influenced by climatic factors. Climate changes may cause phenological variations, especially in the Alps which are considered to be extremely vulnerable to global warming. The main goal of our study is to analyze European larch (Larix decidua Mill.) phenology in alpine environments and the role of the ecological factors involved, using an integrated approach based on accurate field observations and modelling techniques. We present 2 years of field-collected larch phenological data, obtained following a specifically designed observation protocol. We observed that both spring and autumn larch phenology is strongly influenced by altitude. We propose an approach for the optimization of a spring warming model (SW) and the growing season index model (GSI) consisting of a model inversion technique, based on simulated look-up tables (LUTs), that provides robust parameter estimates. The optimized models showed excellent agreement between modelled and observed data: the SW model predicts the beginning of the growing season (B(GS)) with a mean RMSE of 4 days, while GSI gives a prediction of the growing season length (L(GS)) with a RMSE of 5 days. Moreover, we showed that the original GSI parameters led to consistent errors, while the optimized ones significantly increased model accuracy. Finally, we used GSI to investigate interactions of ecological factors during springtime development and autumn senescence. We found that temperature is the most effective factor during spring recovery while photoperiod plays an important role during autumn senescence: photoperiod shows a contrasting effect with altitude decreasing its influence with increasing altitude.

Causes and correlations in cambium phenology: towards an integrated framework of xylogenesis.

PubMed

Rossi, Sergio; Morin, Hubert; Deslauriers, Annie

2012-03-01

Although habitually considered as a whole, xylogenesis is a complex process of division and maturation of a pool of cells where the relationship between the phenological phases generating such a growth pattern remains essentially unknown. This study investigated the causal relationships in cambium phenology of black spruce [Picea mariana (Mill.) BSP] monitored for 8 years on four sites of the boreal forest of Quebec, Canada. The dependency links connecting the timing of xylem cell differentiation and cell production were defined and the resulting causal model was analysed with d-sep tests and generalized mixed models with repeated measurements, and tested with Fisher's C statistics to determine whether and how causality propagates through the measured variables. The higher correlations were observed between the dates of emergence of the first developing cells and between the ending of the differentiation phases, while the number of cells was significantly correlated with all phenological phases. The model with eight dependency links was statistically valid for explaining the causes and correlations between the dynamics of cambium phenology. Causal modelling suggested that the phenological phases involved in xylogenesis are closely interconnected by complex relationships of cause and effect, with the onset of cell differentiation being the main factor directly or indirectly triggering all successive phases of xylem maturation.

Causes and correlations in cambium phenology: towards an integrated framework of xylogenesis

PubMed Central

Rossi, Sergio; Morin, Hubert; Deslauriers, Annie

2012-01-01

Although habitually considered as a whole, xylogenesis is a complex process of division and maturation of a pool of cells where the relationship between the phenological phases generating such a growth pattern remains essentially unknown. This study investigated the causal relationships in cambium phenology of black spruce [Picea mariana (Mill.) BSP] monitored for 8 years on four sites of the boreal forest of Quebec, Canada. The dependency links connecting the timing of xylem cell differentiation and cell production were defined and the resulting causal model was analysed with d-sep tests and generalized mixed models with repeated measurements, and tested with Fisher’s C statistics to determine whether and how causality propagates through the measured variables. The higher correlations were observed between the dates of emergence of the first developing cells and between the ending of the differentiation phases, while the number of cells was significantly correlated with all phenological phases. The model with eight dependency links was statistically valid for explaining the causes and correlations between the dynamics of cambium phenology. Causal modelling suggested that the phenological phases involved in xylogenesis are closely interconnected by complex relationships of cause and effect, with the onset of cell differentiation being the main factor directly or indirectly triggering all successive phases of xylem maturation. PMID:22174441

Climate change and decadal shifts in the phenology of larval fishes in the California Current ecosystem

PubMed Central

Asch, Rebecca G.

2015-01-01

Climate change has prompted an earlier arrival of spring in numerous ecosystems. It is uncertain whether such changes are occurring in Eastern Boundary Current Upwelling ecosystems, because these regions are subject to natural decadal climate variability, and regional climate models predict seasonal delays in upwelling. To answer this question, the phenology of 43 species of larval fishes was investigated between 1951 and 2008 off southern California. Ordination of the fish community showed earlier phenological progression in more recent years. Thirty-nine percent of seasonal peaks in larval abundance occurred earlier in the year, whereas 18% were delayed. The species whose phenology became earlier were characterized by an offshore, pelagic distribution, whereas species with delayed phenology were more likely to reside in coastal, demersal habitats. Phenological changes were more closely associated with a trend toward earlier warming of surface waters rather than decadal climate cycles, such as the Pacific Decadal Oscillation and North Pacific Gyre Oscillation. Species with long-term advances and delays in phenology reacted similarly to warming at the interannual time scale as demonstrated by responses to the El Niño Southern Oscillation. The trend toward earlier spawning was correlated with changes in sea surface temperature (SST) and mesozooplankton displacement volume, but not coastal upwelling. SST and upwelling were correlated with delays in fish phenology. For species with 20th century advances in phenology, future projections indicate that current trends will continue unabated. The fate of species with delayed phenology is less clear due to differences between Intergovernmental Panel on Climate Change models in projected upwelling trends. PMID:26159416

Linking belowground and aboveground phenology in two boreal forests in Northeast China.

PubMed

Du, Enzai; Fang, Jingyun

2014-11-01

The functional equilibrium between roots and shoots suggests an intrinsic linkage between belowground and aboveground phenology. However, much less understanding of belowground phenology hinders integrating belowground and aboveground phenology. We measured root respiration (Ra) as a surrogate for root phenology and integrated it with observed leaf phenology and radial growth in a birch (Betula platyphylla)-aspen (Populus davidiana) forest and an adjacent larch (Larix gmelinii) forest in Northeast China. A log-normal model successfully described the seasonal variations of Ra and indicated the initiation, termination and peak date of root phenology. Both root phenology and leaf phenology were highly specific, with a later onset, earlier termination, and shorter period of growing season for the pioneer tree species (birch and aspen) than the dominant tree species (larch). Root phenology showed later initiation, later peak and later termination dates than leaf phenology. An asynchronous correlation of Ra and radial growth was identified with a time lag of approximately 1 month, indicating aprioritization of shoot growth. Furthermore, we found that Ra was strongly correlated with soil temperature and air temperature, while radial growth was only significantly correlated with air temperature, implying a down-regulating effect of temperature. Our results indicate different phenologies between pioneer and dominant species and support a down-regulation hypothesis of plant phenology which can be helpful in understanding forest dynamics in the context of climate change.

High-resolution prediction of leaf onset date in Japan in the 21st century under the IPCC A1B scenario.

PubMed

Hadano, Mayumi; Nasahara, Kenlo Nishida; Motohka, Takeshi; Noda, Hibiki Muraoka; Murakami, Kazutaka; Hosaka, Masahiro

2013-06-01

Reports indicate that leaf onset (leaf flush) of deciduous trees in cool-temperate ecosystems is occurring earlier in the spring in response to global warming. In this study, we created two types of phenology models, one driven only by warmth (spring warming [SW] model) and another driven by both warmth and winter chilling (parallel chill [PC] model), to predict such phenomena in the Japanese Islands at high spatial resolution (500 m). We calibrated these models using leaf onset dates derived from satellite data (Terra/MODIS) and in situ temperature data derived from a dense network of ground stations Automated Meteorological Data Acquisition System. We ran the model using future climate predictions created by the Japanese Meteorological Agency's MRI-AGCM3.1S model. In comparison to the first decade of the 2000s, our results predict that the date of leaf onset in the 2030s will advance by an average of 12 days under the SW model and 7 days under the PC model throughout the study area. The date of onset in the 2090s will advance by 26 days under the SW model and by 15 days under the PC model. The greatest impact will occur on Hokkaido (the northernmost island) and in the central mountains.

Model-data assimilation of multiple phenological observations to constrain and predict leaf area index.

PubMed

Viskari, Toni; Hardiman, Brady; Desai, Ankur R; Dietze, Michael C

2015-03-01

Our limited ability to accurately simulate leaf phenology is a leading source of uncertainty in models of ecosystem carbon cycling. We evaluate if continuously updating canopy state variables with observations is beneficial for predicting phenological events. We employed ensemble adjustment Kalman filter (EAKF) to update predictions of leaf area index (LAI) and leaf extension using tower-based photosynthetically active radiation (PAR) and moderate resolution imaging spectrometer (MODIS) data for 2002-2005 at Willow Creek, Wisconsin, USA, a mature, even-aged, northern hardwood, deciduous forest. The ecosystem demography model version 2 (ED2) was used as the prediction model, forced by offline climate data. EAKF successfully incorporated information from both the observations and model predictions weighted by their respective uncertainties. The resulting. estimate reproduced the observed leaf phenological cycle in the spring and the fall better than a parametric model prediction. These results indicate that during spring the observations contribute most in determining the correct bud-burst date, after which the model performs well, but accurately modeling fall leaf senesce requires continuous model updating from observations. While the predicted net ecosystem exchange (NEE) of CO2 precedes tower observations and unassimilated model predictions in the spring, overall the prediction follows observed NEE better than the model alone. Our results show state data assimilation successfully simulates the evolution of plant leaf phenology and improves model predictions of forest NEE.

Elucidating Inherent Uncertainties in Data Assimilation for Predictions Incorporating Non-stationary Processes - Focus on Predictive Phenology

NASA Astrophysics Data System (ADS)

Lowman, L.; Barros, A. P.

2017-12-01

Data assimilation (DA) is the widely accepted procedure for estimating parameters within predictive models because of the adaptability and uncertainty quantification offered by Bayesian methods. DA applications in phenology modeling offer critical insights into how extreme weather or changes in climate impact the vegetation life cycle. Changes in leaf onset and senescence, root phenology, and intermittent leaf shedding imply large changes in the surface radiative, water, and carbon budgets at multiple scales. Models of leaf phenology require concurrent atmospheric and soil conditions to determine how biophysical plant properties respond to changes in temperature, light and water demand. Presently, climatological records for fraction of photosynthetically active radiation (FPAR) and leaf area index (LAI), the modelled states indicative of plant phenology, are not available. Further, DA models are typically trained on short periods of record (e.g. less than 10 years). Using limited records with a DA framework imposes non-stationarity on estimated parameters and the resulting predicted model states. This talk discusses how uncertainty introduced by the inherent non-stationarity of the modeled processes propagates through a land-surface hydrology model coupled to a predictive phenology model. How water demand is accounted for in the upscaling of DA model inputs and analysis period serves as a key source of uncertainty in the FPAR and LAI predictions. Parameters estimated from different DA effectively calibrate a plant water-use strategy within the land-surface hydrology model. For example, when extreme droughts are included in the DA period, the plants are trained to uptake water, transpire, and assimilate carbon under favorable conditions and quickly shut down at the onset of water stress.

Impacts of Climate Change and Vegetation Dynamics on Runoff in the Mountainous Region of the Haihe River Basin in the Past Five Decades

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lei, Huimin; Yang, Dawen; Huang, Maoyi

2014-04-16

Climate and atmospheric CO2 concentration have changed significantly in the mountainous region of the Haihe River basin over the past five decades. In the study, a process-based terrestrial model, version 4 of the Community Land Model (CLM4), was used to quantify the spatiotemporal changes in runoff over the region, driven by the varying climate factors and CO2 concentration. Overall, our simulations suggest that climate-induced change in runoff in this region show a decreasing trend since 1960. Changes in precipitation, solar radiation, air temperature, and wind speed accounts for 56%, -14%, 13%, -5% of the overall decrease in annual runoff, respectively,more » but their relative contributions vary across the study area. Rising atmospheric CO2 concentration was found to have limited impacts on runoff. Significant decrease in runoff over the southern and northeastern portion of the region is primarily attributed to decreasing precipitation, while decreasing solar radiation and increasing air temperature are the main causes of slight runoff increase in the northern portion. Our results also suggest that the magnitude of decreasing trend could be greatly underestimated if the dynamical interactions of vegetation phenology with the environmental factors are not considered in the modeling, highlighting the importance of including dynamic vegetation phenology in the prediction of runoff in this region.« less

Partitioning of the net CO2 exchange using an automated chamber system reveals plant phenology as key control of production and respiration fluxes in a boreal peatland.

PubMed

Järveoja, Järvi; Nilsson, Mats B; Gažovič, Michal; Crill, Patrick M; Peichl, Matthias

2018-04-30

The net ecosystem CO 2 exchange (NEE) drives the carbon (C) sink-source strength of northern peatlands. Since NEE represents a balance between various production and respiration fluxes, accurate predictions of its response to global changes require an in depth understanding of these underlying processes. Currently, however, detailed information of the temporal dynamics as well as the separate biotic and abiotic controls of the NEE component fluxes is lacking in peatland ecosystems. In this study, we address this knowledge gap by using an automated chamber system established across natural and trenching-/vegetation removal plots to partition NEE into its production (i.e. gross and net primary production; GPP and NPP) and respiration (i.e. ecosystem, heterotrophic and autotrophic respiration; ER, Rh and Ra) fluxes in a boreal peatland in northern Sweden. Our results showed that daily NEE patterns were driven by GPP while variations in ER were governed by Ra rather than Rh. Moreover, we observed pronounced seasonal shifts in the Ra/Rh and above-/belowground NPP ratios throughout the main phenological phases. Generalized linear model analysis revealed that the greenness index derived from digital images (as a proxy for plant phenology) was the strongest control of NEE, GPP and NPP while explaining considerable fractions also in the variations of ER and Ra. In addition, our data exposed greater temperature sensitivity of NPP compared to Rh resulting in enhanced C sequestration with increasing temperature. Overall, our study suggests that the temporal patterns in NEE and its component fluxes are tightly coupled to vegetation dynamics in boreal peatlands and thus challenges previous studies that commonly identify abiotic factors as key drivers. These findings further emphasize the need for integrating detailed information on plant phenology into process-based models to improve predictions of global change impacts on the peatland C cycle. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Evaluating Gridded Spring Indices Using the USA National Phenology Network's Observational Phenology Data

NASA Astrophysics Data System (ADS)

Crimmins, T. M.; Gerst, K.

2017-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) produces and freely delivers daily and short-term forecast maps of spring onset dates at fine spatial scale for the conterminous United States and Alaska using the Spring Indices. These models, which represent the start of biological activity in the spring season, were developed using a long-term observational record of four species of lilacs and honeysuckles contributed by volunteer observers. Three of the four species continue to be tracked through the USA-NPN's phenology observation program, Nature's Notebook. The gridded Spring Index maps have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, anticipating allergy outbreaks and planning agricultural harvest dates. However, to date, there has not been a comprehensive assessment of how well the gridded Spring Index maps accurately reflect phenological activity in lilacs and honeysuckles or other species of plants. In this study, we used observational plant phenology data maintained by the USA-NPN to evaluate how well the gridded Spring Index maps match leaf and flowering onset dates in a) the lilac and honeysuckle species used to construct the models and b) in several species of deciduous trees. The Spring Index performed strongly at predicting the timing of leaf-out and flowering in lilacs and honeysuckles. The average error between predicted and observed date of onset ranged from 5.9 to 11.4 days. Flowering models performed slightly better than leaf-out models. The degree to which the Spring Indices predicted native deciduous tree leaf and flower phenology varied by year, species, and region. Generally, the models were better predictors of leaf and flowering onset dates in the Northeastern and Midwestern US. These results reveal when and where the Spring Indices are a meaningful proxy of phenological activity across the United States.

Population Dynamics and Flight Phenology Model of Codling Moth Differ between Commercial and Abandoned Apple Orchard Ecosystems.

PubMed

Joshi, Neelendra K; Rajotte, Edwin G; Naithani, Kusum J; Krawczyk, Greg; Hull, Larry A

2016-01-01

Apple orchard management practices may affect development and phenology of arthropod pests, such as the codling moth (CM), Cydia pomonella (L.) (Lepidoptera: Tortricidae), which is a serious internal fruit-feeding pest of apples worldwide. Estimating population dynamics and accurately predicting the timing of CM development and phenology events (for instance, adult flight, and egg-hatch) allows growers to understand and control local populations of CM. Studies were conducted to compare the CM flight phenology in commercial and abandoned apple orchard ecosystems using a logistic function model based on degree-days accumulation. The flight models for these orchards were derived from the cumulative percent moth capture using two types of commercially available CM lure baited traps. Models from both types of orchards were also compared to another model known as PETE (prediction extension timing estimator) that was developed in 1970s to predict life cycle events for many fruit pests including CM across different fruit growing regions of the United States. We found that the flight phenology of CM was significantly different in commercial and abandoned orchards. CM male flight patterns for first and second generations as predicted by the constrained and unconstrained PCM (Pennsylvania Codling Moth) models in commercial and abandoned orchards were different than the flight patterns predicted by the currently used CM model (i.e., PETE model). In commercial orchards, during the first and second generations, the PCM unconstrained model predicted delays in moth emergence compared to current model. In addition, the flight patterns of females were different between commercial and abandoned orchards. Such differences in CM flight phenology between commercial and abandoned orchard ecosystems suggest potential impact of orchard environment and crop management practices on CM biology.

Population Dynamics and Flight Phenology Model of Codling Moth Differ between Commercial and Abandoned Apple Orchard Ecosystems

PubMed Central

Joshi, Neelendra K.; Rajotte, Edwin G.; Naithani, Kusum J.; Krawczyk, Greg; Hull, Larry A.

2016-01-01

Apple orchard management practices may affect development and phenology of arthropod pests, such as the codling moth (CM), Cydia pomonella (L.) (Lepidoptera: Tortricidae), which is a serious internal fruit-feeding pest of apples worldwide. Estimating population dynamics and accurately predicting the timing of CM development and phenology events (for instance, adult flight, and egg-hatch) allows growers to understand and control local populations of CM. Studies were conducted to compare the CM flight phenology in commercial and abandoned apple orchard ecosystems using a logistic function model based on degree-days accumulation. The flight models for these orchards were derived from the cumulative percent moth capture using two types of commercially available CM lure baited traps. Models from both types of orchards were also compared to another model known as PETE (prediction extension timing estimator) that was developed in 1970s to predict life cycle events for many fruit pests including CM across different fruit growing regions of the United States. We found that the flight phenology of CM was significantly different in commercial and abandoned orchards. CM male flight patterns for first and second generations as predicted by the constrained and unconstrained PCM (Pennsylvania Codling Moth) models in commercial and abandoned orchards were different than the flight patterns predicted by the currently used CM model (i.e., PETE model). In commercial orchards, during the first and second generations, the PCM unconstrained model predicted delays in moth emergence compared to current model. In addition, the flight patterns of females were different between commercial and abandoned orchards. Such differences in CM flight phenology between commercial and abandoned orchard ecosystems suggest potential impact of orchard environment and crop management practices on CM biology. PMID:27713702

e-phenology: monitoring leaf phenology and tracking climate changes in the tropics

NASA Astrophysics Data System (ADS)

Morellato, Patrícia; Alberton, Bruna; Almeida, Jurandy; Alex, Jefersson; Mariano, Greice; Torres, Ricardo

2014-05-01

The e-phenology is a multidisciplinary project combining research in Computer Science and Phenology. Its goal is to attack theoretical and practical problems involving the use of new technologies for remote phenological observation aiming to detect local environmental changes. It is geared towards three objectives: (a) the use of new technologies of environmental monitoring based on remote phenology monitoring systems; (b) creation of a protocol for a Brazilian long term phenology monitoring program and for the integration across disciplines, advancing our knowledge of seasonal responses within tropics to climate change; and (c) provide models, methods and algorithms to support management, integration and analysis of data of remote phenology systems. The research team is composed by computer scientists and biology researchers in Phenology. Our first results include: Phenology towers - We set up the first phenology tower in our core cerrado-savanna 1 study site at Itirapina, São Paulo, Brazil. The tower received a complete climatic station and a digital camera. The digital camera is set up to take daily sequence of images (five images per hour, from 6:00 to 18:00 h). We set up similar phenology towers with climatic station and cameras in five more sites: cerrado-savanna 2 (Pé de Gigante, SP), cerrado grassland 3 (Itirapina, SP), rupestrian fields 4 ( Serra do Cipo, MG), seasonal forest 5 (Angatuba, SP) and Atlantic raiforest 6 (Santa Virginia, SP). Phenology database - We finished modeling and validation of a phenology database that stores ground phenology and near-remote phenology, and we are carrying out the implementation with data ingestion. Remote phenology and image processing - We performed the first analyses of the cerrado sites 1 to 4 phenology derived from digital images. Analysis were conducted by extracting color information (RGB Red, Green and Blue color channels) from selected parts of the image named regions of interest (ROI). using the green color channel. We analyzed a daily sequence of images (6:00 to 18:00 h). Our results are innovative and indicate the great variation in color change response for tropical trees. We validate the camera phenology with our on the ground direct observation in the core cerrado site 1. We are developing a Image processing software to authomatic process the digital images and to generate the time series for further analyses. New techniques and image features have been used to extract seasonal features from data and for data processing, such as machine learning and visual rhythms. Machine learning was successful applied to identify similar species within the image. Visual rhythms show up as a new analytic tool for phenological interpretation. Next research steps include the analyses of longer data series, correlation with local climatic data, analyses and comparison of patterns among different vegetation sites, prepare a compressive protocol for digital camera phenology and develop new technologies to access vegetation changes using digital cameras. Support: FAPESP-Micorsoft Research, CNPq, CAPES.

Host phenology and leaf effects on susceptibility of California bay laurel to Phytophthora ramorum

Treesearch

Steven F. Johnston; Michael F. Cohen; Tamas Torok; Ross K. Meentemeyer; Nathan E. Rank

2016-01-01

Spread of the plant pathogen Phytophthora ramorum, causal agent of the forest disease sudden oak death, is driven by a few competent hosts that support spore production from foliar lesions. The relationship between traits of a principal foliar host, California bay laurel (Umbellularia californica), and susceptibility to

Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

NASA Astrophysics Data System (ADS)

Verma, Manish K.

Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in-situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

Extraction of Rice Phenological Differences under Heavy Metal Stress Using EVI Time-Series from HJ-1A/B Data.

PubMed

Liu, Shuyuan; Liu, Xiangnan; Liu, Meiling; Wu, Ling; Ding, Chao; Huang, Zhi

2017-05-30

An effective method to monitor heavy metal stress in crops is of critical importance to assure agricultural production and food security. Phenology, as a sensitive indicator of environmental change, can respond to heavy metal stress in crops and remote sensing is an effective method to detect plant phenological changes. This study focused on identifying the rice phenological differences under varied heavy metal stress using EVI (enhanced vegetation index) time-series, which was obtained from HJ-1A/B CCD images and fitted with asymmetric Gaussian model functions. We extracted three phenological periods using first derivative analysis: the tillering period, heading period, and maturation period; and constructed two kinds of metrics with phenological characteristics: date-intervals and time-integrated EVI, to explore the rice phenological differences under mild and severe stress levels. Results indicated that under severe stress the values of the metrics for presenting rice phenological differences in the experimental areas of heavy metal stress were smaller than the ones under mild stress. This finding represents a new method for monitoring heavy metal contamination through rice phenology.

Change in the Green-Up Dates for Quercus mongolica in Northeast China and Its Climate-Driven Mechanism from 1962 to 2012.

PubMed

Fan, Deqin; Zhu, Wenquan; Zheng, Zhoutao; Zhang, Donghai; Pan, Yaozhong; Jiang, Nan; Zhou, Xiafei

2015-01-01

The currently available studies on the green-up date were mainly based on ground observations and/or satellite data, and few model simulations integrated with wide coverage satellite data have been reported at large scale over a long time period (i.e., > 30 years). In this study, we combined phenology mechanism model, long-term climate data and synoptic scale remote sensing data to investigate the change in the green-up dates for Quercus mongolica over 33 weather stations in Northeast China and its climate-driven mechanism during 1962-2012. The results indicated that the unified phenology model can be well parameterized with the satellite derived green-up dates. The optimal daily mean temperature for chilling effect was between -27°C and 1°C for Q. mongolica in Northeast China, while the optimal daily mean temperature for forcing effect was above -3°C. The green-up dates for Q. mongolica across Northeast China showed a delayed latitudinal gradient of 2.699 days degree-1, with the earliest date on the Julian day 93 (i.e., 3th April) in the south and the latest date on the Julian day 129 (i.e., 9th May) in the north. The green-up date for Q. mongolica in Northeast China has advanced 6.6 days (1.3 days decade-1) from 1962 to 2012. With the prevailing warming in autumn, winter and spring in Northeast China during the past 51 years, the chilling effect for Q. mongolica has been weakened, while the forcing effect has been enhanced. The advancing trend in the green-up dates for Q. mongolica implied that the enhanced forcing effect to accelerate green-up was stronger than the weakened chilling effect to hold back green-up while the changes of both effects were caused by the warming climate.

Net carbon uptake has increased through warming-induced changes in temperate forest phenology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keenan, Trevor; Gray, Josh; Friedl, Mark

2014-01-01

The timing of phenological events exerts a strong control over ecosystem function and leads to multiple feedbacks to the climate system1. Phenology is inherently sensitive to temperature (though the exact sensitivity is disputed2) and recent warming is reported to have led to earlier spring, later autumn3,4 and increased vegetation activity5,6. Such greening could be expected to enhance ecosystem carbon uptake7,8, though reports also suggest decreased uptake for boreal forests4,9. Here we assess changes in phenology of temperate forests over the eastern US during the past two decades, and quantify the resulting changes in forest carbon storage. We combine long-term groundmore » observations of phenology, satellite indices, and ecosystem-scale carbon dioxide flux measurements, along with 18 terrestrial biosphere models. We observe a strong trend of earlier spring and later autumn. In contrast to previous suggestions4,9 we show that carbon uptake through photosynthesis increased considerably more than carbon release through respiration for both an earlier spring and later autumn. The terrestrial biosphere models tested misrepresent the temperature sensitivity of phenology, and thus the effect on carbon uptake. Our analysis of the temperature-phenology-carbon coupling suggests a current and possible future enhancement of forest carbon uptake due to changes in phenology. This constitutes a negative feedback to climate change, and is serving to slow the rate of warming.« less

Spatial and temporal variability of landscape phenology based on EVI data

NASA Astrophysics Data System (ADS)

Hunkár, Márta; Szenyán, Ildikó

2013-04-01

Increasing number of climate change studies in the 1990s evolved the interest in phenological research and thus the demand for phenological observations has increased substantially. Mainly, rising air temperatures in recent decades and the clear phenological response of plants and animals to this increase have caused the growing interest. Monitoring phenological phases is carried out in many European countries. Each country has its own database, in some cases still on paper, mostly on databank-systems, going back in many cases to the 1950s. Recently remote sensing phenology, the use of satellites to track phenological events can complement or in some cases substitute ground observation networks. Satellites provide a unique perspective of the planet and allow for regular, even daily, monitoring of the entire global land surface. Because the most frequently used satellite sensors for monitoring phenological events have relatively large "footprints" on the land surface, they gather data about entire ecosystems or regions rather than individual species. Remote sensing phenology can reveal broad-scale phenological trends that would be difficult, if not impossible, to detect from the ground, and because data collection by satellite sensors can be standardized, the data are reliably objective. Obviously remote sensing data are not the traditional phenological phases but they are reflectance (ρ) in different spectral channels. The status of the vegetation is in close connection with its reflectance especially in the near infrared and red spectrums. In our study we used "Enhanced Vegetation Index" (EVI) to characterize the status of vegetation on a sample area with the size of 5 km x 5 km inhomogeneous terrain NW corner: 46o 19' 33,6"N, 17o 42' 38,52"E , NE corner: 46o 19' 33,6"N; 17o 46' 15,96"E; SW corner: 46o 17' 3,84"N; 17o 41' 50,28"E, SE corner: 46o 17' 3,84"N; 17o 45'27"E. EVI data are available from MODIS placed at Terra and Aqua satellites. High resolution (250m x250m pixels) composite data with 8 day frequency for the last ten years will be analysed. Spatial variation of EVI data is analysed by the variation coefficients of that 400 pixels of the sample area. Temporal variation in EVI data are modelled using piecewise sigmoid models. Each growth cycle is modelled using two sigmoid functions: one for the growth phase, one for the senescence phase. To identify phenological transition dates, the rate of change in the curvature of the fitted logistic models is used for each year. Specifically, transition dates correspond to the times at which the rate of change in curvature in the EVI data exhibits local minima or maximums. For each growth cycle, four phenological transition dates are recorded based on the approach described above. The corresponding phenological transition dates are defined as the onset of greenness increase (F1), the onset of greenness maximum (F2), the onset of greenness decrease (F3), and the onset of greenness minimum (F4). The dates of that four "landscape phenological phases" are compared with the daily meteorological data derived from the closest meteorological station.

Temperature-mediated growth thresholds of Acrobasis vaccinii (Lepidoptera: Pyralidae)

USDA-ARS?s Scientific Manuscript database

Degree-day models link ambient temperature to the development of insects, making such models valuable tools in integrated pest management. Phenology models increase management efficacy by quantifying and predicting pest phenology. In Wisconsin, the top pest of cranberry production is the cranberry f...

The USA-NPN Information Management System: A tool in support of phenological assessments

NASA Astrophysics Data System (ADS)

Rosemartin, A.; Vazquez, R.; Wilson, B. E.; Denny, E. G.

2009-12-01

The USA National Phenology Network (USA-NPN) serves science and society by promoting a broad understanding of plant and animal phenology and the relationships among phenological patterns and all aspects of environmental change. Data management and information sharing are central to the USA-NPN mission. The USA-NPN develops, implements, and maintains a comprehensive Information Management System (IMS) to serve the needs of the network, including the collection, storage and dissemination of phenology data, access to phenology-related information, tools for data interpretation, and communication among partners of the USA-NPN. The IMS includes components for data storage, such as the National Phenology Database (NPD), and several online user interfaces to accommodate data entry, data download, data visualization and catalog searches for phenology-related information. The IMS is governed by a set of standards to ensure security, privacy, data access, and data quality. The National Phenology Database is designed to efficiently accommodate large quantities of phenology data, to be flexible to the changing needs of the network, and to provide for quality control. The database stores phenology data from multiple sources (e.g., partner organizations, researchers and citizen observers), and provides for integration with legacy datasets. Several services will be created to provide access to the data, including reports, visualization interfaces, and web services. These services will provide integrated access to phenology and related information for scientists, decision-makers and general audiences. Phenological assessments at any scale will rely on secure and flexible information management systems for the organization and analysis of phenology data. The USA-NPN’s IMS can serve phenology assessments directly, through data management and indirectly as a model for large-scale integrated data management.

Can we detect a nonlinear response to temperature in European plant phenology?

NASA Astrophysics Data System (ADS)

Jochner, Susanne; Sparks, Tim H.; Laube, Julia; Menzel, Annette

2016-10-01

Over a large temperature range, the statistical association between spring phenology and temperature is often regarded and treated as a linear function. There are suggestions that a sigmoidal relationship with definite upper and lower limits to leaf unfolding and flowering onset dates might be more realistic. We utilised European plant phenological records provided by the European phenology database PEP725 and gridded monthly mean temperature data for 1951-2012 calculated from the ENSEMBLES data set E-OBS (version 7.0). We analysed 568,456 observations of ten spring flowering or leafing phenophases derived from 3657 stations in 22 European countries in order to detect possible nonlinear responses to temperature. Linear response rates averaged for all stations ranged between -7.7 (flowering of hazel) and -2.7 days °C-1 (leaf unfolding of beech and oak). A lower sensitivity at the cooler end of the temperature range was detected for most phenophases. However, a similar lower sensitivity at the warmer end was not that evident. For only ˜14 % of the station time series (where a comparison between linear and nonlinear model was possible), nonlinear models described the relationship significantly better than linear models. Although in most cases simple linear models might be still sufficient to predict future changes, this linear relationship between phenology and temperature might not be appropriate when incorporating phenological data of very cold (and possibly very warm) environments. For these cases, extrapolations on the basis of linear models would introduce uncertainty in expected ecosystem changes.

The Use of Climate Projections in the Modelling of Bud Burst

NASA Astrophysics Data System (ADS)

O'Neill, Bridget F.; Caffara, Amelia; Gleeson, Emily; Semmler, Tido; McGrath, Ray; Donnelly, Alison

2010-05-01

Recent changes in global climate, such as increasing temperature, have had notable effects on the phenology (timing of biological events) of plants. The effects are variable across habitats and between species, but increasing temperatures have been shown to advance certain key phenophases of trees, such as bud burst (beginning of leaf unfolding). This project considered climate change impacts on phenology of plants at a local scale in Ireland. The output from the ENSEMBLES climate simulations were down-scaled to Ireland and utilised by a phenological model to project changes over the next 50-100 years. This project helps to showcase the potential use of climate simulations in phenological research.

Surface phenology and satellite sensor-derived onset of greenness: An initial comparison

USGS Publications Warehouse

Schwartz, Mark D.; Reed, Bradley C.

1999-01-01

The objective of this work was to document the utility of phenological data derived from satellite sensors by comparing them with modelled phenology. Surface phenological model outputs (first leaf and first bloom dates) were correlated positively with satellite sensor-derived start of season (SOS) dates for 1991-1995 across the eastern United States. The correlation was highest for forest (r 0.62 for deciduous trees and 0.64 for mixed woodland) and tall grass (r 0.46) and lowest for short grass (r 0.37). The average correlation over all land cover types was 0.61. Average SOS dates were consistently earlier than Spring Index dates across all land cover types. This finding and limited native tree phenology data suggest that the SOS technique detects understorey green-up in the forest rather than overstorey species. The biweekly temporal resolution of the satellite sensor data placed an upper limit on prediction accuracy; thus, year-to-year variations at individual sites were typically small. Nevertheless, the correct biweek SOS could be identified from the surface models 61% of the time, and 1 biweek 96% of the time. Further temporal refinement of the satellite sensor measurements is necessary in order to connect them with surface phenology adequately and to develop links among 'green wave' components in selected biomes.

Monitoring cotton root rot by synthetic Sentinel-2 NDVI time series using improved spatial and temporal data fusion.

PubMed

Wu, Mingquan; Yang, Chenghai; Song, Xiaoyu; Hoffmann, Wesley Clint; Huang, Wenjiang; Niu, Zheng; Wang, Changyao; Li, Wang; Yu, Bo

2018-01-31

To better understand the progression of cotton root rot within the season, time series monitoring is required. In this study, an improved spatial and temporal data fusion approach (ISTDFA) was employed to combine 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Different Vegetation Index (NDVI) and 10-m Sentinetl-2 NDVI data to generate a synthetic Sentinel-2 NDVI time series for monitoring this disease. Then, the phenology of healthy cotton and infected cotton was modeled using a logistic model. Finally, several phenology parameters, including the onset day of greenness minimum (OGM), growing season length (GLS), onset of greenness increase (OGI), max NDVI value, and integral area of the phenology curve, were calculated. The results showed that ISTDFA could be used to combine time series MODIS and Sentinel-2 NDVI data with a correlation coefficient of 0.893. The logistic model could describe the phenology curves with R-squared values from 0.791 to 0.969. Moreover, the phenology curve of infected cotton showed a significant difference from that of healthy cotton. The max NDVI value, OGM, GSL and the integral area of the phenology curve for infected cotton were reduced by 0.045, 30 days, 22 days, and 18.54%, respectively, compared with those for healthy cotton.

Interannual variations in spring phenology and their response to climate change across the Tibetan Plateau from 1982 to 2013.

PubMed

Liu, Lingling; Zhang, Xiaoyang; Donnelly, Alison; Liu, Xinjie

2016-10-01

Land surface phenology has been widely used to evaluate the effects of climate change on terrestrial ecosystems in recent decades. Climate warming on the Tibetan Plateau (1960-2010, 0.2 °C/decade) has been found to be greater than the global average (1951-2012, 0.12 °C/decade), which has had a significant impact on the timing of spring greenup. However, the magnitude and direction of change in spring phenology and its response to warming temperature and precipitation are currently under scientific debate. In an attempt to explore this issue further, we detected the onset of greenup based on the time series of daily two-band enhanced vegetation index (EVI2) from the advanced very high resolution radiometer (AVHRR) long-term data record (LTDR; 1982-1999) and Moderate Resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG; 2000-2013) using hybrid piecewise logistic models. Further, we examined the temporal trend in greenup onset in both individual pixels and ecoregions across the entire Tibetan Plateau over the following periods: 1982-1999, 2000-2013, and 1982-2013. The interannual variation in greenup onset was linked to the mean temperature and cumulative precipitation in the preceding month, and total precipitation during winter and spring, respectively. Finally, we investigated the relationship between interannual variation in greenup onset dates and temperature and precipitation from 1982 to 2013 at different elevational zones for different ecoregions. The results revealed no significant trend in the onset of greenup from 1982 to 2013 in more than 86 % of the Tibetan Plateau. For each study period, statistically significant earlier greenup trends were observed mainly in the eastern meadow regions while later greenup trends mainly occurred in the southwestern steppe and meadow regions both with areal coverage of less than 8 %. Although spring phenology was negatively correlated with spring temperature and precipitation in the majority of pixels (>60 %), only 15 % and 10 % of these correlations were significant (P < 0.1), respectively. Climate variables had varying effects on the ecoregions with altitude. In the meadow ecoregion, greenup onset was significantly affected by both temperature and precipitation from 3500 to 4000 m altitude and by temperature alone from 4000 to 4500 m. In contrast, greenup onset across all elevational zones, in the steppe ecoregion, was not directly driven by either spring temperature or precipitation, which was likely impacted by soil moisture associated with warming temperature. These findings highlight the complex impacts of climate change on spring phenology in the Tibetan Plateau.

Simulating crop phenology in the Community Land Model and its impact on energy and carbon fluxes

USDA-ARS?s Scientific Manuscript database

A reasonable representation of crop phenology and biophysical processes in land surface models is necessary to accurately simulate energy, water and carbon budgets at the field, regional, and global scales. However, the evaluation of crop models that can be coupled to earth system models is relative...

Comprehensive ecosystem model-experiment synthesis using multiple datasets at two temperate forest free-air CO2 enrichment experiments: model performance and compensating biases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, Anthony P; Hanson, Paul J; DeKauwe, Martin G

2014-01-01

Free Air CO2 Enrichment (FACE) experiments provide a remarkable wealth of data to test the sensitivities of terrestrial ecosystem models (TEMs). In this study, a broad set of 11 TEMs were compared to 22 years of data from two contrasting FACE experiments in temperate forests of the south eastern US the evergreen Duke Forest and the deciduous Oak Ridge forest. We evaluated the models' ability to reproduce observed net primary productivity (NPP), transpiration and Leaf Area index (LAI) in ambient CO2 treatments. Encouragingly, many models simulated annual NPP and transpiration within observed uncertainty. Daily transpiration model errors were often relatedmore » to errors in leaf area phenology and peak LAI. Our analysis demonstrates that the simulation of LAI often drives the simulation of transpiration and hence there is a need to adopt the most appropriate of hypothesis driven methods to simulate and predict LAI. Of the three competing hypotheses determining peak LAI (1) optimisation to maximise carbon export, (2) increasing SLA with canopy depth and (3) the pipe model the pipe model produced LAI closest to the observations. Modelled phenology was either prescribed or based on broader empirical calibrations to climate. In some cases, simulation accuracy was achieved through compensating biases in component variables. For example, NPP accuracy was sometimes achieved with counter-balancing biases in nitrogen use efficiency and nitrogen uptake. Combined analysis of parallel measurements aides the identification of offsetting biases; without which over-confidence in model abilities to predict ecosystem function may emerge, potentially leading to erroneous predictions of change under future climates.« less

Resource waves: phenological diversity enhances foraging opportunities for mobile consumers

USGS Publications Warehouse

Armstrong, Jonathan B.; Takimoto, Gaku; Schindler, Daniel E.; Hayes, Matthew M.; Kauffman, Matthew J.

2016-01-01

Time can be a limiting constraint for consumers, particularly when resource phenology mediates foraging opportunity. Though a large body of research has explored how resource phenology influences trophic interactions, this work has focused on the topics of trophic mismatch or predator swamping, which typically occur over short periods, at small spatial extents or coarse resolutions. In contrast many consumers integrate across landscape heterogeneity in resource phenology, moving to track ephemeral food sources that propagate across space as resource waves. Here we provide a conceptual framework to advance the study of phenological diversity and resource waves. We define resource waves, review evidence of their importance in recent case studies, and demonstrate their broader ecological significance with a simulation model. We found that consumers ranging from fig wasps (Chalcidoidea) to grizzly bears (Ursus arctos) exploit resource waves, integrating across phenological diversity to make resource aggregates available for much longer than their component parts. In model simulations, phenological diversity was often more important to consumer energy gain than resource abundance per se. Current ecosystem-based management assumes that species abundance mediates the strength of trophic interactions. Our results challenge this assumption and highlight new opportunities for conservation and management. Resource waves are an emergent property of consumer–resource interactions and are broadly significant in ecology and conservation.

Linkages between Land Surface Phenology Metrics and Natural and Anthropogenic Events in Drylands (Invited)

NASA Astrophysics Data System (ADS)

de Beurs, K.; Brown, M. E.; Ahram, A.; Walker, J.; Henebry, G. M.

2013-12-01

Tracking vegetation dynamics across landscapes using remote sensing, or 'land surface phenology,' is a key mechanism that allows us to understand ecosystem changes. Land surface phenology models rely on vegetation information from remote sensing, such as the datasets derived from the Advanced Very High Resolution Radiometer (AVHRR), the newer MODIS sensors on Aqua and Terra, and sometimes the higher spatial resolution Landsat data. Vegetation index data can aid in the assessment of variables such as the start of season, growing season length and overall growing season productivity. In this talk we use Landsat, MODIS and AVHRR data and derive growing season metrics based on land surface phenology models that couple vegetation indices with satellite derived accumulated growing degreeday and evapotranspiration estimates. We calculate the timing and the height of the peak of the growing season and discuss the linkage of these land surface phenology metrics with natural and anthropogenic changes on the ground in dryland ecosystems. First we will discuss how the land surface phenology metrics link with annual and interannual price fluctuations in 229 markets distributed over Africa. Our results show that there is a significant correlation between the peak height of the growing season and price increases for markets in countries such as Nigeria, Somalia and Niger. We then demonstrate how land surface phenology metrics can improve models of post-conflict resolution in global drylands. We link the Uppsala Conflict Data Program's dataset of political, economic and social factors involved in civil war termination with an NDVI derived phenology metric and the Palmer Drought Severity Index (PDSI). An analysis of 89 individual conflicts in 42 dryland countries (totaling 892 individual country-years of data between 1982 and 2005) revealed that, even accounting for economic and political factors, countries that have higher NDVI growth following conflict have a lower risk of reverting to civil war. Finally, the patchy and heterogeneous arrangement of vegetation in dryland areas sometimes complicates the extraction of phenological signals using existing remote sensing data. We conclude by demonstrating how the phenological analysis of a range of dryland land cover classes benefits from the availability of synthetic images at Landsat spatial resolution and MODIS time intervals.

Modeling the effects of climate change-induced shifts in reproductive phenology on temperature-dependent traits.

PubMed

Telemeco, Rory S; Abbott, Karen C; Janzen, Fredric J

2013-05-01

By altering phenology, organisms have the potential to match life-history events with suitable environmental conditions. Because of this, phenological plasticity has been proposed as a mechanism whereby populations might buffer themselves from climate change. We examine the potential buffering power of advancing one aspect of phenology, nesting date, on sex ratio in painted turtles (Chrysemys picta), a species with temperature-dependent sex determination. We developed a modified constant temperature equivalent model that accounts for the effect of the interaction among climate change, oviposition date, and seasonal thermal pattern on temperature during sexual differentiation and thus on offspring sex ratio. Our results suggest that females will not be able to buffer their progeny from the negative consequences of climate change by adjusting nesting date alone. Not only are offspring sex ratios predicted to become 100% female, but our model suggests that many nests will fail. Because the seasonal thermal trends that we consider are experienced by most temperate species, our result that adjusting spring phenology alone will be insufficient to counter the effects of directional climate change may be broadly applicable.

Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic data from Landsat and MODIS BRDF/albedo product

USDA-ARS?s Scientific Manuscript database

Climate warming over the past half century has led to observable changes in vegetation phenology and growing season length; which can be measured globally using remote sensing derived vegetation indices. Previous studies in mid- and high northern latitude systems show temperature driven earlier spri...

Can we detect a nonlinear response to temperature in European plant phenology?

PubMed

Jochner, Susanne; Sparks, Tim H; Laube, Julia; Menzel, Annette

2016-10-01

Over a large temperature range, the statistical association between spring phenology and temperature is often regarded and treated as a linear function. There are suggestions that a sigmoidal relationship with definite upper and lower limits to leaf unfolding and flowering onset dates might be more realistic. We utilised European plant phenological records provided by the European phenology database PEP725 and gridded monthly mean temperature data for 1951-2012 calculated from the ENSEMBLES data set E-OBS (version 7.0). We analysed 568,456 observations of ten spring flowering or leafing phenophases derived from 3657 stations in 22 European countries in order to detect possible nonlinear responses to temperature. Linear response rates averaged for all stations ranged between -7.7 (flowering of hazel) and -2.7 days °C -1 (leaf unfolding of beech and oak). A lower sensitivity at the cooler end of the temperature range was detected for most phenophases. However, a similar lower sensitivity at the warmer end was not that evident. For only ∼14 % of the station time series (where a comparison between linear and nonlinear model was possible), nonlinear models described the relationship significantly better than linear models. Although in most cases simple linear models might be still sufficient to predict future changes, this linear relationship between phenology and temperature might not be appropriate when incorporating phenological data of very cold (and possibly very warm) environments. For these cases, extrapolations on the basis of linear models would introduce uncertainty in expected ecosystem changes.

Comparison of three models predicting developmental milestones given environmental and individual variation

Treesearch

Estella Gilbert; James A. Powell; Jesse A. Logan; Barbara J. Bentz

2004-01-01

In all organisms, phenotypic variability is an evolutionary stipulation. Because the development of poikilothermic organisms depends directly on the temperature of their habitat, environmental variability is also an integral factor in models of their phenology. In this paper we present two existing phenology models, the distributed delay model and the Sharpe and...

Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset

NASA Astrophysics Data System (ADS)

Czernecki, Bartosz; Nowosad, Jakub; Jabłońska, Katarzyna

2018-04-01

Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial data can be obtained from airborne sensors and preprocessed gridded meteorological data, not many studies robustly benefit from these data sources. Therefore, the main aim of this study is to create and evaluate different statistical models for reconstructing, predicting, and improving quality of phenological phases monitoring with the use of satellite and meteorological products. A quality-controlled dataset of the 13 BBCH plant phenophases in Poland was collected for the period 2007-2014. For each phenophase, statistical models were built using the most commonly applied regression-based machine learning techniques, such as multiple linear regression, lasso, principal component regression, generalized boosted models, and random forest. The quality of the models was estimated using a k-fold cross-validation. The obtained results showed varying potential for coupling meteorological derived indices with remote sensing products in terms of phenological modeling; however, application of both data sources improves models' accuracy from 0.6 to 4.6 day in terms of obtained RMSE. It is shown that a robust prediction of early phenological phases is mostly related to meteorological indices, whereas for autumn phenophases, there is a stronger information signal provided by satellite-derived vegetation metrics. Choosing a specific set of predictors and applying a robust preprocessing procedures is more important for final results than the selection of a particular statistical model. The average RMSE for the best models of all phenophases is 6.3, while the individual RMSE vary seasonally from 3.5 to 10 days. Models give reliable proxy for ground observations with RMSE below 5 days for early spring and late spring phenophases. For other phenophases, RMSE are higher and rise up to 9-10 days in the case of the earliest spring phenophases.

The USA National Phenology Network: A national science and monitoring program for understanding climate change

NASA Astrophysics Data System (ADS)

Weltzin, J.

2009-04-01

Patterns of phenology for plants and animals control ecosystem processes, determine land surface properties, control biosphere-atmosphere interactions, and affect food production, health, conservation, and recreation. Although phenological data and models have applications related to scientific research, education and outreach, agriculture, tourism and recreation, human health, and natural resource conservation and management, until recently there was no coordinated effort to understand phenology at the national scale in the United States. The USA National Phenology Network (USA-NPN; www.usanpn.org), established in 2007, is an emerging and exciting partnership between federal agencies, the academic community, and the general public to establish a national science and monitoring initiative focused on phenology. The first year of operation of USA-NPN produced many new phenology products and venues for phenology research and citizen involvement. Products include a new web-site (www.usanpn.org) that went live in June 2008; the web-site includes a tool for on-line data entry, and serves as a clearinghouse for products and information to facilitate research and communication related to phenology. The new core Plant Phenology Program includes profiles for 200 vetted local, regional, and national plant species with descriptions and (BBCH-consistent) monitoring protocols, as well as templates for addition of new species. A partnership program describes how other monitoring networks can engage with USA-NPN to collect, manage or disseminate phenological information for science, health, education, management or predictive service applications. Project BudBurst, a USA-NPN field campaign for citizen scientists, went live in February 2008, and now includes over 3000 registered observers monitoring 4000 plants across the nation. For 2009 and beyond, we will initiate a new Wildlife Phenology Program, create an on-line clearing-house for phenology education and outreach, strengthen our national land surface phenology program, continue the development of regional phenology networks, and improve tools for data entry, download and visualization.

High-resolution prediction of leaf onset date in Japan in the 21st century under the IPCC A1B scenario

PubMed Central

Hadano, Mayumi; Nasahara, Kenlo Nishida; Motohka, Takeshi; Noda, Hibiki Muraoka; Murakami, Kazutaka; Hosaka, Masahiro

2013-01-01

Reports indicate that leaf onset (leaf flush) of deciduous trees in cool-temperate ecosystems is occurring earlier in the spring in response to global warming. In this study, we created two types of phenology models, one driven only by warmth (spring warming [SW] model) and another driven by both warmth and winter chilling (parallel chill [PC] model), to predict such phenomena in the Japanese Islands at high spatial resolution (500 m). We calibrated these models using leaf onset dates derived from satellite data (Terra/MODIS) and in situ temperature data derived from a dense network of ground stations Automated Meteorological Data Acquisition System. We ran the model using future climate predictions created by the Japanese Meteorological Agency's MRI-AGCM3.1S model. In comparison to the first decade of the 2000s, our results predict that the date of leaf onset in the 2030s will advance by an average of 12 days under the SW model and 7 days under the PC model throughout the study area. The date of onset in the 2090s will advance by 26 days under the SW model and by 15 days under the PC model. The greatest impact will occur on Hokkaido (the northernmost island) and in the central mountains. PMID:23789086

New insights on plant phenological response to temperature revealed from long-term widespread observations in China.

PubMed

Zhang, Haicheng; Liu, Shuguang; Regnier, Pierre; Yuan, Wenping

2018-05-01

Constraints of temperature on spring plant phenology are closely related to plant growth, vegetation dynamics, and ecosystem carbon cycle. However, the effects of temperature on leaf onset, especially for winter chilling, are still not well understood. Using long-term, widespread in situ phenology observations collected over China for multiple plant species, this study analyzes the quantitative response of leaf onset to temperature, and compares empirical findings with existing theories and modeling approaches, as implemented in 18 phenology algorithms. Results show that the growing degree days (GDD) required for leaf onset vary distinctly among plant species and geographical locations as well as at organizational levels (species and community), pointing to diverse adaptation strategies. Chilling durations (CHD) needed for releasing bud dormancy decline monotonously from cold to warm areas with very limited interspecies variations. Results also reveal that winter chilling is a crucial component of phenology models, and its effect is better captured with an index that accounts for the inhomogeneous effectiveness of low temperature to chilling rate than with the conventional CHD index. The impact of spring warming on leaf onset is nonlinear, better represented by a logistical function of temperature than by the linear function currently implemented in biosphere models. The optimized base temperatures for thermal accumulation and the optimal chilling temperatures are species-dependent and average at 6.9 and 0.2°C, respectively. Overall, plants' chilling requirement is not a constant, and more chilling generally results in less requirement of thermal accumulation for leaf onset. Our results clearly demonstrate multiple deficiencies of the parameters (e.g., base temperature) and algorithms (e.g., method for calculating GDD) in conventional phenology models to represent leaf onset. Therefore, this study not only advances our mechanistic and quantitative understanding of temperature controls on leaf onset but also provides critical information for improving existing phenology models. © 2017 John Wiley & Sons Ltd.

Spatiotemporal phenological changes in fall foliage peak coloration in deciduous forest and the responses to climatic variation

NASA Astrophysics Data System (ADS)

Xie, Y.; Wilson, A. M.

2017-12-01

Plant phenology studies typically focus on the beginning and end of the growing season in temperate forests. We know too little about fall foliage peak coloration, which is a bioindicator of plant response in autumn to environmental changes, an important visual cue in fall associated with animal activities, and a key element in fall foliage ecotourism. Spatiotemporal changes in timing of fall foliage peak coloration of temperate forests and the associated environmental controls are not well understood. In this study, we examined multiple color indices to estimate Land Surface Phenology (LSP) of fall foliage peak coloration of deciduous forest in the northeastern USA using Moderate Resolution Imaging Spectroradiometer (MODIS) daily imagery from 2000 to 2015. We used long term phenology ground observations to validate our estimated LSP, and found that Visible Atmospherically Resistant Index (VARI) and Plant Senescence Reflectance Index (PSRI) were good metrics to estimate peak and end of leaf coloration period of deciduous forest. During the past 16 years, the length of period with peak fall foliage color of deciduous forest at southern New England and northern Appalachian forests regions became longer (0.3 7.7 days), mainly driven by earlier peak coloration. Northern New England, southern Appalachian forests and Ozark and Ouachita mountains areas had shorter period (‒0.2 ‒9.2 days) mainly due to earlier end of leaf coloration. Changes in peak and end of leaf coloration not only were associated with changing temperature in spring and fall, but also to drought and heat in summer, and heavy precipitation in both summer and fall. The associations between leaf peak coloration phenology and climatic variations were not consistent among ecoregions. Our findings suggested divergent change patterns in fall foliage peak coloration phenology in deciduous forests, and improved our understanding in the environmental control on timing of fall foliage color change.

Effect of winter cold duration on spring phenology of the orange tip butterfly, Anthocharis cardamines.

PubMed

Stålhandske, Sandra; Lehmann, Philipp; Pruisscher, Peter; Leimar, Olof

2015-12-01

The effect of spring temperature on spring phenology is well understood in a wide range of taxa. However, studies on how winter conditions may affect spring phenology are underrepresented. Previous work on Anthocharis cardamines (orange tip butterfly) has shown population-specific reaction norms of spring development in relation to spring temperature and a speeding up of post-winter development with longer winter durations. In this experiment, we examined the effects of a greater and ecologically relevant range of winter durations on post-winter pupal development of A. cardamines of two populations from the United Kingdom and two from Sweden. By analyzing pupal weight loss and metabolic rate, we were able to separate the overall post-winter pupal development into diapause duration and post-diapause development. We found differences in the duration of cold needed to break diapause among populations, with the southern UK population requiring a shorter duration than the other populations. We also found that the overall post-winter pupal development time, following removal from winter cold, was negatively related to cold duration, through a combined effect of cold duration on diapause duration and on post-diapause development time. Longer cold durations also lead to higher population synchrony in hatching. For current winter durations in the field, the A. cardamines population of southern UK could have a reduced development rate and lower synchrony in emergence because of short winters. With future climate change, this might become an issue also for other populations. Differences in winter conditions in the field among these four populations are large enough to have driven local adaptation of characteristics controlling spring phenology in response to winter duration. The observed phenology of these populations depends on a combination of winter and spring temperatures; thus, both must be taken into account for accurate predictions of phenology.

Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis

Treesearch

Andrew D. Richardson; Ryan S. Anderson; M. Altaf Arain; Alan G. Barr; Gil Bohrer; Guangsheng Chen; Jing M. Chen; Philippe Ciais; Kenneth J. David; Ankur R. Desai; Michael C. Dietze; Danilo Dragoni; Steven R. Garrity; Christopher M. Gough; Robert Grant; David Hollinger; Hank A. Margolis; Harry McCaughey; Mirco Migliavacca; Russel K. Monson; J. William Munger; Benjamin Poulter; Brett M. Raczka; Daniel M. Ricciuto; Alok K. Sahoo; Kevin Schaefer; Hanqin Tian; Rodrigo Vargas; Hans Verbeeck; Jingfeng Xiao; Yongkang Xue

2012-01-01

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO

As-Built documentation of programs to implement the Robertson and Doraiswamy/Thompson models

NASA Technical Reports Server (NTRS)

Valenziano, D. J. (Principal Investigator)

1981-01-01

The software which implements two spring wheat phenology models is described. The main program routines for the Doraiswamy/Thompson crop phenology model and the basic Robertson crop phenology model are DTMAIN and BRMAIN. These routines read meteorological data files and coefficient files, accept the planting date information and other information from the user, and initiate processing. Daily processing for the basic Robertson program consists only of calculation of the basic Robertson increment of crop development. Additional processing in the Doraiswamy/Thompson program includes the calculation of a moisture stress index and correction of the basic increment of development. Output for both consists of listings of the daily results.

Modeling the influence of genetic and environmental variation on the expression of plant life cycles across landscapes.

PubMed

Burghardt, Liana T; Metcalf, C Jessica E; Wilczek, Amity M; Schmitt, Johanna; Donohue, Kathleen

2015-02-01

Organisms develop through multiple life stages that differ in environmental tolerances. The seasonal timing, or phenology, of life-stage transitions determines the environmental conditions to which each life stage is exposed and the length of time required to complete a generation. Both environmental and genetic factors contribute to phenological variation, yet predicting their combined effect on life cycles across a geographic range remains a challenge. We linked submodels of the plasticity of individual life stages to create an integrated model that predicts life-cycle phenology in complex environments. We parameterized the model for Arabidopsis thaliana and simulated life cycles in four locations. We compared multiple "genotypes" by varying two parameters associated with natural genetic variation in phenology: seed dormancy and floral repression. The model predicted variation in life cycles across locations that qualitatively matches observed natural phenology. Seed dormancy had larger effects on life-cycle length than floral repression, and results suggest that a genetic cline in dormancy maintains a life-cycle length of 1 year across the geographic range of this species. By integrating across life stages, this approach demonstrates how genetic variation in one transition can influence subsequent transitions and the geographic distribution of life cycles more generally.

Biodiversity ensures plant-pollinator phenological synchrony against climate change.

PubMed

Bartomeus, Ignasi; Park, Mia G; Gibbs, Jason; Danforth, Bryan N; Lakso, Alan N; Winfree, Rachael

2013-11-01

Climate change has the potential to alter the phenological synchrony between interacting mutualists, such as plants and their pollinators. However, high levels of biodiversity might buffer the negative effects of species-specific phenological shifts and maintain synchrony at the community level, as predicted by the biodiversity insurance hypothesis. Here, we explore how biodiversity might enhance and stabilise phenological synchrony between a valuable crop, apple and its native pollinators. We combine 46 years of data on apple flowering phenology with historical records of bee pollinators over the same period. When the key apple pollinators are considered altogether, we found extensive synchrony between bee activity and apple peak bloom due to complementarity among bee species' activity periods, and also a stable trend over time due to differential responses to warming climate among bee species. A simulation model confirms that high biodiversity levels can ensure plant-pollinator phenological synchrony and thus pollination function. © 2013 John Wiley & Sons Ltd/CNRS.

Can phenological models predict tree phenology accurately under climate change conditions?

NASA Astrophysics Data System (ADS)

Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

2014-05-01

The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay or compromise dormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budburst dates only, with no information on the dormancy break date because this information is very scarce. We evaluated the efficiency of a set of process-based phenological models to accurately predict the dormancy break dates of four fruit trees. Our results show that models calibrated solely with flowering or budburst dates do not accurately predict the dormancy break date. Providing dormancy break date for the model parameterization results in much more accurate simulation of this latter, with however a higher error than that on flowering or bud break dates. But most importantly, we show also that models not calibrated with dormancy break dates can generate significant differences in forecasted flowering or bud break dates when using climate scenarios. Our results claim for the urgent need of massive measurements of dormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future.

Phenological mismatch in coastal western Alaska may increase summer season greenhouse gas uptake

NASA Astrophysics Data System (ADS)

Kelsey, Katharine C.; Leffler, A. Joshua; Beard, Karen H.; Choi, Ryan T.; Schmutz, Joel A.; Welker, Jeffery M.

2018-04-01

High latitude ecosystems are prone to phenological mismatches due to climate change- driven advances in the growing season and changing arrival times of migratory herbivores. These changes have the potential to alter biogeochemical cycling and contribute to feedbacks on climate change by altering greenhouse gas (GHG) emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) through large regions of the Arctic. Yet the effects of phenological mismatches on gas fluxes are currently unexplored. We used a three-year field experiment that altered the start of the growing season and timing of grazing to investigate how phenological mismatch affects GHG exchange. We found early grazing increased mean GHG emission to the atmosphere despite lower CH4 emissions due to grazing-induced changes in vegetation structure that increased uptake of CO2. In contrast, late grazing reduced GHG emissions because greater plant productivity led to an increase in CO2 uptake that overcame the increase in CH4 emission. Timing of grazing was an important control on both CO2 and CH4 emissions, and net GHG exchange was the result of opposing fluxes of CO2 and CH4. N2O played a negligible role in GHG flux. Advancing the growing season had a smaller effect on GHG emissions than changes to timing of grazing in this study. Our results suggest that a phenological mismatch that delays timing of grazing relative to the growing season, a change which is already developing along in western coastal Alaska, will reduce GHG emissions to the atmosphere through increased CO2 uptake despite greater CH4 emissions.

Phenological mismatch in coastal western Alaska may increase summer season greenhouse gas uptake

USGS Publications Warehouse

Kelsey, Katharine C.; Leffler, A. Joshua; Beard, Karen H.; Choi, Ryan T.; Schmutz, Joel A.; Welker, Jeffery M.

2018-01-01

High latitude ecosystems are prone to phenological mismatches due to climate change- driven advances in the growing season and changing arrival times of migratory herbivores. These changes have the potential to alter biogeochemical cycling and contribute to feedbacks on climate change by altering greenhouse gas (GHG) emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) through large regions of the Arctic. Yet the effects of phenological mismatches on gas fluxes are currently unexplored. We used a three-year field experiment that altered the start of the growing season and timing of grazing to investigate how phenological mismatch affects GHG exchange. We found early grazing increased mean GHG emission to the atmosphere despite lower CH4 emissions due to grazing-induced changes in vegetation structure that increased uptake of CO2. In contrast, late grazing reduced GHG emissions because greater plant productivity led to an increase in CO2 uptake that overcame the increase in CH4 emission. Timing of grazing was an important control on both CO2 and CH4 emissions, and net GHG exchange was the result of opposing fluxes of CO2 and CH4. N2O played a negligible role in GHG flux. Advancing the growing season had a smaller effect on GHG emissions than changes to timing of grazing in this study. Our results suggest that a phenological mismatch that delays timing of grazing relative to the growing season, a change which is already developing along in western coastal Alaska, will reduce GHG emissions to the atmosphere through increased CO2 uptake despite greater CH4 emissions.

Evolutionary and plastic responses of freshwater invertebrates to climate change: realized patterns and future potential.

PubMed

Stoks, Robby; Geerts, Aurora N; De Meester, Luc

2014-01-01

We integrated the evidence for evolutionary and plastic trait changes in situ in response to climate change in freshwater invertebrates (aquatic insects and zooplankton). The synthesis on the trait changes in response to the expected reductions in hydroperiod and increases in salinity indicated little evidence for adaptive, plastic, and genetic trait changes and for local adaptation. With respect to responses to temperature, there are many studies on temporal trait changes in phenology and body size in the wild that are believed to be driven by temperature increases, but there is a general lack of rigorous demonstration whether these trait changes are genetically based, adaptive, and causally driven by climate change. Current proof for genetic trait changes under climate change in freshwater invertebrates stems from a limited set of common garden experiments replicated in time. Experimental thermal evolution experiments and common garden warming experiments associated with space-for-time substitutions along latitudinal gradients indicate that besides genetic changes, also phenotypic plasticity and evolution of plasticity are likely to contribute to the observed phenotypic changes under climate change in aquatic invertebrates. Apart from plastic and genetic thermal adjustments, also genetic photoperiod adjustments are widespread and may even dominate the observed phenological shifts.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Technical Reports Server (NTRS)

Koster, Randal; Walker, G.; Thornton, Patti; Collatz, G. J.

2012-01-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Astrophysics Data System (ADS)

Koster, R. D.; Walker, G.; Thornton, P. E.; Collatz, G. J.

2012-12-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if somewhat biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Anthropogenically driven environmental changes shift the ecological dynamics of hemorrhagic fever with renal syndrome

PubMed Central

Yang, Jing; Tan, Hua; Huang, Shanqian; Cui, Yujun; Dong, Lu; Ma, Chaofeng; Ma, Changan; Zhou, Sen; Wu, Xiaoxu; Zhang, Yanyun; Wang, Jingjun; Yang, Ruifu; Stenseth, Nils Chr.; Xu, Bing

2017-01-01

Zoonoses are increasingly recognized as an important burden on global public health in the 21st century. High-resolution, long-term field studies are critical for assessing both the baseline and future risk scenarios in a world of rapid changes. We have used a three-decade-long field study on hantavirus, a rodent-borne zoonotic pathogen distributed worldwide, coupled with epidemiological data from an endemic area of China, and show that the shift in the ecological dynamics of Hantaan virus was closely linked to environmental fluctuations at the human-wildlife interface. We reveal that environmental forcing, especially rainfall and resource availability, exert important cascading effects on intra-annual variability in the wildlife reservoir dynamics, leading to epidemics that shift between stable and chaotic regimes. Our models demonstrate that bimodal seasonal epidemics result from a powerful seasonality in transmission, generated from interlocking cycles of agricultural phenology and rodent behavior driven by the rainy seasons. PMID:28141833

The Use of Geostatistics in the Study of Floral Phenology of Vulpia geniculata (L.) Link

PubMed Central

León Ruiz, Eduardo J.; García Mozo, Herminia; Domínguez Vilches, Eugenio; Galán, Carmen

2012-01-01

Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS) and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating unsampled points. In the present work, estimations based upon Geostatistics and GIS mapping have enabled the construction of spatial models that reflect phenological evolution of Vulpia geniculata (L.) Link throughout the study area during sampling season. Ten sampling points, scattered troughout the city and low mountains in the “Sierra de Córdoba” were chosen to carry out the weekly phenological monitoring during flowering season. The phenological data were interpolated by applying the traditional geostatitical method of Kriging, which was used to ellaborate weekly estimations of V. geniculata phenology in unsampled areas. Finally, the application of Geostatistics and GIS to create phenological maps could be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps. PMID:22629169

The use of geostatistics in the study of floral phenology of Vulpia geniculata (L.) link.

PubMed

León Ruiz, Eduardo J; García Mozo, Herminia; Domínguez Vilches, Eugenio; Galán, Carmen

2012-01-01

Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS) and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating unsampled points. In the present work, estimations based upon Geostatistics and GIS mapping have enabled the construction of spatial models that reflect phenological evolution of Vulpia geniculata (L.) Link throughout the study area during sampling season. Ten sampling points, scattered throughout the city and low mountains in the "Sierra de Córdoba" were chosen to carry out the weekly phenological monitoring during flowering season. The phenological data were interpolated by applying the traditional geostatitical method of Kriging, which was used to elaborate weekly estimations of V. geniculata phenology in unsampled areas. Finally, the application of Geostatistics and GIS to create phenological maps could be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps.

Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology.

PubMed

Liu, Tianjiao; Liu, Xiangnan; Liu, Meiling; Wu, Ling

2018-03-14

Heavy metal pollution of croplands is a major environmental problem worldwide. Methods for accurately and quickly monitoring heavy metal stress have important practical significance. Many studies have explored heavy metal stress in rice in relation to physiological function or physiological factors, but few studies have considered phenology, which can be sensitive to heavy metal stress. In this study, we used an integrated Normalized Difference Vegetation Index (NDVI) time-series image set to extract remote sensing phenology. A phenological indicator relatively sensitive to heavy metal stress was chosen from the obtained phenological periods and phenological parameters. The Dry Weight of Roots (WRT), which directly affected by heavy metal stress, was simulated by the World Food Study (WOFOST) model; then, a feature space based on the phenological indicator and WRT was established for monitoring heavy metal stress. The results indicated that the feature space can distinguish the heavy metal stress levels in rice, with accuracy greater than 95% for distinguishing the severe stress level. This finding provides scientific evidence for combining rice phenology and physiological characteristics in time and space, and the method is useful to monitor heavy metal stress in rice.

Tree-grass phenology information improves light use efficiency modelling of gross primary productivity for an Australian tropical savanna

NASA Astrophysics Data System (ADS)

Moore, Caitlin E.; Beringer, Jason; Evans, Bradley; Hutley, Lindsay B.; Tapper, Nigel J.

2017-01-01

The coexistence of trees and grasses in savanna ecosystems results in marked phenological dynamics that vary spatially and temporally with climate. Australian savannas comprise a complex variety of life forms and phenologies, from evergreen trees to annual/perennial grasses, producing a boom-bust seasonal pattern of productivity that follows the wet-dry seasonal rainfall cycle. As the climate changes into the 21st century, modification to rainfall and temperature regimes in savannas is highly likely. There is a need to link phenology cycles of different species with productivity to understand how the tree-grass relationship may shift in response to climate change. This study investigated the relationship between productivity and phenology for trees and grasses in an Australian tropical savanna. Productivity, estimated from overstory (tree) and understory (grass) eddy covariance flux tower estimates of gross primary productivity (GPP), was compared against 2 years of repeat time-lapse digital photography (phenocams). We explored the phenology-productivity relationship at the ecosystem scale using Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and flux tower GPP. These data were obtained from the Howard Springs OzFlux/Fluxnet site (AU-How) in northern Australia. Two greenness indices were calculated from the phenocam images: the green chromatic coordinate (GCC) and excess green index (ExG). These indices captured the temporal dynamics of the understory (grass) and overstory (trees) phenology and were correlated well with tower GPP for understory (r2 = 0.65 to 0.72) but less so for the overstory (r2 = 0.14 to 0.23). The MODIS enhanced vegetation index (EVI) correlated well with GPP at the ecosystem scale (r2 = 0.70). Lastly, we used GCC and EVI to parameterise a light use efficiency (LUE) model and found it to improve the estimates of GPP for the overstory, understory and ecosystem. We conclude that phenology is an important parameter to consider in estimating GPP from LUE models in savannas and that phenocams can provide important insights into the phenological variability of trees and grasses.

Spatio-temporal variations of spring phenology of Plantago asiatica and Taraxacum mongolicum in the Tibetan Plateau from 2000 to 2011

NASA Astrophysics Data System (ADS)

Zheng, Z.; Zhu, W.

2016-12-01

Plant phenology is strongly controlled by climate and has become a sensitive bio-indicator to study the plant response to climate change. Since the high altitude, permafrost geography and harsh physical environment of the Tibetan Plateau (TP), the phenology shift in the TP was thought to be more sensitive than many other regions. However, the study of phenology in the TP was greatly limited by the lack of ground-observed phenological data. In this study, we collected the phonological records of first leaf date (FLD) and the first flowering date (FFD) of two herbaceous species (Plantago asiatica and Taraxacum mongolicum) both from 14 stations across the TP during 2000-2011 and analyzed the spatio-temporal variations of spring phenology. The results showed that the onset dates of FLD and FFD exhibited strong dependence on latitude, longitude and altitude because the onset dates of spring phenology occurred earlier at warmer locations. The sensitivities of spring phenology temperature varied among stations and earlier phenological events showed more negative temperature sensitivity except for the FFD of Taraxacum mongolicum. But the relationship between spring phenology and precipitation was not clear. Though the diverse trends of spring phenology of Plantago asiatica and Taraxacum mongolicum were found, the differences between the onset dates of FLD of the two species tended to increase (P < 0.05). However, the differences between the onset dates of FFD of the two species showed a reducing tendency (P < 0.01). These findings can help us to better understand the responses of plants to climate change in alpine ecosystem and provide information for phenology modelling.

Discriminating the Mediterranean Pinus spp. using the land surface phenology extracted from the whole MODIS NDVI time series and machine learning algorithms

NASA Astrophysics Data System (ADS)

Rodriguez-Galiano, Victor; Aragones, David; Caparros-Santiago, Jose A.; Navarro-Cerrillo, Rafael M.

2017-10-01

Land surface phenology (LSP) can improve the characterisation of forest areas and their change processes. The aim of this work was: i) to characterise the temporal dynamics in Mediterranean Pinus forests, and ii) to evaluate the potential of LSP for species discrimination. The different experiments were based on 679 mono-specific plots for the 5 native species on the Iberian Peninsula: P. sylvestris, P. pinea, P. halepensis, P. nigra and P. pinaster. The entire MODIS NDVI time series (2000-2016) of the MOD13Q1 product was used to characterise phenology. The following phenological parameters were extracted: the start, end and median days of the season, and the length of the season in days, as well as the base value, maximum value, amplitude and integrated value. Multi-temporal metrics were calculated to synthesise the inter-annual variability of the phenological parameters. The species were discriminated by the application of Random Forest (RF) classifiers from different subsets of variables: model 1) NDVI-smoothed time series, model 2) multi-temporal metrics of the phenological parameters, and model 3) multi-temporal metrics and the auxiliary physical variables (altitude, slope, aspect and distance to the coastline). Model 3 was the best, with an overall accuracy of 82%, a kappa coefficient of 0.77 and whose most important variables were: elevation, coast distance, and the end and start days of the growing season. The species that presented the largest errors was P. nigra, (kappa= 0.45), having locations with a similar behaviour to P. sylvestris or P. pinaster.

Phenology and density-dependent dispersal predict patterns of mountain pine beetle (Dendroctonus ponderosae) impact

Treesearch

James A. Powell; Barbara J. Bentz

2014-01-01

For species with irruptive population behavior, dispersal is an important component of outbreak dynamics. We developed and parameterized a mechanistic model describing mountain pine beetle (Dendroctonus ponderosae Hopkins) population demographics and dispersal across a landscape. Model components include temperature-dependent phenology, host tree colonization...

A new seasonal-deciduous spring phenology submodel in the Community Land Model 4.5: impacts on carbon and water cycling under future climate scenarios.

PubMed

Chen, Min; Melaas, Eli K; Gray, Josh M; Friedl, Mark A; Richardson, Andrew D

2016-11-01

A spring phenology model that combines photoperiod with accumulated heating and chilling to predict spring leaf-out dates is optimized using PhenoCam observations and coupled into the Community Land Model (CLM) 4.5. In head-to-head comparison (using satellite data from 2003 to 2013 for validation) for model grid cells over the Northern Hemisphere deciduous broadleaf forests (5.5 million km 2 ), we found that the revised model substantially outperformed the standard CLM seasonal-deciduous spring phenology submodel at both coarse (0.9 × 1.25°) and fine (1 km) scales. The revised model also does a better job of representing recent (decadal) phenological trends observed globally by MODIS, as well as long-term trends (1950-2014) in the PEP725 European phenology dataset. Moreover, forward model runs suggested a stronger advancement (up to 11 days) of spring leaf-out by the end of the 21st century for the revised model. Trends toward earlier advancement are predicted for deciduous forests across the whole Northern Hemisphere boreal and temperate deciduous forest region for the revised model, whereas the standard model predicts earlier leaf-out in colder regions, but later leaf-out in warmer regions, and no trend globally. The earlier spring leaf-out predicted by the revised model resulted in enhanced gross primary production (up to 0.6 Pg C yr -1 ) and evapotranspiration (up to 24 mm yr -1 ) when results were integrated across the study region. These results suggest that the standard seasonal-deciduous submodel in CLM should be reconsidered, otherwise substantial errors in predictions of key land-atmosphere interactions and feedbacks may result. © 2016 John Wiley & Sons Ltd.

Pre-Launch Tasks Proposed in our Contract of December 1991

NASA Technical Reports Server (NTRS)

1998-01-01

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data; (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC; (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Pre-Launch Tasks Proposed in our Contract of December 1991

NASA Technical Reports Server (NTRS)

Running, Steven W.; Nemani, Ramakrishna R.; Glassy, Joseph

1997-01-01

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data. (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Pan European Phenological database (PEP725): a single point of access for European data.

PubMed

Templ, Barbara; Koch, Elisabeth; Bolmgren, Kjell; Ungersböck, Markus; Paul, Anita; Scheifinger, Helfried; Rutishauser, This; Busto, Montserrat; Chmielewski, Frank-M; Hájková, Lenka; Hodzić, Sabina; Kaspar, Frank; Pietragalla, Barbara; Romero-Fresneda, Ramiro; Tolvanen, Anne; Vučetič, Višnja; Zimmermann, Kirsten; Zust, Ana

2018-06-01

The Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 "Establishing a European phenological data platform for climatological applications" working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/ . Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.

Pan European Phenological database (PEP725): a single point of access for European data

NASA Astrophysics Data System (ADS)

Templ, Barbara; Koch, Elisabeth; Bolmgren, Kjell; Ungersböck, Markus; Paul, Anita; Scheifinger, Helfried; Rutishauser, This; Busto, Montserrat; Chmielewski, Frank-M.; Hájková, Lenka; Hodzić, Sabina; Kaspar, Frank; Pietragalla, Barbara; Romero-Fresneda, Ramiro; Tolvanen, Anne; Vučetič, Višnja; Zimmermann, Kirsten; Zust, Ana

2018-02-01

The Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 "Establishing a European phenological data platform for climatological applications" working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/. Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.

Phenological plasticity will not help all species adapt to climate change.

PubMed

Duputié, Anne; Rutschmann, Alexis; Ronce, Ophélie; Chuine, Isabelle

2015-08-01

Concerns are rising about the capacity of species to adapt quickly enough to climate change. In long-lived organisms such as trees, genetic adaptation is slow, and how much phenotypic plasticity can help them cope with climate change remains largely unknown. Here, we assess whether, where and when phenological plasticity is and will be adaptive in three major European tree species. We use a process-based species distribution model, parameterized with extensive ecological data, and manipulate plasticity to suppress phenological variations due to interannual, geographical and trend climate variability, under current and projected climatic conditions. We show that phenological plasticity is not always adaptive and mostly affects fitness at the margins of the species' distribution and climatic niche. Under current climatic conditions, phenological plasticity constrains the northern range limit of oak and beech and the southern range limit of pine. Under future climatic conditions, phenological plasticity becomes strongly adaptive towards the trailing edges of beech and oak, but severely constrains the range and niche of pine. Our results call for caution when interpreting geographical variation in trait means as adaptive, and strongly point towards species distribution models explicitly taking phenotypic plasticity into account when forecasting species distribution under climate change scenarios. © 2015 John Wiley & Sons Ltd.

Predicting bird phenology from space: satellite-derived vegetation green-up signal uncovers spatial variation in phenological synchrony between birds and their environment.

PubMed

Cole, Ella F; Long, Peter R; Zelazowski, Przemyslaw; Szulkin, Marta; Sheldon, Ben C

2015-11-01

Population-level studies of how tit species (Parus spp.) track the changing phenology of their caterpillar food source have provided a model system allowing inference into how populations can adjust to changing climates, but are often limited because they implicitly assume all individuals experience similar environments. Ecologists are increasingly using satellite-derived data to quantify aspects of animals' environments, but so far studies examining phenology have generally done so at large spatial scales. Considering the scale at which individuals experience their environment is likely to be key if we are to understand the ecological and evolutionary processes acting on reproductive phenology within populations. Here, we use time series of satellite images, with a resolution of 240 m, to quantify spatial variation in vegetation green-up for a 385-ha mixed-deciduous woodland. Using data spanning 13 years, we demonstrate that annual population-level measures of the timing of peak abundance of winter moth larvae (Operophtera brumata) and the timing of egg laying in great tits (Parus major) and blue tits (Cyanistes caeruleus) is related to satellite-derived spring vegetation phenology. We go on to show that timing of local vegetation green-up significantly explained individual differences in tit reproductive phenology within the population, and that the degree of synchrony between bird and vegetation phenology showed marked spatial variation across the woodland. Areas of high oak tree (Quercus robur) and hazel (Corylus avellana) density showed the strongest match between remote-sensed vegetation phenology and reproductive phenology in both species. Marked within-population variation in the extent to which phenology of different trophic levels match suggests that more attention should be given to small-scale processes when exploring the causes and consequences of phenological matching. We discuss how use of remotely sensed data to study within-population variation could broaden the scale and scope of studies exploring phenological synchrony between organisms and their environment.

Establishing the Role of Digital Repeat Photography in Understanding Phenology and Carbon Cycling in a Subarctic Peatland

NASA Astrophysics Data System (ADS)

Garnello, Anthony John

In this thesis, I establish and explore the role of phenology in understanding the rapidly changing environment of a subarctic peatland. First, I demonstrate how digital repeat photography can be used to characterize and differentiate distinct plant communities using two years of images. Each habitat is composed of different plant functional groups, promoting the individualistic approach to characterization that near-earth remote sensing tools can provide. The camera-product Relative Greenness successfully characterized interannual variability in seasonal growth for each habitat type. Across habitats, there was a direct relationship between advancement of spring onset and active season growth though this overall pattern showed habitat-specific variance. The camera images were also useful in characterizing the flowering phenology of an eriophorum-rich fen habitat, for which a metric named Intensity was created. These results suggest that employment of phenology cameras in highly heterogeneous subarctic environments is a robust method to characterize phenology on a habitat to species scale. Next, I explored the role that this phenology product has in modeling Net Ecosystem Exchange (NEE) also measured at the field site. I hypothesized that the explanatory power of the phenology index, which is conceptually tied to a measure of photosynthetic capacity, would be tightly linked to the timescale it was used for: At sub-daily timescales, environmental forces would dominate, though when averaged over days to weekly scales, the biology represented through the camera index would be more influential. I show that at multiple time scales the environmental factors outperform the camera index when modeling NEE. Together, these studies begin to explore the applicability of phenology camera systems in subarctic environments.

Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010.

PubMed

Yang, Yuting; Guan, Huade; Shen, Miaogen; Liang, Wei; Jiang, Lei

2015-02-01

Vegetation phenology is a sensitive indicator of the dynamic response of terrestrial ecosystems to climate change. In this study, the spatiotemporal pattern of vegetation dormancy onset date (DOD) and its climate controls over temperate China were examined by analysing the satellite-derived normalized difference vegetation index and concurrent climate data from 1982 to 2010. Results show that preseason (May through October) air temperature is the primary climatic control of the DOD spatial pattern across temperate China, whereas preseason cumulative precipitation is dominantly associated with the DOD spatial pattern in relatively cold regions. Temporally, the average DOD over China's temperate ecosystems has delayed by 0.13 days per year during the past three decades. However, the delay trends are not continuous throughout the 29-year period. The DOD experienced the largest delay during the 1980s, but the delay trend slowed down or even reversed during the 1990s and 2000s. Our results also show that interannual variations in DOD are most significantly related with preseason mean temperature in most ecosystems, except for the desert ecosystem for which the variations in DOD are mainly regulated by preseason cumulative precipitation. Moreover, temperature also determines the spatial pattern of temperature sensitivity of DOD, which became significantly lower as temperature increased. On the other hand, the temperature sensitivity of DOD increases with increasing precipitation, especially in relatively dry areas (e.g. temperate grassland). This finding stresses the importance of hydrological control on the response of autumn phenology to changes in temperature, which must be accounted in current temperature-driven phenological models. © 2014 John Wiley & Sons Ltd.

Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

NASA Technical Reports Server (NTRS)

Koster, R. D.; Walker, G. K.

2015-01-01

The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.

Root and Shoot Phenology May Respond Differently to Warming

NASA Astrophysics Data System (ADS)

Radville, L.; Eissenstat, D. M.; Post, E.

2015-12-01

Climate change is increasing temperatures and extending the growing season for many organisms. Shifts in phenology have been widely reported in response to global warming and have strong effects on ecosystem processes and greenhouse gas emissions. It is well understood that warming generally advances aboveground plant phenology, but the influence of temperature on root phenology is unclear. Most terrestrial biosphere models assume that root and shoot growth occur at the same time and are influenced by warming in the same way, but recent studies suggest that this may not be the case. Testing this assumption is particularly important in the Arctic where over 70% of plant biomass can be belowground and warming is happening faster than in other ecosystems. In 2013 and 2014 we examined the timing of root growth in the Arctic in plots that had been warmed or unwarmed for 10 years. We found that peak root growth occurred about one month before leaf growth, suggesting that spring root phenology is not controlled by carbon produced during spring photosynthesis. If root phenology is not controlled by photosynthate early in the season, earlier spring leaf growth may not cause earlier spring root growth. In support of this, we found that warming advanced spring leaf cover but did not significantly affect root phenology. Root growth was not significantly correlated with soil temperature and did not appear to be limited by near-freezing temperatures above the permafrost. These results suggest that although shoots are influenced by temperature, roots in this system may be more influenced by photosynthesis and carbon storage. Aboveground phenology, one of the most widely measured aspects of climate change, may not represent whole-plant phenology and may be a poor indicator of the timing of whole-plant carbon fluxes. Additionally, climate model assumptions that roots and shoots grow at the same time may need to be revised.

Uncovering a Nuisance Influence of a Phenological Trait of Plants Using a Nonlinear Structural Equation: Application to Days to Heading and Culm Length in Asian Cultivated Rice (Oryza Sativa L.).

PubMed

Onogi, Akio; Ideta, Osamu; Yoshioka, Takuma; Ebana, Kaworu; Yamasaki, Masanori; Iwata, Hiroyoshi

2016-01-01

Phenological traits of plants, such as flowering time, are linked to growth phase transition. Thus, phenological traits often influence other traits through the modification of the duration of growth period. This influence is a nuisance in plant breeding because it hampers genetic evaluation of the influenced traits. Genetic effects on the influenced traits have two components, one that directly affects the traits and one that indirectly affects the traits via the phenological trait. These cannot be distinguished by phenotypic evaluation and ordinary linear regression models. Consequently, if a phenological trait is modified by introgression or editing of the responsible genes, the phenotypes of the influenced traits can change unexpectedly. To uncover the influence of the phenological trait and evaluate the direct genetic effects on the influenced traits, we developed a nonlinear structural equation (NSE) incorporating a nonlinear influence of the phenological trait. We applied the NSE to real data for cultivated rice (Oryza sativa L.): days to heading (DH) as a phenological trait and culm length (CL) as the influenced trait. This showed that CL of the cultivars that showed extremely early heading was shortened by the strong influence of DH. In a simulation study, it was shown that the NSE was able to infer the nonlinear influence and direct genetic effects with reasonable accuracy. However, the NSE failed to infer the linear influence in this study. When no influence was simulated, an ordinary bi-trait linear model (OLM) tended to infer the genetic effects more accurately. In such cases, however, by comparing the NSE and OLM using an information criterion, we could assess whether the nonlinear assumption of the NSE was appropriate for the data analyzed. This study demonstrates the usefulness of the NSE in revealing the phenotypic influence of phenological traits.

Uncovering a Nuisance Influence of a Phenological Trait of Plants Using a Nonlinear Structural Equation: Application to Days to Heading and Culm Length in Asian Cultivated Rice (Oryza Sativa L.)

PubMed Central

Onogi, Akio; Ideta, Osamu; Yoshioka, Takuma; Ebana, Kaworu; Yamasaki, Masanori; Iwata, Hiroyoshi

2016-01-01

Phenological traits of plants, such as flowering time, are linked to growth phase transition. Thus, phenological traits often influence other traits through the modification of the duration of growth period. This influence is a nuisance in plant breeding because it hampers genetic evaluation of the influenced traits. Genetic effects on the influenced traits have two components, one that directly affects the traits and one that indirectly affects the traits via the phenological trait. These cannot be distinguished by phenotypic evaluation and ordinary linear regression models. Consequently, if a phenological trait is modified by introgression or editing of the responsible genes, the phenotypes of the influenced traits can change unexpectedly. To uncover the influence of the phenological trait and evaluate the direct genetic effects on the influenced traits, we developed a nonlinear structural equation (NSE) incorporating a nonlinear influence of the phenological trait. We applied the NSE to real data for cultivated rice (Oryza sativa L.): days to heading (DH) as a phenological trait and culm length (CL) as the influenced trait. This showed that CL of the cultivars that showed extremely early heading was shortened by the strong influence of DH. In a simulation study, it was shown that the NSE was able to infer the nonlinear influence and direct genetic effects with reasonable accuracy. However, the NSE failed to infer the linear influence in this study. When no influence was simulated, an ordinary bi-trait linear model (OLM) tended to infer the genetic effects more accurately. In such cases, however, by comparing the NSE and OLM using an information criterion, we could assess whether the nonlinear assumption of the NSE was appropriate for the data analyzed. This study demonstrates the usefulness of the NSE in revealing the phenotypic influence of phenological traits. PMID:26859143

Mesoscale landscape model of gypsy moth phenology

Treesearch

Joseph M. Russo; John G. W. Kelley; Andrew M. Liebhold

1991-01-01

A recently-developed high resolution climatological temperature data base was input into a gypsy moth phenology model. The high resolution data were created from a coupling of 30-year averages of station observations and digital elevation data. The resultant maximum and minimum temperatures have about a 1 km resolution which represents meteorologically the mesoscale....

Joint control of terrestrial gross primary productivity by plant phenology and physiology

PubMed Central

Xia, Jianyang; Niu, Shuli; Ciais, Philippe; Janssens, Ivan A.; Chen, Jiquan; Ammann, Christof; Arain, Altaf; Blanken, Peter D.; Cescatti, Alessandro; Bonal, Damien; Buchmann, Nina; Curtis, Peter S.; Chen, Shiping; Dong, Jinwei; Flanagan, Lawrence B.; Frankenberg, Christian; Georgiadis, Teodoro; Gough, Christopher M.; Hui, Dafeng; Kiely, Gerard; Li, Jianwei; Lund, Magnus; Magliulo, Vincenzo; Marcolla, Barbara; Merbold, Lutz; Olesen, Jørgen E.; Piao, Shilong; Raschi, Antonio; Roupsard, Olivier; Suyker, Andrew E.; Vaccari, Francesco P.; Varlagin, Andrej; Vesala, Timo; Wilkinson, Matthew; Weng, Ensheng; Yan, Liming; Luo, Yiqi

2015-01-01

Terrestrial gross primary productivity (GPP) varies greatly over time and space. A better understanding of this variability is necessary for more accurate predictions of the future climate–carbon cycle feedback. Recent studies have suggested that variability in GPP is driven by a broad range of biotic and abiotic factors operating mainly through changes in vegetation phenology and physiological processes. However, it is still unclear how plant phenology and physiology can be integrated to explain the spatiotemporal variability of terrestrial GPP. Based on analyses of eddy–covariance and satellite-derived data, we decomposed annual terrestrial GPP into the length of the CO2 uptake period (CUP) and the seasonal maximal capacity of CO2 uptake (GPPmax). The product of CUP and GPPmax explained >90% of the temporal GPP variability in most areas of North America during 2000–2010 and the spatial GPP variation among globally distributed eddy flux tower sites. It also explained GPP response to the European heatwave in 2003 (r2 = 0.90) and GPP recovery after a fire disturbance in South Dakota (r2 = 0.88). Additional analysis of the eddy–covariance flux data shows that the interbiome variation in annual GPP is better explained by that in GPPmax than CUP. These findings indicate that terrestrial GPP is jointly controlled by ecosystem-level plant phenology and photosynthetic capacity, and greater understanding of GPPmax and CUP responses to environmental and biological variations will, thus, improve predictions of GPP over time and space. PMID:25730847

Simulating crop phenology in the Community Land Model and its impact on energy and carbon fluxes

NASA Astrophysics Data System (ADS)

Chen, Ming; Griffis, Tim J.; Baker, John; Wood, Jeffrey D.; Xiao, Ke

2015-02-01

A reasonable representation of crop phenology and biophysical processes in land surface models is necessary to accurately simulate energy, water, and carbon budgets at the field, regional, and global scales. However, the evaluation of crop models that can be coupled to Earth system models is relatively rare. Here we evaluated two such models (CLM4-Crop and CLM3.5-CornSoy), both implemented within the Community Land Model (CLM) framework, at two AmeriFlux corn-soybean sites to assess their ability to simulate phenology, energy, and carbon fluxes. Our results indicated that the accuracy of net ecosystem exchange and gross primary production simulations was intimately connected to the phenology simulations. The CLM4-Crop model consistently overestimated early growing season leaf area index, causing an overestimation of gross primary production, to such an extent that the model simulated a carbon sink instead of the measured carbon source for corn. The CLM3.5-CornSoy-simulated leaf area index (LAI), energy, and carbon fluxes showed stronger correlations with observations compared to CLM4-Crop. Net radiation was biased high in both models and was especially pronounced for soybeans. This was primarily caused by the positive LAI bias, which led to a positive net long-wave radiation bias. CLM4-Crop underestimated soil water content during midgrowing season in all soil layers at the two sites, which caused unrealistic water stress, especially for soybean. Future work regarding the mechanisms that drive early growing season phenology and soil water dynamics is needed to better represent crops including their net radiation balance, energy partitioning, and carbon cycle processes.

Impacts of wildfires on interannual trends in land surface phenology: an investigation of the Hayman Fire

NASA Astrophysics Data System (ADS)

Wang, Jianmin; Zhang, Xiaoyang

2017-05-01

Land surface phenology (LSP) derived from satellite data has been widely associated with recent global climate change. However, LSP is frequently influenced by land disturbances, which significantly limits our understanding of the phenological trends driven by climate change. Because wildfire is one of the most significant disturbance agents, we investigated the influences of wildfire on the start of growing season (SOS) and the interannual trends of SOS in the Hayman Fire area that occurred in 2002 in Colorado using time series of daily MODIS data (2001-2014). Results show that the Hayman Fire advanced the area-integrated SOS by 15.2 d and converted SOS from a delaying trend of 3.9 d/decade to an advancing trend of -1.9 d/decade during 2001-2014. The fire impacts on SOS increased from low burn severity to high burn severity. Moreover, the rate of increase of annual maximum and minimum EVI2 from 2003-2014 reflects that vegetation greenness could recover to pre-fire status in 2022 and 2053, respectively, which suggests that the fire impacts on the satellite-derived SOS variability and the interannual trends should continue in the next few decades.

Modeling Net Ecosystem Carbon Exchange of Alpine Grasslands with a Satellite-Driven Model

PubMed Central

Zhao, Yuping; Zhang, Xianzhou; Fan, Yuzhi; Shi, Peili; He, Yongtao; Yu, Guirui; Li, Yingnian

2015-01-01

Estimate of net ecosystem carbon exchange (NEE) between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP) and ecosystem respiration (Reco) has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model. PMID:25849325

Modeling net ecosystem carbon exchange of alpine grasslands with a satellite-driven model.

PubMed

Yan, Wei; Hu, Zhongmin; Zhao, Yuping; Zhang, Xianzhou; Fan, Yuzhi; Shi, Peili; He, Yongtao; Yu, Guirui; Li, Yingnian

2015-01-01

Estimate of net ecosystem carbon exchange (NEE) between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP) and ecosystem respiration (Reco) has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model.

Atmospheric circulation patterns and phenological anomalies of grapevine in Italy

NASA Astrophysics Data System (ADS)

Cola, Gabriele; Alilla, Roberta; Dal Monte, Giovanni; Epifani, Chiara; Mariani, Luigi; Parisi, Simone Gabriele

2014-05-01

Grapevine (Vitis vinifera L.) is a fundamental crop for Italian agriculture as testified by the first place of Italy in the world producers ranking. This justify the importance of quantitative analyses referred to this crucial crop and aimed to quantify meteorological resources and limitations to development and production. Phenological rhythms of grapevine are strongly affected by surface fields of air temperature which in their turn are affected by synoptic circulation. This evidence highlights the importance of an approach based on dynamic climatology in order to detect and explain phenological anomalies that can have relevant effects on quantity and quality of grapevine production. In this context, this research is aimed to study the existing relation among the 850 hPa circulation patterns over the Euro-Mediterranean area from NOAA Ncep dataset and grapevine phenological fields for Italy over the period 2006-2013, highlighting the main phenological anomalies and analyzing synoptic determinants. This work is based on phenological fields with a standard pixel of 2 km routinely produced from 2006 by the Iphen project (Italian Phenological network) on the base of phenological observations spatialized by means of a specific algorithm based on cumulated thermal resources expressed as Normal Heat Hours (NHH). Anomalies have been evaluated with reference to phenological normal fields defined for the Italian area on the base of phenological observations and Iphen model. Results show that relevant phenological anomalies observed over the reference period are primarily associated with long lasting blocking systems driving cold air masses (Arctic or Polar-Continental) or hot ones (Sub-Tropical) towards the Italian area. Specific cases are presented for some years like 2007 and 2011.

Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series

PubMed Central

Bajocco, Sofia; Dragoz, Eleni; Gitas, Ioannis; Smiraglia, Daniela; Salvati, Luca; Ricotta, Carlo

2015-01-01

Traditionally fuel maps are built in terms of ‘fuel types’, thus considering the structural characteristics of vegetation only. The aim of this work is to derive a phenological fuel map based on the functional attributes of coarse-scale vegetation phenology, such as seasonality and productivity. MODIS NDVI 250m images of Sardinia (Italy), a large Mediterranean island with high frequency of fire incidence, were acquired for the period 2000–2012 to construct a mean annual NDVI profile of the vegetation at the pixel-level. Next, the following procedure was used to develop the phenological fuel map: (i) image segmentation on the Fourier components of the NDVI profiles to identify phenologically homogeneous landscape units, (ii) cluster analysis of the phenological units and post-hoc analysis of the fire-proneness of the phenological fuel classes (PFCs) obtained, (iii) environmental characterization (in terms of land cover and climate) of the PFCs. Our results showed the ability of coarse-resolution satellite time-series to characterize the fire-proneness of Sardinia with an adequate level of accuracy. The remotely sensed phenological framework presented may represent a suitable basis for the development of fire distribution prediction models, coarse-scale fuel maps and for various biogeographic studies. PMID:25822505

Nonlinear flowering responses to climate: are species approaching their limits of phenological change?

PubMed

Iler, Amy M; Høye, Toke T; Inouye, David W; Schmidt, Niels M

2013-08-19

Many alpine and subalpine plant species exhibit phenological advancements in association with earlier snowmelt. While the phenology of some plant species does not advance beyond a threshold snowmelt date, the prevalence of such threshold phenological responses within plant communities is largely unknown. We therefore examined the shape of flowering phenology responses (linear versus nonlinear) to climate using two long-term datasets from plant communities in snow-dominated environments: Gothic, CO, USA (1974-2011) and Zackenberg, Greenland (1996-2011). For a total of 64 species, we determined whether a linear or nonlinear regression model best explained interannual variation in flowering phenology in response to increasing temperatures and advancing snowmelt dates. The most common nonlinear trend was for species to flower earlier as snowmelt advanced, with either no change or a slower rate of change when snowmelt was early (average 20% of cases). By contrast, some species advanced their flowering at a faster rate over the warmest temperatures relative to cooler temperatures (average 5% of cases). Thus, some species seem to be approaching their limits of phenological change in response to snowmelt but not temperature. Such phenological thresholds could either be a result of minimum springtime photoperiod cues for flowering or a slower rate of adaptive change in flowering time relative to changing climatic conditions.

Temporal coherence of phenological and climatic rhythmicity in Beijing

NASA Astrophysics Data System (ADS)

Chen, Xiaoqiu; Zhang, Weiqi; Ren, Shilong; Lang, Weiguang; Liang, Boyi; Liu, Guohua

2017-10-01

Using woody plant phenological data in the Beijing Botanical Garden from 1979 to 2013, we revealed three levels of phenology rhythms and examined their coherence with temperature rhythms. First, the sequential and correlative rhythm shows that occurrence dates of various phenological events obey a certain time sequence within a year and synchronously advance or postpone among years. The positive correlation between spring phenophase dates is much stronger than that between autumn phenophase dates and attenuates as the time interval between two spring phenophases increases. This phenological rhythm can be explained by positive correlation between above 0 °C mean temperatures corresponding to different phenophase dates. Second, the circannual rhythm indicates that recurrence interval of a phenophase in the same species in two adjacent years is about 365 days, which can be explained by the 365-day recurrence interval in the first and last dates of threshold temperatures. Moreover, an earlier phenophase date in the current year may lead to a later phenophase date in the next year through extending recurrence interval. Thus, the plant phenology sequential and correlative rhythm and circannual rhythm are interacted, which mirrors the interaction between seasonal variation and annual periodicity of temperature. Finally, the multi-year rhythm implies that phenophase dates display quasi-periodicity more than 1 year. The same 12-year periodicity in phenophase and threshold temperature dates confirmed temperature controls of the phenology multi-year rhythm. Our findings provide new perspectives for examining phenological response to climate change and developing comprehensive phenology models considering temporal coherence of phenological and climatic rhythmicity.

Relating adaptive genetic traits to climate for Sandberg bluegrass from the intermountain western United States.

PubMed

Johnson, Richard C; Horning, Matthew E; Espeland, Erin K; Vance-Borland, Ken

2015-02-01

Genetic variation for potentially adaptive traits of the key restoration species Sandberg bluegrass (Poa secunda J. Presl) was assessed over the intermountain western United States in relation to source population climate. Common gardens were established at two intermountain west sites with progeny from two maternal parents from each of 130 wild populations. Data were collected over 2 years at each site on fifteen plant traits associated with production, phenology, and morphology. Analyses of variance revealed strong population differences for all plant traits (P < 0.0001), indicating genetic variation. Both the canonical correlation and linear correlation established associations between source populations and climate variability. Populations from warmer, more arid climates had generally lower dry weight, earlier phenology, and smaller, narrower leaves than those from cooler, moister climates. The first three canonical variates were regressed with climate variables resulting in significant models (P < 0.0001) used to map 12 seed zones. Of the 700 981 km(2) mapped, four seed zones represented 92% of the area in typically semi-arid and arid regions. The association of genetic variation with source climates in the intermountain west suggested climate driven natural selection and evolution. We recommend seed transfer zones and population movement guidelines to enhance adaptation and diversity for large-scale restoration projects.

Incorporating Plant Phenology Dynamics in a Biophysical Canopy Model

NASA Technical Reports Server (NTRS)

Barata, Raquel A.; Drewry, Darren

2012-01-01

The Multi-Layer Canopy Model (MLCan) is a vegetation model created to capture plant responses to environmental change. Themodel vertically resolves carbon uptake, water vapor and energy exchange at each canopy level by coupling photosynthesis, stomatal conductance and leaf energy balance. The model is forced by incoming shortwave and longwave radiation, as well as near-surface meteorological conditions. The original formulation of MLCan utilized canopy structural traits derived from observations. This project aims to incorporate a plant phenology scheme within MLCan allowing these structural traits to vary dynamically. In the plant phenology scheme implemented here, plant growth is dependent on environmental conditions such as air temperature and soil moisture. The scheme includes functionality that models plant germination, growth, and senescence. These growth stages dictate the variation in six different vegetative carbon pools: storage, leaves, stem, coarse roots, fine roots, and reproductive. The magnitudes of these carbon pools determine land surface parameters such as leaf area index, canopy height, rooting depth and root water uptake capacity. Coupling this phenology scheme with MLCan allows for a more flexible representation of the structure and function of vegetation as it responds to changing environmental conditions.

Variability of Phenology and Fluxes of Water and Carbon with Observed and Simulated Soil Moisture in the Ent Terrestrial Biosphere Model (Ent TBM Version 1.0.1.0.0)

NASA Technical Reports Server (NTRS)

Kim, Y.; Moorcroft, P. R.; Aleinov, Igor; Puma, M. J.; Kiang, N. Y.

2015-01-01

The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0 coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost hardening), soil moisture (linearity of stress with relative saturation) and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leaf-out and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan- Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US) and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs.

Variability of phenology and fluxes of water and carbon with observed and simulated soil moisture in the Ent Terrestrial Biosphere Model (Ent TBM version 1.0.1.0.0)

NASA Astrophysics Data System (ADS)

Kim, Y.; Moorcroft, P. R.; Aleinov, I.; Puma, M. J.; Kiang, N. Y.

2015-12-01

The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0 coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost hardening), soil moisture (linearity of stress with relative saturation) and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leaf-out and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan-Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US) and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs.

Seasonality of isoprenoid emissions from a primary rainforest in central Amazonia

DOE PAGES

Alves, Eliane G.; Jardine, Kolby; Tota, Julio; ...

2016-03-23

Tropical rainforests are an important source of isoprenoid and other volatile organic compound (VOC) emissions to the atmosphere. The seasonal variation of these compounds is however still poorly understood. In this study, vertical profiles of mixing ratios of isoprene, total monoterpenes and total sesquiterpenes, were measured within and above the canopy, in a primary rainforest in central Amazonia, using a proton transfer reaction – mass spectrometer (PTR-MS). Fluxes of these compounds from the canopy into the atmosphere were estimated from PTR-MS measurements by using an inverse Lagrangian transport model. Measurements were carried out continuously from September 2010 to January 2011,more » encompassing the dry and wet seasons. Mixing ratios were higher during the dry (isoprene – 2.68 ± 0.9 ppbv, total monoterpenes – 0.67 ± 0.3 ppbv; total sesquiterpenes – 0.09 ± 0.07 ppbv) than the wet season (isoprene – 1.66 ± 0.9 ppbv, total monoterpenes – 0.47 ± 0.2 ppbv; total sesquiterpenes – 0.03 ± 0.02 ppbv) for all compounds. Ambient air temperature and photosynthetically active radiation (PAR) behaved similarly. Daytime isoprene and total monoterpene mixing ratios were highest within the canopy, rather than near the ground or above the canopy. By comparison, daytime total sesquiterpene mixing ratios were highest near the ground. Daytime fluxes varied significantly between seasons for all compounds. The maximums for isoprene (2.53 ± 0.5 µmol m -2 h -1) and total monoterpenes (1.77 ± 0.05 µmol m -2 h -1) were observed in the late dry season, whereas the maximum for total sesquiterpenes was found during the dry-to-wet transition season (0.77 ± 0.1 µmol m -2 h -1). These flux estimates suggest that the canopy is the main source of isoprenoids emitted into the atmosphere for all seasons. However, uncertainties in turbulence parameterization near the ground could affect estimates of fluxes that come from the ground. Leaf phenology seemed to be an important driver of seasonal variation of isoprenoid emissions. Although remote sensing observations of changes in leaf area index were used to estimate leaf phenology, MEGAN 2.1 did not fully capture the behavior of seasonal emissions observed in this study. This could be a result of very local effects on the observed emissions, but also suggest that other parameters need to be better determined in biogenic volatile organic compound (BVOC) models. Our results support established findings that seasonality of isoprenoids are driven by seasonal changes in light, temperature and leaf phenology. However, they suggest that leaf phenology and its role on isoprenoid production and emission from tropical plant species needs to be better understood in order to develop mechanistic explanations for seasonal variation in emissions. This also may reduce the uncertainties of model estimates associated with the responses to environmental factors. Therefore, this study strongly encourages long-term measurements of isoprenoid emissions, environmental factors and leaf phenology from leaf to ecosystem scale, with the purpose of improving BVOC model approaches that can characterize seasonality of isoprenoid emissions from tropical rainforests.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alves, Eliane G.; Jardine, Kolby; Tota, Julio

Tropical rainforests are an important source of isoprenoid and other volatile organic compound (VOC) emissions to the atmosphere. The seasonal variation of these compounds is however still poorly understood. In this study, vertical profiles of mixing ratios of isoprene, total monoterpenes and total sesquiterpenes, were measured within and above the canopy, in a primary rainforest in central Amazonia, using a proton transfer reaction – mass spectrometer (PTR-MS). Fluxes of these compounds from the canopy into the atmosphere were estimated from PTR-MS measurements by using an inverse Lagrangian transport model. Measurements were carried out continuously from September 2010 to January 2011,more » encompassing the dry and wet seasons. Mixing ratios were higher during the dry (isoprene – 2.68 ± 0.9 ppbv, total monoterpenes – 0.67 ± 0.3 ppbv; total sesquiterpenes – 0.09 ± 0.07 ppbv) than the wet season (isoprene – 1.66 ± 0.9 ppbv, total monoterpenes – 0.47 ± 0.2 ppbv; total sesquiterpenes – 0.03 ± 0.02 ppbv) for all compounds. Ambient air temperature and photosynthetically active radiation (PAR) behaved similarly. Daytime isoprene and total monoterpene mixing ratios were highest within the canopy, rather than near the ground or above the canopy. By comparison, daytime total sesquiterpene mixing ratios were highest near the ground. Daytime fluxes varied significantly between seasons for all compounds. The maximums for isoprene (2.53 ± 0.5 µmol m -2 h -1) and total monoterpenes (1.77 ± 0.05 µmol m -2 h -1) were observed in the late dry season, whereas the maximum for total sesquiterpenes was found during the dry-to-wet transition season (0.77 ± 0.1 µmol m -2 h -1). These flux estimates suggest that the canopy is the main source of isoprenoids emitted into the atmosphere for all seasons. However, uncertainties in turbulence parameterization near the ground could affect estimates of fluxes that come from the ground. Leaf phenology seemed to be an important driver of seasonal variation of isoprenoid emissions. Although remote sensing observations of changes in leaf area index were used to estimate leaf phenology, MEGAN 2.1 did not fully capture the behavior of seasonal emissions observed in this study. This could be a result of very local effects on the observed emissions, but also suggest that other parameters need to be better determined in biogenic volatile organic compound (BVOC) models. Our results support established findings that seasonality of isoprenoids are driven by seasonal changes in light, temperature and leaf phenology. However, they suggest that leaf phenology and its role on isoprenoid production and emission from tropical plant species needs to be better understood in order to develop mechanistic explanations for seasonal variation in emissions. This also may reduce the uncertainties of model estimates associated with the responses to environmental factors. Therefore, this study strongly encourages long-term measurements of isoprenoid emissions, environmental factors and leaf phenology from leaf to ecosystem scale, with the purpose of improving BVOC model approaches that can characterize seasonality of isoprenoid emissions from tropical rainforests.« less

Seasonality of isoprenoid emissions from a primary rainforest in central Amazonia

NASA Astrophysics Data System (ADS)

Alves, Eliane G.; Jardine, Kolby; Tota, Julio; Jardine, Angela; Yãnez-Serrano, Ana Maria; Karl, Thomas; Tavares, Julia; Nelson, Bruce; Gu, Dasa; Stavrakou, Trissevgeni; Martin, Scot; Artaxo, Paulo; Manzi, Antonio; Guenther, Alex

2016-03-01

Tropical rainforests are an important source of isoprenoid and other volatile organic compound (VOC) emissions to the atmosphere. The seasonal variation of these compounds is however still poorly understood. In this study, vertical profiles of mixing ratios of isoprene, total monoterpenes and total sesquiterpenes, were measured within and above the canopy, in a primary rainforest in central Amazonia, using a proton transfer reaction - mass spectrometer (PTR-MS). Fluxes of these compounds from the canopy into the atmosphere were estimated from PTR-MS measurements by using an inverse Lagrangian transport model. Measurements were carried out continuously from September 2010 to January 2011, encompassing the dry and wet seasons. Mixing ratios were higher during the dry (isoprene - 2.68 ± 0.9 ppbv, total monoterpenes - 0.67 ± 0.3 ppbv; total sesquiterpenes - 0.09 ± 0.07 ppbv) than the wet season (isoprene - 1.66 ± 0.9 ppbv, total monoterpenes - 0.47 ± 0.2 ppbv; total sesquiterpenes - 0.03 ± 0.02 ppbv) for all compounds. Ambient air temperature and photosynthetically active radiation (PAR) behaved similarly. Daytime isoprene and total monoterpene mixing ratios were highest within the canopy, rather than near the ground or above the canopy. By comparison, daytime total sesquiterpene mixing ratios were highest near the ground. Daytime fluxes varied significantly between seasons for all compounds. The maximums for isoprene (2.53 ± 0.5 µmol m-2 h-1) and total monoterpenes (1.77 ± 0.05 µmol m-2 h-1) were observed in the late dry season, whereas the maximum for total sesquiterpenes was found during the dry-to-wet transition season (0.77 ± 0.1 µmol m-2 h-1). These flux estimates suggest that the canopy is the main source of isoprenoids emitted into the atmosphere for all seasons. However, uncertainties in turbulence parameterization near the ground could affect estimates of fluxes that come from the ground. Leaf phenology seemed to be an important driver of seasonal variation of isoprenoid emissions. Although remote sensing observations of changes in leaf area index were used to estimate leaf phenology, MEGAN 2.1 did not fully capture the behavior of seasonal emissions observed in this study. This could be a result of very local effects on the observed emissions, but also suggest that other parameters need to be better determined in biogenic volatile organic compound (BVOC) models. Our results support established findings that seasonality of isoprenoids are driven by seasonal changes in light, temperature and leaf phenology. However, they suggest that leaf phenology and its role on isoprenoid production and emission from tropical plant species needs to be better understood in order to develop mechanistic explanations for seasonal variation in emissions. This also may reduce the uncertainties of model estimates associated with the responses to environmental factors. Therefore, this study strongly encourages long-term measurements of isoprenoid emissions, environmental factors and leaf phenology from leaf to ecosystem scale, with the purpose of improving BVOC model approaches that can characterize seasonality of isoprenoid emissions from tropical rainforests.

Seasonality of isoprenoid emissions from a primary rainforest in central Amazonia

NASA Astrophysics Data System (ADS)

Alves, E. G.; Jardine, K.; Tota, J.; Jardine, A.; Yáñez-Serrano, A. M.; Karl, T.; Tavares, J.; Nelson, B.; Gu, D.; Stavrakou, T.; Martin, S.; Manzi, A.; Guenther, A.

2015-10-01

Tropical rainforests are an important source of isoprenoid and other Volatile Organic Compound (VOC) emissions to the atmosphere. The seasonal variation of these compounds is however still poorly understood. In this study, profiles were collected of the vertical profile of mixing ratios of isoprene, total monoterpenes and total sesquiterpenes, within and above the canopy, in a primary rainforest in central Amazonia, using a Proton Transfer Reaction-Mass Spectrometer (PTR-MS). Fluxes of these compounds from the canopy into the atmosphere were estimated from PTR-MS measurements by using an inverse Lagrangian transport model. Measurements were carried out continuously from September 2010 to January 2011, encompassing the dry and wet seasons. Mixing ratios were higher during the dry (isoprene - 2.68 ± 0.9 ppbv, total monoterpenes - 0.67 ± 0.3 ppbv; total sesquiterpenes - 0.09 ± 0.07 ppbv) than the wet season (isoprene - 1.66 ± 0.9 ppbv, total monoterpenes - 0.47 ± 0.2 ppbv; total sesquiterpenes - 0.03 ± 0.02 ppbv) for all compounds. Ambient air temperature and photosynthetically active radiation (PAR) behaved similarly. Daytime isoprene and total monoterpene mixing ratios were highest within the canopy, rather than near the ground or above the canopy. By comparison, daytime total sesquiterpene mixing ratios were highest near the ground. Daytime fluxes varied significantly between seasons for all compounds. The maximums for isoprene (2.53 ± 0.5 μmol m-2 h-1) and total monoterpenes (1.77 ± 0.05 μmol m-2 h-1) were observed in the late dry season, whereas the maximum for total sesquiterpenes was found during the dry-to-wet transition season (0.77 ± 0.1 μmol m-2 h-1). These flux estimates suggest that the canopy is the main source of isoprenoids to the atmosphere for all seasons. However, uncertainties in turbulence parameterization near the ground could affect estimates of fluxes that come from the ground. Leaf phenology seemed to be an important driver of seasonal variation of isoprenoid emissions. Although remote sensing observations of changes in leaf area index were used to estimate leaf phenology, MEGAN 2.1 did not fully capture the behavior of seasonal emissions observed in this study. This could be a result of very local effects on the observed emissions, but also suggest that other parameters need to be better determined in Biogenic Volatile Organic Compound (BVOC) models. Our results support established findings that seasonality of isoprenoids are driven by seasonal changes in light, temperature and leaf phenology. However, they suggest that leaf phenology and its role on isoprenoid production and emission from tropical plant species needs to be better understood in order to develop mechanistic explanations for seasonal variation in emissions. This also may reduce the uncertainties of model estimates associated with the responses to environmental factors. Therefore, this study strongly encourages long-term measurements of isoprenoid emissions, environmental factors and leaf phenology from leaf to ecosystem scale, with the purpose of improving BVOC model approaches that can characterize seasonality of isoprenoid emissions from tropical rainforests.

Phenomapping of rangelands in South Africa using time series of RapidEye data

NASA Astrophysics Data System (ADS)

Parplies, André; Dubovyk, Olena; Tewes, Andreas; Mund, Jan-Peter; Schellberg, Jürgen

2016-12-01

Phenomapping is an approach which allows the derivation of spatial patterns of vegetation phenology and rangeland productivity based on time series of vegetation indices. In our study, we propose a new spatial mapping approach which combines phenometrics derived from high resolution (HR) satellite time series with spatial logistic regression modeling to discriminate land management systems in rangelands. From the RapidEye time series for selected rangelands in South Africa, we calculated bi-weekly noise reduced Normalized Difference Vegetation Index (NDVI) images. For the growing season of 2011⿿2012, we further derived principal phenology metrics such as start, end and length of growing season and related phenological variables such as amplitude, left derivative and small integral of the NDVI curve. We then mapped these phenometrics across two different tenure systems, communal and commercial, at the very detailed spatial resolution of 5 m. The result of a binary logistic regression (BLR) has shown that the amplitude and the left derivative of the NDVI curve were statistically significant. These indicators are useful to discriminate commercial from communal rangeland systems. We conclude that phenomapping combined with spatial modeling is a powerful tool that allows efficient aggregation of phenology and productivity metrics for spatially explicit analysis of the relationships of crop phenology with site conditions and management. This approach has particular potential for disaggregated and patchy environments such as in farming systems in semi-arid South Africa, where phenology varies considerably among and within years. Further, we see a strong perspective for phenomapping to support spatially explicit modelling of vegetation.

Phylogenetic Conservatism in Plant Phenology

NASA Technical Reports Server (NTRS)

Davies, T. Jonathan; Wolkovich, Elizabeth M.; Kraft, Nathan J. B.; Salamin, Nicolas; Allen, Jenica M.; Ault, Toby R.; Betancourt, Julio L.; Bolmgren, Kjell; Cleland, Elsa E.; Cook, Benjamin I.;

Pan European Phenological database (PEP725): a single point of access for European data

NASA Astrophysics Data System (ADS)

Templ, Barbara; Koch, Elisabeth; Bolmgren, Kjell; Ungersböck, Markus; Paul, Anita; Scheifinger, Helfried; Rutishauser, This; Busto, Montserrat; Chmielewski, Frank-M.; Hájková, Lenka; Hodzić, Sabina; Kaspar, Frank; Pietragalla, Barbara; Romero-Fresneda, Ramiro; Tolvanen, Anne; Vučetič, Višnja; Zimmermann, Kirsten; Zust, Ana

2018-06-01

The Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 "Establishing a European phenological data platform for climatological applications" working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/ . Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.

Deciduous forest responses to temperature, precipitation, and drought imply complex climate change impacts.

PubMed

Xie, Yingying; Wang, Xiaojing; Silander, John A

2015-11-03

Changes in spring and autumn phenology of temperate plants in recent decades have become iconic bio-indicators of rapid climate change. These changes have substantial ecological and economic impacts. However, autumn phenology remains surprisingly little studied. Although the effects of unfavorable environmental conditions (e.g., frost, heat, wetness, and drought) on autumn phenology have been observed for over 60 y, how these factors interact to influence autumn phenological events remain poorly understood. Using remotely sensed phenology data from 2001 to 2012, this study identified and quantified significant effects of a suite of environmental factors on the timing of fall dormancy of deciduous forest communities in New England, United States. Cold, frost, and wet conditions, and high heat-stress tended to induce earlier dormancy of deciduous forests, whereas moderate heat- and drought-stress delayed dormancy. Deciduous forests in two eco-regions showed contrasting, nonlinear responses to variation in these explanatory factors. Based on future climate projection over two periods (2041-2050 and 2090-2099), later dormancy dates were predicted in northern areas. However, in coastal areas earlier dormancy dates were predicted. Our models suggest that besides warming in climate change, changes in frost and moisture conditions as well as extreme weather events (e.g., drought- and heat-stress, and flooding), should also be considered in future predictions of autumn phenology in temperate deciduous forests. This study improves our understanding of how multiple environmental variables interact to affect autumn phenology in temperate deciduous forest ecosystems, and points the way to building more mechanistic and predictive models.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment

NASA Astrophysics Data System (ADS)

De Kauwe, M. G.; Medlyn, B.; Walker, A.; Zaehle, S.; Pendall, E.; Norby, R. J.

2017-12-01

Multifactor experiments are often advocated as important for advancing models, yet to date, such models have only been tested against single-factor experiments. We applied 10 models to the multifactor Prairie Heating and CO2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions: comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO2-induced water savings to extend the growing season length. Observed interactive (CO2 × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.

Modeling the impacts of phenological and inter-annual changes in landscape metrics on local biodiversity of agricultural lands of Eastern Ontario using multi-spatial and multi-temporal remote sensing data

NASA Astrophysics Data System (ADS)

Alavi-Shoushtari, N.; King, D.

2017-12-01

Agricultural landscapes are highly variable ecosystems and are home to many local farmland species. Seasonal, phenological and inter-annual agricultural landscape dynamics have potential to affect the richness and abundance of farmland species. Remote sensing provides data and techniques which enable monitoring landscape changes in multiple temporal and spatial scales. MODIS high temporal resolution remote sensing images enable detection of seasonal and phenological trends, while Landsat higher spatial resolution images, with its long term archive enables inter-annual trend analysis over several decades. The objective of this study to use multi-spatial and multi-temporal remote sensing data to model the response of farmland species to landscape metrics. The study area is the predominantly agricultural region of eastern Ontario. 92 sample landscapes were selected within this region using a protocol designed to maximize variance in composition and configuration heterogeneity while controlling for amount of forest and spatial autocorrelation. Two sample landscape extents (1×1km and 3×3km) were selected to analyze the impacts of spatial scale on biodiversity response. Gamma diversity index data for four taxa groups (birds, butterflies, plants, and beetles) were collected during the summers of 2011 and 2012 within the cropped area of each landscape. To extract the seasonal and phenological metrics a 2000-2012 MODIS NDVI time-series was used, while a 1985-2012 Landsat time-series was used to model the inter-annual trends of change in the sample landscapes. The results of statistical modeling showed significant relationships between farmland biodiversity for several taxa and the phenological and inter-annual variables. The following general results were obtained: 1) Among the taxa groups, plant and beetles diversity was most significantly correlated with the phenological variables; 2) Those phenological variables which are associated with the variability in the start of season date across the sample landscapes and the variability in the corresponding NDVI values at that date showed the strongest correlation with the biodiversity indices; 3) The significance of the models improved when using 3×3km site extent both for MODIS and Landsat based models due most likely to the larger sample size over 3x3km.

The USA National Phenology Network's Model for Collaborative Data Generation and Dissemination

NASA Astrophysics Data System (ADS)

Rosemartin, A.; Lincicome, A.; Denny, E. G.; Marsh, L.; Wilson, B. E.

2010-12-01

The USA National Phenology Network (USA-NPN) serves science and society by promoting a broad understanding of plant and animal phenology and the relationships among phenological patterns and all aspects of environmental change. The Network was founded as an NSF-funded Research Coordination Network, for the purpose of fostering collaboration among scientists, policy-makers and the general public to address the challenges posed by global change and its impact on ecosystems and human health. With this mission in mind, the USA-NPN has developed an Information Management System (IMS) to facilitate collaboration and participatory data collection and digitization. The IMS includes components for data storage, such as the National Phenology Database, as well as a Drupal website for information-sharing and data visualization, and a Java application for collection of contemporary observational data. The National Phenology Database is designed to efficiently accommodate large quantities of phenology data and to be flexible to the changing needs of the network. The database allows for the collection, storage and output of phenology data from multiple sources (e.g., partner organizations, researchers and citizen observers), as well as integration with legacy data sets. Participants in the network can submit records (as Drupal content types) for publications, legacy data sets and phenology-related festivals. The USA-NPN’s contemporary phenology data collection effort, Nature’s Notebook also draws on the contributions of participants. Citizen scientists around the country submit data through this Java application (paired with the Drupal site through a shared login) on the life cycle stages of plants and animals in their yards and parks. The North American Bird Phenology Program, now a part of the USA-NPN, also relies on web-based crowdsourcing. Participants in this program are transcribing 6 million scanned paper cards that were collected by observers across the United States from 1880-1970 of migratory bird arrivals. The USA-NPN’s Information Management System represents a collaborative effort to collect, store, synthesize and output phenological data and information for plants, animals and the environment, and is poised to play an key role in understanding phenological response to environmental and climatic change at the local, regional and national scale.

Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data

USGS Publications Warehouse

Gu, Yingxin; Brown, Jesslyn F.; Miura, Tomoaki; van Leeuwen, Willem J.D.; Reed, Bradley C.

2010-01-01

This study introduces a new geographic framework, phenological classification, for the conterminous United States based on Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time-series data and a digital elevation model. The resulting pheno-class map is comprised of 40 pheno-classes, each having unique phenological and topographic characteristics. Cross-comparison of the pheno-classes with the 2001 National Land Cover Database indicates that the new map contains additional phenological and climate information. The pheno-class framework may be a suitable basis for the development of an Advanced Very High Resolution Radiometer (AVHRR)-MODIS NDVI translation algorithm and for various biogeographic studies.

The USA National Phenology Network: A national observatory for assessment of biotic response to environmental variation

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; USA National Phenology Network National Coordinating Office

2011-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org), established in 2007, is a national science and monitoring initiative focused on phenology as a tool to understand how plants, animals and landscapes respond to climatic variability and change. Core functions of the National Coordinating Office (NCO) of USA-NPN are to provide a national information management system including databases, develop and implement internationally standardized phenology monitoring protocols, create partnerships with a variety of organizations including field stations for implementation, facilitate research and the development of decision support tools, and promote education and outreach activities related to phenology and climate change. This presentation will describe programs, tools and materials developed by USA-NPN to facilitate science, management and education related to phenology of plants, animals and landscapes within protected areas at local, regional and national scales. Particular emphasis will be placed on the on-line integrated animal and plant monitoring program, Nature's Notebook, which provides standardized protocols for phenological status monitoring and data management for over 500 animal and plant species. The monitoring system facilitates collection of sampling intensity, absence data, considerable metadata (from site to observation). We recently added functionality for recording estimates of animal abundance and plant canopy development. Real-time raw data for plants (from 2009 to present) and animals (from 2010 to present), including FGDC-compliant metadata and documented methodology, are now available for download from the website. A new data exploration tool premiered in spring 2010 allows sophisticated graphical visualization of integrated phenological and meteorological data. The network seeks to develop partnerships with other organizations interested in (1) implementing vetted, standardized protocols for phenological or ecological monitoring, and (2) using phenology data and information for a variety of modeling applications.

Evolutionary and plastic responses of freshwater invertebrates to climate change: realized patterns and future potential

PubMed Central

Stoks, Robby; Geerts, Aurora N; De Meester, Luc

2014-01-01

We integrated the evidence for evolutionary and plastic trait changes in situ in response to climate change in freshwater invertebrates (aquatic insects and zooplankton). The synthesis on the trait changes in response to the expected reductions in hydroperiod and increases in salinity indicated little evidence for adaptive, plastic, and genetic trait changes and for local adaptation. With respect to responses to temperature, there are many studies on temporal trait changes in phenology and body size in the wild that are believed to be driven by temperature increases, but there is a general lack of rigorous demonstration whether these trait changes are genetically based, adaptive, and causally driven by climate change. Current proof for genetic trait changes under climate change in freshwater invertebrates stems from a limited set of common garden experiments replicated in time. Experimental thermal evolution experiments and common garden warming experiments associated with space-for-time substitutions along latitudinal gradients indicate that besides genetic changes, also phenotypic plasticity and evolution of plasticity are likely to contribute to the observed phenotypic changes under climate change in aquatic invertebrates. Apart from plastic and genetic thermal adjustments, also genetic photoperiod adjustments are widespread and may even dominate the observed phenological shifts. PMID:24454547

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

DOE PAGES

Richardson, Andrew D.; Hufkens, Koen; Milliman, Tom; ...

2018-03-13

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery,more » we derived time series characterizing vegetation colour, including "canopy greenness", processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the "greenness rising" and end of the "greenness falling" stages. Lastly, the database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.« less

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

PubMed Central

Richardson, Andrew D.; Hufkens, Koen; Milliman, Tom; Aubrecht, Donald M.; Chen, Min; Gray, Josh M.; Johnston, Miriam R.; Keenan, Trevor F.; Klosterman, Stephen T.; Kosmala, Margaret; Melaas, Eli K.; Friedl, Mark A.; Frolking, Steve

2018-01-01

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems. PMID:29533393

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Richardson, Andrew D.; Hufkens, Koen; Milliman, Tom

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery,more » we derived time series characterizing vegetation colour, including "canopy greenness", processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the "greenness rising" and end of the "greenness falling" stages. Lastly, the database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.« less

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

NASA Astrophysics Data System (ADS)

Richardson, Andrew D.; Hufkens, Koen; Milliman, Tom; Aubrecht, Donald M.; Chen, Min; Gray, Josh M.; Johnston, Miriam R.; Keenan, Trevor F.; Klosterman, Stephen T.; Kosmala, Margaret; Melaas, Eli K.; Friedl, Mark A.; Frolking, Steve

2018-03-01

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Dispersal

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Myers, O. B.; Budge, A. M.;

Climate change, phenology, and butterfly host plant utilization.

PubMed

Navarro-Cano, Jose A; Karlsson, Bengt; Posledovich, Diana; Toftegaard, Tenna; Wiklund, Christer; Ehrlén, Johan; Gotthard, Karl

2015-01-01

Knowledge of how species interactions are influenced by climate warming is paramount to understand current biodiversity changes. We review phenological changes of Swedish butterflies during the latest decades and explore potential climate effects on butterfly-host plant interactions using the Orange tip butterfly Anthocharis cardamines and its host plants as a model system. This butterfly has advanced its appearance dates substantially, and its mean flight date shows a positive correlation with latitude. We show that there is a large latitudinal variation in host use and that butterfly populations select plant individuals based on their flowering phenology. We conclude that A. cardamines is a phenological specialist but a host species generalist. This implies that thermal plasticity for spring development influences host utilization of the butterfly through effects on the phenological matching with its host plants. However, the host utilization strategy of A. cardamines appears to render it resilient to relatively large variation in climate.

Influence of physiological phenology on the seasonal pattern of ecosystem respiration in deciduous forests.

PubMed

Migliavacca, Mirco; Reichstein, Markus; Richardson, Andrew D; Mahecha, Miguel D; Cremonese, Edoardo; Delpierre, Nicolas; Galvagno, Marta; Law, Beverly E; Wohlfahrt, Georg; Black, T Andrew; Carvalhais, Nuno; Ceccherini, Guido; Chen, Jiquan; Gobron, Nadine; Koffi, Ernest; Munger, J William; Perez-Priego, Oscar; Robustelli, Monica; Tomelleri, Enrico; Cescatti, Alessandro

2015-01-01

Understanding the environmental and biotic drivers of respiration at the ecosystem level is a prerequisite to further improve scenarios of the global carbon cycle. In this study we investigated the relevance of physiological phenology, defined as seasonal changes in plant physiological properties, for explaining the temporal dynamics of ecosystem respiration (RECO) in deciduous forests. Previous studies showed that empirical RECO models can be substantially improved by considering the biotic dependency of RECO on the short-term productivity (e.g., daily gross primary production, GPP) in addition to the well-known environmental controls of temperature and water availability. Here, we use a model-data integration approach to investigate the added value of physiological phenology, represented by the first temporal derivative of GPP, or alternatively of the fraction of absorbed photosynthetically active radiation, for modeling RECO at 19 deciduous broadleaved forests in the FLUXNET La Thuile database. The new data-oriented semiempirical model leads to an 8% decrease in root mean square error (RMSE) and a 6% increase in the modeling efficiency (EF) of modeled RECO when compared to a version of the model that does not consider the physiological phenology. The reduction of the model-observation bias occurred mainly at the monthly time scale, and in spring and summer, while a smaller reduction was observed at the annual time scale. The proposed approach did not improve the model performance at several sites, and we identified as potential causes the plant canopy heterogeneity and the use of air temperature as a driver of ecosystem respiration instead of soil temperature. However, in the majority of sites the model-error remained unchanged regardless of the driving temperature. Overall, our results point toward the potential for improving current approaches for modeling RECO in deciduous forests by including the phenological cycle of the canopy. © 2014 John Wiley & Sons Ltd.

Statistical rice yield modeling using blended MODIS-Landsat based crop phenology metrics in Taiwan

NASA Astrophysics Data System (ADS)

Chen, C. R.; Chen, C. F.; Nguyen, S. T.; Lau, K. V.

2015-12-01

Taiwan is a populated island with a majority of residents settled in the western plains where soils are suitable for rice cultivation. Rice is not only the most important commodity, but also plays a critical role for agricultural and food marketing. Information of rice production is thus important for policymakers to devise timely plans for ensuring sustainably socioeconomic development. Because rice fields in Taiwan are generally small and yet crop monitoring requires information of crop phenology associating with the spatiotemporal resolution of satellite data, this study used Landsat-MODIS fusion data for rice yield modeling in Taiwan. We processed the data for the first crop (Feb-Mar to Jun-Jul) and the second (Aug-Sep to Nov-Dec) in 2014 through five main steps: (1) data pre-processing to account for geometric and radiometric errors of Landsat data, (2) Landsat-MODIS data fusion using using the spatial-temporal adaptive reflectance fusion model, (3) construction of the smooth time-series enhanced vegetation index 2 (EVI2), (4) rice yield modeling using EVI2-based crop phenology metrics, and (5) error verification. The fusion results by a comparison bewteen EVI2 derived from the fusion image and that from the reference Landsat image indicated close agreement between the two datasets (R2 > 0.8). We analysed smooth EVI2 curves to extract phenology metrics or phenological variables for establishment of rice yield models. The results indicated that the established yield models significantly explained more than 70% variability in the data (p-value < 0.001). The comparison results between the estimated yields and the government's yield statistics for the first and second crops indicated a close significant relationship between the two datasets (R2 > 0.8), in both cases. The root mean square error (RMSE) and mean absolute error (MAE) used to measure the model accuracy revealed the consistency between the estimated yields and the government's yield statistics. This study demonstrates advantages of using EVI2-based phenology metrics (derived from Landsat-MODIS fusion data) for rice yield estimation in Taiwan prior to the harvest period.

Evaluation of the Community Land Model (CLM-Crop) in the United States Corn Belt

NASA Astrophysics Data System (ADS)

Chen, M.; Griffis, T.

2013-12-01

An accurate representation of crop phenology in land surface models is crucial for predicting the carbon, water and energy budgets of managed ecosystems. Soybean and corn are cultivated in approximately 600,000 km2 in the Corn Belt- an area greater than the entire State of California. Accurate prediction of the radiation, energy, and carbon budgets of this region is especially important for understanding its influence on radiative forcing, the thermodynamic properties of the atmospheric boundary layer, and changes in climate. Recently, key algorithms describing crop biophysics and interactive crop management (planting, fertilization, irrigation, harvesting) have been implemented in the Community Land Model (CLM-Crop). CLM-Crop provides a framework for prognostic simulation of crop phenology and evaluation of human management decisions under future climate scenarios. However, there is an important need to evaluate CLM-Crop against a broad range of agricultural site observations in order to understand its limitations and to help optimize the crop biophysical parameterization. Here we evaluated CLM-Crop version 4.5 at 9 AmeriFlux corn/soybean sites that are located within the United States Corn Belt. The following questions were addressed: 1) How well does CLM perform for the 9 crop sites with different management techniques (e.g., tillage vs. no-till, rainfed vs. irrigated)? 2) What are the model's strengths and weaknesses of simulating crop phenology, energy fluxes and carbon fluxes? 3) What steps are needed in order to improve the reliability of the CLM-Crop simulations? Our preliminary results indicate that CLM-Crop can simulate the radiation, energy, and carbon fluxes with reasonable accuracy during the mid growing season. The model performance degrades substantially during the early and late growing seasons, which we attribute to a bias in crop phenology. For instance, we observed that the simulated corn and soybean phenology (LAI) has an earlier phase than the observations by about 15 days at many sites. Here, we show how the optimization of carbon allocation and crop phenology influences the modeled radiation, energy, and carbon fluxes and discuss other model deficiencies associated with the crop biophysics scheme.

Forecasting plant phenology: evaluating the phenological models for Betula pendula and Padus racemosa spring phases, Latvia.

PubMed

Kalvāns, Andis; Bitāne, Māra; Kalvāne, Gunta

2015-02-01

A historical phenological record and meteorological data of the period 1960-2009 are used to analyse the ability of seven phenological models to predict leaf unfolding and beginning of flowering for two tree species-silver birch Betula pendula and bird cherry Padus racemosa-in Latvia. Model stability is estimated performing multiple model fitting runs using half of the data for model training and the other half for evaluation. Correlation coefficient, mean absolute error and mean squared error are used to evaluate model performance. UniChill (a model using sigmoidal development rate and temperature relationship and taking into account the necessity for dormancy release) and DDcos (a simple degree-day model considering the diurnal temperature fluctuations) are found to be the best models for describing the considered spring phases. A strong collinearity between base temperature and required heat sum is found for several model fitting runs of the simple degree-day based models. Large variation of the model parameters between different model fitting runs in case of more complex models indicates similar collinearity and over-parameterization of these models. It is suggested that model performance can be improved by incorporating the resolved daily temperature fluctuations of the DDcos model into the framework of the more complex models (e.g. UniChill). The average base temperature, as found by DDcos model, for B. pendula leaf unfolding is 5.6 °C and for the start of the flowering 6.7 °C; for P. racemosa, the respective base temperatures are 3.2 °C and 3.4 °C.

Chapter 6: Temperature

USGS Publications Warehouse

Jones, Leslie A.; Muhlfeld, Clint C.; Hauer, F. Richard; F. Richard Hauer,; Lamberti, G.A.

2017-01-01

Stream temperature has direct and indirect effects on stream ecology and is critical in determining both abiotic and biotic system responses across a hierarchy of spatial and temporal scales. Temperature variation is primarily driven by solar radiation, while landscape topography, geology, and stream reach scale ecosystem processes contribute to local variability. Spatiotemporal heterogeneity in freshwater ecosystems influences habitat distributions, physiological functions, and phenology of all aquatic organisms. In this chapter we provide an overview of methods for monitoring stream temperature, characterization of thermal profiles, and modeling approaches to stream temperature prediction. Recent advances in temperature monitoring allow for more comprehensive studies of the underlying processes influencing annual variation of temperatures and how thermal variability may impact aquatic organisms at individual, population, and community based scales. Likewise, the development of spatially explicit predictive models provide a framework for simulating natural and anthropogenic effects on thermal regimes which is integral for sustainable management of freshwater systems.

Integration for Airborne Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Nickovic, S.; Huete, A.; Budge, A.; Flowers, L.

2008-01-01

The objective of the program is to assess the feasibility of combining a dust transport model with MODIS derived phenology to study pollen transport for integration with a public health decision support system. The use of pollen information has specifically be identified as a critical need by the New Mexico State Health department for inclusion in the Environmental Public Health Tracking (EPHT) program. Material and methods: Pollen can be transported great distances. Local observations of plan phenology may be consistent with the timing and source of pollen collected by pollen sampling instruments. The Dust REgional Atmospheric Model (DREAM) is an integrated modeling system designed to accurately describe the dust cycle in the atmosphere. The dust modules of the entire system incorporate the state of the art parameterization of all the major phases of the atmospheric dust life such as production, diffusion, advection, and removal. These modules also include effects of the particles size distribution on aerosol dispersion. The model was modified to use pollen sources instead of dust. Pollen release was estimated based on satellite-derived phenology of key plan species and vegetation communities. The MODIS surface reflectance product (MOD09) provided information on the start of the plant growing season, growth stage, and pollen release. The resulting deterministic model is useful for predicting and simulating pollen emission and downwind concentration to study details of phenology and meteorology and their dependencies. The proposed linkage in this project provided critical information on the location timing and modeled transport of pollen directly to the EPHT> This information is useful to support the centers for disease control and prevention (CDC)'s National EPHT and the state of New Mexico environmental public health decision support for asthma and allergies alerts.

Short-term dynamics and partitioning of newly assimilated carbon in the foliage of adult beech and pine are driven by seasonal variations

NASA Astrophysics Data System (ADS)

Desalme, Dorine; Priault, Pierrick; Gérant, Dominique; Dannoura, Masako; Maillard, Pascale; Plain, Caroline; Epron, Daniel

2017-04-01

Carbon (C) allocation is a key process determining C cycling in forest ecosystems. However, the mechanisms underlying the annual patterns of C partitioning in trees, influenced by tree phenology and environmental conditions, are not well identified yet. This study aimed to characterize the short-term dynamics and partitioning of newly assimilated carbon in the foliage of adult European beeches (Fagus sylvatica) and maritime pines (Pinus pinaster) across the seasons. We hypothesized that residence times of recently assimilated C in C compounds should change according to the seasons and that seasonal pattern should differ between deciduous and evergreen tree species, since they have different phenology. 13CO2 pulse-labelling experiments were performed in situ at different dates corresponding to different phenological stages. In beech leaves and pine needles, C contents, isotopic compositions, and 13C dynamics parameters were determined in total organic matter (bulk foliage), in polar fraction (PF, including soluble sugars, amino acids, organic acids) and in starch. For both species and at each phenological stage, 13C amount in bulk foliage decreased following a two-pool exponential model, highlighting the partitioning of newly assimilated C between 'mobile' and 'stable' pools. The relative proportion of the stable pool was maximal in beech leaves in May, when leaves were still growing and could incorporate newly assimilated C in structural C compounds. Young pine needles were still receiving C from previous-year needles in June (two months after budburst) although they are already photosynthesizing, acting as a strong C sink. In summer, short mean residence times of 13C (MRT) in foliage of both tree species reflected the fast respiration and exportation of recent photosynthates to support the whole tree C demand (e.g., supplying perennial organ growth). At the end of the growing season, pre-senescing beech leaves were supplying 13C to perennial organs, whereas overwintering pine needles accumulated labelled PF, probably to acclimate to colder winter temperatures. Results of this experiment revealed that the dynamics and the in-leaf partitioning of newly assimilated C varied seasonally according to the phenology of the two species. In the future, coupling 13C pulse labelling with compound-specific isotope analysis will be promising for tracing the allocation of newly assimilated C to various physiological functions such as growth, export, osmoregulation and defence in trees submitted to global changes.

Responses of rubber leaf phenology to climatic variations in Southwest China

NASA Astrophysics Data System (ADS)

Zhai, De-Li; Yu, Haiying; Chen, Si-Chong; Ranjitkar, Sailesh; Xu, Jianchu

2017-11-01

The phenology of rubber trees (Hevea brasiliensis) could be influenced by meteorological factors and exhibits significant changes under different geoclimates. In the sub-optimal environment in Xishuangbanna, rubber trees undergo lengthy periods of defoliation and refoliation. The timing of refoliation from budburst to leaf aging could be affected by powdery mildew disease (Oidium heveae), which negatively impacts seed and latex production. Rubber trees are most susceptible to powdery mildew disease at the copper and leaf changing stages. Understanding and predicting leaf phenology of rubber trees are helpful to develop effective means of controlling the disease. This research investigated the effect of several meteorological factors on different leaf phenological stages in a sub-optimal environment for rubber cultivation in Jinghong, Yunnan in Southwest China. Partial least square regression was used to quantify the relationship between meteorological factors and recorded rubber phenologies from 2003 to 2011. Minimum temperature in December was found to be the critical factor for the leaf phenology development of rubber trees. Comparing the delayed effects of minimum temperature, the maximum temperature, diurnal temperature range, and sunshine hours were found to advancing leaf phenologies. A comparatively lower minimum temperature in December would facilitate the advancing of leaf phenologies of rubber trees. Higher levels of precipitation in February delayed the light green and the entire process of leaf aging. Delayed leaf phenology was found to be related to severe rubber powdery mildew disease. These results were used to build predictive models that could be applied to early warning systems of rubber powdery mildew disease.

Measuring phenological variability from satellite imagery

USGS Publications Warehouse

Reed, Bradley C.; Brown, Jesslyn F.; Vanderzee, D.; Loveland, Thomas R.; Merchant, James W.; Ohlen, Donald O.

1994-01-01

Vegetation phenological phenomena are closely related to seasonal dynamics of the lower atmosphere and are therefore important elements in global models and vegetation monitoring. Normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite sensor offer a means of efficiently and objectively evaluating phenological characteristics over large areas. Twelve metrics linked to key phenological events were computed based on time-series NDVI data collected from 1989 to 1992 over the conterminous United States. These measures include the onset of greenness, time of peak NDVI, maximum NDVI, rate of greenup, rate of senescence, and integrated NDVI. Measures of central tendency and variability of the measures were computed and analyzed for various land cover types. Results from the analysis showed strong coincidence between the satellite-derived metrics and predicted phenological characteristics. In particular, the metrics identified interannual variability of spring wheat in North Dakota, characterized the phenology of four types of grasslands, and established the phenological consistency of deciduous and coniferous forests. These results have implications for large- area land cover mapping and monitoring. The utility of re- motely sensed data as input to vegetation mapping is demonstrated by showing the distinct phenology of several land cover types. More stable information contained in ancillary data should be incorporated into the mapping process, particularly in areas with high phenological variability. In a regional or global monitoring system, an increase in variability in a region may serve as a signal to perform more detailed land cover analysis with higher resolution imagery.

Phenological Impacts of Hurricane Katrina (2005) and Gustav (2008) on Louisiana Coastal Marshes

NASA Astrophysics Data System (ADS)

Mo, Y.; Kearney, M.; Riter, A.

2015-12-01

Coastal marshes provide indispensable ecological functions, such as offering habitat for economic fish and wildlife, improving water quality, protecting inland areas from floods, and stabilizing the shoreline. Hurricanes—though helping to maintain the elevation of coastal wetlands by depositing large amounts of sediments—pose one of the largest threats for coastal marshes in terms of eroding shorelines, scouring marsh surfaces, and resuspending sediments. Coastal marshes phenologies can be important for understanding broad response of marshes to stressors, like hurricanes. We investigated the phenological impacts of Katrina and Gustav (Category 3 and 2 hurricanes at landfall in southeast Louisiana on 29 August, 2005, and 1 September, 2008, respectively) on freshwater, intermediate, brackish, and saline marshes in southeastern Louisiana. Landsat-derived Normalized Difference Vegetation Index data were processed using ENVI 4.8. Phenological patterns of the marshes were modeled using a nonlinear mixed model using SAS 9.4. We created and compared marsh phenologies of 1994 and 2014, the reference years, to those of 2005 and 2008, the hurricane years. Preliminary results show that in normal years: (1) the NDVI of four marsh types peaked in July; (2) freshwater marshes had the highest peak NDVI, followed by intermediate, brackish, and saline marshes; and (3) the growth durations of the marshes are around three to six months. In 2005, the major phenological change was shortening of growth duration, which was most obvious for intermediate and brackish marshes. The peak NDVI values of the four marsh types were not affected because the hurricane occurred at the end of August, one month after the peak NDVI time. By comparison, there was no obvious phenological impact on the marshes by Gustav (2008) with respect to peak NDVI, peak NDVI day, and growth duration.

Development and Validation of National Phenology Data Products

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; Rosemartin, A.; Crimmins, T. M.; Gerst, K.

2015-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) serves science and society by promoting a broad understanding of plant and animal phenology and the relationships among phenological patterns and environmental change. The National Phenology Database (NPDb) maintained by USA-NPN contains almost 6 million in-situ observation records for plants and animals for the period 1954-2015. These data have been used in a number of science, conservation and natural resource management applications, including national assessments of historical and potential future trends in phenology and regional assessments of spatio-temporal variation in organismal activity. Customizable downloads of raw or summarized data, freely available from www.usanpn.org, are accompanied by metadata, data-use and data-attribution policies, published protocols, version/change control, documentation of QA/QC, and links to publications that use historical or contemporary data held in the NPDb. The National Coordinating Office of USA-NPN is developing a suite of standard data products (e.g., quality-controlled raw or summarized status data) and tools (e.g., a new visualization tool released in 2015) to facilitate use and application by a diverse set of data users. This presentation outlines a workflow for the development and validation of spatially gridded phenology products, drawing on recent work related to the Spring Indices now included in two national Indicator systems. In addition, we discuss how we engage observers to collect in-situ data to validate model predictions. Preliminary analyses indicate high fidelity between historical in-situ and modeled observations on a national scale, but with considerable variability at the regional scale. Regions with strong differences between expected and observed data are identified and will be the focus of in-situ data collection campaigns using USA-NPN's Nature's Notebook on-line user interface (www.nn.usanpn.org).

Monitoring Spatial Patterns of Vegetation Phenology in AN Australian Tropical Transect Using Modis Evi

NASA Astrophysics Data System (ADS)

Ma, X.; Huete, A.; Yu, Q.; Davies, K.; Coupe, N. R.

2012-07-01

Phenology is receiving increasing interest in the area of climate change and vegetation adaptation to climate. The phenology of a landscape can be used as a key parameter in land surface models and dynamic global vegetation models to more accurately simulate carbon, water and energy exchanges between land cover and atmosphere. However, the characterisation of phenology is lacking in tropical savannas which cover more than 30% of global land area, and are highly vulnerable to climate change. The objective of this study is to investigate the spatial pattern of vegetation phenology along the Northern Australia Tropical Transect (NATT) where the major biomes are wet and dry tropical savannas. For this analysis we used more than 11 years Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) product from 2000 to 2011. Eight phenological metrics were derived: Start of Season (SOS), End of Season (EOS), Length of Season (LOS), Maximum EVI (MaxG), Minimum EVI (MinG), annual amplitude (AMP), large integral (LIG), and small integral (SIG) were generated for each year and each pixel. Our results showed there are significant spatial patterns and considerable interannual variations of vegetation phenology along the NATT study area. Generally speaking, vegetation growing season started and ended earlier in the north, and started and ended later in the south, resulting in a southward decrease of growing season length (LOS). Vegetation productivity, which was represented by annual integral EVI (LIG), showed a significant descending trend from the northern part of NATT to the southern part. Segmented regression analysis showed that there exists a distinguishable breakpoint along the latitudinal gradient, at least in terms of annual minimum EVI (EVI), which is located between 18.84°S to 20.04°S.

A System for Monitoring and Forecasting Land Surface Phenology Using Time Series of JPSS VIIRS Observations and Its Applications

NASA Astrophysics Data System (ADS)

Zhang, X.; Yu, Y.; Liu, L.

2015-12-01

Land surface phenology quantifies seasonal dynamics of vegetation properties including the timing and magnitude of vegetation greenness from satellite observations. Over the last decade, historical time series of AVHRR and MODIS data has been used to characterize the seasonal and interannual variation in terrestrial ecosystems and their responses to a changing and variable climate. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on board the operational JPSS satellites provides land surface observations in a timely fashion, which has the capability to monitor phenological development in near real time. This capability is particularly important for assisting agriculture, natural resource management, and land modeling for weather prediction systems. Here we introduce a system to monitor in real time and forecast in the short term phenological development based on daily VIIRS observations available with a one-day latency. The system integrates a climatological land surface phenology from long-term MODIS data and available VIIRS observations to simulate a set of potential temporal trajectories of greenness development at a given time and pixel. The greenness trajectories, which are qualified using daily two-band Enhanced Vegetation Index (EVI2), are applied to identify spring green leaf development and autumn color foliage status in real time and to predict the occurrence of future phenological events. This system currently monitors vegetation development across the North America every three days and makes prediction to 10 days ahead. We further introduce the applications of near real time spring green leaf and fall color foliage. Specifically, this system is used for tracing the crop progress across the United States, guiding the field observations in US National Phenology Network, servicing tourists for the observation of color fall foliage, and parameterizing seasonal surface physical conditions for numerical weather prediction models.

Building a Shared Understanding of Phenology

NASA Astrophysics Data System (ADS)

Rosemartin, A.; Posthumus, E.; Gerst, K.

2017-12-01

The USA National Phenology Network (USA-NPN) seeks to advance the science of phenology and support the use of phenology information in decision-making. We envision that natural resource, human health, recreation and land-use decisions, in the context of a variable and changing climate, will be supported by USA-NPN products and tools. To achieve this vision we developed a logic model, breaking down the necessary inputs (e.g., IT infrastructure), participants, activities and the short- to long-term goals (e.g., use of phenological information in adaptive management). Here we compare the ongoing activities and outcomes of three recent collaborations to our logic model, in order to improve the model and inform future collaborations. At Midway Atoll National Wildlife Refuge, resource managers use the USA-NPN's phenology monitoring program to pinpoint the minimum number of days between initial growth and seed set in an invasive species. The data output and calendar visualizations that USA-NPN provides are sufficient to identify the appropriate treatment window. In contrast to a direct relationship with a natural resource manager using USA-NPN tools and products, some collaborations require substantive iterative work between partners. USA-NPN and National Park Service staff, along with academic researchers, assessed advancement in the timing of spring, and delivered the work in a format appropriate for park managers. Lastly, collaborations with indigenous communities reveal a requirement to reconsider the relationship between Western science and indigenous knowledge systems, as well as address ethical considerations and develop trust, before Western science can be meaningfully incorporated into decision-making. While the USA-NPN is a boundary organization, working in between federal agencies, states and universities, and is mandated to support decision-making, we still face challenges in generating usable science. We share lessons learned based on our experience with diverse and evolving partnerships.

Impact of urbanization on abundance and phenology of caterpillars and consequences for breeding in an insectivorous bird.

PubMed

Seress, Gábor; Hammer, Tamás; Bókony, Veronika; Vincze, Ernő; Preiszner, Bálint; Pipoly, Ivett; Sinkovics, Csenge; Evans, Karl L; Liker, András

2018-04-20

Urbanization can have marked effects on plant and animal populations' phenology, population size, predator-prey interactions and reproductive success. These aspects are rarely studied simultaneously in a single system, and some are rarely investigated, e.g. how insect phenology responds to urban development. Here, we study a tri-trophic system of trees - phytophagous insects (caterpillars) - insectivorous birds (great tits) to assess how urbanization influences i) the phenology of each component of this system, ii) insect abundance and iii) avian reproductive success. We use data from two urban and two forest sites in Hungary, central Europe, collected over four consecutive years. Despite a trend of earlier leaf emergence in urban sites there is no evidence for an earlier peak in caterpillar abundance. Thus, contrary to the frequently stated prediction in the literature, the earlier breeding of urban bird populations is not associated with an earlier peak in caterpillar availability. Despite this the seasonal dynamics of caterpillar biomass exhibited striking differences between habitat types with a single clear peak in forests, and several much smaller peaks in urban sites. Caterpillar biomass was higher in forests than urban areas across the entire sampling period, and between 8.5 and 24 times higher during the first brood's chick-rearing period. This higher biomass was not associated with taller trees in forest sites, or with tree species identity, and occurred despite most of our focal trees being native to the study area. Urban great tits laid smaller clutches, experienced more frequent nestling mortality from starvation, reared fewer offspring to fledging age, and their fledglings had lower body mass. Our study strongly indicates that food limitation is responsible for lower avian reproductive success in cities, which is driven by reduced availability of the preferred nestling diet, i.e. caterpillars, rather than phenological shifts in the timing of peak food availability. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

K-12 Phenology Lessons for the Phenocam Project

NASA Astrophysics Data System (ADS)

Bennett, K. F.

2013-12-01

Phenology is defined as periodic [or annual] life cycles of plants and animals driven by seasonal environmental changes. Climate change impinges a strong effect on phenology, potentially altering the structure and functioning of ecosystems. In the fall of 2011, the Ashburnham-Westminster Regional School District became the first of five schools to join Harvard University's Phenocam Network with the installation of a webcam to monitor phenology (or 'phenocam') at Overlook Middle School in Ashburnham, Massachusetts. Our school district is now part of a network of near-surface remote sensing phenocams that capture and send images of forest, shrub, and grassland vegetation cover at more than 130 diverse sites in North America. Our phenocam provides a digital image every half hour of the mixed forest canopy north from the school, enabling the detection of changes in canopy development, quantified as canopy 'greenness'. As a part of the Phenocam project, students at the K-12 level have expanded the scope of phenological monitoring protocol that is part of the Harvard Forest Schoolyard Ecology Program, Buds, Leaves, and Global Warming. In this protocol, students work with ecologists at Harvard Forest to monitor buds and leaves on schoolyard trees to determine the length of the growing season, giving them the opportunity to be a part of real and important research concerning the critical environmental issue of climate change. Students involved in the Buds, Leaves, and Global Warming study have the opportunity to compare their ground data on budburst, color change, and leaf drop to the phenocam images, as well as to similar forested sites in locations throughout the United States. Lessons have been developed for comparing student data to phenocam images, canopy greenness time series graphs extracted from the images, and satellite data. Lessons addressing map scale and the Urban Heat Island effect will also be available for teachers. This project will greatly enhance the district's Science, Technology, Engineering and Math, (STEM) initiative and further our goal of educating ecologically literate citizens.

Links between plant species’ spatial and temporal responses to a warming climate

PubMed Central

Amano, Tatsuya; Freckleton, Robert P.; Queenborough, Simon A.; Doxford, Simon W.; Smithers, Richard J.; Sparks, Tim H.; Sutherland, William J.

2014-01-01

To generate realistic projections of species’ responses to climate change, we need to understand the factors that limit their ability to respond. Although climatic niche conservatism, the maintenance of a species’s climatic niche over time, is a critical assumption in niche-based species distribution models, little is known about how universal it is and how it operates. In particular, few studies have tested the role of climatic niche conservatism via phenological changes in explaining the reported wide variance in the extent of range shifts among species. Using historical records of the phenology and spatial distribution of British plants under a warming climate, we revealed that: (i) perennial species, as well as those with weaker or lagged phenological responses to temperature, experienced a greater increase in temperature during flowering (i.e. failed to maintain climatic niche via phenological changes); (ii) species that failed to maintain climatic niche via phenological changes showed greater northward range shifts; and (iii) there was a complementary relationship between the levels of climatic niche conservatism via phenological changes and range shifts. These results indicate that even species with high climatic niche conservatism might not show range shifts as instead they track warming temperatures during flowering by advancing their phenology. PMID:24478304

Response of the Morus bombycis growing season to temperature and its latitudinal pattern in Japan.

PubMed

Doi, Hideyuki

2012-09-01

Changes in leaf phenology lengthen the growing season length (GSL, the days between leaf budburst and leaf fall) under the global warming. GSL and the leaf phenology response to climate change is one of the most important predictors of climate change effect on plants. Empirical evidence of climatic effects on GSL remains scarce, especially at a regional scale and the latitudinal pattern. This study analyzed the datasets of leaf budburst and fall phenology in Morus bombycis (Urticales), which were observed by the agency of the Japan Meteorological Agency (JMA) from 1953 to 2005 over a wide range of latitudes in Japan (31 to 44° N). In the present study, single regression slopes of leaf phenological timing and air temperature across Japan were calculated and their spatial patterns using general linear models were tested. The results showed that the GSL extension was caused mainly by a delay in leaf fall phenology. Relationships between latitude and leaf phenological and GSL responses against air temperature were significantly negative. The response of leaf phenology and GSL to air temperature at lower latitudes was larger than that at higher latitudes. The findings indicate that GSL extension should be considered with regards to latitude and climate change.

Phenology of species interactions in response to climate change: two case studies of plant-pollinator interactions using long-term data

NASA Astrophysics Data System (ADS)

McKinney, A. M.; Inouye, D. W.

2012-12-01

Climate change may alter the temporal overlap among interacting taxa with potential demographic consequences. Evidence of mistimed interactions in response to climate change, especially between plants and pollinators, is mixed, and few long-term datasets exist to test for changes in synchrony. Furthermore, advancements in flowering driven by climate change are especially pronounced at higher latitudes, so that migratory pollinators from lower latitudes may increasingly arrive at breeding grounds after the appearance of floral resources. We explored long-term shifts in phenological synchrony in two plant-pollinator systems:1) syrphid fly and flowering phenology in the Colorado Rocky Mountains, USA (1992-2011) and 2) hummingbird arrival relative to onset of early-season nectar resources in the Colorado Rocky Mountains (1975-2011) and the Santa Catalina Mountains, Arizona, USA (1984-2010). We investigated the abiotic cues associated with the phenology of the activity period of syrphid flies and their floral resources, including degree days above freezing, precipitation, and timing of snowmelt as potential explanatory variables. Timing of snowmelt was the best predictor of the onset of flowering and syrphid emergence. Snowmelt was also the best predictor of the end of flowering, while temperature and precipitation best predicted the end of the syrphid period. Both the onset and end of flowering advanced more rapidly than syrphids in response to earlier snowmelt. These different rates of phenological advancement resulted in increased temporal overlap between the flower and syrphid community in years of early snowmelt, because of longer flowering and fly activity periods during these years. If snowmelt continues to advance, temporal overlap between syrphids and their floral resources is therefore likely to increase. This case study shows that the phenology of interacting taxa may respond differently to climate cues, but that this does not necessarily lead to phenological mismatch. To explore the hypothesis that changes in phenological synchrony will occur at the northern edge of the breeding range of migratory pollinators, we compared dates of first arrival of Broad-tailed Hummingbirds (Selasphorus platycercus) to dates of flowering of plants they visit for nectar. Near the southern limit of the breeding range, neither hummingbird arrival nor first flowering dates have changed significantly over the past few decades. Near the northern limit of the breeding range, first and peak flowering of early-season food plants have shifted to earlier dates, resulting in a shorter interval between appearance of first hummingbirds and first flowers. If phenological shifts continue at current rates, hummingbirds will eventually arrive at northern breeding grounds after flowering begins, which could reduce their nesting success. This problem could be compounded by a mid-season drop in flower availability that is appearing as the growing season starts earlier. These results support the prediction that migratory species may experience the greatest phenological mismatches at the poleward limits of their migration. A novel hypothesis based on these results posits that the poleward limit for some species may contract toward lower latitudes under continued warming.

Duration of xylogenesis in black spruce lengthened between 1950 and 2010.

PubMed

Boulouf Lugo, Jacqueline; Deslauriers, Annie; Rossi, Sergio

2012-11-01

Reconstructions have identified the 20th century as being uniquely warm in the last 1000 years. Changes in the phenology of primary meristems converged toward increases in length of the growing season. Has the phenology of secondary meristem changed during the last century, and to what extent? Timings of wood formation in black spruce, Picea mariana, were monitored for 9 years on a weekly timescale at four sites in the boreal forest of Quebec, Canada. Models for assessing xylem phenology were defined and applied to reconstruct onset, ending and duration of xylogenesis between 1950 and 2010 using thermal thresholds on chronologies of maximum and minimum temperatures. All sites exhibited increasing trends of both annual and May-September temperatures, with the greatest changes observed at the higher latitudes. Phenological events in spring were more affected than those occurring in autumn, with cambial resumptions occurring 0·5-0·8 d decade(-1) earlier. The duration of xylogenesis has lengthened significantly since 1950, although the models supplied wide ranges of variations, between 0·07 and 1·5 d decade(-1), respectively. The estimated changes in past cambial phenology demonstrated the marked effects of the recent increase in temperature on the phenological traits of secondary meristems. In the long run, the advancement of cambial activity could modify the short time window for growth of boreal species and dramatically affect the dynamics and productivity of trees in these temperature-limited ecosystems.

Duration of xylogenesis in black spruce lengthened between 1950 and 2010

PubMed Central

Boulouf Lugo, Jacqueline; Deslauriers, Annie; Rossi, Sergio

2012-01-01

Background and Aims Reconstructions have identified the 20th century as being uniquely warm in the last 1000 years. Changes in the phenology of primary meristems converged toward increases in length of the growing season. Has the phenology of secondary meristem changed during the last century, and to what extent? Methods Timings of wood formation in black spruce, Picea mariana, were monitored for 9 years on a weekly timescale at four sites in the boreal forest of Quebec, Canada. Models for assessing xylem phenology were defined and applied to reconstruct onset, ending and duration of xylogenesis between 1950 and 2010 using thermal thresholds on chronologies of maximum and minimum temperatures. Key Results All sites exhibited increasing trends of both annual and May–September temperatures, with the greatest changes observed at the higher latitudes. Phenological events in spring were more affected than those occurring in autumn, with cambial resumptions occurring 0·5–0·8 d decade−1 earlier. The duration of xylogenesis has lengthened significantly since 1950, although the models supplied wide ranges of variations, between 0·07 and 1·5 d decade−1, respectively. Conclusions The estimated changes in past cambial phenology demonstrated the marked effects of the recent increase in temperature on the phenological traits of secondary meristems. In the long run, the advancement of cambial activity could modify the short time window for growth of boreal species and dramatically affect the dynamics and productivity of trees in these temperature-limited ecosystems. PMID:23041380

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery: A new, publicly-available dataset

NASA Astrophysics Data System (ADS)

Richardson, A. D.

2015-12-01

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is highly sensitive to climate change and variability, and is thus a key aspect of global change ecology. The goal of the PhenoCam network is to serve as a long-term, continental-scale, phenological observatory. The network uses repeat digital photography—images captured using conventional, visible-wavelength, automated digital cameras—to characterize vegetation phenology in diverse ecosystems across North America and around the world. At present, imagery from over 200 research sites, spanning a wide range of ecoregions, climate zones, and plant functional types, is currently being archived and processed in near-real-time through the PhenoCam project web page (http://phenocam.sr.unh.edu/). Data derived from PhenoCam imagery have been previously used to evaluate satellite phenology products, to constrain and test new phenology models, to understand relationships between canopy phenology and ecosystem processes, and to study the seasonal changes in leaf-level physiology that are associated with changes in leaf color. I will describe a new, publicly-available phenological dataset, derived from over 600 site-years of PhenoCam imagery. For each archived image (ca. 5 million), we extracted RGB (red, green, blue) color channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 minute) imagery, we derived time series characterizing vegetation color, including "canopy greenness", processed to 1- and 3-day intervals. For ecosystems with a single annual cycle of vegetation activity, we derived estimates, with uncertainties, for the start, middle, and end of spring and autumn phenological transitions. Given the lack of multi-year, standardized, and geographically distributed phenological data for North America, we anticipate that these datasets will be widely used by researchers in a variety of fields. Shifts in phenology are a particularly tangible example of the biological impacts of climate change, and thus these data may also find use in science education and outreach to the general public.

Topoclimate effects on growing season length and montane conifer growth in complex terrain

NASA Astrophysics Data System (ADS)

Barnard, D. M.; Barnard, H. R.; Molotch, N. P.

2017-05-01

Spatial variability in the topoclimate-driven linkage between forest phenology and tree growth in complex terrain is poorly understood, limiting our understanding of how ecosystems function as a whole. To characterize the influence of topoclimate on phenology and growth, we determined the start, end, and length of the growing season (GSstart, GSend, and GSL, respectively) using the correlation between transpiration and evaporative demand, measured with sapflow. We then compared these metrics with stem relative basal area increment (relative BAI) at seven sites among elevation and aspects in a Colorado montane forest. As elevation increased, we found shorter GSL (-50 d km-1) due to later GSstart (40 d km-1) and earlier GSend (-10 d km-1). North-facing sites had a 21 d shorter GSL than south-facing sites at similar elevations (i.e. equal to 200 m elevation difference on a given aspect). Growing season length was positively correlated with relative BAI, explaining 83% of the variance. This study shows that topography exerts strong environmental controls on GSL and thus forest growth. Given the climate-related dependencies of these controls, the results presented here have important implications for ecosystem responses to changes in climate and highlight the need for improved phenology representation in complex terrain.

You Can Run, But You Can't Hide Juniper Pollen Phenology and Dispersal

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.

2013-01-01

Pollen can be transported great distances. Van de Water et. al., 2003 reported Juniperus spp. pollen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust. We are modified the DREAM model to incorporate pollen transport. Pollen release is estimated based on MODIS derived phenology of Juniperus spp. communities. Ground based observational records of pollen release timing and quantities are used as verification. This information will be used to support the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.

Forests and Phenology: Designing the Early Warning System to Understand Forest Change

NASA Astrophysics Data System (ADS)

Pierce, T.; Phillips, M. B.; Hargrove, W. W.; Dobson, G.; Hicks, J.; Hutchins, M.; Lichtenstein, K.

2010-12-01

Vegetative phenology is the study of plant development and changes with the seasons, such as the greening-up and browning-down of forests, and how these events are influenced by variations in climate. A National Phenology Data Set, based on Moderate Resolution Imaging Spectroradiometer satellite images covering 2002 through 2009, is now available from work by NASA, the US Forest Service, and Oak Ridge National Laboratory. This new data set provides an easily interpretable product useful for detecting changes to the landscape due to long-term factors such as climate change, as well as finding areas affected by short-term forest threats such as insects or disease. The Early Warning System (EWS) is a toolset being developed by the US Forest Service and the University of North Carolina-Asheville to support distribution and use of the National Phenology Data Set. The Early Warning System will help research scientists, US Forest Service personnel, forest and natural resources managers, decision makers, and the public in the use of phenology data to better understand unexpected change within our nation’s forests. These changes could have multiple natural sources such as insects, disease, or storm damage, or may be due to human-induced events, like thinning, harvest, forest conversion to agriculture, or residential and commercial use. The primary goal of the Early Warning System is to provide a seamless integration between monitoring, detection, early warning and prediction of these forest disturbances as observed through phenological data. The system consists of PC and web-based components that are structured to support four user stages of increasing knowledge and data sophistication. Building Literacy: This stage of the Early Warning System educates potential users about the system, why the system should be used, and the fundamentals about the data the system uses. The channels for this education include a website, interactive tutorials, pamphlets, and other technology transfer methodologies. Achieving Context and Meaning: To provide deeper meaning and knowledge about the Early Warning System to users, this stage of the Early Warning System provides more information about specific examples of disturbances seen in the phenological data, as well the spatial and temporal context to these disturbances. The main components of this stage are specific case studies of forest disturbances. Accessing Data: This component of the Early Warning System includes products for research scientists, the aerial detection survey sketch mapper community, and others who will access and analyze the Early Warning System and phenological data. Products and data will be available through online GIS mashups and WMS and KML downloads. Utilizing Services: The final stage of the Early Warning System supports the analysis of phenological data and serves the results to those end users, including forest managers, the forest industry, and the public, who need to locate past, present, and potential forest disturbances. The main components of this stage include data-driven web tools, automated analysis processes, and end user training programs.

Land Use and Environmental Variability Impacts on the Phenology of Arid Agro-Ecosystems.

PubMed

Romo-Leon, Jose Raul; van Leeuwen, Willem J D; Castellanos-Villegas, Alejandro

2016-02-01

The overexploitation of water resources in arid environments often results in abandonment of large extensions of agricultural lands, which may (1) modify phenological trends, and (2) alter the sensitivity of specific phenophases to environmental triggers. In Mexico, current governmental policies subsidize restoration efforts, to address ecological degradation caused by abandonments; however, there is a need for new approaches to assess their effectiveness. Addressing this, we explore a method to monitor and assess (1) land surface phenology trends in arid agro-ecosystems, and (2) the effect of climatic factors and restoration treatments on the phenology of abandoned agricultural fields. We used 16-day normalized difference vegetation index composites from the moderate resolution imaging spectroradiometer from 2000 to 2009 to derive seasonal phenometrics. We then derived phenoclimatic variables and land cover thematic maps, to serve as a set of independent factors that influence vegetation phenology. We conducted a multivariate analysis of variance to analyze phenological trends among land cover types, and developed multiple linear regression models to assess influential climatic factors driving phenology per land cover analyzed. Our results suggest that the start and length of the growing season had different responses to environmental factors depending on land cover type. Our analysis also suggests possible establishment of arid adapted species (from surrounding ecosystems) in abandoned fields with longer times since abandonment. Using this approach, we were able increase our understanding on how climatic factors influence phenology on degraded arid agro-ecosystems, and how this systems evolve after disturbance.

Assessing the impact of extreme air temperature on fruit trees by modeling weather dependent phenology with variety-specific thermal requirements

NASA Astrophysics Data System (ADS)

Alfieri, Silvia Maria; De Lorenzi, Francesca; Missere, Daniele; Buscaroli, Claudio; Menenti, Massimo

2013-04-01

Extremely high and extremely low temperature may have a terminal impact on the productivity of fruit tree if occurring at critical phases of development. Notorious examples are frost during flowering or extremely high temperature during fruit setting. The dates of occurrence of such critical phenological stages depend on the weather history from the start of the yearly development cycle in late autumn, thus the impact of climate extremes can only be evaluated correctly if the phenological development is modeled taking into account the weather history of the specific year being evaluated. Climate change impact may lead to a shift in timing of phenological stages and change in the duration of vegetative and reproductive phases. A changing climate can also exhibit a greater climatic variability producing quite large changes in the frequency of extreme climatic events. We propose a two-stage approach to evaluate the impact of predicted future climate on the productivity of fruit trees. The phenological development is modeled using phase - specific thermal times and variety specific thermal requirements for several cultivars of pear, apricot and peach. These requirements were estimated using phenological observations over several years in Emilia Romagna region and scientific literature. We calculated the dates of start and end of rest completion, bud swell, flowering, fruit setting and ripening stages , from late autumn through late summer. Then phase-specific minimum and maximum cardinal temperature were evaluated for present and future climate to estimate how frequently they occur during any critically sensitive phenological phase. This analysis has been done for past climate (1961 - 1990) and fifty realizations of a year representative of future climate (2021 - 2050). A delay in rest completion of about 10-20 days has been predicted for future climate for most of the cultivars. On the other hand the predicted rise in air temperature causes an earlier development of crops thus a reduction in the length of the different phenological stages. Despite the earlier timing of phenological phases may expose the crops to frost hazard, the mean increase of air temperature avoids relevant impacts on crops. The frequency of air temperatures higher than the cardinal temperatures is expected to increase by 5% compared with the reference 1961 - 1990 climate. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008)

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Prasad, A.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Budge, A. M.;

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Prasad, A.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Budge, A. M.;

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

NASA Astrophysics Data System (ADS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A. R.; Nickovic, S.; Prasad, A. K.; Pejanovic, G.; Vukovic, A.; Van De Water, P. K.; Budge, A.; Hudspeth, W. B.; Krapfl, H.; Toth, B.; Zelicoff, A.; Myers, O.; Bunderson, L.; Ponce-Campos, G.; Menache, M.; Crimmins, T. M.; Vujadinovic, M.

2012-12-01

Pollen can be transported great distances. Van de Water et. al., 2003 reported Juniperus spp. pollen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and concentrations of dust. We are modifying the DREAM model to incorporate pollen transport. Pollen emission is based on MODIS-derived phenology of Juniperus spp. communities. Ground-based observational records of pollen release timing and quantities will be used as model verification. This information will be used to support the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.

Monitoring phenology of photosynthesis in temperate evergreen and mixed deciduous forests using the normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) at leaf and canopy scales

NASA Astrophysics Data System (ADS)

Wong, C. Y.; Arain, M. A.; Ensminger, I.

2016-12-01

Evergreen conifers in boreal and temperate regions undergo strong seasonal changes in photoperiod and temperatures, which determines their phenology of high photosynthetic activity in the growing season and downregulation during the winter. Monitoring the timing of the transition between summer activity and winter downregulation in evergreens is difficult since this is a largely invisible process, unlike in deciduous trees that have a visible budding and a sequence of leaf unfolding in the spring and leaf abscission in the fall. The light-use efficiency (LUE) model estimates gross primary productivity (GPP) and may be parameterized using remotely sensed vegetation indices. Using spectral reflectance data, we derived the normalized difference vegetation index (NDVI), a measure of leaf "greenness", and the photochemical reflectance index (PRI), a proxy for chlorophyll:carotenoid ratios which is related to photosynthetic activity. To better understand the relationship between these vegetation indices and photosynthetic activity and to contrast this relationship between plant functional types, the phenology of NDVI, PRI and photosynthesis was monitored in an evergreen forest and a mixed deciduous forest at the leaf and canopy scale. Our data indicates that the LUE model can be parameterized by NDVI and PRI to track forest phenology. Differences in the sensitivity of PRI and NDVI will be discussed. These findings have implications to address the phenology of evergreen conifers by using PRI to complement NDVI in the LUE model, potentially improving model productivity estimates in northern hemisphere forests, that are dominated by conifers.

Impact of dynamic vegetation phenology on the simulated pan-Arctic land surface state

NASA Astrophysics Data System (ADS)

Teufel, Bernardo; Sushama, Laxmi; Arora, Vivek K.; Verseghy, Diana

2018-03-01

The pan-Arctic land surface is undergoing rapid changes in a warming climate, with near-surface permafrost projected to degrade significantly during the twenty-first century. Vegetation-related feedbacks have the potential to influence the rate of degradation of permafrost. In this study, the impact of dynamic phenology on the pan-Arctic land surface state, particularly near-surface permafrost, for the 1961-2100 period, is assessed by comparing two simulations of the Canadian Land Surface Scheme (CLASS)—one with dynamic phenology, modelled using the Canadian Terrestrial Ecosystem Model (CTEM), and the other with prescribed phenology. These simulations are forced by atmospheric data from a transient climate change simulation of the 5th generation Canadian Regional Climate Model (CRCM5) for the Representative Concentration Pathway 8.5 (RCP8.5). Comparison of the CLASS coupled to CTEM simulation to available observational estimates of plant area index, spatial distribution of permafrost and active layer thickness suggests that the model captures reasonably well the overall distribution of vegetation and permafrost. It is shown that the most important impact of dynamic phenology on the land surface occurs through albedo and it is demonstrated for the first time that vegetation control on albedo during late spring and early summer has the highest potential to impact the degradation of permafrost. While both simulations show extensive near-surface permafrost degradation by the end of the twenty-first century, the strong projected response of vegetation to climate warming and increasing CO2 concentrations in the coupled simulation results in accelerated permafrost degradation in the northernmost continuous permafrost regions.

Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break.

PubMed

Chuine, Isabelle; Bonhomme, Marc; Legave, Jean-Michel; García de Cortázar-Atauri, Iñaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

2016-10-01

The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future. © 2016 John Wiley & Sons Ltd.

Daily MODIS 500 m Reflectance Anisotropy Direct Broadcast (DB) Products for Monitoring Vegetation Phenology Dynamics

NASA Technical Reports Server (NTRS)

Shuai, Yanmin; Schaaf, Crystal; Zhang, Xiaoyang; Strahler, Alan; Roy, David; Morisette, Jeffrey; Wang, Zhuosen; Nightingale, Joanne; Nickeson, Jaime; Richardson, Andrew D.;

Synthesizing plant phenological indicators from multispecies datasets

NASA Astrophysics Data System (ADS)

Rutishauser, This; Peñuelas, Josep; Filella, Iolanda; Gehrig, Regula; Scherrer, Simon C.; Röthlisberger, Christian

2014-05-01

Changes in the seasonality of life cycles of plants from phenological observations are traditionally analysed at the species level. Trends and correlations with main environmental driving variables show a coherent picture across the globe. The question arises whether there is an integrated phenological signal across species that describes common interannual variability. Is there a way to express synthetic phenological indicators from multispecies datasets that serve decision makers as usefull tools? Can these indicators be derived in such a robust way that systematic updates yield necessary information for adaptation measures? We address these questions by analysing multi-species phenological data sets with leaf-unfolding and flowering observations from 30 sites across Europe between 40° and 63°N including data from PEP725, the Swiss Plant Phenological Observation Network and one legacy data set. Starting in 1951 the data sets were synthesized by multivariate analysis (Principal Component Analysis). The representativeness of the site specific indicator was tested against subsets including only leaf-unfolding or flowering phases, and by a comparison with a 50% random sample of the available phenophases for 500 time steps. Results show that a synthetic indicators explains up to 79% of the variance at each site - usually 40-50% or more. Robust linear trends over the common period 1971-2000 indicate an overall change of the indicator of -0.32 days/year with lower uncertainty than previous studies. Advances were more pronounced in southern and northern Europe. The indicator-based analysis provides a promising tool for synthesizing site-based plant phenological records and is a companion to, and validating data for, an increasing number of phenological measurements derived from phenological models and satellite sensors.

The USA National Phenology Network; taking the pulse of our planet

USGS Publications Warehouse

Weltzin, Jake F.

2011-01-01

People have tracked phenology for centuries and for the most practical reasons: it helped them know when to hunt and fish, when to plant and harvest crops, and when to navigate waterways. Now phenology is being used as a tool to assess climate change and its effects on both natural and modified ecosystems. How is the timing of events in plant and animal life cycles, like flowering or migration, responding to climate change? And how are those responses, in turn, affecting people and ecosystems? The USA National Phenology Network (the Network) is working to answer these questions for science and society by promoting a broad understanding of plant and animal phenology and their relationship to environmental change. The Network is a consortium of organizations and individuals that collect, share, and use phenology data, models, and related information to enable scientists, resource managers, and the public to adapt in response to changing climates and environments. In addition, the Network encourages people of all ages and backgrounds to observe and record phenology as a way to discover and explore the nature and pace of our dynamic world. The National Coordinating Office (NCO) of the Network is a resource center that facilitates and encourages widespread collection, integration, and sharing of phenology data and related information (for example, meteorological and hydrological data). The NCO develops and promotes standardized methods for field data collection and maintains several online user interfaces for data upload and download, as well as data exploration, visualization, and analysis. The NCO also facilitates basic and applied research related to phenology, the development of decision-support tools for resource managers and planners, and the design of educational and outreach materials

Phenology Data Products to Support Assessment and Forecasting of Phenology on Multiple Spatiotemporal Scales

NASA Astrophysics Data System (ADS)

Gerst, K.; Enquist, C.; Rosemartin, A.; Denny, E. G.; Marsh, L.; Moore, D. J.; Weltzin, J. F.

2014-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) serves science and society by promoting a broad understanding of plant and animal phenology and the relationships among phenological patterns and environmental change. The National Phenology Database maintained by USA-NPN now has over 3.7 million records for plants and animals for the period 1954-2014, with the majority of these observations collected since 2008 as part of a broad, national contributory science strategy. These data have been used in a number of science, conservation and resource management applications, including national assessments of historical and potential future trends in phenology, regional assessments of spatio-temporal variation in organismal activity, and local monitoring for invasive species detection. Customizable data downloads are freely available, and data are accompanied by FGDC-compliant metadata, data-use and data-attribution policies, vetted and documented methodologies and protocols, and version control. While users are free to develop custom algorithms for data cleaning, winnowing and summarization prior to analysis, the National Coordinating Office of USA-NPN is developing a suite of standard data products to facilitate use and application by a diverse set of data users. This presentation provides a progress report on data product development, including: (1) Quality controlled raw phenophase status data; (2) Derived phenometrics (e.g. onset, duration) at multiple scales; (3) Data visualization tools; (4) Tools to support assessment of species interactions and overlap; (5) Species responsiveness to environmental drivers; (6) Spatially gridded phenoclimatological products; and (7) Algorithms for modeling and forecasting future phenological responses. The prioritization of these data products is a direct response to stakeholder needs related to informing management and policy decisions. We anticipate that these products will contribute to broad understanding of plant and animal phenology across scientific disciplines.

Response of vegetation phenology to urbanization in the conterminous United States

DOE PAGES

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.; ...

2016-12-18

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003–2012. We found that phenology cycle (changes in vegetation greenness) in urban areas starts earlier (start of season, SOS) and ends latermore » (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days.Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6–6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. In conclusion, the quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology.« less

Density dependence and phenological mismatch: consequences for growth and survival of sub-arctic nesting Canada Geese

USGS Publications Warehouse

Brook, Rodney W.; Leafloor, James O.; Douglas, David C.; Abraham, Kenneth F.

2015-01-01

The extent to which species are plastic in the timing of their reproductive events relative to phenology suggests how change might affect their demography. An ecological mismatch between the timing of hatch for avian species and the peak availability in quality and quantity of forage for rapidly growing offspring might ultimately affect recruitment to the breeding population unless individuals can adjust the timing of breeding to adapt to changing phenology. We evaluated effects of goose density, hatch timing relative to forage plant phenology, and weather indices on annual growth of pre-fledging Canada geese (Branta canadensis) from 1993-2010 at Akimiski Island, Nunavut. We found effects of both density and hatch timing relative to forage plant phenology; the earlier that eggs hatched relative to forage plant phenology, the larger the mean gosling size near fledging. Goslings were smallest in years when hatch was latest relative to forage plant phenology, and when local abundance of breeding adults was highest. We found no evidence for a trend in relative hatch timing, but it was apparent that in early springs, Canada geese tended to hatch later relative to vegetation phenology, suggesting that geese were not always able to adjust the timing of nesting as rapidly as vegetation phenology was advanced. Analyses using forage biomass information revealed a positive relationship between gosling size and per capita biomass availability, suggesting a causal mechanism for the density effect. The effects of weather parameters explained additional variation in mean annual gosling size, although total June and July rainfall had a small additive effect on gosling size. Modelling of annual first year survival probability using mean annual gosling size as an annual covariate revealed a positive relationship, suggesting that reduced gosling growth negatively impacts recruitment.

Assessing climate change impacts on fruit plant and pest phenology and their synchrony: the case of apple and codling moth

NASA Astrophysics Data System (ADS)

Felber, Raphael; Stöckli, Sibylle; Calanca, Pierluigi

2017-04-01

Temperature is a main climatic driver of plant phenology and the dominant abiotic factor directly affecting insect pests. Global warming is therefore expected to accelerate the development of plants and insects. Moreover, in the case of multivoltine pest species higher temperatures are expected to lead to the appearance of additional generations toward the end of the warm season. These changes could entail higher pest pressure and hence require an adaptation of pest management, but ultimately this would depend on whether plant and pest phenology remain synchronized or not. In this contribution we present an analysis of potential impacts of climate change on the phenology of the apple tree (Malus pumila L.), a fruit crop of economic relevance worldwide, and the codling moth (Cydia pomonella L.), one of its main pests. Key developmental stages of the apple and the codling moth were simulated by means of two heat summation models. The models were calibrated with lab and field data from Switzerland and subsequently run with observed weather data and various climate change scenarios. The time period between flowering termination and the harvest of the apples was compared to the appearance of the second and third generation of codling moth larvae to study the interlinkage between host and pest. To illustrate the potential for practical applications of the phenology models, we used spatial temperature data of Switzerland to produce risk maps that can serve as a basis for further studies and decision support.

MODIS phenology image service ArcMap toolbox

USGS Publications Warehouse

Talbert, Colin; Kern, Tim J.; Morisette, Jeff; Brown, Don; James, Kevin

2013-01-01

Seasonal change is important to consider when managing conservation areas at landscape scales. The study of such patterns throughout the year is referred to as phenology. Recurring life-cycle events that are initiated and driven by environmental factors include animal migration and plant flowering. Phenological events capture public attention, such as fall color change in deciduous forests, the first flowering in spring, and for those with allergies, the start of the pollen season. These events can affect our daily lives, provide clues to help understand and manage ecosystems, and provide evidence of how climate variability can affect the natural cycle of plants and animals. Phenological observations can be gathered at a range of scales, from plots smaller than an acre to landscapes of hundreds to thousands of acres. Linking these observations to diverse disciplines such as evolutionary biology or climate sciences can help further research in species and ecosystem responses to climate change scenarios at appropriate scales. A cooperative study between the National Park Service (NPS), the U.S. Geological Survey (USGS), and the National Aeronautics and Space Administration (NASA) has been exploring how satellite information can be used to summarize phenological patterns observed at the park or landscape scale and how those summaries can be presented to both park managers and visitors. This study specifically addressed seasonal changes in plants, including the onset of growth, photosynthesis in the spring, and the senescence of deciduous vegetation in the fall. The primary objective of the work is to demonstrate that seasonality even in protected areas changes considerably across years. A major challenge is to decouple natural variability from possible trends—directional change that can lead to a permanent and radically different ecosystem state. Trends can be either a gradual degradation of the landscape (often from external influences) or steady improvement (by implementing long-term conservation plans). In either case, it is important to first grasp the magnitude of natural variation so that it is not confused with actual trends. This work used existing and freely available remote sensing data, specifically the NASA-funded 250-meter (m) spatial resolution land-surface phenology product for North America. This product is calculated from an annual record of vegetation health observed by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The land-surface phenology product is, in essence, a method to summarize all the observations throughout a year into a few key, ecologically relevant “metrics”.

Simulating the probability of grain sorghum maturity before the first frost in northeastern Colorado

USDA-ARS?s Scientific Manuscript database

Expanding grain sorghum [Sorghum bicolor (L.) Moench] production northward from southeastern Colorado is thought to be limited by shorter growing seasons due to lower temperatures and earlier frost dates. This study used a simulation model for predicting crop phenology (PhenologyMMS) to predict the ...

Predicting maize phenology: Intercomparison of functions for developmental response to temperature

USDA-ARS?s Scientific Manuscript database

Accurate prediction of phenological development in maize is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. The objectives of this study were t...

Potential and Limitations of Low-Cost Unmanned Aerial Systems for Monitoring Altitudinal Vegetation Phenology in the Tropics

NASA Astrophysics Data System (ADS)

Silva, T. S. F.; Torres, R. S.; Morellato, P.

2017-12-01

Vegetation phenology is a key component of ecosystem function and biogeochemical cycling, and highly susceptible to climatic change. Phenological knowledge in the tropics is limited by lack of monitoring, traditionally done by laborious direct observation. Ground-based digital cameras can automate daily observations, but also offer limited spatial coverage. Imaging by low-cost Unmanned Aerial Systems (UAS) combines the fine resolution of ground-based methods with and unprecedented capability for spatial coverage, but challenges remain in producing color-consistent multitemporal images. We evaluated the applicability of multitemporal UAS imaging to monitor phenology in tropical altitudinal grasslands and forests, answering: 1) Can very-high resolution aerial photography from conventional digital cameras be used to reliably monitor vegetative and reproductive phenology? 2) How is UAS monitoring affected by changes in illumination and by sensor physical limitations? We flew imaging missions monthly from Feb-16 to Feb-17, using a UAS equipped with an RGB Canon SX260 camera. Flights were carried between 10am and 4pm, at 120-150m a.g.l., yielding 5-10cm spatial resolution. To compensate illumination changes caused by time of day, season and cloud cover, calibration was attempted using reference targets and empirical models, as well as color space transformations. For vegetative phenological monitoring, multitemporal response was severely affected by changes in illumination conditions, strongly confounding the phenological signal. These variations could not be adequately corrected through calibration due to sensor limitations. For reproductive phenology, the very-high resolution of the acquired imagery allowed discrimination of individual reproductive structures for some species, and its stark colorimetric differences to vegetative structures allowed detection of the reproductive timing on the HSV color space, despite illumination effects. We conclude that reliable vegetative phenology monitoring may exceed the capabilities of consumer cameras, but reproductive phenology can be successfully monitored for species with conspicuous reproductive structures. Further research is being conducted to improve calibration methods and information extraction through machine learning.

Temperature-Dependent Sex Determination under Rapid Anthropogenic Environmental Change: Evolution at a Turtle's Pace?

PubMed

Refsnider, Jeanine M; Janzen, Fredric J

2016-01-01

Organisms become adapted to their environment by evolving through natural selection, a process that generally transpires over many generations. Currently, anthropogenically driven environmental changes are occurring orders of magnitude faster than they did prior to human influence, which could potentially outpace the ability of some organisms to adapt. Here, we focus on traits associated with temperature-dependent sex determination (TSD), a classic polyphenism, in a model turtle species to address the evolutionary potential of species with TSD to respond to rapid climate change. We show, first, that sex-ratio outcomes in species with TSD are sensitive to climatic variation. We then identify the evolutionary potential, in terms of heritability, of TSD and quantify the evolutionary potential of 3 key traits involved in TSD: pivotal temperature, maternal nest-site choice, and nesting phenology. We find that these traits display different patterns of adaptive potential: pivotal temperature exhibits moderate heritable variation, whereas nest-site choice and nesting phenology, with considerable phenotypic plasticity, have only modest evolutionary potential to alter sex ratios. Therefore, the most likely response of species with TSD to anthropogenically induced climate change may be a combination of microevolution in thermal sensitivity of the sex-determining pathway and of plasticity in maternal nesting behavior. © The American Genetic Association. 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Dispersal

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.

2011-01-01

Pollen can be transported great distances. Van de Water et. al. reported Juniperus spp. pollen was transported 200-600 km. Hence local obse rvations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using MODIS data produ cts to identify source regions and quantities of dust. We are modifyi ng the DREAM model to incorporate pollen transport. Pollen release wi ll be estimated based on MODIS derived phenology of Juniperus spp. communities. Ground based observations records of pollen release timing and quantities will be used as verification. This information will be used to support the Centers for Disease Control and Prevention?s Nat ional Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model To Evaluate Juniperus spp. Pollen Phenology and Dispersal

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, Estelle; Huete, Alfredo; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Myers, O. B.; Budge, A. M.;

USA National Phenology Network’s volunteer-contributed observations yield predictive models of phenological transitions

USGS Publications Warehouse

Crimmins, Theresa M.; Crimmins, Michael A.; Gerst, Katherine L.; Rosemartin, Alyssa H.; Weltzin, Jake F.

2017-01-01

In support of science and society, the USA National Phenology Network (USA-NPN) maintains a rapidly growing, continental-scale, species-rich dataset of plant and animal phenology observations that with over 10 million records is the largest such database in the United States. Contributed voluntarily by professional and citizen scientists, these opportunistically collected observations are characterized by spatial clustering, inconsistent spatial and temporal sampling, and short temporal depth. We explore the potential for developing models of phenophase transitions suitable for use at the continental scale, which could be applied to a wide range of resource management contexts. We constructed predictive models of the onset of breaking leaf buds, leaves, open flowers, and ripe fruits – phenophases that are the most abundant in the database and also relevant to management applications – for all species with available data, regardless of plant growth habit, location, geographic extent, or temporal depth of the observations. We implemented a very basic model formulation - thermal time models with a fixed start date. Sufficient data were available to construct 107 individual species × phenophase models. Of these, fifteen models (14%) met our criteria for model fit and error and were suitable for use across the majority of the species’ geographic ranges. These findings indicate that the USA-NPN dataset holds promise for further and more refined modeling efforts. Further, the candidate models that emerged could be used to produce real-time and short-term forecast maps of the timing of such transitions to directly support natural resource management.

Physiological time model of Scirpophaga incertulas (Lepidoptera: Pyralidae) in rice in Guandong Province, People's Republic of China.

PubMed

Stevenson, Douglass E; Feng, Ge; Zhang, Runjie; Harris, Marvin K

2005-08-01

Scirpophaga incertulas (Walker) (Lepidoptera: Pyralidae) is autochthonous and monophagous on rice, Oryza spp., which favors the development of a physiological time model using degree-days (degrees C) to establish a well defined window during which adults will be present in fields. Model development of S. incertulas adult flight phenology used climatic data and historical field observations of S. incertulas from 1962 through 1988. Analysis of variance was used to evaluate 5,203 prospective models with starting dates ranging from 1 January (day 1) to 30 April (day 121) and base temperatures ranging from -3 through 18.5 degrees C. From six candidate models, which shared the lowest standard deviation of prediction error, a model with a base temperature of 10 degrees C starting on 19 January was selected for validation. Validation with linear regression evaluated the differences between predicted and observed events and showed the model consistently predicted phenological events of 10 to 90% cumulative flight activity within a 3.5-d prediction interval regarded as acceptable for pest management decision making. The degree-day phenology model developed here is expected to find field application in Guandong Province. Expansion to other areas of rice production will require field validation. We expect the degree-day characterization of the activity period will remain essentially intact, but the start day may vary based on climate and geographic location. The development and validation of the phenology model of the S. incertulas by using procedures originally developed for pecan nut casebearer, Acrobasis nuxvorella Neunzig, shows the fungibility of this approach to developing prediction models for other insects.

A specific PFT and sub-canopy structure for simulating oil palm in the Community Land Model

NASA Astrophysics Data System (ADS)

Fan, Y.; Knohl, A.; Roupsard, O.; Bernoux, M.; LE Maire, G.; Panferov, O.; Kotowska, M.; Meijide, A.

2015-12-01

Towards an effort to quantify the effects of rainforests to oil palm conversion on land-atmosphere carbon, water and energy fluxes, a specific plant functional type (PFT) and sub-canopy structure are developed for simulating oil palm within the Community Land Model (CLM4.5). Current global land surface models only simulate annual crops beside natural vegetation. In this study, a multilayer oil palm subroutine is developed in CLM4.5 for simulating oil palm's phenology and carbon and nitrogen allocation. The oil palm has monopodial morphology and sequential phenology of around 40 stacked phytomers, each carrying a large leaf and a fruit bunch, forming a natural multilayer canopy. A sub-canopy phenological and physiological parameterization is thus introduced, so that multiple phytomer components develop simultaneously but according to their different phenological steps (growth, yield and senescence) at different canopy layers. This specific multilayer structure was proved useful for simulating canopy development in terms of leaf area index (LAI) and fruit yield in terms of carbon and nitrogen outputs in Jambi, Sumatra (Fan et al. 2015). The study supports that species-specific traits, such as palm's monopodial morphology and sequential phenology, are necessary representations in terrestrial biosphere models in order to accurately simulate vegetation dynamics and feedbacks to climate. Further, oil palm's multilayer structure allows adding all canopy-level calculations of radiation, photosynthesis, stomatal conductance and respiration, beside phenology, also to the sub-canopy level, so as to eliminate scale mismatch problem among different processes. A series of adaptations are made to the CLM model. Initial results show that the adapted multilayer radiative transfer scheme and the explicit represention of oil palm's canopy structure improve on simulating photosynthesis-light response curve. The explicit photosynthesis and dynamic leaf nitrogen calculations per canopy layer also enhance simulated CO2 flux when compared to eddy covariance flux data. More investigations on energy and water fluxes and nitrogen balance are being conducted. These new schemes would hopefully promote the understanding of climatic effects of the tropical land use transformation system.

Phenology of lilac (Syringa vulgaris) and elderberry (Sambucus nigra) as the indicator of spring warming

NASA Astrophysics Data System (ADS)

Vincze, E.; Hunkár, M.; Dunkel, Z.

2012-04-01

Phenological observations in Hungary started in 1871. The observation system collapsed and revived time by time. The aim of the observations as well as the locations, the methods and observed plants have been changed many times, therefore data series for a given plant species derived from the same place are rare. If we want to study the responses of biosphere to climate variability we need long time data series from the same places, especially phenological data of native plants. Phenological observations organized by the Hungarian Meteorological Service between 1983- 1999 contain valuable data for lilac (Syringa vulgaris) and elderberry (Sambucus nigra). Those perennial native plants are good indicators of spring warming therefore it is worth to study their phenological development concerning to climate variability. Eight locations in Hungary were selected where the site of the observations remaind the same year by year. Observed phenological phases were: Sprouting of leaves (SL, BBCH:11); Begin of Flowers (BF, BBCH:61); Fall of leaves (FO, BBCH:95). Spatial and temporal trends and variability of phenophases will be presented. The effect of meteorological conditions is studied to build up phenological model controlled by the temperature. Growing degree days above the base temperature was involved together with the duration and severeness of the chilling period. The study is supported by the National Scientific Foundation (OTKA-81979).

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment.

PubMed

De Kauwe, Martin G; Medlyn, Belinda E; Walker, Anthony P; Zaehle, Sönke; Asao, Shinichi; Guenet, Bertrand; Harper, Anna B; Hickler, Thomas; Jain, Atul K; Luo, Yiqi; Lu, Xingjie; Luus, Kristina; Parton, William J; Shu, Shijie; Wang, Ying-Ping; Werner, Christian; Xia, Jianyang; Pendall, Elise; Morgan, Jack A; Ryan, Edmund M; Carrillo, Yolima; Dijkstra, Feike A; Zelikova, Tamara J; Norby, Richard J

2017-09-01

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2  yr -1 ). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO 2 -induced water savings to extend the growing season length. Observed interactive (CO 2  × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change. © 2017 John Wiley & Sons Ltd.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO 2 enrichment experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Kauwe, Martin G.; Medlyn, Belinda E.; Walker, Anthony P.

Multi-factor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date such models have only been tested against single-factor experiments. We applied 10 TBMs to the multi-factor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multi-factor experiments can be used to constrain models, and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2 yr -1). Comparison with data highlighted model failures particularlymore » in respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against single-factors was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO 2-induced water savings to extend growing season length. Observed interactive (CO 2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. Finally, we outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.« less

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO 2 enrichment experiment

DOE PAGES

De Kauwe, Martin G.; Medlyn, Belinda E.; Walker, Anthony P.; ...

2017-02-01

Multi-factor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date such models have only been tested against single-factor experiments. We applied 10 TBMs to the multi-factor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multi-factor experiments can be used to constrain models, and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2 yr -1). Comparison with data highlighted model failures particularlymore » in respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against single-factors was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO 2-induced water savings to extend growing season length. Observed interactive (CO 2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. Finally, we outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.« less

Long-term shifts in the phenology of rare and endemic Rocky Mountain plants.

PubMed

Munson, Seth M; Sher, Anna A

2015-08-01

• Mountainous regions support high plant productivity, diversity, and endemism, yet are highly vulnerable to climate change. Historical records and model predictions show increasing temperatures across high elevation regions including the Southern Rocky Mountains, which can have a strong influence on the performance and distribution of montane plant species. Rare plant species can be particularly vulnerable to climate change because of their limited abundance and distribution.• We tracked the phenology of rare and endemic species, which are identified as imperiled, across three different habitat types with herbarium records to determine if flowering time has changed over the last century, and if phenological change was related to shifts in climate.• We found that the flowering date of rare species has accelerated 3.1 d every decade (42 d total) since the late 1800s, with plants in sagebrush interbasins showing the strongest accelerations in phenology. High winter temperatures were associated with the acceleration of phenology in low elevation sagebrush and barren river habitats, whereas high spring temperatures explained accelerated phenology in the high elevation alpine habitat. In contrast, high spring temperatures delayed the phenology of plant species in the two low-elevation habitats and precipitation had mixed effects depending on the season.• These results provide evidence for large shifts in the phenology of rare Rocky Mountain plants related to climate, which can have strong effects on plant fitness, the abundance of associated wildlife, and the future of plant conservation in mountainous regions. © 2015 Botanical Society of America, Inc.

Phenology research for natural resource management in the United States.

PubMed

Enquist, Carolyn A F; Kellermann, Jherime L; Gerst, Katharine L; Miller-Rushing, Abraham J

2014-05-01

Natural resource professionals in the United States recognize that climate-induced changes in phenology can substantially affect resource management. This is reflected in national climate change response plans recently released by major resource agencies. However, managers on-the-ground are often unclear about how to use phenological information to inform their management practices. Until recently, this was at least partially due to the lack of broad-based, standardized phenology data collection across taxa and geographic regions. Such efforts are now underway, albeit in very early stages. Nonetheless, a major hurdle still exists: phenology-linked climate change research has focused more on describing broad ecological changes rather than making direct connections to local to regional management concerns. To help researchers better design relevant research for use in conservation and management decision-making processes, we describe phenology-related research topics that facilitate "actionable" science. Examples include research on evolution and phenotypic plasticity related to vulnerability, the demographic consequences of trophic mismatch, the role of invasive species, and building robust ecological forecast models. Such efforts will increase phenology literacy among on-the-ground resource managers and provide information relevant for short- and long-term decision-making, particularly as related to climate response planning and implementing climate-informed monitoring in the context of adaptive management. In sum, we argue that phenological information is a crucial component of the resource management toolbox that facilitates identification and evaluation of strategies that will reduce the vulnerability of natural systems to climate change. Management-savvy researchers can play an important role in reaching this goal.

Community patterns of tropical tree phenology derived from Unmanned Aerial Vehicle images: intra- and interspecific variation, association with species plant traits, and response to interannual climate variation

NASA Astrophysics Data System (ADS)

Bohlman, Stephanie; Rifai, Sami; Park, John; Dandois, Jonathan; Muller-Landau, Helene

2017-04-01

Phenology is a key life history trait of plant species and critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical forest phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns, which makes it difficult to collect sufficient ground-based field data to characterize individual tropical tree species phenologies. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. The objective of this study is to quantify inter- and intra-specific responses of tropical tree leaf phenology to environmental variation over large spatial scales and identify key environmental variables and physiological mechanisms underpinning phenological variation. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. UAV imagery was corrected for exposure, orthorectified, and then processed to extract spectral, texture, and image information for individual tree crowns, which was then used as inputs for a machine learning algorithm that successfully predicted the percentages of leaf, branch, and flower cover for each tree crown (r2=0.76 between observed and predicted percent branch cover for individual tree crowns). We then quantified cumulative annual deciduousness for each crown by fitting a non-parametric curve of flexible shape to its predicted percent branch time series and calculated the area under the curve. We obtained the species identities of 2000 crowns in the images by linking the crowns to stem tags in the field, thus producing a time series of cumulative annual deciduousness for 65 species. Deciduousness showed continuous variation among species rather than distinct phenological categories (ie evergreen and deciduous) that are commonly used in physiological, ecosystem and modeling studies. Some species labelled as evergreen by expert-based classification had annual deciduousness higher than those labelled as deciduous. We found significant, positive relationships between species mean deciduousness and species' leaf phosphorous, photosynthetic capacity and adult relative growth rate, suggesting that higher deciduousness is associated with greater resource acquisition. Comparing May 2015 (during an El Nino drought) and May 2014 (an non El Nino year with normal rainfall), mean deciduousness values for nearly all species was greater in 2015 but with differing levels of intraspecific variation. We discuss how the variation in deciduousness among species, its relationship with plant traits and response to the drought might be incorporated into terrestrial biosphere models of tropical forests to more accurately represent phenology and understand the consequences of community-level variation in phenology for ecosystem processes.

Environmental effects on growth phenology of co-occurring Eucalyptus species.

PubMed

Rawal, Deepa S; Kasel, Sabine; Keatley, Marie R; Aponte, Cristina; Nitschke, Craig R

2014-05-01

Growth is one of the most important phenological cycles in a plant's life. Higher growth rates increase the competitive ability, survival and recruitment and can provide a measure of a plant's adaptive capacity to climate variability and change. This study identified the growth relationship of six Eucalyptus species to variations in temperature, soil moisture availability, photoperiod length and air humidity over 12 months. The six species represent two naturally co-occurring groups of three species each representing warm-dry and the cool-moist sclerophyll forests, respectively. Warm-dry eucalypts were found to be more tolerant of higher temperatures and lower air humidity than the cool-moist eucalypts. Within groups, species-specific responses were detected with Eucalyptus microcarpa having the widest phenological niche of the warm-dry species, exhibiting greater resistance to high temperature and lower air humidity. Temperature dependent photoperiodic responses were exhibited by all the species except Eucalyptus tricarpa and Eucalyptus sieberi, which were able to maintain growth as photoperiod shortened but temperature requirements were fulfilled. Eucalyptus obliqua exhibited a flexible growth rate and tolerance to moisture limitation which enables it to maintain its growth rate as water availability changes. The wider temperature niche exhibited by E. sieberi compared with E. obliqua and Eucalyptus radiata may improve its competitive ability over these species where winters are warm and moisture does not limit growth. With climate change expected to result in warmer and drier conditions in south-east Australia, the findings of this study suggest all cool-moist species will likely suffer negative effects on growth while the warm-dry species may still maintain current growth rates. Our findings highlight that climate driven shifts in growth phenology will likely occur as climate changes and this may facilitate changes in tree communities by altering inter-specific competition.

Photoperiod cues and patterns of genetic variation limit phenological responses to climate change in warm parts of species’ range: Modeling diameter-growth cessation in coast Douglas-fir

Treesearch

Kevin R. Ford; Constance A. Harrington; J. Bradley St. Clair

2017-01-01

The phenology of diameter-growth cessation in trees will likely play a key role in mediating species and ecosystem responses to climate change. A common expectation is that warming will delay cessation, but the environmental and genetic influences on this process are poorly understood. We modeled the effects of temperature, photoperiod, and seed-source climate on...

Canadian crop calendars in support of the early warning project

NASA Technical Reports Server (NTRS)

Trenchard, M. H.; Hodges, T. (Principal Investigator)

1980-01-01

The Canadian crop calendars for LACIE are presented. Long term monthly averages of daily maximum and daily minimum temperatures for subregions of provinces were used to simulate normal daily maximum and minimum temperatures. The Robertson (1968) spring wheat and Williams (1974) spring barley phenology models were run using the simulated daily temperatures and daylengths for appropriate latitudes. Simulated daily temperatures and phenology model outputs for spring wheat and spring barley are given.

Landsat phenological metrics and their relation to aboveground carbon in the Brazilian Savanna.

PubMed

Schwieder, M; Leitão, P J; Pinto, J R R; Teixeira, A M C; Pedroni, F; Sanchez, M; Bustamante, M M; Hostert, P

2018-05-15

The quantification and spatially explicit mapping of carbon stocks in terrestrial ecosystems is important to better understand the global carbon cycle and to monitor and report change processes, especially in the context of international policy mechanisms such as REDD+ or the implementation of Nationally Determined Contributions (NDCs) and the UN Sustainable Development Goals (SDGs). Especially in heterogeneous ecosystems, such as Savannas, accurate carbon quantifications are still lacking, where highly variable vegetation densities occur and a strong seasonality hinders consistent data acquisition. In order to account for these challenges we analyzed the potential of land surface phenological metrics derived from gap-filled 8-day Landsat time series for carbon mapping. We selected three areas located in different subregions in the central Brazil region, which is a prominent example of a Savanna with significant carbon stocks that has been undergoing extensive land cover conversions. Here phenological metrics from the season 2014/2015 were combined with aboveground carbon field samples of cerrado sensu stricto vegetation using Random Forest regression models to map the regional carbon distribution and to analyze the relation between phenological metrics and aboveground carbon. The gap filling approach enabled to accurately approximate the original Landsat ETM+ and OLI EVI values and the subsequent derivation of annual phenological metrics. Random Forest model performances varied between the three study areas with RMSE values of 1.64 t/ha (mean relative RMSE 30%), 2.35 t/ha (46%) and 2.18 t/ha (45%). Comparable relationships between remote sensing based land surface phenological metrics and aboveground carbon were observed in all study areas. Aboveground carbon distributions could be mapped and revealed comprehensible spatial patterns. Phenological metrics were derived from 8-day Landsat time series with a spatial resolution that is sufficient to capture gradual changes in carbon stocks of heterogeneous Savanna ecosystems. These metrics revealed the relationship between aboveground carbon and the phenology of the observed vegetation. Our results suggest that metrics relating to the seasonal minimum and maximum values were the most influential variables and bear potential to improve spatially explicit mapping approaches in heterogeneous ecosystems, where both spatial and temporal resolutions are critical.

Model estimates of leaf area and reference canopy stomatal conductance suggest correlation between phenology and physiology in both trembling aspen and red pine

NASA Astrophysics Data System (ADS)

Mackay, D. S.; Ewers, B. E.; Kruger, E. L.

2006-12-01

Phenological variations impact water and carbon fluxes, as evidenced by the large interannual variability of net ecosystem exchange of carbon dioxide and evapotranspiration (ET). In northern Wisconsin we observed daily variations of canopy transpiration from hardwoods from 1.0 to 1.7 mm/day during the leaf unfolding period and 1.7 to 2.6 mm/day with leaves fully out. Correlations between such flux rates and phenology have not been extensively tested and mechanistic connections are in their infancy. Some data suggest that stomatal conductance and photosynthesis increases up to full expansion. Moreover, in conifers, the interaction of phenology and physiology is more complicated than in deciduous trees because needles are retained for several years. Using inverse modeling with a coupled photosynthesis-transpiration model we estimated reference canopy stomatal conductance, Gsref, for red pine (Pinus resinosa), and Gsref and leaf area index, L, for trembling aspen (Populus tremuloides), using 30-min continuous sap flux data spanning a period from just prior to the start of leaf expansion to just after leaf senescence. The red pine showed Gsref ramp up from 105 to 179 mmol m-2 leaf s-1, which represented a 37 to 50 percent increase in Gsref after accounting for maximum possible changes in L. After full leaf out, the trembling aspen were almost immediately defoliated, and then reflushed after three weeks. Model estimates of L reflected this pattern and were consistent with measurements. However, Gsref never exceeded 45 mmol m-2 s-1 prior to defoliation, but peaked at 112 mmol m-2 s-1 after reflushing. These results support the need for further work that aims to separate phenology and physiology.

Development of the BIOME-BGC model for the simulation of managed Moso bamboo forest ecosystems.

PubMed

Mao, Fangjie; Li, Pingheng; Zhou, Guomo; Du, Huaqiang; Xu, Xiaojun; Shi, Yongjun; Mo, Lufeng; Zhou, Yufeng; Tu, Guoqing

2016-05-01

Numerical models are the most appropriate instrument for the analysis of the carbon balance of terrestrial ecosystems and their interactions with changing environmental conditions. The process-based model BIOME-BGC is widely used in simulation of carbon balance within vegetation, litter and soil of unmanaged ecosystems. For Moso bamboo forests, however, simulations with BIOME-BGC are inaccurate in terms of the growing season and the carbon allocation, due to the oversimplified representation of phenology. Our aim was to improve the applicability of BIOME-BGC for managed Moso bamboo forest ecosystem by implementing several new modules, including phenology, carbon allocation, and management. Instead of the simple phenology and carbon allocation representations in the original version, a periodic Moso bamboo phenology and carbon allocation module was implemented, which can handle the processes of Moso bamboo shooting and high growth during "on-year" and "off-year". Four management modules (digging bamboo shoots, selective cutting, obtruncation, fertilization) were integrated in order to quantify the functioning of managed ecosystems. The improved model was calibrated and validated using eddy covariance measurement data collected at a managed Moso bamboo forest site (Anji) during 2011-2013 years. As a result of these developments and calibrations, the performance of the model was substantially improved. Regarding the measured and modeled fluxes (gross primary production, total ecosystem respiration, net ecosystem exchange), relative errors were decreased by 42.23%, 103.02% and 18.67%, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

Researcher-driven Campaigns Engage Nature's Notebook Participants in Scientific Data Collection

NASA Technical Reports Server (NTRS)

Crimmins, Theresa M.; Elmore, A. J.; Huete, A.; Keller, S.; Levetin, E.; Luvall, J.; Meyers, O.; Stylinski, C. D.; VandeWater, P.K.; Vukovic, A.

2013-01-01

One of the many benefits of citizen science projects is the capacity they hold for facilitating data collection on a grand scale and thereby enabling scientists to answer questions they would otherwise not been able to address. Nature's Notebook, the plant and animal phenology observing program of the USA National Phenology Network (USA-NPN) suitable for scientists and non-scientists alike, offers scientifically-vetted data collection protocols and infrastructure and mechanisms to quickly reach out to hundreds to thousands of potential contributors. The USA-NPN has recently partnered with several research teams to engage participants in contributing to specific studies. In one example, a team of scientists from NASA, the New Mexico Department of Health, and universities in Arizona, New Mexico, Oklahoma, and California are using juniper phenology observations submitted by Nature's Notebookparticipants to improve predictions of pollen release and inform asthma and allergy alerts. In a second effort, researchers from the University of Maryland Center for Environmental Science are engaging Nature's Notebookparticipants in tracking leafing phenophases of poplars across the U.S. These observations will be compared to information acquired via satellite imagery and used to determine geographic areas where the tree species are most and least adapted to predicted climate change. Results/Conclusions Researchers in these partnerships receive benefits primarily in the form of ground observations. Launched in 2010, the juniper pollen effort has engaged participants in several western states and has yielded thousands of observations that can play a role in model ground validation. Periodic evaluation of these observations has prompted the team to improve and enhance the materials that participants receive, in an effort to boost data quality. The poplar project is formally launching in spring of 2013 and will run for three years; preliminary findings from 2013 will be presented. Participants in these special campaigns benefit through direct engagement in science. This form of researcher partnership has now been successfully pilot-tested and implemented in several instances, and provides a template for future research project campaigns.

Researcher-driven Campaigns Engage Nature's Notebook Participants in Scientific Data Collection

NASA Technical Reports Server (NTRS)

Crimmins, Theresa M.; Elmore, Andrew J.; Huete, Alfredo; Keller, Stephen; Levetin, Estelle; Luvall, Jeffrey; Meyers, Orrin; Stylinski, Cathlyn D.; Van De Water, Peter K.; Vukovic, Ana

2013-01-01

One of the many benefits of citizen science projects is the capacity they hold for facilitating data collection on a grand scale and thereby enabling scientists to answer questions they would otherwise not been able to address. Nature's Notebook, the plant and animal phenology observing program of the USA National Phenology Network (USA-NPN) suitable for scientists and non-scientists alike, offers scientifically-vetted data collection protocols and infrastructure and mechanisms to quickly reach out to hundreds to thousands of potential contributors. The USA-NPN has recently partnered with several research teams to engage participants in contributing to specific studies. In one example, a team of scientists from NASA, the New Mexico Department of Health, and universities in Arizona, New Mexico, Oklahoma, and California are using juniper phenology observations submitted by Nature's Notebookparticipants to improve predictions of pollen release and inform asthma and allergy alerts. In a second effort, researchers from the University of Maryland Center for Environmental Science are engaging Nature's Notebookparticipants in tracking leafing phenophases of poplars across the U.S. These observations will be compared to information acquired via satellite imagery and used to determine geographic areas where the tree species are most and least adapted to predicted climate change. Researchers in these partnerships receive benefits primarily in the form of ground observations. Launched in 2010, the juniper pollen effort has engaged participants in several western states and has yielded thousands of observations that can play a role in model ground validation. Periodic evaluation of these observations has prompted the team to improve and enhance the materials that participants receive, in an effort to boost data quality. The poplar project is formally launching in spring of 2013 and will run for three years; preliminary findings from 2013 will be presented. Participants in these special campaigns benefit through direct engagement in science. This form of researcher partnership has now been successfully pilot-tested and implemented in several instances, and provides a template for future research project campaigns.

Influence of spring phenology on seasonal and annual carbon balance in two contrasting New England forests.

PubMed

Richardson, Andrew D; Hollinger, David Y; Dail, D Bryan; Lee, John T; Munger, J William; O'keefe, John

2009-03-01

Spring phenology is thought to exert a major influence on the carbon (C) balance of temperate and boreal ecosystems. We investigated this hypothesis using four spring onset phenological indicators in conjunction with surface-atmosphere CO(2) exchange data from the conifer-dominated Howland Forest and deciduous-dominated Harvard Forest AmeriFlux sites. All phenological measures, including CO(2) source-sink transition dates, could be well predicted on the basis of a simple two-parameter spring warming model, indicating good potential for improving the representation of phenological transitions and their dynamic responsiveness to climate variability in land surface models. The date at which canopy-scale photosynthetic capacity reached a threshold value of 12 micromol m(-2) s(-1) was better correlated with spring and annual flux integrals than were either deciduous or coniferous bud burst dates. For all phenological indicators, earlier spring onset consistently, but not always significantly, resulted in higher gross primary productivity (GPP) and ecosystem respiration (RE) for both seasonal (spring months, April-June) and annual flux integrals. The increase in RE was less than that in GPP; depending on the phenological indicator used, a one-day advance in spring onset increased springtime net ecosystem productivity (NEP) by 2-4 g C m(-2) day(-1). In general, we could not detect significant differences between the two forest types in response to earlier spring, although the response to earlier spring was generally more pronounced for Harvard Forest than for Howland Forest, suggesting that future climate warming may favor deciduous species over coniferous species, at least in this region. The effect of earlier spring tended to be about twice as large when annual rather than springtime flux integrals were considered. This result is suggestive of both immediate and lagged effects of earlier spring onset on ecosystem C cycling, perhaps as a result of accelerated N cycling rates and cascading effects on N uptake, foliar N concentrations and photosynthetic capacity.

Operational data products to support phenological research and applications at local to continental scales

NASA Astrophysics Data System (ADS)

Weltzin, J. F.

2017-12-01

Phenological data from a variety of platforms - across a range of spatial and temporal scales - are required to support research, natural resource management, and policy- and decision-making in a changing world. Observational and modeled phenological data, especially when integrated with associated biophysical data (e.g., climate, land-use/land-cover, hydrology) has great potential to provide multi-faceted information critical to decision support systems, vulnerability and risk assessments, change detection applications, and early-warning and forecasting systems for natural and modified ecosystems. The USA National Phenology Network (USA-NPN; www.usanpn.org) is a national-scale science and monitoring initiative focused on understanding the drivers and feedback effects of phenological variation in changing environments. The Network maintains a centralized database of over 10M ground-based observations of plants and animals for 1954-present, and leverages these data to produce operational data products for use by a variety of audiences, including researchers and resource managers. This presentation highlights our operational data products, including the tools, maps, and services that facilitate discovery, accessibility and usability of integrated phenological information. We describe (1) the data download tool, a customizable GUI that provides geospatially referenced raw, bounded or summarized organismal and climatological data and associated metadata (including calendars, time-series curves, and XY graphs), (2) the visualization tool, which provides opportunities to explore, visualize and export or download both organismal and modeled (gridded) products at daily time-steps and relatively fine spatial resolutions ( 2.5 km to 4 km) for the period 1980 to 6 days into the future, and (3) web services that enable custom query and download of map, feature and cover services in a variety of standard formats. These operational products facilitate scaling of integrated phenological and associated data to landscapes and regions, and enable novel investigations of biophysical interactions at unprecedented scales, e.g., continental-scale migrations.

A collection of European sweet cherry phenology data for assessing climate change

NASA Astrophysics Data System (ADS)

Wenden, Bénédicte; Campoy, José Antonio; Lecourt, Julien; López Ortega, Gregorio; Blanke, Michael; Radičević, Sanja; Schüller, Elisabeth; Spornberger, Andreas; Christen, Danilo; Magein, Hugo; Giovannini, Daniela; Campillo, Carlos; Malchev, Svetoslav; Peris, José Miguel; Meland, Mekjell; Stehr, Rolf; Charlot, Gérard; Quero-García, José

2016-12-01

Professional and scientific networks built around the production of sweet cherry (Prunus avium L.) led to the collection of phenology data for a wide range of cultivars grown in experimental sites characterized by highly contrasted climatic conditions. We present a dataset of flowering and maturity dates, recorded each year for one tree when available, or the average of several trees for each cultivar, over a period of 37 years (1978-2015). Such a dataset is extremely valuable for characterizing the phenological response to climate change, and the plasticity of the different cultivars' behaviour under different environmental conditions. In addition, this dataset will support the development of predictive models for sweet cherry phenology exploitable at the continental scale, and will help anticipate breeding strategies in order to maintain and improve sweet cherry production in Europe.

A collection of European sweet cherry phenology data for assessing climate change.

PubMed

Wenden, Bénédicte; Campoy, José Antonio; Lecourt, Julien; López Ortega, Gregorio; Blanke, Michael; Radičević, Sanja; Schüller, Elisabeth; Spornberger, Andreas; Christen, Danilo; Magein, Hugo; Giovannini, Daniela; Campillo, Carlos; Malchev, Svetoslav; Peris, José Miguel; Meland, Mekjell; Stehr, Rolf; Charlot, Gérard; Quero-García, José

2016-12-06

Professional and scientific networks built around the production of sweet cherry (Prunus avium L.) led to the collection of phenology data for a wide range of cultivars grown in experimental sites characterized by highly contrasted climatic conditions. We present a dataset of flowering and maturity dates, recorded each year for one tree when available, or the average of several trees for each cultivar, over a period of 37 years (1978-2015). Such a dataset is extremely valuable for characterizing the phenological response to climate change, and the plasticity of the different cultivars' behaviour under different environmental conditions. In addition, this dataset will support the development of predictive models for sweet cherry phenology exploitable at the continental scale, and will help anticipate breeding strategies in order to maintain and improve sweet cherry production in Europe.

A collection of European sweet cherry phenology data for assessing climate change

PubMed Central

Wenden, Bénédicte; Campoy, José Antonio; Lecourt, Julien; López Ortega, Gregorio; Blanke, Michael; Radičević, Sanja; Schüller, Elisabeth; Spornberger, Andreas; Christen, Danilo; Magein, Hugo; Giovannini, Daniela; Campillo, Carlos; Malchev, Svetoslav; Peris, José Miguel; Meland, Mekjell; Stehr, Rolf; Charlot, Gérard; Quero-García, José

2016-01-01

Professional and scientific networks built around the production of sweet cherry (Prunus avium L.) led to the collection of phenology data for a wide range of cultivars grown in experimental sites characterized by highly contrasted climatic conditions. We present a dataset of flowering and maturity dates, recorded each year for one tree when available, or the average of several trees for each cultivar, over a period of 37 years (1978–2015). Such a dataset is extremely valuable for characterizing the phenological response to climate change, and the plasticity of the different cultivars’ behaviour under different environmental conditions. In addition, this dataset will support the development of predictive models for sweet cherry phenology exploitable at the continental scale, and will help anticipate breeding strategies in order to maintain and improve sweet cherry production in Europe. PMID:27922629

Comparing near-earth and satellite remote sensing based phenophase estimates: an analysis using multiple webcams and MODIS (Invited)

NASA Astrophysics Data System (ADS)

Hufkens, K.; Richardson, A. D.; Migliavacca, M.; Frolking, S. E.; Braswell, B. H.; Milliman, T.; Friedl, M. A.

2010-12-01

In recent years several studies have used digital cameras and webcams to monitor green leaf phenology. Such "near-surface" remote sensing has been shown to be a cost effective means of accurately capturing phenology. Specifically, it allows for accurate tracking of intra- and inter-annual phenological dynamics at high temporal frequency and over broad spatial scales compared to visual observations or tower-based fAPAR and broadband NDVI measurements. Near surface remote sensing measurements therefore show promise for bridging the gap between traditional in-situ measurements of phenology and satellite remote sensing data. For this work, we examined the relationship between phenophase estimates derived from satellite remote sensing (MODIS) and near-earth remote sensing derived from webcams for a select set of sites with high-quality webcam data. A logistic model was used to characterize phenophases for both the webcam and MODIS data. We documented model fit accuracy, phenophase estimates, and model biases for both data sources. Our results show that different vegetation indices (VI's) derived from MODIS produce significantly different phenophase estimates compared to corresponding estimates derived from webcam data. Different VI's showed markedly different radiometric properties, and as a result, influenced phenophase estimates. The study shows that phenophase estimates are not only highly dependent on the algorithm used but also depend on the VI used by the phenology retrieval algorithm. These results highlight the need for a better understanding of how near-earth and satellite remote data relate to eco-physiological and canopy changes during different parts of the growing season.

Why Can't We Resolve Recruitment?

NASA Astrophysics Data System (ADS)

Ferreira, S. A.; Payne, M. R.; Hátún, H.; MacKenzie, B. R.; Butenschön, M.; Visser, A. W.

2016-02-01

During the last century, Johan Hjort's work has lead to signicant advances in explaining anomalous year-classes within sheries science. However, distinguishing between the competing mechanisms of year-class regulation (e.g., food conditions, predation, transport) has proved challenging. We use blue whiting (Micromesistius poutassou) in the North-east Atlantic Ocean as a case study, which, during the late 1990s and early 2000s, generated year-classes up to nearly an order of magnitude higher than those seen before or after. There presently exists no models that can quantify past variations in recruitment for this stock. Using modern stock-statistical and observational tools, we catalog a range of environmentally-driven hypotheses relevant for recruitment of blue whiting, including physical and biogeographic conditions, phenology, parental effects and predation. We have run the analyses to test some hypotheses and results will be presented at the session.

Historical Phenological Observations: Past Climate Impact Analyses and Climate Reconstructions

NASA Astrophysics Data System (ADS)

Rutishauser, T.; Luterbacher, J.; Meier, N.; Jeanneret, F.; Pfister, C.; Wanner, H.

2007-12-01

Plant phenological observations have been found an important indicator of climate change impacts on seasonal and interannual vegetation development for the late 20th/early 21st century. Our contribution contains three parts that are essential for the understanding (part 1), the analysis (part 2) and the application (part 3) of historical phenological observations in global change research. First, we propose a definition for historical phenonolgy (Rutishauser, 2007). We shortly portray the first appearance of phenological observations in Medieval philosophical and literature sources, the usage and application of this method in the Age of Enlightenment (Carl von Linné, Charles Morren), as well as the development in the 20th century (Schnelle, Lieth) to present-day networks (COST725, USA-NPN) Second, we introduce a methodological approach to estimate 'Statistical plants' from historical phenological observations (Rutishauser et al., JGR-Biogeoscience, in press). We combine spatial averaging methods and regression transfer modeling to estimate 'statistical plant' dates from historical observations that often contain gaps, changing observers and changing locations. We apply the concept to reconstruct a statistical 'Spring plant' as the weighted mean of the flowering date of cherry and apple tree and beech budburst of Switzerland 1702- 2005. Including dating total data uncertainty we estimate 10 at interannual and 3.4 days at decadal time scales. Third, we apply two long-term phenological records to describe plant phenological response to spring temperature and reconstruct warm-season temperatures from grape harvest dates (Rutishauser et al, submitted; Meier et al, GRL, in press).

Topoclimate effects on growing season length and montane conifer growth in complex terrain

DOE PAGES

Barnard, David M.; Barnard, H. R.; Molotch, N. P.

2017-05-23

Spatial variability in the topoclimate-driven linkage between forest phenology and tree growth in complex terrain is poorly understood, limiting our understanding of how ecosystems function as a whole. To characterize the influence of topoclimate on phenology and growth, we determined the start, end, and length of the growing season (GS start, GS end, and GSL, respectively) using the correlation between transpiration and evaporative demand, measured with sapflow. We then compared these metrics with stem relative basal area increment (relative BAI) at seven sites among elevation and aspects in a Colorado montane forest. As elevation increased, we found shorter GSL (–50more » d km –1) due to later GSstart (40 d km –1) and earlier GSend (–10 d km –1). North-facing sites had a 21 d shorter GSL than south-facing sites at similar elevations (i.e. equal to 200 m elevation difference on a given aspect). Growing season length was positively correlated with relative BAI, explaining 83% of the variance. This study shows that topography exerts strong environmental controls on GSL and thus forest growth. Here, given the climate-related dependencies of these controls, the results presented here have important implications for ecosystem responses to changes in climate and highlight the need for improved phenology representation in complex terrain.« less

Longer wings for faster springs - wing length relates to spring phenology in a long-distance migrant across its range.

PubMed

Hahn, Steffen; Korner-Nievergelt, Fränzi; Emmenegger, Tamara; Amrhein, Valentin; Csörgő, Tibor; Gursoy, Arzu; Ilieva, Mihaela; Kverek, Pavel; Pérez-Tris, Javier; Pirrello, Simone; Zehtindjiev, Pavel; Salewski, Volker

2016-01-01

In migratory birds, morphological adaptations for efficient migratory flight often oppose morphological adaptations for efficient behavior during resident periods. This includes adaptations in wing shape for either flying long distances or foraging in the vegetation and in climate-driven variation of body size. In addition, the timing of migratory flights and particularly the timely arrival at local breeding sites is crucial because fitness prospects depend on site-specific phenology. Thus, adaptations for efficient long-distance flights might be also related to conditions at destination areas. For an obligatory long-distance migrant, the common nightingale, we verified that wing length as the aerodynamically important trait, but not structural body size increased from the western to the eastern parts of the species range. In contrast with expectation from aerodynamic theory, however, wing length did not increase with increasing migration distances. Instead, wing length was associated with the phenology at breeding destinations, namely the speed of local spring green-up. We argue that longer wings are beneficial for adjusting migration speed to local conditions for birds breeding in habitats with fast spring green-up and thus short optimal arrival periods. We suggest that the speed of spring green-up at breeding sites is a fundamental variable determining the timing of migration that fine tune phenotypes in migrants across their range.

Morphological and phenological shoot plasticity in a Mediterranean evergreen oak facing long-term increased drought.

PubMed

Limousin, Jean-Marc; Rambal, Serge; Ourcival, Jean-Marc; Rodríguez-Calcerrada, Jesus; Pérez-Ramos, Ignacio M; Rodríguez-Cortina, Raquel; Misson, Laurent; Joffre, Richard

2012-06-01

Mediterranean trees must adjust their canopy leaf area to the unpredictable timing and severity of summer drought. The impact of increased drought on the canopy dynamics of the evergreen Quercus ilex was studied by measuring shoot growth, leaf production, litterfall, leafing phenology and leaf demography in a mature forest stand submitted to partial throughfall exclusion for 7 years. The leaf area index rapidly declined in the throughfall-exclusion plot and was 19% lower than in the control plot after 7 years of treatment. Consequently, leaf litterfall was significantly lower in the dry treatment. Such a decline in leaf area occurred through a change in branch allometry with a decreased number of ramifications produced and a reduction of the leaf area supported per unit sapwood area of the shoot (LA/SA). The leafing phenology was slightly delayed and the median leaf life span was slightly longer in the dry treatment. The canopy dynamics in both treatments were driven by water availability with a 1-year lag: leaf shedding and production were reduced following dry years; in contrast, leaf turnover was increased following wet years. The drought-induced decrease in leaf area, resulting from both plasticity in shoot development and slower leaf turnover, appeared to be a hydraulic adjustment to limit canopy transpiration and maintain leaf-specific hydraulic conductivity under drier conditions.

Topoclimate effects on growing season length and montane conifer growth in complex terrain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnard, David M.; Barnard, H. R.; Molotch, N. P.

Spatial variability in the topoclimate-driven linkage between forest phenology and tree growth in complex terrain is poorly understood, limiting our understanding of how ecosystems function as a whole. To characterize the influence of topoclimate on phenology and growth, we determined the start, end, and length of the growing season (GS start, GS end, and GSL, respectively) using the correlation between transpiration and evaporative demand, measured with sapflow. We then compared these metrics with stem relative basal area increment (relative BAI) at seven sites among elevation and aspects in a Colorado montane forest. As elevation increased, we found shorter GSL (–50more » d km –1) due to later GSstart (40 d km –1) and earlier GSend (–10 d km –1). North-facing sites had a 21 d shorter GSL than south-facing sites at similar elevations (i.e. equal to 200 m elevation difference on a given aspect). Growing season length was positively correlated with relative BAI, explaining 83% of the variance. This study shows that topography exerts strong environmental controls on GSL and thus forest growth. Here, given the climate-related dependencies of these controls, the results presented here have important implications for ecosystem responses to changes in climate and highlight the need for improved phenology representation in complex terrain.« less

Leaf Area Adjustment As an Optimal Drought-Adaptation Strategy

NASA Astrophysics Data System (ADS)

Manzoni, S.; Beyer, F.; Thompson, S. E.; Vico, G.; Weih, M.

2014-12-01

Leaf phenology plays a major role in land-atmosphere mass and energy exchanges. Much work has focused on phenological responses to light and temperature, but less to leaf area changes during dry periods. Because the duration of droughts is expected to increase under future climates in seasonally-dry as well as mesic environments, it is crucial to (i) predict drought-related phenological changes and (ii) to develop physiologically-sound models of leaf area dynamics during dry periods. Several optimization criteria have been proposed to model leaf area adjustment as soil moisture decreases. Some theories are based on the plant carbon (C) balance, hypothesizing that leaf area will decline when instantaneous net photosynthetic rates become negative (equivalent to maximization of cumulative C gain). Other theories draw on hydraulic principles, suggesting that leaf area should adjust to either maintain a constant leaf water potential (isohydric behavior) or to avoid leaf water potentials with negative impacts on photosynthesis (i.e., minimization of water stress). Evergreen leaf phenology is considered as a control case. Merging these theories into a unified framework, we quantify the effect of phenological strategy and climate forcing on the net C gain over the entire growing season. By accounting for the C costs of leaf flushing and the gains stemming from leaf photosynthesis, this metric assesses the effectiveness of different phenological strategies, under different climatic scenarios. Evergreen species are favored only when the dry period is relatively short, as they can exploit most of the growing season, and only incur leaf maintenance costs during the short dry period. In contrast, deciduous species that lower maintenance costs by losing leaves are advantaged under drier climates. Moreover, among drought-deciduous species, isohydric behavior leads to lowest C gains. Losing leaves gradually so as to maintain a net C uptake equal to zero during the driest period in the growing season provides the highest gain. Since these strategies are all defined based on often-modeled quantities, they can be implemented in ecosystem models depending on plant functional type and climate.

A meta-analysis of cambium phenology and growth: linear and non-linear patterns in conifers of the northern hemisphere.

PubMed

Rossi, Sergio; Anfodillo, Tommaso; Cufar, Katarina; Cuny, Henri E; Deslauriers, Annie; Fonti, Patrick; Frank, David; Gricar, Jozica; Gruber, Andreas; King, Gregory M; Krause, Cornelia; Morin, Hubert; Oberhuber, Walter; Prislan, Peter; Rathgeber, Cyrille B K

2013-12-01

Ongoing global warming has been implicated in shifting phenological patterns such as the timing and duration of the growing season across a wide variety of ecosystems. Linear models are routinely used to extrapolate these observed shifts in phenology into the future and to estimate changes in associated ecosystem properties such as net primary productivity. Yet, in nature, linear relationships may be special cases. Biological processes frequently follow more complex, non-linear patterns according to limiting factors that generate shifts and discontinuities, or contain thresholds beyond which responses change abruptly. This study investigates to what extent cambium phenology is associated with xylem growth and differentiation across conifer species of the northern hemisphere. Xylem cell production is compared with the periods of cambial activity and cell differentiation assessed on a weekly time scale on histological sections of cambium and wood tissue collected from the stems of nine species in Canada and Europe over 1-9 years per site from 1998 to 2011. The dynamics of xylogenesis were surprisingly homogeneous among conifer species, although dispersions from the average were obviously observed. Within the range analysed, the relationships between the phenological timings were linear, with several slopes showing values close to or not statistically different from 1. The relationships between the phenological timings and cell production were distinctly non-linear, and involved an exponential pattern. The trees adjust their phenological timings according to linear patterns. Thus, shifts of one phenological phase are associated with synchronous and comparable shifts of the successive phases. However, small increases in the duration of xylogenesis could correspond to a substantial increase in cell production. The findings suggest that the length of the growing season and the resulting amount of growth could respond differently to changes in environmental conditions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003–2012. We found that phenology cycle (changes in vegetation greenness) in urban areas starts earlier (start of season, SOS) and ends latermore » (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days.Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6–6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. In conclusion, the quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003–2012. We found that phenology cycle (changes in vegetation greenness) in rural areas starts earlier (start of season, SOS) and ends latermore » (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days. Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6–6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. The quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology.« less

Crop Phenology Detection Using High Spatio-Temporal Resolution Data Fused from SPOT5 and MODIS Products

PubMed Central

Zheng, Yang; Wu, Bingfang; Zhang, Miao; Zeng, Hongwei

2016-01-01

Timely and efficient monitoring of crop phenology at a high spatial resolution are crucial for the precise and effective management of agriculture. Recently, satellite-derived vegetation indices (VIs), such as the Normalized Difference Vegetation Index (NDVI), have been widely used for the phenology detection of terrestrial ecosystems. In this paper, a framework is proposed to detect crop phenology using high spatio-temporal resolution data fused from Systeme Probatoire d'Observation de la Tarre5 (SPOT5) and Moderate Resolution Imaging Spectroradiometer (MODIS) images. The framework consists of a data fusion method to produce a synthetic NDVI dataset at SPOT5’s spatial resolution and at MODIS’s temporal resolution and a phenology extraction algorithm based on NDVI time-series analysis. The feasibility of our phenology detection approach was evaluated at the county scale in Shandong Province, China. The results show that (1) the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm can accurately blend SPOT5 and MODIS NDVI, with an R2 of greater than 0.69 and an root mean square error (RMSE) of less than 0.11 between the predicted and referenced data; and that (2) the estimated phenology parameters, such as the start and end of season (SOS and EOS), were closely correlated with the field-observed data with an R2 of the SOS ranging from 0.68 to 0.86 and with an R2 of the EOS ranging from 0.72 to 0.79. Our research provides a reliable approach for crop phenology mapping in areas with high fragmented farmland, which is meaningful for the implementation of precision agriculture. PMID:27973404

Crop Phenology Detection Using High Spatio-Temporal Resolution Data Fused from SPOT5 and MODIS Products.

PubMed

Zheng, Yang; Wu, Bingfang; Zhang, Miao; Zeng, Hongwei

2016-12-10

Timely and efficient monitoring of crop phenology at a high spatial resolution are crucial for the precise and effective management of agriculture. Recently, satellite-derived vegetation indices (VIs), such as the Normalized Difference Vegetation Index (NDVI), have been widely used for the phenology detection of terrestrial ecosystems. In this paper, a framework is proposed to detect crop phenology using high spatio-temporal resolution data fused from Systeme Probatoire d'Observation de la Tarre5 (SPOT5) and Moderate Resolution Imaging Spectroradiometer (MODIS) images. The framework consists of a data fusion method to produce a synthetic NDVI dataset at SPOT5's spatial resolution and at MODIS's temporal resolution and a phenology extraction algorithm based on NDVI time-series analysis. The feasibility of our phenology detection approach was evaluated at the county scale in Shandong Province, China. The results show that (1) the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm can accurately blend SPOT5 and MODIS NDVI, with an R ² of greater than 0.69 and an root mean square error (RMSE) of less than 0.11 between the predicted and referenced data; and that (2) the estimated phenology parameters, such as the start and end of season (SOS and EOS), were closely correlated with the field-observed data with an R ² of the SOS ranging from 0.68 to 0.86 and with an R ² of the EOS ranging from 0.72 to 0.79. Our research provides a reliable approach for crop phenology mapping in areas with high fragmented farmland, which is meaningful for the implementation of precision agriculture.

The Role of Silicon Limitation in Phytoplankton Phenology in a Sub-Arctic Fjord System

NASA Astrophysics Data System (ADS)

Dobbins, W.; Krause, J. W.; Agustí, S.; Duarte, C. M.; Schulz, I. K.; Winding, M.; Rowe, K. A.; Sejr, M.

2017-12-01

Bacillariophyceae (diatoms) are a significant driver of the biological pump and thus various chemical cycles in high latitude ecosystems. Diatoms have an obligate silicon requirement that has been established as a growth-limiting factor in a variety of ecosystems, and silicon availability likely plays an important role in the temporal evolution of high latitude phytoplankton blooms. However, no previous work has been done to assess the progression of this limitation across a full bloom cycle in the West Greenlandic Nuup Kangerlua fjord or equivalent systems with rapidly evolving land-sea-ice interfaces. Here we provide experimental evidence that the Nuup Kangerlua spring bloom is both diatom driven and strongly silicon constrained. Chlorophyll concentration and growth rates derived from biogenic silica measurements peaked contemporaneously; indicating diatoms were primary members of the phytoplankton assemblage. Moreover, incubation experiments revealed strong biomass increases in response to silicon additions during the bloom period. This work shows silicon availability may play a significant role in bloom phenology in the Nuup Kangerlua fjord.

Plant phenology and composition controls of carbon fluxes in a boreal peatland

NASA Astrophysics Data System (ADS)

Peichl, Matthias; Gažovič, Michal; Vermeij, Ilse; De Goede, Eefje; Sonnentag, Oliver; Limpens, Juul; Nilsson, Mats B.

2016-04-01

Vegetation drives the peatland carbon (C) cycle via the processes of photosynthesis, plant respiration and decomposition as well as by providing substrate for methane (CH4) and dissolved organic carbon production. However, due to the lack of comprehensive vegetation data, variations in the peatland C fluxes are commonly related to temperature and other more easily measured abiotic (i.e. weather and soil) variables. Due to the temporal co-linearity between plant development and abiotic variables, these relationships may describe the variations in C fluxes reasonably well, however, without representing the true mechanistic processes driving the peatland C cycle. As a consequence, current process-based models are poorly parameterized and unable to adequately predict the responses of the peatland C cycle to climate change, extreme events and anthropogenic impacts. To fill this knowledge gap, we explored vegetation phenology and composition effects on the peatland C cycle at the Degerö peatland located in northern Sweden. We used a greenness index derived from digital repeat photography to quantitatively describe plant canopy development with high temporal (i.e. daily) and spatial (plot to ecosystem) resolution. In addition, eddy covariance and static chamber measurements of carbon dioxide (CO2) and CH4 fluxes over an array of vegetation manipulation plots were conducted over multiple years. Our results suggest that vascular plant phenology controls the onset and pattern of eddy covariance-derived gross primary production (GPP) during the spring period, while abiotic conditions modify GPP during the summer period when plant canopy cover is fully developed. Inter-annual variations in the spring onset and patterns of plant canopy development were best explained by differences in the preceding growing degree day sum. We also observed strong correlations of canopy greenness with the net ecosystem CO2 exchange and ecosystem respiration. On average, vascular plant and moss production accounted for ~60 and 40% of GPP, respectively. However, while the seasonal variation of vascular plant productivity was driven by plant phenology, water table level was the strongest control of moss productivity. Across vegetation manipulation plots, highest chamber-derived GPP and net CO2 uptake occurred when both vascular and moss species were present. Furthermore, CH4 fluxes increased with the amount of sedge species leaf area; however, their seasonal flux patterns were more closely related to water table level than to plant phenology. Overall these findings highlight the need for better understanding the separate controls of biotic and abiotic drivers of the peatland C fluxes to improve predictions of ecosystem processes and the peatland C sink strength in response to future climate change and management impacts.

Evaluating Hyperspectral Vegetation Indices for Leaf Area Index Estimation of Oryza sativa L. at Diverse Phenological Stages

PubMed Central

Din, Mairaj; Zheng, Wen; Rashid, Muhammad; Wang, Shanqin; Shi, Zhihua

2017-01-01

Hyperspectral reflectance derived vegetation indices (VIs) are used for non-destructive leaf area index (LAI) monitoring for precise and efficient N nutrition management. This study tested the hypothesis that there is potential for using various hyperspectral VIs for estimating LAI at different growth stages of rice under varying N rates. Hyperspectral reflectance and crop canopy LAI measurements were carried out over 2 years (2015 and 2016) in Meichuan, Hubei, China. Different N fertilization, 0, 45, 82, 127, 165, 210, 247, and 292 kg ha-1, were applied to generate various scales of VIs and LAI values. Regression models were used to perform quantitative analyses between spectral VIs and LAI measured under different phenological stages. In addition, the coefficient of determination and RMSE were employed to evaluate these models. Among the nine VIs, the ratio vegetation index, normalized difference vegetation index (NDVI), modified soil-adjusted vegetation index (MSAVI), modified triangular vegetation index (MTVI2) and exhibited strong and significant relationships with the LAI estimation at different phenological stages. The enhanced vegetation index performed moderately. However, the green normalized vegetation index and blue normalized vegetation index confirmed that there is potential for crop LAI estimation at early phenological stages; the soil-adjusted vegetation index and optimized soil-adjusted vegetation index were more related to the soil optical properties, which were predicted to be the least accurate for LAI estimation. The noise equivalent accounted for the sensitivity of the VIs and MSAVI, MTVI2, and NDVI for the LAI estimation at phenological stages. The results note that LAI at different crop phenological stages has a significant influence on the potential of hyperspectral derived VIs under different N management practices. PMID:28588596

Geostatistical analysis of data on air temperature and plant phenology from Baden-Württemberg (Germany) as a basis for regional scaled models of climate change.

PubMed

Schröder, Winfried; Schmidt, Gunther; Hasenclever, Judith

2006-09-01

The rise of the air temperature is assured to be part of the global climatic change, but there is still a lack of knowledge about its effects at a regional scale. The article tackles the correlation of air temperature with the phenology of selected plants by the example of Baden-Württemberg to provide a spatial valid data base for regional climate change models. To this end, the data on air temperature and plant phenology, gathered from measurement sites without congruent coverage, were correlated after performing geostatistical analysis and estimation. In addition, geostatistics are used to analyze and cartographically depict the spatial structure of the phenology of plants in spring and in summer. The statistical analysis reveals a significant relationship between the rising air temperature and the earlier beginning of phenological phases like blooming or fruit maturation: From 1991 to 1999 spring time, as indicated by plant phenology, has begun up to 15 days earlier than from 1961 to 1990. As shown by geostatistics, this holds true for the whole territory of Baden-Württemberg. The effects of the rise of air temperature should be investigated not only by monitoring biological individuals, as for example plants, but on an ecosystem level as well. In Germany, the environmental monitoring should be supplemented by the study of the effects of the climatic change in ecosystems. Because air temperature and humidity have a great influence on the temporal and spatial distribution of pathogen carriers (vectors) and pathogens, mapping of the environmental determinants of vector and pathogen distribution in space and time should be performed in order to identify hot spots for risk assessment and further detailed epidemiological studies.

Validation of VIIRS Land Surface Phenology using Field Observations, PhenoCam Imagery, and Landsat data

NASA Astrophysics Data System (ADS)

Zhang, X.; Jayavelu, S.; Wang, J.; Henebry, G. M.; Gray, J. M.; Friedl, M. A.; Liu, Y.; Schaaf, C.; Shuai, A.

2016-12-01

A large number of land surface phenology (LSP) products have been produced from various detection algorithms applied to coarse resolution satellite datasets across regional to global scales. However, validation of the resulting LSP products is very challenging because in-situ observations at comparable spatiotemporal scales are generally not available. This research focuses on efforts to evaluate and validate the global 500m LSP product produced from Visible Infrared Imaging Radiometer Suite (VIIRS) NBAR time series for 2013 and 2014. Specifically, we used three different datasets to evaluate six VIIRS LSP metrics of greenup onset, mid-point of greenup phase, maturity onset, senescence onset, mid-point of senescence phase, and dormancy onset. First, we obtained the field observations from the USA National Phenology Network that has gathered extensive phenological data on individual species. Although it is inappropriate to compare these data directly with the LSP footprints, this large and spatially distributed dataset allows us to evaluate the overall quality of VIIRS LSP results. Second, we gathered PhenoCam imagery from 164 sites, which was used to extract the daily green chromatic coordinate (GCC) and vegetation contrast index (VCI)values. Utilizing these PhenoCam time series, the phenological events were quantified using a hybrid piecewise logistic models for each site. Third, we detected the phenological timing at the landscape scale (30m) from surface reflectance simulated by fusing MODIS data and Landsat 8 OLI observations in an agricultural area (in the central USA) and from overlap zones of OLI scenes in semiarid areas (California and Tibetan Plateau). The phenological timing from these three datasets was used to compare with VIIRS LSP data. Preliminary results show that the VIIRS LSP are generally comparable with phenological data from the USA-NPN, PhenoCam, and Landsat data, with differences arising in specific phenological events and land cover types.

Response of vegetation phenology to urbanization in the conterminous United States.

PubMed

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R; Mao, Jiafu; Li, Xiaoma; Li, Wenyu

2017-07-01

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003-2012. We found that phenology cycle (changes in vegetation greenness) in urban areas starts earlier (start of season, SOS) and ends later (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days. Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6-6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. The quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology. © 2016 John Wiley & Sons Ltd.

Temperature sensitivity of a numerical pollen forecast model

NASA Astrophysics Data System (ADS)

Scheifinger, Helfried; Meran, Ingrid; Szabo, Barbara; Gallaun, Heinz; Natali, Stefano; Mantovani, Simone

2016-04-01

Allergic rhinitis has become a global health problem especially affecting children and adolescence. Timely and reliable warning before an increase of the atmospheric pollen concentration means a substantial support for physicians and allergy suffers. Recently developed numerical pollen forecast models have become means to support the pollen forecast service, which however still require refinement. One of the problem areas concerns the correct timing of the beginning and end of the flowering period of the species under consideration, which is identical with the period of possible pollen emission. Both are governed essentially by the temperature accumulated before the entry of flowering and during flowering. Phenological models are sensitive to a bias of the temperature. A mean bias of -1°C of the input temperature can shift the entry date of a phenological phase for about a week into the future. A bias of such an order of magnitude is still possible in case of numerical weather forecast models. If the assimilation of additional temperature information (e.g. ground measurements as well as satellite-retrieved air / surface temperature fields) is able to reduce such systematic temperature deviations, the precision of the timing of phenological entry dates might be enhanced. With a number of sensitivity experiments the effect of a possible temperature bias on the modelled phenology and the pollen concentration in the atmosphere is determined. The actual bias of the ECMWF IFS 2 m temperature will also be calculated and its effect on the numerical pollen forecast procedure presented.

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers

Treesearch

John A. Gamon; K. Fred Huemmrich; Christopher Y. S. Wong; Ingo Ensminger; Steven Garrity; David Y. Hollinger; Asko Noormets; Josep Peñuelas

2016-01-01

In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying “photosynthetic phenology” from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as...

Scaling forest phenology from trees to the landscape using an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Klosterman, S.; Melaas, E. K.; Martinez, A.; Richardson, A. D.

2013-12-01

Vegetation phenology monitoring has yielded a decades-long archive documenting the impacts of global change on the biosphere. However, the coarse spatial resolution of remote sensing obscures the organismic level processes driving phenology, while point measurements on the ground limit the extent of observation. Unmanned aerial vehicles (UAVs) enable low altitude remote sensing at higher spatial and temporal resolution than available from space borne platforms, and have the potential to elucidate the links between organism scale processes and landscape scale analyses of terrestrial phenology. This project demonstrates the use of a low cost multirotor UAV, equipped with a consumer grade digital camera, for observation of deciduous forest phenology and comparison to ground- and tower-based data as well as remote sensing. The UAV was flown approximately every five days during the spring green-up period in 2013, to obtain aerial photography over an area encompassing a 250m resolution MODIS (Moderate Resolution Imaging Spectroradiometer) pixel at Harvard Forest in central Massachusetts, USA. The imagery was georeferenced and tree crowns were identified using a detailed species map of the study area. Image processing routines were used to extract canopy 'greenness' time series, which were used to calculate phenology transition dates corresponding to early, middle, and late stages of spring green-up for the dominant canopy trees. Aggregated species level phenology estimates from the UAV data, including the mean and variance of phenology transition dates within species in the study area, were compared to model predictions based on visual assessment of a smaller sample size of individual trees, indicating the extent to which limited ground observations represent the larger landscape. At an intermediate scale, the UAV data was compared to data from repeat digital photography, integrating over larger portions of canopy within and near the study area, as a validation step and to see how well tower-based approaches characterize the surrounding landscape. Finally, UAV data was compared to MODIS data to determine how tree crowns within a remote sensing pixel combine to create the aggregate landscape phenology measured by remote sensing, using an area weighted average of the phenology of all dominant crowns.

Using ground observations of a digital camera in the VIS-NIR range for quantifying the phenology of Mediterranean woody species

NASA Astrophysics Data System (ADS)

Weil, Gilad; Lensky, Itamar M.; Levin, Noam

2017-10-01

The spectral reflectance of most plant species is quite similar, and thus the feasibility of identifying most plant species based on single date multispectral data is very low. Seasonal phenological patterns of plant species may enable to face the challenge of using remote sensing for mapping plant species at the individual level. We used a consumer-grade digital camera with near infra-red capabilities in order to extract and quantify vegetation phenological information in four East Mediterranean sites. After illumination corrections and other noise reduction steps, the phenological patterns of 1839 individuals representing 12 common species were analyzed, including evergreen trees, winter deciduous trees, semi-deciduous summer shrubs and annual herbaceous patches. Five vegetation indices were used to describe the phenology: relative green and red (green/red chromatic coordinate), excess green (ExG), normalized difference vegetation index (NDVI) and green-red vegetation index (GRVI). We found significant differences between the phenology of the various species, and defined the main phenological groups using agglomerative hierarchical clustering. Differences between species and sites regarding the start of season (SOS), maximum of season (MOS) and end of season (EOS) were displayed in detail, using ExG values, as this index was found to have the lowest percentage of outliers. An additional visible band spectral index (relative red) was found as useful for characterizing seasonal phenology, and had the lowest correlation with the other four vegetation indices, which are more sensitive to greenness. We used a linear mixed model in order to evaluate the influences of various factors on the phenology, and found that unlike the significant effect of species and individuals on SOS, MOS and EOS, the sites' location did not have a direct significant effect on the timing of phenological events. In conclusion, the relative advantage of the proposed methodology is the exploitation of representative temporal information that is collected with accessible and simple devices, for the subsequent determination of optimal temporal acquisition of images by overhead sensors, for vegetation mapping over larger areas.

Will the Effects of Sea-Level Rise Create Ecological Traps for Pacific Island Seabirds?

PubMed

Reynolds, Michelle H; Courtot, Karen N; Berkowitz, Paul; Storlazzi, Curt D; Moore, Janet; Flint, Elizabeth

2015-01-01

More than 18 million seabirds nest on 58 Pacific islands protected within vast U.S. Marine National Monuments (1.9 million km2). However, most of these seabird colonies are on low-elevation islands and sea-level rise (SLR) and accompanying high-water perturbations are predicted to escalate with climate change. To understand how SLR may impact protected islands and insular biodiversity, we modeled inundation and wave-driven flooding of a globally important seabird rookery in the subtropical Pacific. We acquired new high-resolution Digital Elevation Models (DEMs) and used the Delft3D wave model and ArcGIS to model wave heights and inundation for a range of SLR scenarios (+0.5, +1.0, +1.5, and +2.0 m) at Midway Atoll. Next, we classified vegetation to delineate habitat exposure to inundation and identified how breeding phenology, colony synchrony, and life history traits affect species-specific sensitivity. We identified 3 of 13 species as highly vulnerable to SLR in the Hawaiian Islands and quantified their atoll-wide distribution (Laysan albatross, Phoebastria immutabilis; black-footed albatross, P. nigripes; and Bonin petrel, Pterodroma hypoleuca). Our models of wave-driven flooding forecast nest losses up to 10% greater than passive inundation models at +1.0 m SLR. At projections of + 2.0 m SLR, approximately 60% of albatross and 44% of Bonin petrel nests were overwashed displacing more than 616,400 breeding albatrosses and petrels. Habitat loss due to passive SLR may decrease the carrying capacity of some islands to support seabird colonies, while sudden high-water events directly reduce survival and reproduction. This is the first study to simulate wave-driven flooding and the combined impacts of SLR, groundwater rise, and storm waves on seabird colonies. Our results highlight the need for early climate change planning and restoration of higher elevation seabird refugia to prevent low-lying protected islands from becoming ecological traps in the face of rising sea levels.

Will the effects of sea-level rise create ecological traps for Pacific Island seabirds?

USGS Publications Warehouse

Reynolds, Michelle H.; Courtot, Karen; Berkowitz, Paul; Storlazzi, Curt; Moore, Janet; Flint, Elizabeth

2015-01-01

More than 18 million seabirds nest on 58 Pacific islands protected within vast U.S. Marine National Monuments (1.9 million km2). However, most of these seabird colonies are on low-elevation islands and sea-level rise (SLR) and accompanying high-water perturbations are predicted to escalate with climate change. To understand how SLR may impact protected islands and insular biodiversity, we modeled inundation and wave-driven flooding of a globally important seabird rookery in the subtropical Pacific. We acquired new high-resolution Digital Elevation Models (DEMs) and used the Delft3D wave model and ArcGIS to model wave heights and inundation for a range of SLR scenarios (+0.5, +1.0, +1.5, and +2.0 m) at Midway Atoll. Next, we classified vegetation to delineate habitat exposure to inundation and identified how breeding phenology, colony synchrony, and life history traits affect species-specific sensitivity. We identified 3 of 13 species as highly vulnerable to SLR in the Hawaiian Islands and quantified their atoll-wide distribution (Laysan albatross, Phoebastria immutabilis; black-footed albatross, P. nigripes; and Bonin petrel, Pterodroma hypoleuca). Our models of wave-driven flooding forecast nest losses up to 10% greater than passive inundation models at +1.0 m SLR. At projections of + 2.0 m SLR, approximately 60% of albatross and 44% of Bonin petrel nests were overwashed displacing more than 616,400 breeding albatrosses and petrels. Habitat loss due to passive SLR may decrease the carrying capacity of some islands to support seabird colonies, while sudden high-water events directly reduce survival and reproduction. This is the first study to simulate wave-driven flooding and the combined impacts of SLR, groundwater rise, and storm waves on seabird colonies. Our results highlight the need for early climate change planning and restoration of higher elevation seabird refugia to prevent low-lying protected islands from becoming ecological traps in the face of rising sea levels.

Will the Effects of Sea-Level Rise Create Ecological Traps for Pacific Island Seabirds?

PubMed Central

Reynolds, Michelle H.; Courtot, Karen N.; Berkowitz, Paul; Storlazzi, Curt D.; Moore, Janet; Flint, Elizabeth

2015-01-01

More than 18 million seabirds nest on 58 Pacific islands protected within vast U.S. Marine National Monuments (1.9 million km2). However, most of these seabird colonies are on low-elevation islands and sea-level rise (SLR) and accompanying high-water perturbations are predicted to escalate with climate change. To understand how SLR may impact protected islands and insular biodiversity, we modeled inundation and wave-driven flooding of a globally important seabird rookery in the subtropical Pacific. We acquired new high-resolution Digital Elevation Models (DEMs) and used the Delft3D wave model and ArcGIS to model wave heights and inundation for a range of SLR scenarios (+0.5, +1.0, +1.5, and +2.0 m) at Midway Atoll. Next, we classified vegetation to delineate habitat exposure to inundation and identified how breeding phenology, colony synchrony, and life history traits affect species-specific sensitivity. We identified 3 of 13 species as highly vulnerable to SLR in the Hawaiian Islands and quantified their atoll-wide distribution (Laysan albatross, Phoebastria immutabilis; black-footed albatross, P. nigripes; and Bonin petrel, Pterodroma hypoleuca). Our models of wave-driven flooding forecast nest losses up to 10% greater than passive inundation models at +1.0 m SLR. At projections of + 2.0 m SLR, approximately 60% of albatross and 44% of Bonin petrel nests were overwashed displacing more than 616,400 breeding albatrosses and petrels. Habitat loss due to passive SLR may decrease the carrying capacity of some islands to support seabird colonies, while sudden high-water events directly reduce survival and reproduction. This is the first study to simulate wave-driven flooding and the combined impacts of SLR, groundwater rise, and storm waves on seabird colonies. Our results highlight the need for early climate change planning and restoration of higher elevation seabird refugia to prevent low-lying protected islands from becoming ecological traps in the face of rising sea levels. PMID:26398209

Global Urban Mapping and Modeling for Sustainable Urban Development

NASA Astrophysics Data System (ADS)

Zhou, Y.; Li, X.; Asrar, G.; Yu, S.; Smith, S.; Eom, J.; Imhoff, M. L.

2016-12-01

In the past several decades, the world has experienced fast urbanization, and this trend is expected to continue for decades to come. Urbanization, one of the major land cover and land use changes (LCLUC), is becoming increasingly important in global environmental changes, such as urban heat island (UHI) growth and vegetation phenology change. Better scientific insights and effective decision-making unarguably require reliable science-based information on spatiotemporal changes in urban extent and their environmental impacts. In this study, we developed a globally consistent 20-year urban map series to evaluate the time-reactive nature of global urbanization from the nighttime lights remote sensing data, and projected future urban expansion in the 21st century by employing an integrated modeling framework (Zhou et al. 2014, Zhou et al. 2015). We then evaluated the impacts of urbanization on building energy use and vegetation phenology that affect both ecosystem services and human health. We extended the modeling capability of building energy use in the Global Change Assessment Model (GCAM) with consideration of UHI effects by coupling the remote sensing based urbanization modeling and explored the impact of UHI on building energy use. We also investigated the impact of urbanization on vegetation phenology by using an improved phenology detection algorithm. The derived spatiotemporal information on historical and potential future urbanization and its implications in building energy use and vegetation phenology will be of great value in sustainable urban design and development for building energy use and human health (e.g., pollen allergy), especially when considered together with other factors such as climate variability and change. Zhou, Y., S. J. Smith, C. D. Elvidge, K. Zhao, A. Thomson & M. Imhoff (2014) A cluster-based method to map urban area from DMSP/OLS nightlights. Remote Sensing of Environment, 147, 173-185. Zhou, Y., S. J. Smith, K. Zhao, M. Imhoff, A. Thomson, B. Bond-Lamberty, G. R. Asrar, X. Zhang, C. He & C. D. Elvidge (2015) A global map of urban extent from nightlights. Environmental Research Letters, 10, 054011.

Detecting crop growth stages of maize and soybeans by using time-series MODIS data

NASA Astrophysics Data System (ADS)

Sakamoto, T.; Wardlow, B. D.; Gitelson, A. A.; Verma, S. B.; Suyker, A. E.; Arkebauer, T. J.

2009-12-01

The crop phenological stages are one of essential parameters for evaluating crop productivity based on a crop simulation model. In this study, we improved a method named the Wavelet-based Filter for detecting Crop Phenology (WFCP) for detecting the specific phenological dates of maize and soybeans. The improved method was applied to MODIS-derived Wide Dynamic Range Vegetation Index (WDRVI) over a 6-year period (2003 to 2008) for three experimental fields planted to either maize or soybeans as part of the Carbon Sequestration Program (CSP) at the University of Nebraska-Lincoln (UNL). Using the ground-based crop growth stage observations collected by the CSP, it was confirmed that the improved method can estimate the specific phenological dates of maize (V2.5, R1, R5 and R6) and soybeans (V1, R5, R6 and R7) with reasonable accuracy.

Linkages between Snow Cover Seasonality, Terrain, and Land Surface Phenology in the Highland Pastures of Kyrgyzstan

NASA Astrophysics Data System (ADS)

Henebry, Geoffrey; Tomaszewska, Monika; Kelgenbaeva, Kamilya

2017-04-01

In the highlands of Kyrgyzstan, vertical transhumance is the foundation of montane agropastoralism. Terrain attributes, such as elevation, slope, and aspect, affect snow cover seasonality, which is a key influence on the timing of plant growth and forage availability. Our study areas include the highland pastures in Central Tien Shan mountains, specifically in the rayons of Naryn and At-Bashy in Naryn oblast, and Alay and Chong-Alay rayons in Osh oblast. To explore the linkages between snow cover seasonality and land surface phenology as modulated by terrain and variations in thermal time, we use 16 years (2001-2016) of Landsat surface reflectance data at 30 m resolution with MODIS land surface temperature and snow cover products at 1 km and 500 m resolution, respectively, and two digital elevation models, SRTM and ASTER GDEM. We model snow cover seasonality using frost degree-days and land surface phenology using growing degree-days as quadratic functions of thermal time: a convex quadratic (CxQ) model for land surface phenology and a concave quadratic (CvQ) model for snow cover seasonality. From the fitted parameter coefficients, we calculated phenometrics, including "peak height" and "thermal time to peak" for the CxQ models and "trough depth" and "thermal time to trough" for the CvQ models. We explore how these phenometrics change as a function of elevation and slope-aspect interactions and due to interannual variability. Further, we examine how snow cover duration and timing affects the subsequent peak height and thermal time to peak in wetter, drier, and normal years.

Informing agricultural management - The challenge of modelling grassland phenology

NASA Astrophysics Data System (ADS)

Calanca, Pierluigi

2017-04-01

Grasslands represent roughly 70% of the agricultural land worldwide, are the backbone of animal husbandry and contribute substantially to agricultural income. At the farm scale a proper management of meadows and pastures is necessary to attain a balance between forage production and consumption. A good hold on grassland phenology is of paramount importance in this context, because forage quantity and quality critically depend on the developmental stage of the sward. Traditionally, empirical rules have been used to advise farmers in this respect. Yet the provision of supporting information for decision making would clearly benefit from dedicated tools that integrate reliable models of grassland phenology. As with annual crops, in process-based models grassland phenology is usually described as a linear function of so-called growing degree days, whereby data from field trials and monitoring networks are used to calibrate the relevant parameters. It is shown in this contribution that while the approach can provide reasonable estimates of key developmental stages in an average sense, it fails to account for the variability observed in managed grasslands across sites and years, in particular concerning the start of the growing season. The analysis rests on recent data from western Switzerland, which serve as a benchmark for simulations carried out with grassland models of increasing complexity. Reasons for an unsatisfactory model performance and possibilities to improve current models are discussed, including the necessity to better account for species composition, late season management decisions, as well as plant physiological processes taking place during the winter season. The need to compile existing, and collect new data doe managed grasslands is also stressed.

[MODIS-driven estimation of regional evapotranspiration in Karst area of Southwest China based on the Penman-Monteith-Leuning algorithm.

PubMed

Zhong, Hao Zhe; Xu, Xian Li; Zhang, Rong Fei; Liu, Mei Xian

2018-05-01

Karst area in southwestern China is characterized with complex topography, low soil water capacity, and fragile ecosystem. Accurate estimation of regional evapotranspiration is essential for ecological restoration and water resources management in southwestern China. Based on observed evapotranspiration and meteorological data, this study aimed to estimate spatial upscale evapotranspiration using the MOD15A2 LAI and Penman-Monteith-Leuning (PML) model, within which the stomatal conductance and soil wetness index were optimized by the least-square method. The results showed that the modeled ET well fitted with the observations, with the determination coefficient, Nash efficiency coefficient and RMSE being 0.85, 0.75 and 1.56 mm·d -1 , respectively. The ET exhibited clear seasonality and reached to its maximum in summer, coinciding with vegetation phenology. The annual ET ranged from 534 to 1035 mm·a -1 , with strong spatial heterogeneity which highly related to the precipitation. Evapotranspiration may be affected by precipitation as well as land use types.

What are plants doing and when? Using plant phenology to facilitate sustainable natural resources management

USGS Publications Warehouse

Chong, Geneva W.; Allen, Leslie A.

2012-01-01

Climate change models for the northern Rocky Mountains predict changes in temperature and water availability that in turn will alter vegetation. Changes include timing of plant life-history events, or phenology, such as green-up, flowering and senescence, and shifts in species composition. Moreover, climate changes may favor different species, such as nonnative, annual grasses over native species. Changes in vegetation could make forage for ungulates, sage-grouse, and livestock available earlier in the growing season, but shifts in species composition and phenology may also result in earlier senescence (die-off or dormancy) and reduced overall forage production.

Model-data integration to improve the LPJmL dynamic global vegetation model

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno

2017-04-01

Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the simulated ecosystem dynamics which consequently changed the development of ecosystem carbon stocks and fluxes under future climate and CO2 change. In summary, our results demonstrate challenges and the potential of using model-data integration approaches to improve a dynamic global vegetation model.

Are there local-scale effects of altitude, slope and aspect on temporal trends in a spatially high-resolved plant phenological network in the Swiss Alps 1971-2000?

NASA Astrophysics Data System (ADS)

Jeanneret, François; Rutishauser, This; Kottmann, Silvan; Brügger, Robert

2010-05-01

Shifts in phenology of plants and animals have been widely observed as consequence of climate change impacts and temperature increase. Species-specific data are often assigned to limited and generalized site information on the precise location of the observation. However, as much meta-information as possible on the individual plant under observations is necessary to assess the impacts of changing weather patterns at the local scale that are related to changes in radiation, fog, frost and dominating circulation. Here we used plant phenological data of the BERNCLIM network that collects data in the Canton of Bern (Switzerland) and adjacent areas covering a total area of 7,000 km2 since 1970. The number of observation sites reached up to 600 observation sites with detailed meta-information of several locations within each site. The precision of coordinates for each location is generally less than one hectare. This information allows to differentiate several terrain-types, based on altitude, slope and aspect. We used original observations and two interpolated data sets based of the blooming of hazel (Corylus avellana L.) for early spring, dandelion (Taraxacum officinale aggr.) for mid spring, and apple trees (Malus domestica Borkh.) for late spring. In addition we used interpolated data by using averaged maximum differences between several locations of a site and an algorithm based on constant spatial patterns in the 1971-1974 period. Phenological maps were created using multiple linear regression models with longitude, latitude, altitude, slope and aspect as independent variables and phenological date of each phase as dependent variable models in a Geographical Information System (GIS). For this contribution we analysed the impact of local terrain differences on phenological trends of three plant species. Specifically, we addressed the question whether differences in altitude, slope and aspect lead to systematic differences in temporal trends for the 1971-2000 period. Whereas altitude shows generally high correlations with phenology, we aimed at quantifying additional impacts on phenological trends such as microclimate and local adaptation of individual plants. We present results from an ongoing analysis and discuss the impact and additional uncertainties of local parameters on phenological observations and trends. Strongest variations between locations are expected for Corylus and Malus whereas Taraxacum is most strongly influenced by temperature along altitudinal gradients. This information derived from a regional observations network with long-term observations and high precision meta-information can be useful for detailed analyses of large data sets that stored in a number of European databases.

Linking canopy phenology to the seasonality of biosphere-atmosphere interactions in a temperate deciduous forest (Invited)

NASA Astrophysics Data System (ADS)

Richardson, A. D.; Toomey, M. P.; Aubrecht, D.; Sonnentag, O.; Ryu, Y.; Hilker, T.

2013-12-01

Phenology - the annual rhythm of canopy development and senescence - is a key control on the seasonality of surface-atmosphere fluxes of CO2, water, and energy. Phenology is also a highly sensitive indicator of the biological impacts of climate change. In many biomes, there is strong evidence of trends towards earlier spring onset, and later autumn senescence, over the last four decades. These shifts in phenology may play an imprortant role in mitigating - or amplifying - feedbacks between terrestrial ecosystems and the climate system. To better understand relationships between canopy structure and function in a temperate deciduous forest, we installed a wide array of radiometric instruments and imaging sensors near the top of a 40-m high tower at Harvard Forest beginning in 2011. Our data set includes: - incoming and outgoing visible (including incoming direct and diffuse components), shortwave, and longwave radiation; - narrowband (five visible and three near-infrared channels) canopy reflectance; - leaf area index (LAI, from continuous below-canopy digital cover photography), fraction of absorbed photosynthetically active radiation (fAPAR, from above- and below-canopy quantum sensors), normalized difference vegetation index (NDVI, from broad- and narrow-band radiometric sensors), and photochemical reflectance index (PRI, from narrow-band radiometric sensors); - visible and near-infrared PhenoCam (http://phenocam.sr.unh.edu) canopy imagery; - multi-angular narrowband hyperspectral canopy reflectance (AMSPEC, in 2012); and - beginning in 2013, hyperspectral and thermal canopy imagery. Together with eddy covariance measurements of CO2 and water fluxes from the Harvard Forest AmeriFlux site, located in similar forest about 1 km to the east, on-the-ground visual observations of phenology, and continuous stem diameter measurements with automated band dendrometers, these data provide an unusually detailed view of phenological processes at scales from leaves to trees to the forest canopy. In this presentation I will discuss our efforts to use these data for model-based analyses that link phenology to biosphere-atmosphere interactions through the cycling of CO2, water and energy. As an example, I will describe how we are using a two-layer canopy model, in conjunction with both LAI data and narrowband reflectance indices, to improve model representation of the seasonal cycle of canopy photosynthesis and hence understanding of surface-atmosphere fluxes of CO2.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.

Seasonal phenology of vegetation plays an important role in global carbon cycle and ecosystem productivity. In urban environments, vegetation phenology is also important because of its influence on public health (e.g., allergies), and energy demand (e.g. cooling effects). In this study, we studied the potential use of remotely sensed observations (i.e. Landsat data) to derive some phenology indicators for vegetation embedded within the urban core domains in four distinctly different U.S. regions (Washington, D.C., King County in Washington, Polk County in Iowa, and Baltimore City and County in Maryland) during the past three decades. We used all available Landsat observationsmore » (circa 3000 scenes) from 1982 to 2015 and a self-adjusting double logistic model to detect and quantify the annual change of vegetation phenophases, i.e. indicators of seasonal changes in vegetation. The proposed model can capture and quantify not only phenophases of dense vegetation in rural areas, but also those of mixed vegetation in urban core domains. The derived phenology indicators show a good agreement with similar indicators derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in situ observations, suggesting that the phenology dynamic depicted by the proposed model is reliable. The vegetation phenology and its seasonal and interannual dynamics demonstrate a distinct spatial pattern in urban domains with an earlier (9–14 days) start-of season (SOS) and a later (13–20 days) end-of season (EOS), resulting in an extended (5–30 days) growing season length (GSL) when compared to the surrounding suburban and rural areas in the four study regions. There is a general long-term trend of decreasing SOS (-0.30 day per year), and increasing EOS and GSL (0.50 and 0.90 day per year, respectively) over past three decades for these study regions. The magnitude of these trends varies among the four urban systems due to their diverse local climate conditions, vegetation types, and different urban-rural settings. The Landsat derived phenology information for urban domains provides more details when compared to the coarse-resolution datasets such as MODIS, thus improves our understanding of human-natural systems interactions (or feedbacks) in urban domains. Such information is very valuable for urban planning in light of rapid urbanization and expansion of major metropolitans at the national and global levels.« less

Phenologically informed re-ordering of Landsat to account for inter-annual variability: a method to map Ash trees (Fraxinus spp.) using remotely sensed imagery

NASA Astrophysics Data System (ADS)

Isaacson, B. N.; Singh, A.; Serbin, S. P.; Townsend, P. A.

2009-12-01

Rapid ecosystem invasion by the emerald ash borer (Agrilus planipennis Fairemaire) is forcing resource managers to make decisions regarding how best to manage the pest, but a detailed map of abundance of the host, ash trees of the genus Fraxinus, does not exist, frustrating fully informed management decisions. We have developed methods to map ash tree abundance across a broad spatial extent in Wisconsin using their unique phenology (late leaf-out, early leaf-fall) and the rich dataset of Landsat imagery that can be used to characterize ash senescence with respect to other deciduous species. However, across environmental gradients in Wisconsin, senescence can vary by days or even weeks such that leaf-drop within one species can temporally vary even within a single Landsat footprint. To address this issue, we used phenology products from NASA’s MODIS for North American Carbon Program (NACP) coupled with vegetation indices derived from a time series of Landsat imagery across multiple years to determine the phenological position of each Landsat pixel within a single idealized growing season. Pixels within Landsat images collected in different years were re-arranged in a phenologically-informed time series that described autumn senescence. This characterization of leaf-drop was then related to the abundance of ash trees, producing a spatially-generalizable model of moderate resolution capable of predicting ash abundance across the state using multiple Landsat scenes. Empirical models predicting ash abundance for two Landsat footprints in Wisconsin indicate model fits for ash abundance of R^2=0.65 in north-central WI, and R^2>0.70 in southeastern WI.

An observation-based progression modeling approach to spring and autumn deciduous tree phenology

NASA Astrophysics Data System (ADS)

Yu, Rong; Schwartz, Mark D.; Donnelly, Alison; Liang, Liang

2016-03-01

It is important to accurately determine the response of spring and autumn phenology to climate change in forest ecosystems, as phenological variations affect carbon balance, forest productivity, and biodiversity. We observed phenology intensively throughout spring and autumn in a temperate deciduous woodlot at Milwaukee, WI, USA, during 2007-2012. Twenty-four phenophase levels in spring and eight in autumn were recorded for 106 trees, including white ash, basswood, white oak, boxelder, red oak, and hophornbeam. Our phenological progression models revealed that accumulated degree-days and day length explained 87.9-93.4 % of the variation in spring canopy development and 75.8-89.1 % of the variation in autumn senescence. In addition, the timing of community-level spring and autumn phenophases and the length of the growing season from 1871 to 2012 were reconstructed with the models developed. All simulated spring phenophases significantly advanced at a rate from 0.24 to 0.48 days/decade ( p ≤ 0.001) during the 1871-2012 period and from 1.58 to 2.00 days/decade ( p < 0.02) during the 1970-2012 period; two simulated autumn phenophases were significantly delayed at a rate of 0.37 (mid-leaf coloration) and 0.50 (full-leaf coloration) days/decade ( p < 0.01) during the 1970-2012 period. Consequently, the simulated growing season lengthened at a rate of 0.45 and 2.50 days/decade ( p < =0.001), respectively, during the two periods. Our results further showed the variability of responses to climate between early and late spring phenophases, as well as between leaf coloration and leaf fall, and suggested accelerating simulated ecosystem responses to climate warming over the last four decades in comparison to the past 142 years.

An observation-based progression modeling approach to spring and autumn deciduous tree phenology.

PubMed

Yu, Rong; Schwartz, Mark D; Donnelly, Alison; Liang, Liang

2016-03-01

It is important to accurately determine the response of spring and autumn phenology to climate change in forest ecosystems, as phenological variations affect carbon balance, forest productivity, and biodiversity. We observed phenology intensively throughout spring and autumn in a temperate deciduous woodlot at Milwaukee, WI, USA, during 2007-2012. Twenty-four phenophase levels in spring and eight in autumn were recorded for 106 trees, including white ash, basswood, white oak, boxelder, red oak, and hophornbeam. Our phenological progression models revealed that accumulated degree-days and day length explained 87.9-93.4 % of the variation in spring canopy development and 75.8-89.1 % of the variation in autumn senescence. In addition, the timing of community-level spring and autumn phenophases and the length of the growing season from 1871 to 2012 were reconstructed with the models developed. All simulated spring phenophases significantly advanced at a rate from 0.24 to 0.48 days/decade (p ≤ 0.001) during the 1871-2012 period and from 1.58 to 2.00 days/decade (p < 0.02) during the 1970-2012 period; two simulated autumn phenophases were significantly delayed at a rate of 0.37 (mid-leaf coloration) and 0.50 (full-leaf coloration) days/decade (p < 0.01) during the 1970-2012 period. Consequently, the simulated growing season lengthened at a rate of 0.45 and 2.50 days/decade (p < =0.001), respectively, during the two periods. Our results further showed the variability of responses to climate between early and late spring phenophases, as well as between leaf coloration and leaf fall, and suggested accelerating simulated ecosystem responses to climate warming over the last four decades in comparison to the past 142 years.

Pre-rain green-up is ubiquitous across southern tropical Africa: implications for temporal niche separation and model representation.

PubMed

Ryan, Casey M; Williams, Mathew; Grace, John; Woollen, Emily; Lehmann, Caroline E R

2017-01-01

Tree phenology mediates land-atmosphere mass and energy exchange and is a determinant of ecosystem structure and function. In the dry tropics, including African savannas, many trees grow new leaves during the dry season - weeks or months before the rains typically start. This syndrome of pre-rain green-up has long been recognized at small scales, but the high spatial and interspecific variability in leaf phenology has precluded regional generalizations. We used remote sensing data to show that this precocious phenology is ubiquitous across the woodlands and savannas of southern tropical Africa. In 70% of the study area, green-up preceded rain onset by > 20 d (42% > 40 d). All the main vegetation formations exhibited pre-rain green-up, by as much as 53 ± 18 d (in the wet miombo). Green-up showed low interannual variability (SD between years = 11 d), and high spatial variability (> 100 d). These results are consistent with a high degree of local phenological adaptation, and an insolation trigger of green-up. Tree-tree competition and niche separation may explain the ubiquity of this precocious phenology. The ubiquity of pre-rain green-up described here challenges existing model representations and suggests resistance (but not necessarily resilience) to the delay in rain onset predicted under climate change. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Later springs green-up faster: the relation between onset and completion of green-up in deciduous forests of North America

NASA Astrophysics Data System (ADS)

Klosterman, Stephen; Hufkens, Koen; Richardson, Andrew D.

2018-05-01

In deciduous forests, spring leaf phenology controls the onset of numerous ecosystem functions. While most studies have focused on a single annual spring event, such as budburst, ecosystem functions like photosynthesis and transpiration increase gradually after budburst, as leaves grow to their mature size. Here, we examine the "velocity of green-up," or duration between budburst and leaf maturity, in deciduous forest ecosystems of eastern North America. We use a diverse data set that includes 301 site-years of phenocam data across a range of sites, as well as 22 years of direct ground observations of individual trees and 3 years of fine-scale high-frequency aerial photography, both from Harvard Forest. We find a significant association between later start of spring and faster green-up: - 0.47 ± 0.04 (slope ± 1 SE) days change in length of green-up for every day later start of spring within phenocam sites, - 0.31 ± 0.06 days/day for trees under direct observation, and - 1.61 ± 0.08 days/day spatially across fine-scale landscape units. To explore the climatic drivers of spring leaf development, we fit degree-day models to the observational data from Harvard Forest. We find that the default phenology parameters of the ecosystem model PnET make biased predictions of leaf initiation (39 days early) and maturity (13 days late) for red oak, while the optimized model has biases of 1 day or less. Springtime productivity predictions using optimized parameters are closer to results driven by observational data (within 1%) than those of the default parameterization (17% difference). Our study advances empirical understanding of the link between early and late spring phenophases and demonstrates that accurately modeling these transitions is important for simulating seasonal variation in ecosystem productivity.

Large scale pre-rain vegetation green up across Africa.

PubMed

Adole, Tracy; Dash, Jadunandan; Atkinson, Peter M

2018-05-16

Information on the response of vegetation to different environmental drivers, including rainfall, forms a critical input to ecosystem models. Currently, such models are run based on parameters that, in some cases, are either assumed or lack supporting evidence (e.g., that vegetation growth across Africa is rainfall-driven). A limited number of studies have reported that the onset of rain across Africa does not fully explain the onset of vegetation growth, for example, drawing on the observation of pre-rain flush effects in some parts of Africa. The spatial extent of this pre-rain green-up effect, however, remains unknown, leaving a large gap in our understanding that may bias ecosystem modelling. This paper provides the most comprehensive spatial assessment to-date of the magnitude and frequency of the different patterns of phenology response to rainfall across Africa, and for different vegetation types. To define the relations between phenology and rainfall, we investigated the spatial variation in the difference, in number of days, between the start of rainy season (SRS) and start of vegetation growing season (SOS); and between the end of rainy season (ERS) and end of vegetation growing season (EOS). We reveal a much more extensive spread of pre-rain green-up over Africa than previously reported, with pre-rain green-up being the norm rather than the exception. We also show the relative sparsity of post-rain green-up, confined largely to the Sudano-Sahel region. While the pre-rain green-up phenomenon is well documented, its large spatial extent was not anticipated. Our results, thus, contrast with the widely held view that rainfall drives the onset and end of the vegetation growing season across Africa. Our findings point to a much more nuanced role of rainfall in Africa's vegetation growth cycle than previously thought, specifically as one of a set of several drivers, with important implications for ecosystem modelling. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Continental-scale patterns and climatic drivers of fruiting phenology: A quantitative Neotropical review

NASA Astrophysics Data System (ADS)

Mendoza, Irene; Peres, Carlos A.; Morellato, Leonor Patrícia C.

2017-01-01

Changes in the life cycle of organisms (i.e. phenology) are one of the most widely used early-warning indicators of climate change, yet this remains poorly understood throughout the tropics. We exhaustively reviewed any published and unpublished study on fruiting phenology carried out at the community level in the American tropics and subtropics (latitudinal range: 26°N-26°S) to (1) provide a comprehensive overview of the current status of fruiting phenology research throughout the Neotropics; (2) unravel the climatic factors that have been widely reported as drivers of fruiting phenology; and (3) provide a preliminary assessment of the potential phenological responses of plants under future climatic scenarios. Despite the large number of phenological datasets uncovered (218), our review shows that their geographic distribution is very uneven and insufficient for the large surface of the Neotropics ( 1 dataset per 78,000 km2). Phenological research is concentrated in few areas with many studies (state of São Paulo, Brazil, and Costa Rica), whereas vast regions elsewhere are entirely unstudied. Sampling effort in fruiting phenology studies was generally low: the majority of datasets targeted fewer than 100 plant species (71%), lasted 2 years or less (72%), and only 10.4% monitored > 15 individuals per species. We uncovered only 10 sites with ten or more years of phenological monitoring. The ratio of numbers of species sampled to overall estimates of plant species richness was wholly insufficient for highly diverse vegetation types such as tropical rainforest, seasonal forest and cerrado, and only slightly more robust for less diverse vegetation types, such as deserts, arid shrublands and open grassy savannas. Most plausible drivers of phenology extracted from these datasets were environmental (78.5%), whereas biotic drivers were rare (6%). Among climatic factors, rainfall was explicitly included in 73.4% of cases, followed by air temperature (19.3%). Other environmental cues such as water level (6%), solar radiation or photoperiod (3.2%), and ENSO events (1.4%) were rarely addressed. In addition, drivers were analyzed statistically in only 38% of datasets and techniques were basically correlative, with only 4.8% of studies including any consideration of the inherently autocorrelated character of phenological time series. Fruiting peaks were significantly more often reported during the rainy season both in rainforests and cerrado woodlands, which is at odds with the relatively aseasonal character of the former vegetation type. Given that climatic models predict harsh future conditions for the tropics, we urgently need to determine the magnitude of changes in plant reproductive phenology and distinguish those from cyclical oscillations. Long-term monitoring and herbarium data are therefore key for detecting these trends. Our review shows that the unevenness in geographic distribution of studies, and diversity of sampling methods, vegetation types, and research motivation hinder the emergence of clear general phenological patterns and drivers for the Neotropics. We therefore call for prioritizing research in unexplored areas, and improving the quantitative component and statistical design of reproductive phenology studies to enhance our predictions of climate change impacts on tropical plants and animals.

Satellite-based phenology detection in broadleaf forests in South-Western Germany

NASA Astrophysics Data System (ADS)

Misra, Gourav; Buras, Allan; Menzel, Annette

2016-04-01

Many techniques exist for extracting phenological information from time series of satellite data. However, there have been only a few successful attempts to temporarily match satellite-derived observations with ground based phenological observations (Fisher et al., 2006; Hamunyela et al., 2013; Galiano et al., 2015). Such studies are primarily plagued with problems relating to shorter time series of satellite data including spatial and temporal resolution issues. A great challenge is to correlate spatially continuous and pixel-based satellite information with spatially discontinuous and point-based, mostly species-specific, ground observations of phenology. Moreover, the minute differences in phenology observed by ground volunteers might not be sufficient to produce changes in satellite-measured reflectance of vegetation, which also exposes the difference in the definitions of phenology (Badeck et al., 2004; White et al., 2014). In this study Start of Season (SOS) was determined for broadleaf forests at a site in south-western Germany using MODIS-sensor time series of Normalised Difference Vegetation Index (NDVI) data for the years covering 2001 to 2013. The NDVI time series raster data was masked for broadleaf forests using Corine Land Cover dataset, filtered and corrected for snow and cloud contaminations, smoothed with a Gaussian filter and interpolated to daily values. Several SOS techniques cited in literature, namely thresholds of amplitudes (20%, 50%, 60% and 75%), rates of change (1st, 2nd and 3rd derivative) and delayed moving average (DMA) were tested for determination of satellite SOS. The different satellite SOS were then compared with a species-rich ground based phenology information (e.g. understory leaf unfolding, broad leaf unfolding and greening of evergreen tree species). Working with all the pixels at a finer resolution, it is seen that the temporal trends in understory and broad leaf species are well captured. Initial analyses show promising results and suggest that different satellite SOS extraction techniques work well for specific phases of ground phenology information. More than half of the broadleaf pixels show an earliness in SOS which matches with the trend in ground phenology. References 1. F.-W. Badeck, A. Bondeau, K. Bottcher, D. Doktor, W. Lucht, J. Schaber, and S. Sitch, 2004, "Responses of spring phenology to climate change," New Phytologist, vol. 162, no. 2, pp. 295-309. 2. E. Hamunyela, J. Verbesselt, G. Roerink, and M. Herold, 2013, "Trends in Spring Phenology of Western European Deciduous Forests," Remote Sensing, vol. 5, no. 12, pp. 6159-6179. 3. V. F. Rodriguez-Galiano, J. Dash, and P. M. Atkinson, 2015, "Intercomparison of satellite sensor land surface phenology and ground phenology in Europe: Inter-annual comparison and modelling," Geophysical Research Letters, vol. 42, no. 7, pp. 2253-2260. 4. J. Fisher, J. Mustard, and M. Vadeboncoeur, 2006, "Green leaf phenology at Landsat resolution: Scaling from the field to the satellite," Remote Sensing of Environment, vol. 100, no. 2, pp. 265-279. 5. K. White, J. Pontius, and P. Schaberg, 2014, "Remote sensing of spring phenology in northeastern forests: A comparison of methods, field metrics and sources of uncertainty," Remote Sensing of Environment, vol. 148, pp. 97-107.

Phenological cues drive an apparent trade-off between freezing tolerance and growth in the family Salicaceae.

PubMed

Savage, Jessica A; Cavender-Bares, Jeannine

2013-08-01

With increasing concern about the ecological consequences of global climate change, there has been renewed interest in understanding the processes that determine species range limits. We tested a long-hypothesized trade-off between freezing tolerance and growth rate that is often used to explain species range limits. We grew 24 willow and poplar species (family Salicaceae) collected from across North America in a greenhouse common garden under two climate treatments. Maximum entropy models were used to describe species distributions and to estimate species-specific climate parameters. A range of traits related to freezing tolerance, including senescence, budburst, and susceptibility to different temperature minima during and after acclimation were measured. As predicted, species from colder climates exhibited higher freezing tolerance and slower growth rates than species from warmer climates under certain environmental conditions. However, the average relative growth rate (millimeters per meter per day) of northern species markedly increased when a subset of species was grown under a long summer day length (20.5 h), indicating that genetically based day-length cues are required for growth regulation in these species. We conclude that the observed relationship between freezing tolerance and growth rate is not driven by differences in species' intrinsic growth capacity but by differences in the environmental cues that trigger growth. We propose that the coordinated evolution of freezing tolerance and growth phenology could be important in circumscribing willow and poplar range limits and may have important implications for species' current and future distributions.

Toward a Probabilistic Phenological Model for Wheat Growing Degree Days (GDD)

NASA Astrophysics Data System (ADS)

Rahmani, E.; Hense, A.

2017-12-01

Are there deterministic relations between phenological and climate parameters? The answer is surely `No'. This answer motivated us to solve the problem through probabilistic theories. Thus, we developed a probabilistic phenological model which has the advantage of giving additional information in terms of uncertainty. To that aim, we turned to a statistical analysis named survival analysis. Survival analysis deals with death in biological organisms and failure in mechanical systems. In survival analysis literature, death or failure is considered as an event. By event, in this research we mean ripening date of wheat. We will assume only one event in this special case. By time, we mean the growing duration from sowing to ripening as lifetime for wheat which is a function of GDD. To be more precise we will try to perform the probabilistic forecast for wheat ripening. The probability value will change between 0 and 1. Here, the survivor function gives the probability that the not ripened wheat survives longer than a specific time or will survive to the end of its lifetime as a ripened crop. The survival function at each station is determined by fitting a normal distribution to the GDD as the function of growth duration. Verification of the models obtained is done using CRPS skill score (CRPSS). The positive values of CRPSS indicate the large superiority of the probabilistic phonologic survival model to the deterministic models. These results demonstrate that considering uncertainties in modeling are beneficial, meaningful and necessary. We believe that probabilistic phenological models have the potential to help reduce the vulnerability of agricultural production systems to climate change thereby increasing food security.

Leaf ontogeny and demography explain photosynthetic seasonality in Amazon evergreen forests

NASA Astrophysics Data System (ADS)

Wu, J.; Albert, L.; Lopes, A. P.; Restrepo-Coupe, N.; Hayek, M.; Wiedemann, K. T.; Guan, K.; Stark, S. C.; Prohaska, N.; Tavares, J. V.; Marostica, S. F.; Kobayashi, H.; Ferreira, M. L.; Campos, K.; Silva, R. D.; Brando, P. M.; Dye, D. G.; Huxman, T. E.; Huete, A. R.; Nelson, B. W.; Saleska, S. R.

2015-12-01

Photosynthetic seasonality couples the evolutionary ecology of plant leaves to large-scale rhythms of carbon and water exchanges that are important feedbacks to climate. However, the extent, magnitude, and controls on photosynthetic seasonality of carbon-rich tropical forests are poorly resolved, controversial in the remote sensing literature, and inadequately represented in most earth system models. Here we show that ecosystem-scale phenology (measured by photosynthetic capacity), rather than environmental seasonality, is the primary driver of photosynthetic seasonality at four Amazon evergreen forests spanning gradients in rainfall seasonality, forest composition, and flux seasonality. We further demonstrate that leaf ontogeny and demography explain most of this ecosystem phenology at two central Amazon evergreen forests, using a simple leaf-cohort canopy model that integrates eddy covariance-derived CO2 fluxes, novel near-surface camera-detected leaf phenology, and ground observations of litterfall and leaf physiology. The coordination of new leaf growth and old leaf divestment (litterfall) during the dry season shifts canopy composition towards younger leaves with higher photosynthetic efficiency, driving large seasonal increases (~27%) in ecosystem photosynthetic capacity. Leaf ontogeny and demography thus reconciles disparate observations of forest seasonality from leaves to eddy flux towers to satellites. Strategic incorporation of such whole-plant coordination processes as phenology and ontogeny will improve ecological, evolutionary and earth system theories describing tropical forests structure and function, allowing more accurate representation of forest dynamics and feedbacks to climate in earth system models.

Energetic Physiology Mediates Individual Optimization of Breeding Phenology in a Migratory Arctic Seabird.

PubMed

Hennin, Holly L; Bêty, Jöel; Legagneux, Pierre; Gilchrist, H Grant; Williams, Tony D; Love, Oliver P

2016-10-01

The influence of variation in individual state on key reproductive decisions impacting fitness is well appreciated in evolutionary ecology. Rowe et al. (1994) developed a condition-dependent individual optimization model predicting that three key factors impact the ability of migratory female birds to individually optimize breeding phenology to maximize fitness in seasonal environments: arrival condition, arrival date, and ability to gain in condition on the breeding grounds. While empirical studies have confirmed that greater arrival body mass and earlier arrival dates result in earlier laying, no study has assessed whether individual variation in energetic management of condition gain effects this key fitness-related decision. Using an 8-year data set from over 350 prebreeding female Arctic common eiders (Somateria mollissima), we tested this component of the model by examining whether individual variation in two physiological traits influencing energetic management (plasma triglycerides: physiological fattening rate; baseline corticosterone: energetic demand) predicted individual variation in breeding phenology after controlling for arrival date and body mass. As predicted by the optimization model, individuals with higher fattening rates and lower energetic demand had the earliest breeding phenology (shortest delays between arrival and laying; earliest laying dates). Our results are the first to empirically determine that individual flexibility in prebreeding energetic management influences key fitness-related reproductive decisions, suggesting that individuals have the capacity to optimally manage reproductive investment.

Detrending phenological time series improves climate-phenology analyses and reveals evidence of plasticity.

PubMed

Iler, Amy M; Inouye, David W; Schmidt, Niels M; Høye, Toke T

2017-03-01

Time series have played a critical role in documenting how phenology responds to climate change. However, regressing phenological responses against climatic predictors involves the risk of finding potentially spurious climate-phenology relationships simply because both variables also change across years. Detrending by year is a way to address this issue. Additionally, detrending isolates interannual variation in phenology and climate, so that detrended climate-phenology relationships can represent statistical evidence of phenotypic plasticity. Using two flowering phenology time series from Colorado, USA and Greenland, we detrend flowering date and two climate predictors known to be important in these ecosystems: temperature and snowmelt date. In Colorado, all climate-phenology relationships persist after detrending. In Greenland, 75% of the temperature-phenology relationships disappear after detrending (three of four species). At both sites, the relationships that persist after detrending suggest that plasticity is a major component of sensitivity of flowering phenology to climate. Finally, simulations that created different strengths of correlations among year, climate, and phenology provide broader support for our two empirical case studies. This study highlights the utility of detrending to determine whether phenology is related to a climate variable in observational data sets. Applying this as a best practice will increase our understanding of phenological responses to climatic variation and change. © 2016 by the Ecological Society of America.

The role of spring and autumn phenological switches on spatiotemporal variation in temperate and boreal forest C balance: A FLUXNET synthesis

NASA Astrophysics Data System (ADS)

Richardson, A. D.; Reichstein, M.; Piao, S.; Ciais, P.; Luyssaert, S.; Stockli, R.; Friedl, M.; Gobron, N.; Fluxnet Site Pis, 21

2009-04-01

In temperate and boreal ecosystems, phenological transitions (particularly the timing of spring onset and autumn senescence) are thought to represent a major control on spatial and temporal variation in forest carbon sequestration. To investigate these patterns, we analyzed 153 site-years of data from the FLUXNET ‘La Thuile' database. Eddy covariance measurements of surface-atmosphere exchanges of carbon and water from 21 research sites at latitudes from 36°N to 67°N were used in the synthesis. We defined a range of phenological indicators based on the first (spring) and last (autumn) dates of (1) C source/sink transitions (‘carbon uptake period'); (2) measurable photosynthetic uptake (‘physiologically active period'); (3) relative thresholds for latent heat (evapotranspiration) flux; (4) phenological thresholds derived from a range of remote sensing products (JRC fAPAR, MOD12Q2, and the PROGNOSTIC model with MODIS data assimilation); and (5) a climatological metric based on the date where soil temperature equals mean annual air temperature. We then tested whether site-level flux anomalies were significantly correlated with phenological anomalies across these metrics, and whether the slopes of these relationships (representing the sensitivity to phenological variation) differed between deciduous broadleaf (DBF) and evergreen needleleaf (ENF) forests. Within sites, interannual variation in most phenological metrics was about 5-10 d, compared to 10-30 d across sites. Both spatial and temporal phenological variation were consistently larger at ENF, compared to DBF, sites. Averaged across metrics, phenological variability was roughly comparable in spring and autumn, both across (17 d) and within (9 d) sites. However, patterns of interannual variation in fluxes were less well explained by the derived phenological metrics than were patterns of spatial variation in fluxes. Also, the observed pattern strongly depended on the metric used, with flux-derived metrics generally explaining more, and remote sensing-derived metrics generally explaining less, of the variation in flux anomalies. We found that GPP (gross primary productivity) was consistently more sensitive (both in terms of magnitude and statistical significance; ≈3 g C m-2 d-1 for DBF and ≈2 g C m-2 d-1 for ENF) to phenology than was Reco (ecosystem respiration), which meant that NEP (net ecosystem productivity) tended to be increased both by earlier springs and later autumns. Without exception, when the difference between DBF and ENF in the sensitivity to phenological anomalies was statistically significant, DBF sensitivity was always larger in absolute magnitude than ENF sensitivity. Phenology explained a much larger fraction of the variation in fluxes across sites compared to within sites. Across sites, the rate of increase in GPP with an "exta" day in spring (≈10 g C m-2 d-1) was much larger than in autumn (≈3 g C m-2 d-1). Furthermore, a one-day increase in growing season length across sites increased annual NEP by just ≈2 g C m-2 d-1; this resulted from an increase in GPP of ≈6 g C m-2 d-1 being offset by an increase in RE of ≈4 g C m-2 d-1. In general, there was no statistically significant difference between DBF and ENF in the sensitivity to spatial variation in phenology for either NEP or the component fluxes GPP and Reco. In relation to both within- and across-site variation in phenology and fluxes, the results obtained tended to depend on the phenological metric used, i.e. definition of "start" and "end" of growing season, emphasizing the need for improved understanding of the relationships between these different metrics and ecosystem processes. Furthermore, the differences in flux-phenology relationships in the context of spatial and temporal variation in phenology raise questions about using results from either short-term or space-for-time studies to anticipate responses to future climate change.

USA National Phenology Network's volunteer-contributed observations yield predictive models of phenological transitions.

PubMed

Crimmins, Theresa M; Crimmins, Michael A; Gerst, Katharine L; Rosemartin, Alyssa H; Weltzin, Jake F

2017-01-01

In support of science and society, the USA National Phenology Network (USA-NPN) maintains a rapidly growing, continental-scale, species-rich dataset of plant and animal phenology observations that with over 10 million records is the largest such database in the United States. The aim of this study was to explore the potential that exists in the broad and rich volunteer-collected dataset maintained by the USA-NPN for constructing models predicting the timing of phenological transition across species' ranges within the continental United States. Contributed voluntarily by professional and citizen scientists, these opportunistically collected observations are characterized by spatial clustering, inconsistent spatial and temporal sampling, and short temporal depth (2009-present). Whether data exhibiting such limitations can be used to develop predictive models appropriate for use across large geographic regions has not yet been explored. We constructed predictive models for phenophases that are the most abundant in the database and also relevant to management applications for all species with available data, regardless of plant growth habit, location, geographic extent, or temporal depth of the observations. We implemented a very basic model formulation-thermal time models with a fixed start date. Sufficient data were available to construct 107 individual species × phenophase models. Remarkably, given the limited temporal depth of this dataset and the simple modeling approach used, fifteen of these models (14%) met our criteria for model fit and error. The majority of these models represented the "breaking leaf buds" and "leaves" phenophases and represented shrub or tree growth forms. Accumulated growing degree day (GDD) thresholds that emerged ranged from 454 GDDs (Amelanchier canadensis-breaking leaf buds) to 1,300 GDDs (Prunus serotina-open flowers). Such candidate thermal time thresholds can be used to produce real-time and short-term forecast maps of the timing of these phenophase transition. In addition, many of the candidate models that emerged were suitable for use across the majority of the species' geographic ranges. Real-time and forecast maps of phenophase transitions could support a wide range of natural resource management applications, including invasive plant management, issuing asthma and allergy alerts, and anticipating frost damage for crops in vulnerable states. Our finding that several viable thermal time threshold models that work across the majority of the species ranges could be constructed from the USA-NPN database provides clear evidence that great potential exists this dataset to develop more enhanced predictive models for additional species and phenophases. Further, the candidate models that emerged have immediate utility for supporting a wide range of management applications.

Multi-Source Image Analysis.

DTIC Science & Technology

1979-12-01

vegetation shows on the imagery but emphasis has been placed on the detection of wooded and scrub areas and the differentiation between deciduous and...S. A., 1974b, Phenology and remote sensing, phenology and seasonality modeling: in Helmut Lieth, H. (ed.), Ecological Studies-Analysis and Synthesis...Remote Sensing of Ecology , University of d-eorgia Press, Athens, Georgia, p. 63-94. Phillipson, W. R. and T. Liang, 1975, Airphoto analysis in the

PHENOALP: a new project on phenology in the Western Alps

NASA Astrophysics Data System (ADS)

Cremonese, E.

2009-04-01

PHENOALP is a new EU co-funded Interreg Project under the operational programme for cross-border cooperation "Italy-France (Alps-ALCOTRA)" 2007 - 2013, aiming to get a better understanding of phenological changes in the Alps. The major goals of the project are: 1- The implementation of an observation network in the involved territories (i.e. the Aosta Valley and the Savoies in the Western Alps); 2- The definition of a common observation strategy and common protocols; 3- The involvement of local community members (e.g. through schools) in the observation activities as a way to increase the awareness on the issue of the effects of climate change. Project leader is the Environmental Protection Agency of Aosta Valley (ARPA Valle d'Aosta - IT) and the partners are the Research Center on High Altitude Ecosystem (CREA - FR), Mont Avic Regional Parc (IT), Bauges Massif Regional Natural Parc (FR) and the Protected Area Service of Aosta Valley (IT). Project activities are: 1. Pheno-plantes: definition of common observation protocols (e.g. field observation and webcams) of different alpine species (trees and herbaceous) and implementation of the observation network; analysis of the relations between climate and phenological events; application and evaluation of phenological models. 2. Pheno-detection: remote sensing of European larch and high elevation pastures with MODIS data; multitemporal analysis (2000-2011) of phenological variations in the Western Alps. 3. Pheno-flux: analysis of the relation between the seasonal and interannual variability of plant phenology and productivity, assessed measuring CO2 fluxes (eddy-covariance technique), radiometric indexes and phenological events at specific (European larch stand and alpine pastures) monitoring site. 4. Pheno-zoo: definition of common observation protocols for the phenology of animal taxa (birds, mammals, amphibians and insects) along altitudinal gradients; implementation of the observation network. 5. Inter-pheno: integrated analysis of the relationships between plants and animals phenology and their relation with climatic and other environmental conditions. 6. Meteo-reseau: implementation of a monitoring network of temperature data in the sites where phenological observations are done. 7. Pheno-form: involvement of community members (e.g. schools, naturalistic guides, ...) in the observations and diffusion of results. During the conference, details on project structures, methodology and expected outcomes will be exposed and discussed.

What You See Depends on Your Point of View: Comparison of Greenness Indices Across Spatial and Temporal Scales and What That Means for Mule Deer Migration and Fitness

NASA Astrophysics Data System (ADS)

Miller, B. W.; Chong, G.; Steltzer, H.; Aikens, E.; Morisette, J. T.; Talbert, C.; Talbert, M.; Shory, R.; Krienert, J. M.; Gurganus, D.

2015-12-01

Climate change models for the north­ern Rocky Mountains predict warming and changes in water availability that may alter vegetation. Changes to vegetation may include timing of plant life-history events, or phenology, such as green-up, flower­ing, and senescence. These changes could make forage available earlier in the growing season, but shifts in phenol­ogy may also result in earlier senescence (die-off or dormancy) and reduced overall production. Greenness indices such as the normalized difference vegetation index (NDVI) are regularly used to quantify greenness over large areas using remotely sensed reflectance data. The timing and scale of current satellite data, however, may be insufficient to capture fine-scale differences in phenology that are important indicators of habitat quality. The Wyoming Range Mule Deer herd is one of the largest in the west but it declined precipitously in the early 1990s and has not recovered. Accurate measurement of greenness over space and time would allow managers to better understand the role of plant phenology and productivity in mule deer population dynamics, for example. To connect spatial and temporal patterns of plant productivity with habitat quality, we compare greenness patterns (MODIS data) with migratory mule deer movement (GPS collars). Sagebrush systems provide winter habitat for mule deer. To understand sagebrush phenology as an indicator of productivity, we constructed NDVI time series and compared dates of phenological stages and magnitudes of greenness from three perspectives: at-surface/species-specific (mantis sensors: downward looking, <1m above vegetation); near surface/site-specific (PhenoCam: oblique, 2m); and satellite/landscape-scale (varied platforms). Greenness indices from these sensors contribute unique insights to understanding vegetation phenology, snow cover and reflectance. Understanding phenology and productivity at multiple scales can help guide resource management decisions related to habitat quality, and evaluate what remotely sensed phenology measurements mean on the ground. Monitoring changes in phenology and productivity over the long-term can provide insight into ecosystem responses to climate change.

Responses of spring phenology to climate warming reduced over the past decades

NASA Astrophysics Data System (ADS)

Fu, Yongshuo. H.; Zhao, hongfang; piao, Shilong; Peaucelle, Marc; Peng, Shushi; Zhou, Guiyun; Ciais, Philippe; Huang, Mengtian; Menzel, Annette; Penuelas, Josep; Song, Yang; Vitasse, Yann; Zeng, Zhenzhong; Janssens, Ivan. A.

2016-04-01

The phenology of spring leaf unfolding is one of the key indicators of the climate change on ecosystems, and influences regional and hemispheric-scale carbon balances and plant-animal interactions. Changes in the phenology of spring leaf unfolding can also exert biophysical feedbacks on climate by modifying the surface albedo and energy budget. Recent studies have reported significant advances in spring phenology as a result of warming in most northern hemisphere regions. Climate warming is projected to further increase, but the future evolution of the phenology of spring leaf unfolding remains uncertain - in view of the imperfect understanding of how the underlying mechanisms respond to environmental stimuli. In addition, the relative contributions of each environmental stimulus, which together define the apparent temperature sensitivity of the phenology of spring leaf unfolding (advances in days per degree Celsius warming, ST), may also change over time. An improved characterization of the variation in phenological responses to spring temperature is thus valuable, provided that it addresses temporal and spatial scales relevant for regional projections. Using long-term in situ observations of leaf unfolding for seven dominant European tree species at 1,245 sites, we show here that the apparent response of leaf unfolding to climate warming (ST, expressed in days advance per ° C) has significantly decreased from 1980 to 2013 in all monitored tree species. Averaged across all species and sites, ST decreased by 40% from 4.0 ± 1.8 days ° C-1 during 1980-1994 to 2.3 ± 1.6 days ° C-1 during 1999-2013. The declining ST was also simulated by chilling-based phenology models, albeit with a weaker decline (24%-30%) than observed in situ. The reduction in ST is likely to be partly attributable to reduced chilling. Nonetheless, other mechanisms may also play a role, such as 'photoperiod limitation' mechanisms that may become ultimately limiting when leaf unfolding dates occur too early in the season. Our results provide empirical evidence for a declining ST, but also suggest that the predicted strong winter warming in the future may further reduce ST and therefore result in a slowdown in the advance of tree spring phenology.

No Consistent Evidence for Advancing or Delaying Trends in Spring Phenology on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Wang, Xufeng; Xiao, Jingfeng; Li, Xin; Cheng, Guodong; Ma, Mingguo; Che, Tao; Dai, Liyun; Wang, Shaoying; Wu, Jinkui

2017-12-01

Vegetation phenology is a sensitive indicator of climate change and has significant effects on the exchange of carbon, water, and energy between the terrestrial biosphere and the atmosphere. The Tibetan Plateau, the Earth's "third pole," is a unique region for studying the long-term trends in vegetation phenology in response to climate change because of the sensitivity of its alpine ecosystems to climate and its low-level human disturbance. There has been a debate whether the trends in spring phenology over the Tibetan Plateau have been continuously advancing over the last two to three decades. In this study, we examine the trends in the start of growing season (SOS) for alpine meadow and steppe using the Global Inventory Modeling and Mapping Studies (GIMMS)3g normalized difference vegetation index (NDVI) data set (1982-2014), the GIMMS NDVI data set (1982-2006), the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data set (2001-2014), the Satellite Pour l'Observation de la Terre Vegetation (SPOT-VEG) NDVI data set (1999-2013), and the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) NDVI data set (1998-2007). Both logistic and polynomial fitting methods are used to retrieve the SOS dates from the NDVI data sets. Our results show that the trends in spring phenology over the Tibetan Plateau depend on both the NDVI data set used and the method for retrieving the SOS date. There are large discrepancies in the SOS trends among the different NDVI data sets and between the two different retrieval methods. There is no consistent evidence that spring phenology ("green-up" dates) has been advancing or delaying over the Tibetan Plateau during the last two to three decades. Ground-based budburst data also indicate no consistent trends in spring phenology. The responses of SOS to environmental factors (air temperature, precipitation, soil temperature, and snow depth) also vary among NDVI data sets and phenology retrieval methods. The increases in winter and spring temperature had offsetting effects on spring phenology.

Climate change and spring frost damages for sweet cherries in Germany

NASA Astrophysics Data System (ADS)

Chmielewski, Frank-M.; Götz, Klaus-P.; Weber, Katharina C.; Moryson, Susanne

2018-02-01

Spring frost can be a limiting factor in sweet cherry ( Prunus avium L.) production. Rising temperatures in spring force the development of buds, whereby their vulnerability to freezing temperatures continuously increases. With the beginning of blossom, flowers can resist only light frosts without any significant damage. In this study, we investigated the risk of spring frost damages during cherry blossom for historical and future climate conditions at two different sites in NE (Berlin) and SW Germany (Geisenheim). Two phenological models, developed on the basis of phenological observations at the experimental sweet cherry orchard in Berlin-Dahlem and validated for endodormancy release and for warmer climate conditions (already published), were used to calculate the beginning of cherry blossom in Geisenheim, 1951-2015 (external model validation). Afterwards, on the basis of a statistical regionalisation model WETTREG (RCP 8.5), the frequency of frost during cherry blossom was calculated at both sites for historical (1971-2000) and future climate conditions (2011-2100). From these data, we derived the final flower damage, defined as the percentage of frozen flowers due to single or multiple frost events during blossom. The results showed that rising temperatures in this century can premature the beginning of cherry blossom up to 17 days at both sites, independent of the used phenological model. The frequency and strength of frost was characterised by a high temporal and local variability. For both sites, no significant increase in frost frequency and frost damage during blossom was found. In Geisenheim, frost damages significantly decreased from the middle of the twenty-first century. This study additionally emphasises the importance of reliable phenological models which not only work for current but also for changed climate conditions and at different sites. The date of endodormancy release should always be a known parameter in chilling/forcing models.

Phenological models to predict the main flowering phases of olive ( Olea europaea L.) along a latitudinal and longitudinal gradient across the Mediterranean region

NASA Astrophysics Data System (ADS)

Aguilera, Fátima; Fornaciari, Marco; Ruiz-Valenzuela, Luis; Galán, Carmen; Msallem, Monji; Dhiab, Ali Ben; la Guardia, Consuelo Díaz-de; del Mar Trigo, María; Bonofiglio, Tommaso; Orlandi, Fabio

2015-05-01

The aim of the present study was to develop pheno-meteorological models to explain and forecast the main olive flowering phenological phases within the Mediterranean basin, across a latitudinal and longitudinal gradient that includes Tunisia, Spain, and Italy. To analyze the aerobiological sampling points, study periods from 13 years (1999-2011) to 19 years (1993-2011) were used. The forecasting models were constructed using partial least-squares regression, considering both the flowering start and full-flowering dates as dependent variables. The percentages of variance explained by the full-flowering models (mean 84 %) were greater than those explained by the flowering start models (mean 77 %). Moreover, given the time lag from the North African areas to the central Mediterranean areas in the main olive flowering dates, the regional full-flowering predictive models are proposed as the most useful to improve the knowledge of the influence of climate on the olive tree floral phenology. The meteorological parameters related to the previous autumn and both the winter and the spring seasons, and above all the temperatures, regulate the reproductive phenology of olive trees in the Mediterranean area. The mean anticipation of flowering start and full flowering for the future period from 2081 to 2100 was estimated at 10 and 12 days, respectively. One question can be raised: Will the olive trees located in the warmest areas be northward displaced or will they be able to adapt their physiology in response to the higher temperatures? The present study can be considered as an approach to design more detailed future bioclimate research.

Climate change and spring frost damages for sweet cherries in Germany.

PubMed

Chmielewski, Frank-M; Götz, Klaus-P; Weber, Katharina C; Moryson, Susanne

2018-02-01

Spring frost can be a limiting factor in sweet cherry (Prunus avium L.) production. Rising temperatures in spring force the development of buds, whereby their vulnerability to freezing temperatures continuously increases. With the beginning of blossom, flowers can resist only light frosts without any significant damage. In this study, we investigated the risk of spring frost damages during cherry blossom for historical and future climate conditions at two different sites in NE (Berlin) and SW Germany (Geisenheim). Two phenological models, developed on the basis of phenological observations at the experimental sweet cherry orchard in Berlin-Dahlem and validated for endodormancy release and for warmer climate conditions (already published), were used to calculate the beginning of cherry blossom in Geisenheim, 1951-2015 (external model validation). Afterwards, on the basis of a statistical regionalisation model WETTREG (RCP 8.5), the frequency of frost during cherry blossom was calculated at both sites for historical (1971-2000) and future climate conditions (2011-2100). From these data, we derived the final flower damage, defined as the percentage of frozen flowers due to single or multiple frost events during blossom. The results showed that rising temperatures in this century can premature the beginning of cherry blossom up to 17 days at both sites, independent of the used phenological model. The frequency and strength of frost was characterised by a high temporal and local variability. For both sites, no significant increase in frost frequency and frost damage during blossom was found. In Geisenheim, frost damages significantly decreased from the middle of the twenty-first century. This study additionally emphasises the importance of reliable phenological models which not only work for current but also for changed climate conditions and at different sites. The date of endodormancy release should always be a known parameter in chilling/forcing models.

Citizen Science in Grand Teton National Park Reveals Phenological Response of Wildlife to Climate Change and Increases Public Involvement in Earth Science

NASA Astrophysics Data System (ADS)

Bloom, T. D. S.; Riginos, C.

2017-12-01

Around the world, phenology —or the timing of ecological events — is shifting as the climate warms. This can lead to a variety of consequences for individual species and for ecological communities as a whole, most notably through asynchronies that can develop between plants and animals that depend upon each other (e.g. nectar-consuming pollinators). Within the Greater Yellowstone Ecosystem (GYE) and Grand Teton National Park (GTNP), there is little understanding of how climate change is affecting plant and animal phenology, yet through detailed scientific and citizen science observation there is tremendous potential to further our knowledge of this topic and increase public awareness. Detailed historic data are rare, but in GTNP we have the opportunity to capitalize on phenology data gathered by Dr. Frank Craighead, Jr. in the 1970s, before significant warming had occurred. We have already gathered, digitized, and quality-controlled Craighead's observations of plant first flowering dates. First flowering date for 87% of a 72-species data set correlate significantly with spring temperatures in the 1970s, suggesting that these plants are now flowering earlier and will continue to flower earlier in the future. Our multi-year project has project has 3 primary goals: (1) initiate a citizen science project, Wildflower Watch GTNP, to train volunteer scientists to collect contemporary phenology data on these species (2) gather further historical records of plant phenology in the region, and (3) model continued phenological changes under future climate change scenarios using satellite derived climate data and on the ground observations. This project simultaneously increases public involvement in climate research, collaborates with the National Park Service to inform management strategies for at-risk species, and furthers scientific understanding of phenological response to climate change in the Rocky Mountains.

Future Phenology: Challenges for an Integrative Environmental Science

NASA Astrophysics Data System (ADS)

Schwartz, M. D.

2004-12-01

Phenology is an interdisciplinary environmental science, and as such brings together individuals from many different scientific backgrounds, but the full benefits of their combined disciplinary perspectives to enrich phenological research have yet to be realized. The last few years have seen rapid progress in the transmission of "phenological perspectives" into the mainstream of science, especially related to the needs of global change research. While other parts of phenological research are still important and need to progress, it is global change science that will stimulate, challenge, and transform the discipline of phenology most in the coming decades. In order to maximize the benefits of phenology for global change research as rapidly as possible, commitments to integrative thinking and large-scale data collection must be accelerated. First of all, the limitations of the primary forms of data collection (remote sensing derived, native species, cloned indicator species, and model output) must be accepted. None of these data sources can meet the needs of all research questions, and an "integrative approach" that combines data types provides synergistic benefits. The most needed data are traditional native and cloned plant species observations. Networks that select a small number of common plants for coordinated observation among national and global scale networks will prove the most useful. These networks should be embraced and integrated into the missions of national weather services around the world, as is now the case in many European countries. A little more than one hundred years ago, the countries of the world began to cooperate in a global-scale network of weather and climate monitoring stations. The results of this long-term investment are the considerable progress that has been made in understanding the workings of the earth's climate systems. We have a similar opportunity with phenological data--small investments in national and global-scale observation networks are crucial to global change science, and will yield an impressive return in the years ahead.

A meta-analysis of cambium phenology and growth: linear and non-linear patterns in conifers of the northern hemisphere

PubMed Central

Rossi, Sergio; Anfodillo, Tommaso; Čufar, Katarina; Cuny, Henri E.; Deslauriers, Annie; Fonti, Patrick; Frank, David; Gričar, Jožica; Gruber, Andreas; King, Gregory M.; Krause, Cornelia; Morin, Hubert; Oberhuber, Walter; Prislan, Peter; Rathgeber, Cyrille B. K.

2013-01-01

Background and Aims Ongoing global warming has been implicated in shifting phenological patterns such as the timing and duration of the growing season across a wide variety of ecosystems. Linear models are routinely used to extrapolate these observed shifts in phenology into the future and to estimate changes in associated ecosystem properties such as net primary productivity. Yet, in nature, linear relationships may be special cases. Biological processes frequently follow more complex, non-linear patterns according to limiting factors that generate shifts and discontinuities, or contain thresholds beyond which responses change abruptly. This study investigates to what extent cambium phenology is associated with xylem growth and differentiation across conifer species of the northern hemisphere. Methods Xylem cell production is compared with the periods of cambial activity and cell differentiation assessed on a weekly time scale on histological sections of cambium and wood tissue collected from the stems of nine species in Canada and Europe over 1–9 years per site from 1998 to 2011. Key Results The dynamics of xylogenesis were surprisingly homogeneous among conifer species, although dispersions from the average were obviously observed. Within the range analysed, the relationships between the phenological timings were linear, with several slopes showing values close to or not statistically different from 1. The relationships between the phenological timings and cell production were distinctly non-linear, and involved an exponential pattern Conclusions The trees adjust their phenological timings according to linear patterns. Thus, shifts of one phenological phase are associated with synchronous and comparable shifts of the successive phases. However, small increases in the duration of xylogenesis could correspond to a substantial increase in cell production. The findings suggest that the length of the growing season and the resulting amount of growth could respond differently to changes in environmental conditions. PMID:24201138

The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data.

PubMed

Stucky, Brian J; Guralnick, Rob; Deck, John; Denny, Ellen G; Bolmgren, Kjell; Walls, Ramona

2018-01-01

Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.

Flowering time of butterfly nectar food plants is more sensitive to temperature than the timing of butterfly adult flight.

PubMed

Kharouba, Heather M; Vellend, Mark

2015-09-01

1. Variation among species in their phenological responses to temperature change suggests that shifts in the relative timing of key life cycle events between interacting species are likely to occur under climate warming. However, it remains difficult to predict the prevalence and magnitude of these shifts given that there have been few comparisons of phenological sensitivities to temperature across interacting species. 2. Here, we used a broad-scale approach utilizing collection records to compare the temperature sensitivity of the timing of adult flight in butterflies vs. flowering of their potential nectar food plants (days per °C) across space and time in British Columbia, Canada. 3. On average, the phenology of both butterflies and plants advanced in response to warmer temperatures. However, the two taxa were differentially sensitive to temperature across space vs. across time, indicating the additional importance of nontemperature cues and/or local adaptation for many species. 4. Across butterfly-plant associations, flowering time was significantly more sensitive to temperature than the timing of butterfly flight and these sensitivities were not correlated. 5. Our results indicate that warming-driven shifts in the relative timing of life cycle events between butterflies and plants are likely to be prevalent, but that predicting the magnitude and direction of such changes in particular cases is going to require detailed, fine-scale data. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

A cicada that ensures its fitness during climate warming by synchronizing its hatching time with the rainy season.

PubMed

Moriyama, Minoru; Numata, Hideharu

2011-12-01

A shift in phenology due to climate change is associated with some recent changes in populations, as it can disrupt the synchrony between organisms' requirements and resource availability. This conceptual framework has been developed mostly in systems of trophic interactions. Many coincidental changes, however, are involved in trophic interactions, preventing us from describing the direct impact of phenological shifts on fitness consequences. Here we address the phenological relationship in a simple non-trophic interaction to document a causal process of a warming-driven fitness change in a cicada, Cryptotympana facialis, whose numbers increased dramatically in Osaka, Japan in the late 20th century. We show that synchrony of the rainy season and hatching time may have a substantial influence on hatching success, by 1) shifting the time of completion of embryonic development, and 2) supplying water at various intervals. We estimate the change in hatching time over the last eleven decades (1901-2009) based on meteorological records and the temperature-dependent rate of C. facialis embryogenesis. Our estimate shows that hatching had initially occurred after the rainy season, and that warming had advanced it into the rainy season in the late 20th century. The probability of hatching success was markedly variable, and often very low before this synchronization occurred, but became stably high thereafter. Our findings suggest that the stabilizing effect of this synchrony on fitness was indispensable to the recent population increase of C. facialis.

Intraspecific lineage divergence and its association with reproductive trait change during species range expansion in central Eurasian wild wheat Aegilops tauschii Coss. (Poaceae).

PubMed

Matsuoka, Yoshihiro; Takumi, Shigeo; Kawahara, Taihachi

2015-09-30

How species ranges form in landscapes is a matter of long-standing evolutionary interest. However, little is known about how natural phenotypic variations of ecologically important traits contribute to species range expansion. In this study, we examined the phylogeographic patterns of phenotypic changes in life history (seed production) and phenological (flowering time) traits during the range expansion of Aegilops tauschii Coss. from the Transcaucasus and Middle East to central Asia. Our comparative analyses of the patterns of natural variations for those traits and their association with the intraspecific lineage structure showed that (1) the eastward expansion to Asia was driven by an intraspecific sublineage (named TauL1b), (2) high seed production ability likely had an important role at the initial dispersal stage of TauL1b's expansion to Asia, and (3) the phenological change to early flowering phenotypes was one of the key adaptation events for TauL1b to further expand its range in Asia. This study provides for the first time a broad picture of the process of Ae. tauschii's eastward range expansion in which life history and phenological traits may have had respective roles in its dispersal and adaptation in Asia. The clear association of seed production and flowering time patterns with the intraspecific lineage divergence found in this study invites further genetic research to bring the mechanistic understanding of the changes in these key functional traits during range expansion within reach.

Modeling vertebrate diversity in Oregon using satellite imagery

NASA Astrophysics Data System (ADS)

Cablk, Mary Elizabeth

Vertebrate diversity was modeled for the state of Oregon using a parametric approach to regression tree analysis. This exploratory data analysis effectively modeled the non-linear relationships between vertebrate richness and phenology, terrain, and climate. Phenology was derived from time-series NOAA-AVHRR satellite imagery for the year 1992 using two methods: principal component analysis and derivation of EROS data center greenness metrics. These two measures of spatial and temporal vegetation condition incorporated the critical temporal element in this analysis. The first three principal components were shown to contain spatial and temporal information about the landscape and discriminated phenologically distinct regions in Oregon. Principal components 2 and 3, 6 greenness metrics, elevation, slope, aspect, annual precipitation, and annual seasonal temperature difference were investigated as correlates to amphibians, birds, all vertebrates, reptiles, and mammals. Variation explained for each regression tree by taxa were: amphibians (91%), birds (67%), all vertebrates (66%), reptiles (57%), and mammals (55%). Spatial statistics were used to quantify the pattern of each taxa and assess validity of resulting predictions from regression tree models. Regression tree analysis was relatively robust against spatial autocorrelation in the response data and graphical results indicated models were well fit to the data.

Trends in spring and autumn phenology over the Tibetan Plateau based on four NDVI datasets

NASA Astrophysics Data System (ADS)

Wang, X.; Xiao, J.; Li, X.; Cheng, G.; Ma, M.

2016-12-01

Vegetation phenology is a sensitive indicator of climate change, and has significant effects on ecosystem carbon uptake. As the Earth's "third pole", the Tibetan Plateau has witnessed rapid warming during the last several decades. The Tibetan Plateau is a unique region to study the trends in vegetation phenology in response to climate change because of the sensitivity of its ecosystems to climate and its low-level human disturbance. The trends in spring and autumn phenology over the plateau are highly controversial. In this study, we examine the trends in the start of growing season (SOS) and end of growing season (EOS) for alpine meadow and steppe using the GIMMS NDVI3g dataset (1982-2013), the GIMMS NDVI dataset (1982-2006), the MODIS NDVI dataset (2001-2013) and the SPOT Vegetation NDVI dataset (1999-2013). Both logistic and polynomial fitting models are used to estimate the SOS and EOS dates. The results are evaluated at four meadow/steppe phenology observation stations. The NDVI-derived SOS and EOS dates are systematically greater than the field-based SOS (emergence seedling date) and EOS (wilting date). There are large discrepancies in both spring and autumn phenology among the different NDVI datasets. For a given NDVI dataset, both SOS and EOS also exhibit significant differences between the two different approaches. Our results show that the trends in spring and autumn phenology over the Tibetan Plateau depend on both the NDVI dataset used and the method for retrieving the SOS and EOS dates. There is no consistent evidence that the "green-up" dates (SOS) has been advancing over the Tibetan Plateau during the last two decades.

Herbarium specimens can reveal impacts of climate change on plant phenology; a review of methods and applications.

PubMed

Jones, Casey A; Daehler, Curtis C

2018-01-01

Studies in plant phenology have provided some of the best evidence for large-scale responses to recent climate change. Over the last decade, more than thirty studies have used herbarium specimens to analyze changes in flowering phenology over time, although studies from tropical environments are thus far generally lacking. In this review, we summarize the approaches and applications used to date. Reproductive plant phenology has primarily been analyzed using two summary statistics, the mean flowering day of year and first-flowering day of year, but mean flowering day has proven to be a more robust statistic. Two types of regression models have been applied to test for associations between flowering, temperature and time: flowering day regressed on year and flowering day regressed on temperature. Most studies analyzed the effect of temperature by averaging temperatures from three months prior to the date of flowering. On average, published studies have used 55 herbarium specimens per species to characterize changes in phenology over time, but in many cases fewer specimens were used. Geospatial grid data are increasingly being used for determining average temperatures at herbarium specimen collection locations, allowing testing for finer scale correspondence between phenology and climate. Multiple studies have shown that inferences from herbarium specimen data are comparable to findings from systematically collected field observations. Understanding phenological responses to climate change is a crucial step towards recognizing implications for higher trophic levels and large-scale ecosystem processes. As herbaria are increasingly being digitized worldwide, more data are becoming available for future studies. As temperatures continue to rise globally, herbarium specimens are expected to become an increasingly important resource for analyzing plant responses to climate change.

Satellite time-series data for vegetation phenology detection and environmental assessment in Southeast Asia

NASA Astrophysics Data System (ADS)

Suepa, Tanita

The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability and internal climatic fluctuation. The EVI and phenological patterns varied spatially according to climate variations and human management. The overall regional mean EVI value in SEA from 2001 to 2010 has gradually decreased and phenological trends appeared to shift towards a later and slightly longer growing season. Regional vegetation dynamics over SEA exhibited patterns associated with major climate events such as El Nino in 2005. The rainy season tended to start early and end late and the length of rainy season was slightly longer. However, the amount of rainfall has decreased from 2001 to 2010. The relationship between phenology and rainfall varied among different ecosystems. Additionally, the local scale results indicated that rainfall is a dominant force of phenological changes in naturally vegetated areas and rainfed croplands, whereas human management is a key factor in heavily agricultural areas with irrigated systems. The results of estimating GHG emissions from rice fields in Thailand demonstrated that human management, climate variation, and physical geography had a significant influence on the change in GHG emissions. In addition, the complexity of spatio-temporal patterns in phenology and related variables were displayed on the visualization system with effective functions and an interactive interface. The information and knowledge in this research are useful for local and regional environmental management and for identifying mitigation strategies in the context of climate change and ecosystem dynamics in this region.

Monitoring vegetation phenology using MODIS

USGS Publications Warehouse

Zhang, Xiayong; Friedl, Mark A.; Schaaf, Crystal B.; Strahler, Alan H.; Hodges, John C.F.; Gao, Feng; Reed, Bradley C.; Huete, Alfredo

2003-01-01

Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success.

The effects of short- and long-term air pollutants on plant phenology and leaf characteristics.

PubMed

Jochner, Susanne; Markevych, Iana; Beck, Isabelle; Traidl-Hoffmann, Claudia; Heinrich, Joachim; Menzel, Annette

2015-11-01

Pollution adversely affects vegetation; however, its impact on phenology and leaf morphology is not satisfactorily understood yet. We analyzed associations between pollutants and phenological data of birch, hazel and horse chestnut in Munich (2010) along with the suitability of leaf morphological parameters of birch for monitoring air pollution using two datasets: cumulated atmospheric concentrations of nitrogen dioxide and ozone derived from passive sampling (short-term exposure) and pollutant information derived from Land Use Regression models (long-term exposure). Partial correlations and stepwise regressions revealed that increased ozone (birch, horse chestnut), NO2, NOx and PM levels (hazel) were significantly related to delays in phenology. Correlations were especially high when rural sites were excluded suggesting a better estimation of long-term within-city pollution. In situ measurements of foliar characteristics of birch were not suitable for bio-monitoring pollution. Inconsistencies between long- and short-term exposure effects suggest some caution when interpreting short-term data collected within field studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

A comprehensive data processing plan for crop calendar MSS signature development from satellite imagery: Crop identification using vegetation phenology

NASA Technical Reports Server (NTRS)

Hlavka, C. A. (Principal Investigator); Carlyle, S. M.; Haralick, R. M.; Yokoyama, R.

1978-01-01

The author has identified the following significant results. The phenological method of crop identification involves the creation of crop signatures which characterize multispectral observations as phenological growth states. The phenological signature models spectral reflectance explicitly as a function of crop maturity rather than as a function of date. A correspondence of time to growth state is established which minimizes the smallest difference between the given multispectral multitemporal vector and a category mean vector. The application of the method to the identification of winter wheat and corn shows (1) the method is capable of discriminating crop type with about the same degree of accuracy as more traditional classifiers; (2) the use of LANDSAT observations on two or more dates yields better results than the use of a single observation; and (3) some potential is demonstrated for labeling the degree of maturity of the crop, as well as the crop type.

Investigating the relationship between peat biogeochemistry and above-ground plant phenology with remote sensing along a gradient of permafrost thaw.

NASA Astrophysics Data System (ADS)

Garnello, A.; Dye, D. G.; Bogle, R.; Hough, M.; Raab, N.; Dominguez, S.; Rich, V. I.; Crill, P. M.; Saleska, S. R.

2016-12-01

Global climate models predict a 50% - 85% decrease in permafrost area in northern regions by 2100 due to increased temperature and precipitation variability, potentially releasing large stores of carbon as greenhouse gases (GHG) due to microbial activity. Linking belowground biogeochemical processes with observable above ground plant dynamics would greatly increase the ability to track and model GHG emissions from permafrost thaw, but current research has yet to satisfactorily develop this link. We hypothesized that seasonal patterns in peatland biogeochemistry manifests itself as observable plant phenology due to the tight coupling resulting from plant-microbial interactions. We tested this by using an automated, tower-based camera to acquire daily composite (red, green, blue) and near infrared (NIR) images of a thawing permafrost peatland site near Abisko, Sweden. The images encompassed a range of exposures which were merged into high-dynamic-range images, a novel application to remote sensing of plant phenology. The 2016 growing season camera images are accompanied by mid-to-late season CH4 and CO2 fluxes measured from soil collars, and by early-mid-late season peat core samples of the composition of microbial communities and key metabolic genes, and of the organic matter and trace gas composition of peat porewater. Additionally, nearby automated gas flux chambers measured sub-hourly fluxes of CO2 and CH4 from the peat, which will also be incorporated into analysis of relationships between seasonal camera-derived vegetation indices and gas fluxes from habitats with different vegetation types. While remote sensing is a proven method in observing plant phenology, this technology has yet to be combined with soil biogeochemical and microbial community data in regions of permafrost thaw. Establishing a high resolution phenology monitoring system linked to soil biogeochemical processes in subarctic peatlands will advance the understanding of how observable patterns in plant phenology can be used to monitor permafrost thaw and ecosystem carbon cycling.

Effects of climate change on phenology in two French LTER (Alps and Brittany) for the period 1998-2009

NASA Astrophysics Data System (ADS)

Perrimond, B.; Bigot, S.; Quénol, H.; Spielgelberger, T.; Baudry, J.

2012-04-01

Climate and vegetation are linked all over the world. In this study, we work on a seasonal weather classification based on air temperature and precipitation to deduce a link with different phenological stage (greening up, senescence, ...) over a 12 year period (1998-2009) for two different domains in France (Alps and Brittany). In temperate land, the main climatic variable with a potential effect on vegetation is the mean temperature followed by the rainfall deficit. A better understanding in season and their climatic characteristic is need to establish link between climate and phenology; so a weather classification is proposed based on empirical orthogonal functions and ascending hierarchical classification on atmospheric variables. This classification allows us to exhibit the inter-annual and intra-seasonal climatic spatiotemporal variability for both experimental site. Relationships between climate and phenology consist in a comparison between advance and delay in phenological stage and weather type issue from the classification. Experiment field are two french Long Term Ecological Research (LTER). The first one (LTER 'Alps' ) have mountain characteristics about 1000 to 4780 m ASL, ~65% of forest occupation ; the second one (LTER Armorique) is an Atlantic coastal landscape, 0-360 m ASL, ~70% of agricultural field. Climatic data are SAFRAN-France reanalysis which are developed to run SVAT model and come from the French meteorological service 'Météo-France'. All atmospheric variable needed to run a hydrological model are available (air temperature, rainfall/snowfall, wind speed, relative humidity, incoming/outcoming radiation) at a 8-8 km2 space resolution and with a daily time resolution. The phenological data are extracted from SPOT-VGT product 1-1 km2 space resolution and 10 days time resolution) by time series analysis process. Such of study is particularly important to understand relationships between environmental and ecological variables and it will allow to better predict ecological reaction under climate change constraint.

Delayed autumn phenology in the Northern Hemisphere is related to change in both climate and spring phenology.

PubMed

Liu, Qiang; Fu, Yongshuo H; Zhu, Zaichun; Liu, Yongwen; Liu, Zhuo; Huang, Mengtian; Janssens, Ivan A; Piao, Shilong

2016-11-01

The timing of the end of the vegetation growing season (EOS) plays a key role in terrestrial ecosystem carbon and nutrient cycles. Autumn phenology is, however, still poorly understood, and previous studies generally focused on few species or were very limited in scale. In this study, we applied four methods to extract EOS dates from NDVI records between 1982 and 2011 for the Northern Hemisphere, and determined the temporal correlations between EOS and environmental factors (i.e., temperature, precipitation and insolation), as well as the correlation between spring and autumn phenology, using partial correlation analyses. Overall, we observed a trend toward later EOS in ~70% of the pixels in Northern Hemisphere, with a mean rate of 0.18 ± 0.38 days yr -1 . Warming preseason temperature was positively associated with the rate of EOS in most of our study area, except for arid/semi-arid regions, where the precipitation sum played a dominant positive role. Interestingly, increased preseason insolation sum might also lead to a later date of EOS. In addition to the climatic effects on EOS, we found an influence of spring vegetation green-up dates on EOS, albeit biome dependent. Our study, therefore, suggests that both environmental factors and spring phenology should be included in the modeling of EOS to improve the predictions of autumn phenology as well as our understanding of the global carbon and nutrient balances. © 2016 John Wiley & Sons Ltd.

Delayed autumn phenology in the Northern Hemisphere is related to change in both climate and spring phenology

NASA Astrophysics Data System (ADS)

Liu, Qiang; Fu, Yongshuo H.; Zhu, Zaichun; Liu, Yongwen; Liu, Zhuo; Huang, Mengtian; Janssens, Ivan A.; Piao, Shilong

2017-04-01

The timing of the end of the vegetation growing season (EOS) plays a key role in terrestrial ecosystem carbon and nutrient cycles. Autumn phenology is, however, still poorly understood and previous studies generally focused on few species or were very limited in scale. In this study, we applied four methods to extract EOS dates from NDVI records between 1982 and 2011 for the northern hemisphere, and determined the temporal correlations between EOS and environmental factors (i.e. temperature, precipitation and insolation), as well as the correlation between spring and autumn phenology, using partial correlation analyses. Overall, we observed trend towards later EOS in 70% of the pixels in Northern Hemisphere, with a mean rate of 0.18 ± 0.38 days per year. Warming preseason temperature was positively associated with the rate of EOS in most of our study area, except for arid/semi-arid regions, where the precipitation sum played a dominant positive role. Interestingly, increased preseason insolation sum might also lead to a later date of EOS. In addition to the climatic effects on EOS, we found an influence of spring vegetation green-up dates (SOS) on EOS, albeit biome dependent. Our study, therefore, suggests that both environmental factors and spring phenology should be included in the modeling of EOS to improve the predictions of autumn phenology as well as our understanding of the global carbon and nutrient balances.

Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape.

PubMed

Naithani, Kusum J; Baldwin, Doug C; Gaines, Katie P; Lin, Henry; Eissenstat, David M

2013-01-01

Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L) and volumetric soil water content (θ) on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests.

Phenologically-tuned MODIS NDVI-based production anomaly estimates for Zimbabwe

USGS Publications Warehouse

Funk, Chris; Budde, Michael E.

2009-01-01

For thirty years, simple crop water balance models have been used by the early warning community to monitor agricultural drought. These models estimate and accumulate actual crop evapotranspiration, evaluating environmental conditions based on crop water requirements. Unlike seasonal rainfall totals, these models take into account the phenology of the crop, emphasizing conditions during the peak grain filling phase of crop growth. In this paper we describe an analogous metric of crop performance based on time series of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) imagery. A special temporal filter is used to screen for cloud contamination. Regional NDVI time series are then composited for cultivated areas, and adjusted temporally according to the timing of the rainy season. This adjustment standardizes the NDVI response vis-??-vis the expected phenological response of maize. A national time series index is then created by taking the cropped-area weighted average of the regional series. This national time series provides an effective summary of vegetation response in agricultural areas, and allows for the identification of NDVI green-up during grain filling. Onset-adjusted NDVI values following the grain filling period are well correlated with U.S. Department of Agriculture production figures, possess desirable linear characteristics, and perform better than more common indices such as maximum seasonal NDVI or seasonally averaged NDVI. Thus, just as appropriately calibrated crop water balance models can provide more information than seasonal rainfall totals, the appropriate agro-phenological filtering of NDVI can improve the utility and accuracy of space-based agricultural monitoring.

Remote sensing of land surface phenology

USGS Publications Warehouse

Meier, G.A.; Brown, Jesslyn F.

2014-01-01

Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

Mast fruiting of large ectomycorrhizal African rain forest trees: importance of dry season intensity, and the resource-limitation hypothesis.

PubMed

Newbery, David M; Chuyong, George B; Zimmermann, Lukas

2006-01-01

Mast fruiting is a distinctive reproductive trait in trees. This rain forest study, at a nutrient-poor site with a seasonal climate in tropical Africa, provides new insights into the causes of this mode of phenological patterning. At Korup, Cameroon, 150 trees of the large, ectomycorrhizal caesalp, Microberlinia bisulcata, were recorded almost monthly for leafing, flowering and fruiting during 1995-2000. The series was extended to 1988-2004 with less detailed data. Individual transitions in phenology were analysed. Masting occurred when the dry season before fruiting was drier, and the one before that was wetter, than average. Intervals between events were usually 2 or 3 yr. Masting was associated with early leaf exchange, followed by mass flowering, and was highly synchronous in the population. Trees at higher elevation showed more fruiting. Output declined between 1995 and 2000. Mast fruiting in M. bisulcata appears to be driven by climate variation and is regulated by internal tree processes. The resource-limitation hypothesis was supported. An 'alternative bearing' system seems to underlie masting. That ectomycorrhizal habit facilitates masting in trees is strongly implied.

Modeling landscape evapotranspiration by integrating land surface phenology and a water balance algorithm

USGS Publications Warehouse

Senay, Gabriel B.

2008-01-01

The main objective of this study is to present an improved modeling technique called Vegetation ET (VegET) that integrates commonly used water balance algorithms with remotely sensed Land Surface Phenology (LSP) parameter to conduct operational vegetation water balance modeling of rainfed systems at the LSP’s spatial scale using readily available global data sets. Evaluation of the VegET model was conducted using Flux Tower data and two-year simulation for the conterminous US. The VegET model is capable of estimating actual evapotranspiration (ETa) of rainfed crops and other vegetation types at the spatial resolution of the LSP on a daily basis, replacing the need to estimate crop- and region-specific crop coefficients.

Simulating phenological shifts in French temperate forests under two climatic change scenarios and four driving global circulation models

NASA Astrophysics Data System (ADS)

Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin

2010-09-01

After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.

Simulating phenological shifts in French temperate forests under two climatic change scenarios and four driving global circulation models.

PubMed

Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin

2010-09-01

After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.

Examining wildlife responses to phenology and wildfire using a landscape-scale camera trap network

USGS Publications Warehouse

Villarreal, Miguel L.; Gass, Leila; Norman, Laura; Sankeya, Joel B.; Wallace, Cynthia S.A.; McMacken, Dennis; Childs, Jack L.; Petrakis, Roy E.

2012-01-01

Between 2001 and 2009, the Borderlands Jaguar Detection Project deployed 174 camera traps in the mountains of southern Arizona to record jaguar activity. In addition to jaguars, the motion-activated cameras, placed along known wildlife travel routes, recorded occurrences of ~ 20 other animal species. We examined temporal relationships of white-tailed deer (Odocoileus virginianus) and javelina (Pecari tajacu) to landscape phenology (as measured by monthly Normalized Difference Vegetation Index data) and the timing of wildfire (Alambre Fire of 2007). Mixed model analyses suggest that temporal dynamics of these two species were related to vegetation phenology and natural disturbance in the Sky Island region, information important for wildlife managers faced with uncertainty regarding changing climate and disturbance regimes.

Potential and limitations of using digital repeat photography to track structural and physiological phenology in Mediterranean tree-grass ecosystems

NASA Astrophysics Data System (ADS)

Luo, Yunpeng; EI-Madany, Tarek; Filippa, Gianluca; Carrara, Arnaud; Cremonese, Edoardo; Galvagno, Marta; Hammer, Tiana; Pérez-Priego, Oscar; Reichstein, Markus; Martín Isabel, Pilar; González Cascón, Rosario; Migliavacca, Mirco

2017-04-01

Tree-Grass ecosystems are global widely distributed (16-35% of the land surface). However, its phenology (especially in water-limited areas) has not yet been well characterized and modeled. By using commercial digital cameras, continuous and relatively vast phenology data becomes available, which provides a good opportunity to monitor and develop a robust method used to extract the important phenological events (phenophases). Here we aimed to assess the usability of digital repeat photography for three Tree-Grass Mediterranean ecosystems over two different growing seasons (Majadas del Tietar, Spain) to extract critical phenophases for grass and evergreen broadleaved trees (autumn regreening of grass- Start of growing season; resprouting of tree leaves; senescence of grass - End of growing season), assess their uncertainty, and to correlate them with physiological phenology (i.e. phenology of ecosystem scale fluxes such as Gross Primary Productivity, GPP). We extracted green chromatic coordinates (GCC) and camera based normalized difference vegetation index (Camera-NDVI) from an infrared enabled digital camera using the "Phenopix" R package. Then we developed a novel method to retrieve important phenophases from GCC and Camera-NDVI from various region of interests (ROIs) of the imagery (tree areas, grass, and both - ecosystem) as well as from GPP, which was derived from Eddy Covariance tower in the same experimental site. The results show that, at ecosystem level, phenophases derived from GCC and Camera-NDVI are strongly correlated (R2 = 0.979). Remarkably, we observed that at the end of growing season phenophases derived from GCC were systematically advanced (ca. 8 days) than phenophase from Camera-NDVI. By using the radiative transfer model Soil Canopy Observation Photochemistry and Energy (SCOPE) we demonstrated that this delay is related to the different sensitivity of GCC and NDVI to the fraction of green/dry grass in the canopy, resulting in a systematic higher NDVI during the dry-down of the canopy. Phenophases derived from GCC and Camera-NDVI are correlated with phenophase extracted from GPP across sites and years (R2 =0.966 and 0.976 respectively). For the start of growing season the determination coefficient was higher (R2 =0.89 and 0.98 for GCC vs GPP and Camera-NDVI vs GPP, respectively) than for the end of growing season (R2 =0.75 and 0.70, for GCC and Camera-NDVI, respectively). The statistics obtained using phenophases derived from grass or ecosystem ROI are similar. In contrast, GCC and Camera-NDVI derived from trees ROI are relatively constant and not related to the seasonality of GPP. However, the GCC of tree shows a characteristic peak that is synchronous to leaf flushing in spring assessed using regular Chlorophyll content measurements and automatic dendrometers. Concluding, we first developed a method to derive phenological events of Tree-Grass ecosystems using digital repeat photography, second we demonstrated that the phenology of GPP is strongly dominated by the phenology of grassland layer, third we discussed the uncertainty related to the use of GCC and Camera-NDVI in senescence, and finally we demonstrate the capability of GCC to track in evergreen broadleaved forest crucial phenological events. Our findings confirm digital repeat photography is a vital data source for characterizing phenology in Mediterranean Tree-Grass Ecosystem.

Insect herbivory in a mature Eucalyptus woodland canopy depends on leaf phenology but not CO2 enrichment.

PubMed

Gherlenda, Andrew N; Moore, Ben D; Haigh, Anthony M; Johnson, Scott N; Riegler, Markus

2016-10-19

Climate change factors such as elevated atmospheric carbon dioxide concentrations (e[CO 2 ]) and altered rainfall patterns can alter leaf composition and phenology. This may subsequently impact insect herbivory. In sclerophyllous forests insects have developed strategies, such as preferentially feeding on new leaf growth, to overcome physical or foliar nitrogen constraints, and this may shift under climate change. Few studies of insect herbivory at elevated [CO 2 ] have occurred under field conditions and none on mature evergreen trees in a naturally established forest, yet estimates for leaf area loss due to herbivory are required in order to allow accurate predictions of plant productivity in future climates. Here, we assessed herbivory in the upper canopy of mature Eucalyptus tereticornis trees at the nutrient-limited Eucalyptus free-air CO 2 enrichment (EucFACE) experiment during the first 19 months of CO 2 enrichment. The assessment of herbivory extended over two consecutive spring-summer periods, with a first survey during four months of the [CO 2 ] ramp-up phase after which full [CO 2 ] operation was maintained, followed by a second survey period from months 13 to 19. Throughout the first 2 years of EucFACE, young, expanding leaves sustained significantly greater damage from insect herbivory (between 25 and 32 % leaf area loss) compared to old or fully expanded leaves (less than 2 % leaf area loss). This preference of insect herbivores for young expanding leaves combined with discontinuous production of new foliage, which occurred in response to rainfall, resulted in monthly variations in leaf herbivory. In contrast to the significant effects of rainfall-driven leaf phenology, elevated [CO 2 ] had no effect on leaf consumption or preference of insect herbivores for different leaf age classes. In the studied nutrient-limited natural Eucalyptus woodland, herbivory contributes to a significant loss of young foliage. Leaf phenology is a significant factor that determines the level of herbivory experienced in this evergreen sclerophyllous woodland system, and may therefore also influence the population dynamics of insect herbivores. Furthermore, leaf phenology appears more strongly impacted by rainfall patterns than by e[CO 2 ]. e[CO 2 ] responses of herbivores on mature trees may only become apparent after extensive CO 2 fumigation periods.

Physiological time model for predicting adult emergence of western corn rootworm (Coleoptera: Chrysomelidae) in the Texas High Plains.

PubMed

Stevenson, Douglass E; Michels, Gerald J; Bible, John B; Jackman, John A; Harris, Marvin K

2008-10-01

Field observations at three locations in the Texas High Plains were used to develop and validate a degree-day phenology model to predict the onset and proportional emergence of adult Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae) adults. Climatic data from the Texas High Plains Potential Evapotranspiration network were used with records of cumulative proportional adult emergence to determine the functional lower developmental temperature, optimum starting date, and the sum of degree-days for phenological events from onset to 99% adult emergence. The model base temperature, 10 degrees C (50 degrees F), corresponds closely to known physiological lower limits for development. The model uses a modified Gompertz equation, y = 96.5 x exp (-(exp(6.0 - 0.00404 x (x - 4.0), where x is cumulative heat (degree-days), to predict y, cumulative proportional emergence expressed as a percentage. The model starts degree-day accumulation on the date of corn, Zea mays L., emergence, and predictions correspond closely to corn phenological stages from tasseling to black layer development. Validation shows the model predicts cumulative proportional adult emergence within a satisfactory interval of 4.5 d. The model is flexible enough to accommodate early planting, late emergence, and the effects of drought and heat stress. The model provides corn producers ample lead time to anticipate and implement adult control practices.

GIS, geostatistics, metadata banking, and tree-based models for data analysis and mapping in environmental monitoring and epidemiology.

PubMed

Schröder, Winfried

2006-05-01

By the example of environmental monitoring, some applications of geographic information systems (GIS), geostatistics, metadata banking, and Classification and Regression Trees (CART) are presented. These tools are recommended for mapping statistically estimated hot spots of vectors and pathogens. GIS were introduced as tools for spatially modelling the real world. The modelling can be done by mapping objects according to the spatial information content of data. Additionally, this can be supported by geostatistical and multivariate statistical modelling. This is demonstrated by the example of modelling marine habitats of benthic communities and of terrestrial ecoregions. Such ecoregionalisations may be used to predict phenomena based on the statistical relation between measurements of an interesting phenomenon such as, e.g., the incidence of medically relevant species and correlated characteristics of the ecoregions. The combination of meteorological data and data on plant phenology can enhance the spatial resolution of the information on climate change. To this end, meteorological and phenological data have to be correlated. To enable this, both data sets which are from disparate monitoring networks have to be spatially connected by means of geostatistical estimation. This is demonstrated by the example of transformation of site-specific data on plant phenology into surface data. The analysis allows for spatial comparison of the phenology during the two periods 1961-1990 and 1991-2002 covering whole Germany. The changes in both plant phenology and air temperature were proved to be statistically significant. Thus, they can be combined by GIS overlay technique to enhance the spatial resolution of the information on the climate change and use them for the prediction of vector incidences at the regional scale. The localisation of such risk hot spots can be done by geometrically merging surface data on promoting factors. This is demonstrated by the example of the transfer of heavy metals through soils. The predicted hot spots of heavy metal transfer can be validated empirically by measurement data which can be inquired by a metadata base linked with a geographic information system. A corresponding strategy for the detection of vector hot spots in medical epidemiology is recommended. Data on incidences and habitats of the Anophelinae in the marsh regions of Lower Saxony (Germany) were used to calculate a habitat model by CART, which together with climate data and data on ecoregions can be further used for the prediction of habitats of medically relevant vector species. In the future, this approach should be supported by an internet-based information system consisting of three components: metadata questionnaire, metadata base, and GIS to link metadata, surface data, and measurement data on incidences and habitats of medically relevant species and related data on climate, phenology, and ecoregional characteristic conditions.

Geographic mosaics of species' association: a definition and an example driven by plant-insect phenological synchrony.

PubMed

Singer, Michael C; McBride, Carolyn S

2012-12-01

Spatial mosaics occur in both evolutionary and ecological properties of species' interactions. Studies of these patterns have facilitated description and prediction of evolutionary responses of interacting species to each other and to changing environments. We propose seeking complementary understanding of community assembly and dynamics by studying ecological and mechanistic properties of mosaics. We define "species' association mosaics" as deviations from a null model in which spatial variation in the extent to which particular species interact ecologically is explained solely by variation in their densities. In extreme deviations from the null, a focal species interacts exclusively with different partners at different sites despite similar abundances of potential partners. We investigate this type of mosaic involving the butterfly Euphydryas editha and its hosts, the perennial Pedicularis semibarbata (Psem) and the ephemeral annual Collinsia torreyi (Ctor). A reciprocal transplant experiment showed that the proximate, mechanistic driver of the mosaic was variation in butterfly oviposition preference: the identity of the preferred host species depended on the site of origin of the insects, not that of the plants. In contrast, the evolutionary driver was phenological asynchrony between the insects and Ctor. Censuses showed that larvae hatching from eggs laid on Ctor would have suffered significantly greater mortality from host senescence at five sites where Ctor was avoided than at two sites where it was used. These differences among sites in phenological synchrony were caused by variation in life span of Ctor. At sites where Ctor was avoided, natural selection on host preference was stabilizing because Ctor life span was too short to accommodate the development time of most larvae. At sites where Ctor was used, selection on preference was also stabilizing because larvae lacked physiological adaptation to feed on Psem. These reciprocal forces of stabilizing selection formed a mosaic maintaining spatial variation in insect host preference that was the proximate cause of the species-association mosaic. In the Discussion, we examine the extent to which our findings hindcast an observed anthropogenic host shift by E. editha from Psem to Ctor. This example shows that elucidation of species-association mosaics can facilitate understanding of community evolution and dynamics.

Linking Land Surface Phenology and Growth Limiting Factor Shifts over the Past 30 Years

NASA Astrophysics Data System (ADS)

Garonna, I.; Schenkel, D.; de Jong, R.; Schaepman, M. E.

2015-12-01

The study of global vegetation dynamics contributes to a better understanding of global change drivers and how these affect ecosystems and ecological diversity. Land-surface phenology (LSP) is a key response and feedback of vegetation to the climate system, and hence a parameter that needs to be accurately represented in terrestrial biosphere models [1]. However, the effects of climatic changes on LSP depend on the relative importance of climatic constraints in specific regions - which are not well understood at global scale. In this study, we analyzed a Phenology Reanalysis dataset [2] to evaluate shifts in three climatic drivers of phenology at global scale and over the last 30 years (1982-2012): incoming radiation, evaporative demand and minimum temperature. As a first step, we compared LAI as modeled from these three factors (LAIre) to remotely sensed observations of LSP (LAI3g, [3]) over the same time period. As a second step, we examined temporal trends in the climatic constraints at Start- and End- of the Growing Season. There was good agreement between phenology metrics as derived form LAI3g and LAIre over the last 30 years - thus providing confidence in the climatic constraints underlying the modeled data. Our analysis reveals inter-annual variation in the relative importance of the three climatic factors in limiting vegetation growth at Start- and End- of the Growing Season over the last 30 years. High northern latitudes, as well as northern Europe and central Asia, appear to have undergone significant changes in dominance between the three controls. We also find that evaporative demand has become increasingly limiting for growth in many parts of the world, in particular in South America and eastern Asia. [1] Richardson, A.D. et al. Global Change Biology 18, 566-584 (2012). [2] Stöckli, R. et al. J. Geophys. Res 116, G03020 (2011). [3] Zhu, Z. et al. Remote Sensing 5, 927-948 (2013).

Space-based Ornithology-Studying Bird Migration and Environmental Change in North America

NASA Technical Reports Server (NTRS)

Smith, James; Deppe, Jill

2008-01-01

Natural fluctuations in the availability of critical stopover sites coupled with anthropogenic destruction of wetlands, land-use change, and anticipated losses due to climate change present migratory birds with a formidable challenge. We have developed an individual-based, spatially explicit bird migration model that simulates the migration routes, timing and energy budgets of individual birds under dynamic weather and land surface conditions. Our model incorporates biophysical constraints, individual bird energy status, bird behavior, and flight aerodynamics. We model the speed, direction, and timing of individual birds moving through a user specified Lagrangian grid. The model incorporates environmental properties including wind speed and direction, topography, dynamic hydrologic properties of the landscape, and environmental suitability. The model is driven by important variables estimated from satellite observations of the land surface, by data assimilation products from weather and climate models, and biological field data. We illustrate the use of the model to study the impact of both short- and long-term environmental variatios, e.g. climate, drought, anthropogenic, on migration timing (phenology), spatial pattern, and fitness (survival and reproductive success). We present several theoretical simulations of the spring migration of Pectoral Sandpiper (Calidris melanotos) in North America with emphasis on the Central flyway from the Gulf of Mexico to Alaska.

Land surface phenology of Northeast China during 2000-2015: temporal changes and relationships with climate changes.

PubMed

Zhang, Yue; Li, Lin; Wang, Hongbin; Zhang, Yao; Wang, Naijia; Chen, Junpeng

2017-10-01

As an important crop growing area, Northeast China (NEC) plays a vital role in China's food security, which has been severely affected by climate change in recent years. Vegetation phenology in this region is sensitive to climate change, and currently, the relationship between the phenology of NEC and climate change remains unclear. In this study, we used a satellite-derived normalized difference vegetation index (NDVI) to obtain the temporal patterns of the land surface phenology in NEC from 2000 to 2015 and validated the results using ground phenology observations. We then explored the relationships among land surface phenology, temperature, precipitation, and sunshine hours for relevant periods. Our results showed that the NEC experienced great phenological changes in terms of spatial heterogeneity during 2000-2015. The spatial patterns of land surface phenology mainly changed with altitude and land cover type. In most regions of NEC, the start date of land surface phenology had advanced by approximately 1.0 days year -1 , and the length of land surface phenology had been prolonged by approximately 1.0 days year -1 except for the needle-leaf and cropland areas, due to the warm conditions. We found that a distinct inter-annual variation in land surface phenology related to climate variables, even if some areas presented non-significant trends. Land surface phenology was coupled with climate variables and distinct responses at different combinations of temperature, precipitation, sunshine hours, altitude, and anthropogenic influence. These findings suggest that remote sensing and our phenology extracting methods hold great potential for helping to understand how land surface phenology is sensitive to global climate change.

Reproductive phenology of coastal plain Atlantic forest vegetation: comparisons from seashore to foothills.

PubMed

Staggemeier, Vanessa Graziele; Morellato, Leonor Patrícia Cerdeira

2011-11-01

The diversity of tropical forest plant phenology has called the attention of researchers for a long time. We continue investigating the factors that drive phenological diversity on a wide scale, but we are unaware of the variation of plant reproductive phenology at a fine spatial scale despite the high spatial variation in species composition and abundance in tropical rainforests. We addressed fine scale variability by investigating the reproductive phenology of three contiguous vegetations across the Atlantic rainforest coastal plain in Southeastern Brazil. We asked whether the vegetations differed in composition and abundance of species, the microenvironmental conditions and the reproductive phenology, and how their phenology is related to regional and local microenvironmental factors. The study was conducted from September 2007 to August 2009 at three contiguous sites: (1) seashore dominated by scrub vegetation, (2) intermediary covered by restinga forest and (3) foothills covered by restinga pre-montane transitional forest. We conducted the microenvironmental, plant and phenological survey within 30 transects of 25 m × 4 m (10 per site). We detected significant differences in floristic, microenvironment and reproductive phenology among the three vegetations. The microenvironment determines the spatial diversity observed in the structure and composition of the flora, which in turn determines the distinctive flowering and fruiting peaks of each vegetation (phenological diversity). There was an exchange of species providing flowers and fruits across the vegetation complex. We conclude that plant reproductive patterns as described in most phenological studies (without concern about the microenvironmental variation) may conceal the fine scale temporal phenological diversity of highly diverse tropical vegetation. This phenological diversity should be taken into account when generating sensor-derived phenologies and when trying to understand tropical vegetation responses to environmental changes.

USA National Phenology Network’s volunteer-contributed observations yield predictive models of phenological transitions

PubMed Central

Crimmins, Michael A.; Gerst, Katharine L.; Rosemartin, Alyssa H.; Weltzin, Jake F.

2017-01-01

Purpose In support of science and society, the USA National Phenology Network (USA-NPN) maintains a rapidly growing, continental-scale, species-rich dataset of plant and animal phenology observations that with over 10 million records is the largest such database in the United States. The aim of this study was to explore the potential that exists in the broad and rich volunteer-collected dataset maintained by the USA-NPN for constructing models predicting the timing of phenological transition across species’ ranges within the continental United States. Contributed voluntarily by professional and citizen scientists, these opportunistically collected observations are characterized by spatial clustering, inconsistent spatial and temporal sampling, and short temporal depth (2009-present). Whether data exhibiting such limitations can be used to develop predictive models appropriate for use across large geographic regions has not yet been explored. Methods We constructed predictive models for phenophases that are the most abundant in the database and also relevant to management applications for all species with available data, regardless of plant growth habit, location, geographic extent, or temporal depth of the observations. We implemented a very basic model formulation—thermal time models with a fixed start date. Results Sufficient data were available to construct 107 individual species × phenophase models. Remarkably, given the limited temporal depth of this dataset and the simple modeling approach used, fifteen of these models (14%) met our criteria for model fit and error. The majority of these models represented the “breaking leaf buds” and “leaves” phenophases and represented shrub or tree growth forms. Accumulated growing degree day (GDD) thresholds that emerged ranged from 454 GDDs (Amelanchier canadensis-breaking leaf buds) to 1,300 GDDs (Prunus serotina-open flowers). Such candidate thermal time thresholds can be used to produce real-time and short-term forecast maps of the timing of these phenophase transition. In addition, many of the candidate models that emerged were suitable for use across the majority of the species’ geographic ranges. Real-time and forecast maps of phenophase transitions could support a wide range of natural resource management applications, including invasive plant management, issuing asthma and allergy alerts, and anticipating frost damage for crops in vulnerable states. Implications Our finding that several viable thermal time threshold models that work across the majority of the species ranges could be constructed from the USA-NPN database provides clear evidence that great potential exists this dataset to develop more enhanced predictive models for additional species and phenophases. Further, the candidate models that emerged have immediate utility for supporting a wide range of management applications. PMID:28829783

Genetic Architecture of Flowering Phenology in Cereals and Opportunities for Crop Improvement

PubMed Central

Hill, Camilla B.; Li, Chengdao

2016-01-01

Cereal crop species including bread wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), rice (Oryza sativa L.), and maize (Zea mays L.) provide the bulk of human nutrition and agricultural products for industrial use. These four cereals are central to meet future demands of food supply for an increasing world population under a changing climate. A prerequisite for cereal crop production is the transition from vegetative to reproductive and grain-filling phases starting with flower initiation, a key developmental switch tightly regulated in all flowering plants. Although studies in the dicotyledonous model plant Arabidopsis thaliana build the foundations of our current understanding of plant phenology genes and regulation, the availability of genome assemblies with high-confidence sequences for rice, maize, and more recently bread wheat and barley, now allow the identification of phenology-associated gene orthologs in monocots. Together with recent advances in next-generation sequencing technologies, QTL analysis, mutagenesis, complementation analysis, and RNA interference, many phenology genes have been functionally characterized in cereal crops and conserved as well as functionally divergent genes involved in flowering were found. Epigenetic and other molecular regulatory mechanisms that respond to environmental and endogenous triggers create an enormous plasticity in flowering behavior among cereal crops to ensure flowering is only induced under optimal conditions. In this review, we provide a summary of recent discoveries of flowering time regulators with an emphasis on four cereal crop species (bread wheat, barley, rice, and maize), in particular, crop-specific regulatory mechanisms and genes. In addition, pleiotropic effects on agronomically important traits such as grain yield, impact on adaptation to new growing environments and conditions, genetic sequence-based selection and targeted manipulation of phenology genes, as well as crop growth simulation models for predictive crop breeding, are discussed. PMID:28066466

Estimating unbiased phenological trends by adapting site-occupancy models.

PubMed

Roth, Tobias; Strebel, Nicolas; Amrhein, Valentin

2014-08-01

As a response to climate warming, many animals and plants have been found to shift phenologies, such as appearance in spring or timing of reproduction. However, traditional measures for shifts in phenology that are based on observational data likely are biased due to a large influence of population size, observational effort, starting date of a survey, or other causes that may affect the probability of detecting a species. Understanding phenological responses of species to climate change, however, requires a robust measure that could be compared among studies and study years. Here, we developed a new method for estimating arrival and departure dates based on site-occupancy models. Using simulated data, we show that our method provided virtually unbiased estimates of phenological events even if detection probability or the number of sites occupied by the species is changing over time. To illustrate the flexibility of our method, we analyzed spring arrival of two long-distance migrant songbirds and the length of the flight period of two butterfly species, using data from a long-term biodiversity monitoring program in Switzerland. In contrast to many birds that migrate short distances, the two long-distance migrant songbirds tended to postpone average spring arrival by -0.5 days per year between 1995 and 2012. Furthermore, the flight period of the short-distance-flying butterfly species apparently became even shorter over the study period, while the flight period of the longer-distance-flying butterfly species remained relatively stable. Our method could be applied to temporally and spatially extensive data from a wide range of monitoring programs and citizen science projects, to help unravel how species and communities respond to global warming.

Leaf phenology as one important driver of seasonal changes in isoprene emission in central Amazonia

DOE PAGES

Alves, Eliane G.; Tota, Julio; Turnipseed, Andrew; ...

2018-03-06

Isoprene fluxes vary seasonally with changes in environmental factors (e.g., solar radiation and temperature) and biological factors (e.g., leaf phenology). However, our understanding of seasonal patterns of isoprene fluxes and associated mechanistic controls are still limited, especially in Amazonian evergreen forests. Here in this article, we aim to connect intensive, field-based measurements of canopy isoprene flux over a central Amazonian evergreen forest with meteorological observations and with tower-camera leaf phenology to improve understanding of patterns and causes of isoprene flux seasonality. Our results demonstrate that the highest isoprene emissions are observed during the dry and dry-to-wet transition seasons, whereas themore » lowest emissions were found during the wet-to-dry transition season. Our results also indicate that light and temperature can not totally explain the isoprene flux seasonality. Instead, the camera-derived leaf area index (LAI) of recently mature leaf-age class (e.g. leaf ages of 3–5 months) exhibits the highest correlation with observed isoprene flux seasonality (R 2=0.59, p<0.05). Attempting to better represent leaf phenology in the Model of Emissions of Gases and Aerosols from Nature (MEGAN 2.1), we improved the leaf age algorithm utilizing results from the camera-derived leaf phenology that provided LAI categorized in three different leaf ages. The model results show that the observations of age-dependent isoprene emission capacity, in conjunction with camera-derived leaf age demography, significantly improved simulations in terms of seasonal variations of isoprene fluxes (R 2=0.52, p<0.05). This study highlights the importance of accounting for differences in isoprene emission capacity across canopy leaf age classes and of identifying forest adaptive mechanisms that underlie seasonal variation of isoprene emissions in Amazonia.« less

Leaf phenology as one important driver of seasonal changes in isoprene emission in central Amazonia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alves, Eliane G.; Tota, Julio; Turnipseed, Andrew

Isoprene fluxes vary seasonally with changes in environmental factors (e.g., solar radiation and temperature) and biological factors (e.g., leaf phenology). However, our understanding of seasonal patterns of isoprene fluxes and associated mechanistic controls are still limited, especially in Amazonian evergreen forests. Here in this article, we aim to connect intensive, field-based measurements of canopy isoprene flux over a central Amazonian evergreen forest with meteorological observations and with tower-camera leaf phenology to improve understanding of patterns and causes of isoprene flux seasonality. Our results demonstrate that the highest isoprene emissions are observed during the dry and dry-to-wet transition seasons, whereas themore » lowest emissions were found during the wet-to-dry transition season. Our results also indicate that light and temperature can not totally explain the isoprene flux seasonality. Instead, the camera-derived leaf area index (LAI) of recently mature leaf-age class (e.g. leaf ages of 3–5 months) exhibits the highest correlation with observed isoprene flux seasonality (R 2=0.59, p<0.05). Attempting to better represent leaf phenology in the Model of Emissions of Gases and Aerosols from Nature (MEGAN 2.1), we improved the leaf age algorithm utilizing results from the camera-derived leaf phenology that provided LAI categorized in three different leaf ages. The model results show that the observations of age-dependent isoprene emission capacity, in conjunction with camera-derived leaf age demography, significantly improved simulations in terms of seasonal variations of isoprene fluxes (R 2=0.52, p<0.05). This study highlights the importance of accounting for differences in isoprene emission capacity across canopy leaf age classes and of identifying forest adaptive mechanisms that underlie seasonal variation of isoprene emissions in Amazonia.« less

New perspective on spring vegetation phenology and global climate change based on Tibetan Plateau tree-ring data

PubMed Central

Yang, Bao; He, Minhui; Shishov, Vladimir; Tychkov, Ivan; Vaganov, Eugene; Rossi, Sergio; Ljungqvist, Fredrik Charpentier; Bräuning, Achim; Grießinger, Jussi

2017-01-01

Phenological responses of vegetation to climate, in particular to the ongoing warming trend, have received much attention. However, divergent results from the analyses of remote sensing data have been obtained for the Tibetan Plateau (TP), the world’s largest high-elevation region. This study provides a perspective on vegetation phenology shifts during 1960–2014, gained using an innovative approach based on a well-validated, process-based, tree-ring growth model that is independent of temporal changes in technical properties and image quality of remote sensing products. Twenty composite site chronologies were analyzed, comprising about 3,000 trees from forested areas across the TP. We found that the start of the growing season (SOS) has advanced, on average, by 0.28 d/y over the period 1960–2014. The end of the growing season (EOS) has been delayed, by an estimated 0.33 d/y during 1982–2014. No significant changes in SOS or EOS were observed during 1960–1981. April–June and August–September minimum temperatures are the main climatic drivers for SOS and EOS, respectively. An increase of 1 °C in April–June minimum temperature shifted the dates of xylem phenology by 6 to 7 d, lengthening the period of tree-ring formation. This study extends the chronology of TP phenology farther back in time and reconciles the disparate views on SOS derived from remote sensing data. Scaling up this analysis may improve understanding of climate change effects and related phenological and plant productivity on a global scale. PMID:28630302

Chilling and heat requirements for leaf unfolding in European beech and sessile oak populations at the southern limit of their distribution range.

PubMed

Dantec, Cécile F; Vitasse, Yann; Bonhomme, Marc; Louvet, Jean-Marc; Kremer, Antoine; Delzon, Sylvain

2014-11-01

With global warming, an advance in spring leaf phenology has been reported worldwide. However, it is difficult to forecast phenology for a given species, due to a lack of knowledge about chilling requirements. We quantified chilling and heat requirements for leaf unfolding in two European tree species and investigated their relative contributions to phenological variations between and within populations. We used an extensive database containing information about the leaf phenology of 14 oak and 10 beech populations monitored over elevation gradients since 2005. In parallel, we studied the various bud dormancy phases, in controlled conditions, by regularly sampling low- and high-elevation populations during fall and winter. Oak was 2.3 times more sensitive to temperature for leaf unfolding over the elevation gradient and had a lower chilling requirement for dormancy release than beech. We found that chilling is currently insufficient for the full release of dormancy, for both species, at the lowest elevations in the area studied. Genetic variation in leaf unfolding timing between and within oak populations was probably due to differences in heat requirement rather than differences in chilling requirement. Our results demonstrate the importance of chilling for leaf unfolding in forest trees and indicate that the advance in leaf unfolding phenology with increasing temperature will probably be less pronounced than forecasted. This highlights the urgent need to determine experimentally the interactions between chilling and heat requirements in forest tree species, to improve our understanding and modeling of changes in phenological timing under global warming.

New perspective on spring vegetation phenology and global climate change based on Tibetan Plateau tree-ring data

NASA Astrophysics Data System (ADS)

Yang, Bao; He, Minhui; Shishov, Vladimir; Tychkov, Ivan; Vaganov, Eugene; Rossi, Sergio; Charpentier Ljungqvist, Fredrik; Bräuning, Achim; Grießinger, Jussi

2017-07-01

Phenological responses of vegetation to climate, in particular to the ongoing warming trend, have received much attention. However, divergent results from the analyses of remote sensing data have been obtained for the Tibetan Plateau (TP), the world’s largest high-elevation region. This study provides a perspective on vegetation phenology shifts during 1960-2014, gained using an innovative approach based on a well-validated, process-based, tree-ring growth model that is independent of temporal changes in technical properties and image quality of remote sensing products. Twenty composite site chronologies were analyzed, comprising about 3,000 trees from forested areas across the TP. We found that the start of the growing season (SOS) has advanced, on average, by 0.28 d/y over the period 1960-2014. The end of the growing season (EOS) has been delayed, by an estimated 0.33 d/y during 1982-2014. No significant changes in SOS or EOS were observed during 1960-1981. April-June and August-September minimum temperatures are the main climatic drivers for SOS and EOS, respectively. An increase of 1 °C in April-June minimum temperature shifted the dates of xylem phenology by 6 to 7 d, lengthening the period of tree-ring formation. This study extends the chronology of TP phenology farther back in time and reconciles the disparate views on SOS derived from remote sensing data. Scaling up this analysis may improve understanding of climate change effects and related phenological and plant productivity on a global scale.

Spatiotemporal Analysis of Corn Phenoregions in the Continental United States

NASA Astrophysics Data System (ADS)

Konduri, V. S.; Kumar, J.; Hoffman, F. M.; Ganguly, A. R.; Hargrove, W. W.

2017-12-01

The delineation of regions exhibiting similar crop performance has potential benefits for agricultural planning and management, policymaking and natural resource conservation. Studies of natural ecosystems have used multivariate clustering algorithms based on environmental characteristics to identify ecoregions for species range prediction and habitat conservation. However, few studies have used clustering to delineate regions based on crop phenology. The aim of this study was to perform a spatiotemporal analysis of phenologically self-similar clusters, or phenoregions, for the major corn growing areas in the Continental United States (CONUS) for the period 2008-2016. Annual trajectories of remotely sensed normalized difference vegetation index (NDVI), a useful proxy for land surface phenology, derived from Moderate Resolution Spectroradiometer (MODIS) instruments at 8-day intervals and 250 m resolution was used as the phenological metric. Because of the large data volumes involved, the phenoregion delineation was performed using a highly scalable, unsupervised clustering technique with the help of high performance computing. These phenoregions capture the spatial variability in the timing of important crop phenological stages (like emergence and maturity dates) and thus could be used to develop more accurate parameterizations for crop models applied at regional to global scales. Moreover, historical crop performance from phenoregions, in combination with climate and soils data, could be used to improve production forecasts. The temporal variability in NDVI at each location could also be used to develop an early warning system to identify locations where the crop deviates from its expected phenological behavior. Such deviations may indicate a need for irrigation or fertilization or suggest where pest outbreaks or other disturbances have occurred.

Spatio-Temporal Changes of Net Primary Productivity and its Response to Phenology in Northeast China during 2000-2015

NASA Astrophysics Data System (ADS)

Qiu, Y.; Zhang, L.; Fan, D.

2018-04-01

The relationship between net primary productivity (NPP) and phenological changes is of great significance to the study of regional ecosystem processes. In this study, firstly, NPP was estimated with the remote sensing model based on the SPOT-VGT NDVI dataset (2000-2015), meteorological data and the vegetation map in Northeast China. Then, using NDVI time series data which was reconstructed by polynomial fitting, phenology was extracted with the dynamic threshold method. Finally, the relationship between NPP and phenology was analyzed. The results showed that NPP mainly increased in the cropland, grassland, forestland and shrubland; however, vegetation NPP decreased in the ecotone among cropland, grassland and forestland. Correlation analysis suggested that the relationships between NPP and phenological metrics (i.e., the start of the growing season (SOS), the end of the growing season (EOS), the length of the growing season (LOS)) were different due to geographical location. On the whole, there was a positive correlation between NPP and the LOS in the forestland, and negative in the cropland and grassland, indicating that extended LOS can promote the accumulation of forestland NPP. By analyzing the monthly NDVI data during the vigorous growth period, the increase of NPP in the grassland and cropland was mainly due to the better growth from June to August, and shortened LOS did not lead to reduce the NPP. Generally, the response of NPP to phenology in Northeast China were more complex, showing obvious difference of vegetation types and spatial variability, we need to consider topography, community structure and other factors in the further studies.

Predicting future forests: Understanding diverse phenological responses within a community and functional trait framework

NASA Astrophysics Data System (ADS)

Wolkovich, E. M.; Flynn, D. F. B.

2016-12-01

In recent years increasing attention has focused on plant phenology as an important indicator of the biological impacts of climate change, as many plants have shifted their leafing and flowering earlier with increasing temperatures. As data have accumulated, researchers have found a link between phenological responses to warming and plant performance and invasions. Such work suggests phenology may not only be a major impact of warming, but a critical predictor of future plant performance. Yet alongside this increasing interest in phenology, important issues remain unanswered: responses to warming for species at the same site or in the same genus vary often by weeks or more and the explanatory power of phenology for performance and invasions when analyzed across diverse datasets remains low. We propose progress can come from explicitly considering phenology within a community context and as a critical plant trait correlated with other major plant functional traits. Here, we lay out a framework for our proposal: specifically we review how we expect phenology and phenological cues of different species within a community to vary and what other functional traits are predicted to co-vary with phenological traits. Much research currently suggests phenology is a critical functional trait that is shaped strongly by the environment. Plants are expected to adjust their phenologies to avoid periods of high abiotic risk and/or high competition. Thus we may expect phenology to correlate strongly to other traits involved in mitigating risk and high competition. Results from recent meta-analyses as well as experimental and observational research from 28 species in northeastern North American temperate forests suggest that species within a community show the predicted diversified set of phenological cues. We review early work on links to other functional traits and in closing review how these correlations may in turn determine the diversity of phenological responses observed for some species and communities.

Estimating photosynthesis with high resolution field spectroscopy in a Mediterranean grassland under different nutrient availability

NASA Astrophysics Data System (ADS)

Perez-Priego, O.; Guan, J.; Fava, F.; Rossini, M.; Wutzler, T.; Moreno, G.; Carrara, A.; Kolle, O.; Schrumpf, M.; Reichstein, M.; Migliavacca, M.

2014-12-01

Recent studies have shown how human induced N:P imbalances are affecting essential processes (e.g. photosynthesis, plant growth rate) that lead to important changes in ecosystem structure and function. In this regard, the accuracy of the approaches based on remotely-sensed data for monitoring and modeling gross primary production (GPP) relies on the ability of vegetation indices (VIs) to track the dynamics of vegetation physiological and biophysical properties/variables. Promising results have been recently obtained when Chlorophyll-sensitive VIs and Chlorophyll fluorescence are combined with structural indices in the framework of the Monteith's light use efficiency (LUE) model. However, further ground-based experiments are required to validate LUE model performances, and their capability to be generalized under different nutrient availability conditions. In this study, the overall objective was to investigate the sensitivity of VIs to track short- and long-term GPP variations in a Mediterranean grassland under different N and P fertilization treatments. Spectral VIs were acquired manually using high resolution spectrometers (HR4000, OceanOptics, USA) along a phenological cycle. The VIs examined included photochemical reflectance index (PRI), MERIS terrestrial-chlorophyll index (MTCI) and normalized difference vegetation index (NDVI). Solar-induced chlorophyll fluorescence calculated at the oxygen absorption band O2-A (F760) using spectral fitting methods was also used. Simultaneously, measurements of GPP and environmental variables were conducted using a transient-state canopy chamber. Overall, GPP, F760 and VIs showed a clear seasonal time-trend in all treatments, which was driven by the phenological development of the grassland. Results showed significant differences (p<0.05) in midday GPP values between N and without N addition plots, in particular at the peak of the growing season during the flowering stage and at the end of the season during senescence. While NDVI did not show any significant difference between treatments, VIs sensitive to pigment variations and physiology (PRI, MTCI) and F760 behaved as GPP. Model performance test indicated that VIs related to physiology and fluorescence are key to account for nutrient availability in LUE models and to better predict GPP.

Detecting phenology change in the mayfly Ephemera danica in response to water temperature variations

NASA Astrophysics Data System (ADS)

Johnson, Matthew; Everall, Nicholas; Wilby, Robert

2014-05-01

Water temperature is critical to aquatic life. Rising river temperatures under climate change are expected to affect the phenology (i.e. timing of life events) of aquatic insects, including Ephemera danica which is a large burrowing mayfly that is widespread throughout Europe. To assess the temporal and spatial variability in mayfly emergence, E. danica were monitored at two reaches in the River Dove, English Peak District over the period 2007 to 2013. Inter-annual variations in Growing Degree Days (GDDs) were modelled for an upstream site with intermittent spring flows supplementing main channel flow (Beresford Dale) and a downstream site dominated by near constant discharges of cool groundwater (Dovedale). The emergence cycle of E. danica was strongly related to GDDs at each site. E. danica usually remains in an aquatic larval stage for two years before emerging in its adult, terrestrial form. However, after particularly warm summers in Beresford Dale, E. danica was recorded to emerge after only one year in its aquatic form. Following the particularly wet/cold year of 2012, E. danica began to revert back to a bi-annual cycle. In Dovedale, an average of 374 fewer GDDs were accumulated in comparison to Beresford Dale. As a result, E. danica maintained a two-year growth cycle throughout the monitoring period despite the phenology changes observed 8 km upstream at Beresford. Changes to insect phenology are significant because populations with a one-year cycle are potentially more vulnerable to adverse weather when the majority of the population is in terrestrial form. Also, altering the growth, development and size of insects affects reproductive success with implications for population dynamics. Conventional monitoring of both water temperature and invertebrates as used by regulatory authorities in the UK, did not identify the changes in insect phenology or the association between phenology and water temperature. Data from the present study suggest that habitats near cool groundwater may provide important refugia for populations of insects, potentially delaying permanent shifts in phenology under climate change. However, the ability to detect changes in thermal triggers and phenological response may be hindered by conventional spot sampling protocols.

Enhancing Ecological Thought Through Phenological Observation, Research, and Education

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; Losleben, M.; Benton, L. M.

2008-12-01

Background The USA National Phenology Network (USA-NPN) is an emerging and exciting partnership between federal agencies, the academic community, and the general public to monitor and understand the influence of seasonal cycles and phenology on the Nation's resources. Phenology is the study of the timing of recurring biological phases, the causes of their timing with regard to biotic and abiotic forces, and the interrelation among phases of same or different species. Phenological data and models developed as part of the network can be applied to scientific research, education and outreach, as well as to stakeholders interested in agriculture, tourism and recreation, human health, and natural resource conservation and management. The goal of the USA-NPN (www.usanpn.org) is to establish a nationwide science and monitoring program to better understand how plants, animals and landscapes respond to climatic variation, and to facilitate human adaptation to ongoing and potential future climate change. Results The NPN has a number of programs through which learners of all ages can observe and interpret their environment using phenology as a platform to facilitate understanding through active learning, engagement, and inquiry-based approaches. For example, since February 2008, the NPN-affiliated network Project BudBurst has registered almost 3000 people who are observing nearly 4000 plants across the continental US and are reporting their observations on-line. In addition, we are developing educational programs, modules, and activities applicable to all stages in the educational process from 'K to gray,' and are partnering with local, state, and federal governmental and non- governmental organizations on education/outreach programming. Dissemination of educational materials and information will be facilitated by the creation of an on-line clearing-house for phenology education and outreach. In sum, the NPN is developing a number of programs and products that will capitalize on myriad educational opportunities and a new readiness of the public to participate in investigations of nature on a national scale. Here, we describe how phenology can be considered an integrative science for local assessment of global change, and how citizen scientists can help meet science objectives while increasing their awareness of environmental impacts of human activities.

Growing C4 perennial grass for bioenergy using a new Agro-BGC ecosystem model

NASA Astrophysics Data System (ADS)

di Vittorio, A. V.; Anderson, R. S.; Miller, N. L.; Running, S. W.

2009-12-01

Accurate, spatially gridded estimates of bioenergy crop yields require 1) biophysically accurate crop growth models and 2) careful parameterization of unavailable inputs to these models. To meet the first requirement we have added the capacity to simulate C4 perennial grass as a bioenergy crop to the Biome-BGC ecosystem model. This new model, hereafter referred to as Agro-BGC, includes enzyme driven C4 photosynthesis, individual live and dead leaf, stem, and root carbon/nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that effectively simulates fertilization, harvest, fire, and incremental irrigation. There are four Agro-BGC vegetation parameters that are unavailable for Panicum virgatum (switchgrass), and to meet the second requirement we have optimized the model across multiple calibration sites to obtain representative values for these parameters. We have verified simulated switchgrass yields against observations at three non-calibration sites in IL. Agro-BGC simulates switchgrass growth and yield at harvest very well at a single site. Our results suggest that a multi-site optimization scheme would be adequate for producing regional-scale estimates of bioenergy crop yields on high spatial resolution grids.

Future Bloom and Blossom Frost Risk for Malus domestica Considering Climate Model and Impact Model Uncertainties

PubMed Central

Hoffmann, Holger; Rath, Thomas

2013-01-01

The future bloom and risk of blossom frosts for Malus domestica were projected using regional climate realizations and phenological ( = impact) models. As climate impact projections are susceptible to uncertainties of climate and impact models and model concatenation, the significant horizon of the climate impact signal was analyzed by applying 7 impact models, including two new developments, on 13 climate realizations of the IPCC emission scenario A1B. Advancement of phenophases and a decrease in blossom frost risk for Lower Saxony (Germany) for early and late ripeners was determined by six out of seven phenological models. Single model/single grid point time series of bloom showed significant trends by 2021–2050 compared to 1971–2000, whereas the joint signal of all climate and impact models did not stabilize until 2043. Regarding blossom frost risk, joint projection variability exceeded the projected signal. Thus, blossom frost risk cannot be stated to be lower by the end of the 21st century despite a negative trend. As a consequence it is however unlikely to increase. Uncertainty of temperature, blooming date and blossom frost risk projection reached a minimum at 2078–2087. The projected phenophases advanced by 5.5 d K−1, showing partial compensation of delayed fulfillment of the winter chill requirement and faster completion of the following forcing phase in spring. Finally, phenological model performance was improved by considering the length of day. PMID:24116022

Future bloom and blossom frost risk for Malus domestica considering climate model and impact model uncertainties.

PubMed

Hoffmann, Holger; Rath, Thomas

2013-01-01

The future bloom and risk of blossom frosts for Malus domestica were projected using regional climate realizations and phenological ( = impact) models. As climate impact projections are susceptible to uncertainties of climate and impact models and model concatenation, the significant horizon of the climate impact signal was analyzed by applying 7 impact models, including two new developments, on 13 climate realizations of the IPCC emission scenario A1B. Advancement of phenophases and a decrease in blossom frost risk for Lower Saxony (Germany) for early and late ripeners was determined by six out of seven phenological models. Single model/single grid point time series of bloom showed significant trends by 2021-2050 compared to 1971-2000, whereas the joint signal of all climate and impact models did not stabilize until 2043. Regarding blossom frost risk, joint projection variability exceeded the projected signal. Thus, blossom frost risk cannot be stated to be lower by the end of the 21st century despite a negative trend. As a consequence it is however unlikely to increase. Uncertainty of temperature, blooming date and blossom frost risk projection reached a minimum at 2078-2087. The projected phenophases advanced by 5.5 d K(-1), showing partial compensation of delayed fulfillment of the winter chill requirement and faster completion of the following forcing phase in spring. Finally, phenological model performance was improved by considering the length of day.

USA National Phenology Network gridded products documentation

USGS Publications Warehouse

Crimmins, Theresa M.; Marsh, R. Lee; Switzer, Jeff R.; Crimmins, Michael A.; Gerst, Katharine L.; Rosemartin, Alyssa H.; Weltzin, Jake F.

2017-02-23

The goals of the USA National Phenology Network (USA-NPN, www.usanpn.org) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to facilitate informed ecosystem stewardship and management by providing phenological information freely and openly. One way the USA-NPN is endeavoring to accomplish these goals is by providing data and data products in a wide range of formats, including gridded real-time, short-term forecasted, and historical maps of phenological events, patterns and trends. This document describes the suite of gridded phenologically relevant data products produced and provided by the USA National Phenology Network, which can be accessed at www.usanpn.org/data/phenology_maps and also through web services at geoserver.usanpn.org/geoserver/wms?request=GetCapabilities.

Observed & Modeled Changes in the Onset of Spring: A Preliminary Comparative Analysis by Geographic Regions of the USA

NASA Astrophysics Data System (ADS)

Enquist, C.

2012-12-01

Phenology, the study of seasonal life cycle events in plants and animals, is a well-recognized indicator of climate change impacts on people and nature. Models, experiments, and observational studies show changes in plant and animal phenology as a function of environmental change. Current research aims to improve our understanding of changes by enhancing existing models, analyzing observations, synthesizing previous research, and comparing outputs. Local to regional climatology is a critical driver of phenological variation of organisms across scales. Because plants respond to the cumulative effects of daily weather over an extended period, timing of life cycle events are effective integrators of climate data. One specific measure, leaf emergence, is particularly important because it often shows a strong response to temperature change, and is crucial for assessment of processes related to start and duration of the growing season. Schwartz et al. (2006) developed a suite of models (the "Spring Indices") linking plant development from historical data from leafing and flowering of cloned lilac and honeysuckle with basic climatic drivers to monitor changes related to the start of the spring growing season. These models can be generated at any location that has daily max-min temperature time series. The new version of these models is called the "Extended Spring Indices," or SI-x (Schwartz et al. in press). The SI-x model output (first leaf date and first bloom date) are produced similarly to the original models (SI-o), but do not incorporate accumulated chilling hours; rather energy accumulation starts for all stations on January 1. This change extends the locations SI model output can be generated into the sub-tropics, allowing full coverage of the conterminous USA. Both SI model versions are highly correlated, with mean bias and mean absolute differences around two days or less, and a similar bias and absolute errors when compared to cloned lilac data. To qualitatively test SI-x output and synthesize climate-linked regional variation in phenological events across the United States, we conducted a review of the recent phenology literature and assembled this information into 8 geographic regions. Additionally, we compared these outputs to analyses of species data found in the USA National Phenology Network database. We found that (1) all outputs showed advancement of spring onset across regions and taxa, despite great variability in species and site-level response, (2) many studies suggest that there may be evolutionary selection for organisms that track climatic changes, (3) although some organisms may benefit from lengthening growing seasons, there may be a cost, such as susceptibility to late frost, or "false springs," and (4) invasive organisms may have more capacity to track these changes than natives. More work is needed to (1) better understand precipitation and hydrology related cues and (2) understand the demographic consequences of trophic mismatch and effects on ecosystem processes and services. Next steps in this research include performing quantitative analyses to further explore if SI-x can be used to indicate and forecast changes in ecological and hydrological processes across geographic regions.

Using Linear and Non-Linear Temporal Adjustments to Align Multiple Phenology Curves, Making Vegetation Status and Health Directly Comparable

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Norman, S. P.; Kumar, J.; Hoffman, F. M.

2017-12-01

National-scale polar analysis of MODIS NDVI allows quantification of degree of seasonality expressed by local vegetation, and also selects the most optimum start/end of a local "phenological year" that is empirically customized for the vegetation that is growing at each location. Interannual differences in timing of phenology make direct comparisons of vegetation health and performance between years difficult, whether at the same or different locations. By "sliding" the two phenologies in time using a Procrustean linear time shift, any particular phenological event or "completion milestone" can be synchronized, allowing direct comparison of differences in timing of other remaining milestones. Going beyond a simple linear translation, time can be "rubber-sheeted," compressed or dilated. Considering one phenology curve to be a reference, the second phenology can be "rubber-sheeted" to fit that baseline as well as possible by stretching or shrinking time to match multiple control points, which can be any recognizable phenological events. Similar to "rubber sheeting" to georectify a map inside a GIS, rubber sheeting a phenology curve also yields a warping signature that shows at every time and every location how many days the adjusted phenology is ahead or behind the phenological development of the reference vegetation. Using such temporal methods to "adjust" phenologies may help to quantify vegetation impacts from frost, drought, wildfire, insects and diseases by permitting the most commensurate quantitative comparisons with unaffected vegetation.

Impact of warming climate and cultivar change on maize phenology in the last three decades in North China Plain

NASA Astrophysics Data System (ADS)

Xiao, Dengpan; Qi, Yongqing; Shen, Yanjun; Tao, Fulu; Moiwo, Juana P.; Liu, Jianfeng; Wang, Rede; Zhang, He; Liu, Fengshan

2016-05-01

As climate change could significantly influence crop phenology and subsequent crop yield, adaptation is a critical mitigation process of the vulnerability of crop growth and production to climate change. Thus, to ensure crop production and food security, there is the need for research on the natural (shifts in crop growth periods) and artificial (shifts in crop cultivars) modes of crop adaptation to climate change. In this study, field observations in 18 stations in North China Plain (NCP) are used in combination with Agricultural Production Systems Simulator (APSIM)-Maize model to analyze the trends in summer maize phenology in relation to climate change and cultivar shift in 1981-2008. Apparent warming in most of the investigated stations causes early flowering and maturity and consequently shortens reproductive growth stage. However, APSIM-Maize model run for four representative stations suggests that cultivar shift delays maturity and thereby prolongs reproductive growth (flowering to maturity) stage by 2.4-3.7 day per decade (d 10a-1). The study suggests a gradual adaptation of maize production process to ongoing climate change in NCP via shifts in high thermal cultivars and phenological processes. It is concluded that cultivation of maize cultivars with longer growth periods and higher thermal requirements could mitigate the negative effects of warming climate on crop production and food security in the NCP study area and beyond.

Testing efficacy of monthly forecast application in agrometeorology: Winter wheat phenology dynamic

NASA Astrophysics Data System (ADS)

Lalic, B.; Jankovic, D.; Dekic, Lj; Eitzinger, J.; Firanj Sremac, A.

2017-02-01

Use of monthly weather forecast as input meteorological data for agrometeorological forecasting, crop modelling and plant protection can foster promising applications in agricultural production. Operational use of monthly or seasonal weather forecast can help farmers to optimize field operations (fertilizing, irrigation) and protection measures against plant diseases and pests by taking full advantage of monthly forecast information in predicting plant development, pest and disease risks and yield potentials few weeks in advance. It can help producers to obtain stable or higher yield with the same inputs and to minimise losses caused by weather. In Central and South-Eastern Europe ongoing climate change lead to shifts of crops phenology dynamics (i.e. in Serbia 4-8 weeks earlier in 2016 than in previous years) and brings this subject in the front of agronomy science and practice. Objective of this study is to test efficacy of monthly forecast in predicting phenology dynamics of different winter wheat varieties, using phenological model developed by Forecasting and Warning Service of Serbia in plant protection. For that purpose, historical monthly forecast for four months (March 1, 2005 - June 30, 2005) was assimilated from ECMWF MARS archive for 50 ensemble members and control run. Impact of different agroecological conditions is tested by using observed and forecasted data for two locations - Rimski Sancevi (Serbia) and Groß-Enzersdorf (Austria).

Integration of Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Sprigg, W. A.; Huete, A.; Nickovic, S.; Pejanovic, G.; Levetin, E.; Van de water, P.; Myers, O.; Budge, A. M.; Krapfl, H.;

Response of deciduous trees spring phenology to recent and projected climate change in Central Lithuania

NASA Astrophysics Data System (ADS)

Juknys, Romualdas; Kanapickas, Arvydas; Šveikauskaitė, Irma; Sujetovienė, Gintarė

2016-10-01

The analysis of long-term time series of spring phenology for different deciduous trees species has shown that leaf unfolding for all the investigated species is the most sensitive to temperatures in March and April and illustrates that forcing temperature is the main driver of the advancement of leaf unfolding. Available chilling amount has increased by 22.5 % over the last 90 years, indicating that in the investigated geographical region there is no threat of chilling shortage. The projection of climatic parameters for Central Lithuania on the basis of three global circulation models has shown that under the optimistic climate change scenario (RCP 2.6) the mean temperature tends to increase by 1.28 °C and under the pessimistic scenario (RCP 8.5) by 5.03 °C until the end of the current century. Recently, different statistical models are used not only to analyze but also to project the changes in spring phenology. Our study has shown that when the data of long-term phenological observations are available, multiple regression models are suitable for the projection of the advancement of leaf unfolding under the changing climate. According to the RCP 8.5 scenario, the projected advancement in leaf unfolding for early-season species birch consists of almost 15 days as an average of all three used GSMs. Markedly less response to the projected far future (2071-2100), climate change is foreseen for other investigated climax species: -9 days for lime, 10 days for oak, and 11 days for maple.

Response of deciduous trees spring phenology to recent and projected climate change in Central Lithuania.

PubMed

Juknys, Romualdas; Kanapickas, Arvydas; Šveikauskaitė, Irma; Sujetovienė, Gintarė

2016-10-01

The analysis of long-term time series of spring phenology for different deciduous trees species has shown that leaf unfolding for all the investigated species is the most sensitive to temperatures in March and April and illustrates that forcing temperature is the main driver of the advancement of leaf unfolding. Available chilling amount has increased by 22.5 % over the last 90 years, indicating that in the investigated geographical region there is no threat of chilling shortage. The projection of climatic parameters for Central Lithuania on the basis of three global circulation models has shown that under the optimistic climate change scenario (RCP 2.6) the mean temperature tends to increase by 1.28 °C and under the pessimistic scenario (RCP 8.5) by 5.03 °C until the end of the current century. Recently, different statistical models are used not only to analyze but also to project the changes in spring phenology. Our study has shown that when the data of long-term phenological observations are available, multiple regression models are suitable for the projection of the advancement of leaf unfolding under the changing climate. According to the RCP 8.5 scenario, the projected advancement in leaf unfolding for early-season species birch consists of almost 15 days as an average of all three used GSMs. Markedly less response to the projected far future (2071-2100), climate change is foreseen for other investigated climax species: -9 days for lime, 10 days for oak, and 11 days for maple.

Linking Landsat observations with MODIS derived Land Surface Phenology data to map agricultural expansion and contraction in Russia

NASA Astrophysics Data System (ADS)

Caliskan, S.; de Beurs, K.

2010-12-01

Direct human impacts on the land surface are especially pronounced in agricultural regions that cover a substantial portion of the global land surface: 12% of the terrestrial surface is under active agricultural management. Crops display phenologies distinct from natural vegetation; the growing seasons are often shifted in time, crop establishment is generally fast and the vegetation is rapidly removed at harvest. Previously we have demonstrated that agricultural land abandonment alters land surface phenology sufficiently to be detectable from a time series of coarse resolution imagery. With land surface phenology models based on accumulated growing degree-days (AGDD) and AVHRR NDVI, we demonstrated that abandoned croplands covered with native grasses and weeds typically greened-up and peaked sooner than active croplands. Here we present an expansion of these analyses for the MODIS time period with the ultimate goal to map agricultural abandonment and expansion in European Russia from 2000 to 2010. We used the 8-day, 1km L3 Land Surface Temperature data (MOD11A2) to generate the accumulated growing degree days and the 16-day L3 Nadir BRDF-Adjusted reflectance data at 500m resolution (MCD43A4) to calculate NDVI. We calculated phenological metrics based on three methods: 1) Double-logistic models such as those applied to produce the standard MODIS phenology product (MOD12Q2); 2) A combination of NDII and NDVI; this method has been shown to provide start/end of season measurement closest to field observations in snowy areas; and 3) A quadratic model linking accumulated growing degree days and vegetation indices which we successfully applied in agricultural areas of Kazakhstan and semi-arid Africa. We selected Landsat imagery for two vastly different regions in Russia and present a Landsat-guided probabilistic detection of abandoned and active croplands for all available years of the MODIS image time series (2000-2010). For each region, we selected at least two images during the growing season and calculated the following indices: Normalized Difference Vegetation Index (NDVI), Tasseled Cap indices (Brightness, Greenness, Wetness), as well as the first three principal components for each image. We used the selected images to distinguish between the basic classes of agriculture, water, forest and urban areas, with the primary goal to separate between agricultural and non-agricultural regions. We compared class membership with ancillary regional agricultural statistics and targeted field observations collected in the summer of 2010. In the last part, we linked the Landsat based agricultural estimates and the MODIS phenological measurements using logistic regression and compared the agricultural maps with globally available land cover classifications.

Phenology of forest-grassland transition zones in the Community Land Model

NASA Astrophysics Data System (ADS)

Dahlin, K.; Fisher, R. A.

2013-12-01

Forest-grassland transition zones (savannas, woodlands, wooded grasslands, and shrublands) are highly sensitive to climate and may already be changing due to warming, changes in precipitation patterns, and/or CO2 fertilization. Shifts between closed canopy forest and open grassland, as well as shifts in phenology, could have large impacts on the global carbon cycle, water balance, albedo, and on the humans and other animals that depend on these regions. From an earth system perspective these impacts may then feed back into the climate system and impact how, when, and where climate change occurs. Here we compare 29 years of monthly leaf area index (LAI) outputs from several offline versions of the Community Land Model (CLM), the land component of the Community Earth System Model, to LAI derived from the AVHRR NDVI3g product (LAI3g). Specifically, we focus on seasonal patterns in regions dominated by tropical broadleaved deciduous trees (T-BDT), broadleaved deciduous shrubs (BDS) and grasslands (C3 and C4) in CLM, all of which follow a 'stress deciduous' phenological algorithm. We consider and compare two versions of CLM (v. 4CN and v. 4.5BGC) to the satellite derived product. We found that both versions of CLM were able to capture seasonal variations in grasslands relatively well at the regional scale, but that the 'stress deciduous' phenology algorithm did not perform well in areas dominated by T-BDT or BDS. When we compared the performance of the models at single points we found slight improvements in CLM4.5BGC over CLM4CN, but generally that the magnitude of seasonality was too low in CLM as compared to the LAI3g satellite product. To explore the parameters within CLM that had the most leverage on seasonality of LAI, we used a Latin hypercube approach to vary values for critical soil water potential (threshold at which plants drop leaves), the critical number of days that soil water potential must be too low for leaves to drop, and the carbon allocation scheme. In single-point simulations we found that changing how carbon is allocated improved the 'flat-topped' nature of the CLM LAI during summer, which is not present in LAI3g, while adjustments to the soil water potential parameters allowed for less extreme and fewer switches between leaf-on and leaf-off. Future work will include applying a subset of the new parameter values to global runs of the model to assess whether the improvements to phenology at single points improve global phenological patterns and/or other components of the CLM carbon cycle.

A new approach to generating research-quality phenology data: The USA National Phenology Monitoring System

NASA Astrophysics Data System (ADS)

Denny, E. G.; Miller-Rushing, A. J.; Haggerty, B. P.; Wilson, B. E.

2009-12-01

The USA National Phenology Network has recently initiated a national effort to encourage people at different levels of expertise—from backyard naturalists to professional scientists—to observe phenological events and contribute to a national database that will be used to greatly improve our understanding of spatio-temporal variation in phenology and associated phenological responses to climate change. Traditional phenological observation protocols identify specific single dates at which individual phenological events are observed, but the scientific usefulness of long-term phenological observations can be improved with a more carefully structured protocol. At the USA-NPN we have developed a new approach that directs observers to record each day that they observe an individual plant, and to assess and report the state of specific life stages (or phenophases) as occurring or not occurring on that plant for each observation date. Evaluation is phrased in terms of simple, easy-to-understand, questions (e.g. “Do you see open flowers?”), which makes it very appropriate for a broad audience. From this method, a rich dataset of phenological metrics can be extracted, including the duration of a phenophase (e.g. open flowers), the beginning and end points of a phenophase (e.g. traditional phenological events such as first flower and last flower), multiple distinct occurrences of phenophases within a single growing season (e.g multiple flowering events, common in drought-prone regions), as well as quantification of sampling frequency and observational uncertainties. The system also includes a mechanism for translation of phenophase start and end points into standard traditional phenological events to facilitate comparison of contemporary data collected with this new “phenophase status” monitoring approach to historical datasets collected with the “phenological event” monitoring approach. These features greatly enhance the utility of the resulting data for statistical analyses addressing questions such as how phenological events vary in time and space, and in response to global change.

A new approach to generating research-quality phenology data: The USA National Phenology Monitoring System

NASA Astrophysics Data System (ADS)

Denny, Ellen; Miller-Rushing, Abraham; Haggerty, Brian; Wilson, Bruce; Weltzin, Jake

2010-05-01

The USA National Phenology Network (www.usanpn.org) has recently initiated a national effort to encourage people at different levels of expertise—from backyard naturalists to professional scientists—to observe phenological events and contribute to a national database that will be used to greatly improve our understanding of spatio-temporal variation in phenology and associated phenological responses to climate change. Traditional phenological observation protocols identify specific single dates at which individual phenological events are observed, but the scientific usefulness of long-term phenological observations can be improved with a more carefully structured protocol. At the USA-NPN we have developed a new approach that directs observers to record each day that they observe an individual plant, and to assess and report the state of specific life stages (or phenophases) as occurring or not occurring on that plant for each observation date. Evaluation is phrased in terms of simple, easy-to-understand, questions (e.g. "Do you see open flowers?"), which makes it very appropriate for a broad audience. From this method, a rich dataset of phenological metrics can be extracted, including the duration of a phenophase (e.g. open flowers), the beginning and end points of a phenophase (e.g. traditional phenological events such as first flower and last flower), multiple distinct occurrences of phenophases within a single growing season (e.g multiple flowering events, common in drought-prone regions), as well as quantification of sampling frequency and observational uncertainties. The system also includes a mechanism for translation of phenophase start and end points into standard traditional phenological events to facilitate comparison of contemporary data collected with this new "phenophase status" monitoring approach to historical datasets collected with the "phenological event" monitoring approach. These features greatly enhance the utility of the resulting data for statistical analyses addressing questions such as how phenological events vary in time and space, and in response to global change.

Space-Derived Phenology, Retrieval and Use for Drought and Food Security Monitoring

NASA Astrophysics Data System (ADS)

Meroni, M.; Kayitakire, F.; Rembold, F.; Urbano, F.; Schucknecht, A.; LEO, O.

2014-12-01

Monitoring vegetation conditions is a critical activity for assessing food security in Africa. Rural populations relying on rain-fed agriculture and livestock grazing are highly exposed to large seasonal and inter-annual fluctuations in water availability. Monitoring the state, evolution, and productivity of vegetation, crops and pastures in particular, is important to conduct food emergency responses and plan for a long-term, resilient, development strategy in this area. The timing of onset, the duration, and the intensity of vegetation growth can be retrieved from space observations and used for food security monitoring to assess seasonal vegetation development and forecast the likely seasonal outcome when the season is ongoing. In this contribution we present a set of phenology-based remote sensing studies in support to food security analysis. Key phenological indicators are retrieved using a model-fit approach applied to SOPT-VEGETATION FAPAR time series. Remote-sensing phenology is first used to estimate i) the impact of the drought in the Horn of Africa, ii) crop yield in Tunisia and, iii) rangeland biomass production in Niger. Then the impact of the start and length of vegetation growing period on the total biomass production is assessed over the Sahel. Finally, a probabilistic approach using phenological information to forecast the occurrence of an end-of-season biomass production deficit is applied over the Sahel to map hot-spots of drought-related risk.

Standardized phenology monitoring methods to track plant and animal activity for science and resource management applications

NASA Astrophysics Data System (ADS)

Denny, Ellen G.; Gerst, Katharine L.; Miller-Rushing, Abraham J.; Tierney, Geraldine L.; Crimmins, Theresa M.; Enquist, Carolyn A. F.; Guertin, Patricia; Rosemartin, Alyssa H.; Schwartz, Mark D.; Thomas, Kathryn A.; Weltzin, Jake F.

2014-05-01

Phenology offers critical insights into the responses of species to climate change; shifts in species' phenologies can result in disruptions to the ecosystem processes and services upon which human livelihood depends. To better detect such shifts, scientists need long-term phenological records covering many taxa and across a broad geographic distribution. To date, phenological observation efforts across the USA have been geographically limited and have used different methods, making comparisons across sites and species difficult. To facilitate coordinated cross-site, cross-species, and geographically extensive phenological monitoring across the nation, the USA National Phenology Network has developed in situ monitoring protocols standardized across taxonomic groups and ecosystem types for terrestrial, freshwater, and marine plant and animal taxa. The protocols include elements that allow enhanced detection and description of phenological responses, including assessment of phenological "status", or the ability to track presence-absence of a particular phenophase, as well as standards for documenting the degree to which phenological activity is expressed in terms of intensity or abundance. Data collected by this method can be integrated with historical phenology data sets, enabling the development of databases for spatial and temporal assessment of changes in status and trends of disparate organisms. To build a common, spatially, and temporally extensive multi-taxa phenological data set available for a variety of research and science applications, we encourage scientists, resources managers, and others conducting ecological monitoring or research to consider utilization of these standardized protocols for tracking the seasonal activity of plants and animals.

Standardized phenology monitoring methods to track plant and animal activity for science and resource management applications

USGS Publications Warehouse

Denny, Ellen G.; Gerst, Katharine L.; Miller-Rushing, Abraham J.; Tierney, Geraldine L.; Crimmins, Theresa M.; Enquist, Carolyn A.F.; Guertin, Patricia; Rosemartin, Alyssa H.; Schwartz, Mark D.; Thomas, Kathryn A.; Weltzin, Jake F.

2014-01-01

Phenology offers critical insights into the responses of species to climate change; shifts in species’ phenologies can result in disruptions to the ecosystem processes and services upon which human livelihood depends. To better detect such shifts, scientists need long-term phenological records covering many taxa and across a broad geographic distribution. To date, phenological observation efforts across the USA have been geographically limited and have used different methods, making comparisons across sites and species difficult. To facilitate coordinated cross-site, cross-species, and geographically extensive phenological monitoring across the nation, the USA National Phenology Network has developed in situ monitoring protocols standardized across taxonomic groups and ecosystem types for terrestrial, freshwater, and marine plant and animal taxa. The protocols include elements that allow enhanced detection and description of phenological responses, including assessment of phenological “status”, or the ability to track presence–absence of a particular phenophase, as well as standards for documenting the degree to which phenological activity is expressed in terms of intensity or abundance. Data collected by this method can be integrated with historical phenology data sets, enabling the development of databases for spatial and temporal assessment of changes in status and trends of disparate organisms. To build a common, spatially, and temporally extensive multi-taxa phenological data set available for a variety of research and science applications, we encourage scientists, resources managers, and others conducting ecological monitoring or research to consider utilization of these standardized protocols for tracking the seasonal activity of plants and animals.

Standardized phenology monitoring methods to track plant and animal activity for science and resource management applications.

PubMed

Denny, Ellen G; Gerst, Katharine L; Miller-Rushing, Abraham J; Tierney, Geraldine L; Crimmins, Theresa M; Enquist, Carolyn A F; Guertin, Patricia; Rosemartin, Alyssa H; Schwartz, Mark D; Thomas, Kathryn A; Weltzin, Jake F

2014-05-01

Phenology offers critical insights into the responses of species to climate change; shifts in species' phenologies can result in disruptions to the ecosystem processes and services upon which human livelihood depends. To better detect such shifts, scientists need long-term phenological records covering many taxa and across a broad geographic distribution. To date, phenological observation efforts across the USA have been geographically limited and have used different methods, making comparisons across sites and species difficult. To facilitate coordinated cross-site, cross-species, and geographically extensive phenological monitoring across the nation, the USA National Phenology Network has developed in situ monitoring protocols standardized across taxonomic groups and ecosystem types for terrestrial, freshwater, and marine plant and animal taxa. The protocols include elements that allow enhanced detection and description of phenological responses, including assessment of phenological "status", or the ability to track presence-absence of a particular phenophase, as well as standards for documenting the degree to which phenological activity is expressed in terms of intensity or abundance. Data collected by this method can be integrated with historical phenology data sets, enabling the development of databases for spatial and temporal assessment of changes in status and trends of disparate organisms. To build a common, spatially, and temporally extensive multi-taxa phenological data set available for a variety of research and science applications, we encourage scientists, resources managers, and others conducting ecological monitoring or research to consider utilization of these standardized protocols for tracking the seasonal activity of plants and animals.

The role of plant phenology in stomatal ozone flux modeling.

PubMed

Anav, Alessandro; Liu, Qiang; De Marco, Alessandra; Proietti, Chiara; Savi, Flavia; Paoletti, Elena; Piao, Shilong

2018-01-01

Plant phenology plays a pivotal role in the climate system as it regulates the gas exchange between the biosphere and the atmosphere. The uptake of ozone by forest is estimated through several meteorological variables and a specific function describing the beginning and the termination of plant growing season; actually, in many risk assessment studies, this function is based on a simple latitude and topography model. In this study, using two satellite datasets, we apply and compare six methods to estimate the start and the end dates of the growing season across a large region covering all Europe for the year 2011. Results show a large variability between the green-up and dormancy dates estimated using the six different methods, with differences greater than one month. However, interestingly, all the methods display a common spatial pattern in the uptake of ozone by forests with a marked change in the magnitude, up to 1.9 TgO 3 /year, and corresponding to a difference of 25% in the amount of ozone that enters the leaves. Our results indicate that improved estimates of ozone fluxes require a better representation of plant phenology in the models used for O 3 risk assessment. © 2017 John Wiley & Sons Ltd.

Warming and Chilling: Assessing Aspects of Changing Plant Ecology with Continental-scale Phenology

NASA Astrophysics Data System (ADS)

Schwartz, M. D.; Hanes, J. M.

2009-12-01

Many recent ecological studies have concentrated on the direct impacts of climate warming, such as modifications to seasonal plant and animal life cycle events (phenology). There are many examples, with most indicating earlier onset of spring plant growth and delayed onset of autumn senescence. However, the implication of continued warming for plant species’ chilling requirements has received comparatively less attention. Temperate zone woody plants often require a certain level of cool season "chilling" (accumulated time at temperatures below a specific threshold) to break dormancy and prepare to respond to springtime warming. Thus, the potential impacts of insufficient chilling must be included in a comprehensive assessment of plant species' responses to climate warming. Vegetation phenological data, when collected for specific plant species at continental-scale, can be used to extract information relating to the combined impacts of reduced chilling and warming on plant species physiology. In a recent study, we demonstrated that common lilac first leaf and first bloom phenology (collected from multiple locations in the western United States and matched with air temperature records) can estimate the species' chilling requirement (in this case 1748 chilling hours, below a base temperature of 7.2°C) and highlight the changing impact of warming on the plant's phenological response in light of that requirement. Specifically, when chilling is above the requirement, lilac first leaf dates advance at a rate of -5.0 days per 100 hour chilling accumulation reduction, and lilac first bloom dates advance at a rate of -4.2 days per 100 hour chilling accumulation reduction. In contrast, when chilling is below the requirement, the lilac event dates advance at a much reduced rate of -1.6 days per 100 hour reduction for first leaf date and -2.2 days per 100 hour reduction for first bloom date. Overall, these encouraging results for common lilac suggest that similar continental-scale phenological measurements could facilitate a better understanding of relationships among phenological response, springtime warming, and chilling requirements for other species. Further, it should be possible to address more detailed follow-up plant ecology questions in future studies using similar methodology. Example questions would include: 1) Are the chilling requirements for a species the same across its entire range? 2) Do species adapt to warming conditions by changing their chilling requirements? and 3) How much variation is there among species chilling requirements within the same community? Continental-scale phenological data sets are being developed by the USA National Phenology Network (http://www.usanpn.org), that will facilitate such investigations, and in turn be essential for understanding of (and eventually consideration of possible adaptations to) the coming impacts of climate warming on temperate plant communities. Additionally, these phenological data, because they provide plants species’ responses across large portions of species geographic ranges, will facilitate deeper understanding of the full range of plant-environment responses and consequently foster development of more robust phenological models.

A global synthesis of animal phenological responses to climate change

NASA Astrophysics Data System (ADS)

Cohen, Jeremy M.; Lajeunesse, Marc J.; Rohr, Jason R.

2018-03-01

Shifts in phenology are already resulting in disruptions to the timing of migration and breeding, and asynchronies between interacting species1-5. Recent syntheses have concluded that trophic level1, latitude6 and how phenological responses are measured7 are key to determining the strength of phenological responses to climate change. However, researchers still lack a comprehensive framework that can predict responses to climate change globally and across diverse taxa. Here, we synthesize hundreds of published time series of animal phenology from across the planet to show that temperature primarily drives phenological responses at mid-latitudes, with precipitation becoming important at lower latitudes, probably reflecting factors that drive seasonality in each region. Phylogeny and body size are associated with the strength of phenological shifts, suggesting emerging asynchronies between interacting species that differ in body size, such as hosts and parasites and predators and prey. Finally, although there are many compelling biological explanations for spring phenological delays, some examples of delays are associated with short annual records that are prone to sampling error. Our findings arm biologists with predictions concerning which climatic variables and organismal traits drive phenological shifts.

Predicting apricot phenology using meteorological data.

PubMed

Ruml, Mirjana; Milatović, Dragan; Vulić, Todor; Vuković, Ana

2011-09-01

The main objective of this study was to develop feasible, easy to apply models for early prediction of full flowering (FF) and maturing (MA) in apricot (Prunus armeniaca L.). Phenological data for 20 apricot cultivars grown in the Belgrade region were modeled against averages of daily temperature records over ten seasons for FF and eight seasons for MA. A much stronger correlation was found between the phenological timing and temperature at the very beginning than at the end of phenophases. Also, the length of developmental periods were better correlated to daily maximum than to daily minimum and mean air temperatures. Using prediction models based on daily maximum temperatures averaged over 30-, 45- and 60-day periods, starting from 1 January for FF prediction and from the date of FF for MA prediction, the onset of examined phenophases in apricot cultivars could be predicted from a few weeks to up to 2 months ahead with acceptable accuracy. The mean absolute differences between the observations and cross-validated predictions obtained by 30-, 45- and 60-day models were 8.6, 6.9 and 5.7 days for FF and 6.1, 3.6 and 2.8 days for MA, respectively. The validity of the results was confirmed using an independent data set for the year 2009.

Predicting apricot phenology using meteorological data

NASA Astrophysics Data System (ADS)

Ruml, Mirjana; Milatović, Dragan; Vulić, Todor; Vuković, Ana

2011-09-01

The main objective of this study was to develop feasible, easy to apply models for early prediction of full flowering (FF) and maturing (MA) in apricot ( Prunus armeniaca L.). Phenological data for 20 apricot cultivars grown in the Belgrade region were modeled against averages of daily temperature records over ten seasons for FF and eight seasons for MA. A much stronger correlation was found between the phenological timing and temperature at the very beginning than at the end of phenophases. Also, the length of developmental periods were better correlated to daily maximum than to daily minimum and mean air temperatures. Using prediction models based on daily maximum temperatures averaged over 30-, 45- and 60-day periods, starting from 1 January for FF prediction and from the date of FF for MA prediction, the onset of examined phenophases in apricot cultivars could be predicted from a few weeks to up to 2 months ahead with acceptable accuracy. The mean absolute differences between the observations and cross-validated predictions obtained by 30-, 45- and 60-day models were 8.6, 6.9 and 5.7 days for FF and 6.1, 3.6 and 2.8 days for MA, respectively. The validity of the results was confirmed using an independent data set for the year 2009.

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions.

PubMed

Mosedale, Jonathan R; Wilson, Robert J; Maclean, Ilya M D

2015-01-01

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions.

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions

PubMed Central

Mosedale, Jonathan R.; Wilson, Robert J.; Maclean, Ilya M. D.

2015-01-01

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions. PMID:26496127

Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Friedl, Mark A.; Schaaf, Crystal B.

2006-12-01

In the last two decades the availability of global remote sensing data sets has provided a new means of studying global patterns and dynamics in vegetation. The vast majority of previous work in this domain has used data from the Advanced Very High Resolution Radiometer, which until recently was the primary source of global land remote sensing data. In recent years, however, a number of new remote sensing data sources have become available that have significantly improved the capability of remote sensing to monitor global ecosystem dynamics. In this paper, we describe recent results using data from NASA's Moderate Resolution Imaging Spectroradiometer to study global vegetation phenology. Using a novel new method based on fitting piecewise logistic models to time series data from MODIS, key transition dates in the annual cycle(s) of vegetation growth can be estimated in an ecologically realistic fashion. Using this method we have produced global maps of seven phenological metrics at 1-km spatial resolution for all ecosystems exhibiting identifiable annual phenologies. These metrics include the date of year for (1) the onset of greenness increase (greenup), (2) the onset of greenness maximum (maturity), (3) the onset of greenness decrease (senescence), and (4) the onset of greenness minimum (dormancy). The three remaining metrics are the growing season minimum, maximum, and summation of the enhanced vegetation index derived from MODIS. Comparison of vegetation phenology retrieved from MODIS with in situ measurements shows that these metrics provide realistic estimates of the four transition dates identified above. More generally, the spatial distribution of phenological metrics estimated from MODIS data is qualitatively realistic, and exhibits strong correspondence with temperature patterns in mid- and high-latitude climates, with rainfall seasonality in seasonally dry climates, and with cropping patterns in agricultural areas.

Dissecting the contributions of plasticity and local adaptation to the phenology of a butterfly and its host plants.

PubMed

Phillimore, Albert B; Stålhandske, Sandra; Smithers, Richard J; Bernard, Rodolphe

2012-11-01

Phenology affects the abiotic and biotic conditions that an organism encounters and, consequently, its fitness. For populations of high-latitude species, spring phenology often occurs earlier in warmer years and regions. Here we apply a novel approach, a comparison of slope of phenology on temperature over space versus over time, to identify the relative roles of plasticity and local adaptation in generating spatial phenological variation in three interacting species, a butterfly, Anthocharis cardamines, and its two host plants, Cardamine pratensis and Alliaria petiolata. All three species overlap in the time window over which mean temperatures best predict variation in phenology, and we find little evidence that a day length requirement causes the sensitive time window to be delayed as latitude increases. The focal species all show pronounced temperature-mediated phenological plasticity of similar magnitude. While we find no evidence for local adaptation in the flowering times of the plants, geographic variation in the phenology of the butterfly is consistent with countergradient local adaptation. The butterfly's phenology appears to be better predicted by temperature than it is by the flowering times of either host plant, and we find no evidence that coevolution has generated geographic variation in adaptive phenological plasticity.

A strategy to study regional hydrology and terrestrial ecosystem processes using satellite remote sensing, ground-based data and computer modeling

NASA Technical Reports Server (NTRS)

Vorosmarty, C.; Grace, A.; Moore, B.; Choudhury, B.; Willmott, C. J.

1990-01-01

A strategy is presented for integrating scanning multichannel microwave radiometer data from the Nimbus-7 satellite with meteorological station records and computer simulations of land surface hydrology, terrestrial nutrient cycling, and trace gas emission. Analysis of the observations together with radiative transfer analysis shows that in the tropics the temporal and spatial variations of the polarization difference are determined primarily by the structure and phenology of vegetation and seasonal inundations of major rivers and wetlands. It is concluded that the proposed surface hydrology model, along with climatological records, and, potentially, 37-GHz data for phenology, will provide inputs to a terrestrial ecosystem model that predicts regional net primary production and CO2 gas exchange.

Phenological Indicators of Vegetation Recovery in Wetland Ecosystems

NASA Astrophysics Data System (ADS)

Taddeo, S.; Dronova, I.

2017-12-01

Landscape phenology is increasingly used to measure the impacts of climatic and environmental disturbances on plant communities. As plants show rapid phenological responses to environmental changes, variation in site phenology can help characterize vegetation recovery following restoration treatments and qualify their resistance to environmental fluctuations. By leveraging free remote sensing datasets, a phenology-based analysis of vegetation dynamics could offer a cost-effective assessment of restoration progress in wetland ecosystems. To fulfill this objective, we analyze 20 years of free remote sensing data from NASA's Landsat archive to offer a landscape-scale synthesis of wetland restoration efforts in the Sacramento-San Joaquin Delta of California, USA. Through an analysis of spatio-temporal changes in plant phenology and greenness, we assess how 25 restored wetlands across the Delta have responded to restoration treatments, time, and landscape context. We use a spline smoothing approach to generate both site-wide and pixel-specific phenological curves and identify key phenological events. Preliminary results reveal a greater variability in greenness and growing season length during the initial post-restoration years and a significant impact of landscape context in the time needed to reach phenological stability. Well-connected sites seem to benefit from an increased availability of propagules enabling them to reach peak greenness and maximum growing season length more rapidly. These results demonstrate the potential of phenological analyses to measure restoration progress and detect factors promoting wetland recovery. A thorough understanding of wetland phenology is key to the quantification of ecosystem processes including carbon sequestration and habitat provisioning.

[Differences of vegetation phenology monitoring by remote sensing based on different spectral vegetation indices.

PubMed

Zuo, Lu; Wang, Huan Jiong; Liu, Rong Gao; Liu, Yang; Shang, Rong

2018-02-01

Vegetation phenology is a comprehensive indictor for the responses of terrestrial ecosystem to climatic and environmental changes. Remote sensing spectrum has been widely used in the extraction of vegetation phenology information. However, there are many differences between phenology extracted by remote sensing and site observations, with their physical meaning remaining unclear. We selected one tile of MODIS data in northeastern China (2000-2014) to examine the SOS and EOS differences derived from the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (SR) based on both the red and near-infrared bands. The results showed that there were significant differences between NDVI-phenology and SR-phenology. SOS derived from NDVI averaged 18.9 days earlier than that from SR. EOS derived from NDVI averaged 19.0 days later than from SR. NDVI-phenology had a longer growing season. There were significant differences in the inter-annual variation of phenology from NDVI and SR. More than 20% of the pixel SOS and EOS derived from NDVI and SR showed the opposite temporal trend. These results caused by the seasonal curve characteristics and noise resistance differences of NDVI and SR. The observed data source of NDVI and SR were completely consistent, only the mathematical expressions were different, but phenology results were significantly different. Our results indicated that vegetation phenology monitoring by remote sensing is highly dependent on the mathematical expression of vegetation index. How to establish a reliable method for extracting vegetation phenology by remote sensing needs further research.

The potential of using Landsat time-series to extract tropical dry forest phenology

NASA Astrophysics Data System (ADS)

Zhu, X.; Helmer, E.

2016-12-01

Vegetation phenology is the timing of seasonal developmental stages in plant life cycles. Due to the persistent cloud cover in tropical regions, current studies often use satellite data with high frequency, such as AVHRR and MODIS, to detect vegetation phenology. However, the spatial resolution of these data is from 250 m to 1 km, which does not have enough spatial details and it is difficult to relate to field observations. To produce maps of phenology at a finer spatial resolution, this study explores the feasibility of using Landsat images to detect tropical forest phenology through reconstructing a high-quality, seasonal time-series of images, and tested it in Mona Island, Puerto Rico. First, an automatic method was applied to detect cloud and cloud shadow, and a spatial interpolator was use to retrieve pixels covered by clouds, shadows, and SLC-off gaps. Second, enhanced vegetation index time-series derived from the reconstructed Landsat images were used to detect 11 phenology variables. Detected phenology is consistent with field investigations, and its spatial pattern is consistent with the rainfall distribution on this island. In addition, we may expect that phenology should correlate with forest biophysical attributes, so 47 plots with field measurement of biophysical attributes were used to indirectly validate the phenology product. Results show that phenology variables can explain a lot of variations in biophysical attributes. This study suggests that Landsat time-series has great potential to detect phenology in tropical areas.

Phenology satellite experiment. [detection of brown wave and green wave in north-south corridors of United States

NASA Technical Reports Server (NTRS)

Dethier, B. E.; Ashley, M. D.; Blair, B. O.; Caprio, J. M.; Hopp, R. J.; Rouse, J., Jr. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The 1972 Brown Wave and 1973 Green Wave were detected at 24 sites located in four north-south corridors across the United States through analysis of ERTS-1 imagery and multispectral scanner digital tapes. Ground observations from these sites were correlated with ERTS data. These two phenological events were documented by observations from more than 3200 sites across the United States. The problem of changing atmospheric and illumination conditions were studied and corrections to ERTS data suggested. Band-to-band ratios were developed and correlated with the fall and spring phenological changes in field crops and forests. The results to date show the feasibility of developing and refining phenoclimatic models for use in characterizing crop status and as an aid to yield prediction.

Hydrology, phenology and the USA National Phenology Network

USGS Publications Warehouse

Kish, George R.

2010-01-01

Phenology is the study of seasonally-recurring biological events (such as leaf-out, fruit production, and animal reproduction and migration) and how these events are influenced by environmental change. Phenological changes are some of the most sensitive biological indicators of climate change, and also affect nearly all aspects of ecosystem function. Spatially extensive patterns of phenological observations have been closely linked with climate variability. Phenology and hydrology are closely linked and affect one another across a variety of scales, from leaf intercellular spaces to the troposphere, and over periods of seconds to centuries. Ecosystem life cycles and diversity are also influenced by hydrologic processes such as floods and droughts. Therefore, understanding the relationships between hydrology and phenology is increasingly important in understanding how climate change affects biological and physical systems.

From Caprio's lilacs to the USA National Phenology Network

USGS Publications Warehouse

Schwartz, Mark D.; Betancourt, Julio L.; Weltzin, Jake F.

2012-01-01

Continental-scale monitoring is vital for understanding and adapting to temporal changes in seasonal climate and associated phenological responses. The success of monitoring programs will depend on recruiting, retaining, and managing members of the public to routinely collect phenological observations according to standardized protocols. Here, we trace the development of infrastructure for phenological monitoring in the US, culminating in the USA National Phenology Network, a program that engages scientists and volunteers.

Nile Basin Vegetation Response and Vulnerability to Climate Change: A Multi-Sensor Remote Sensing Approach

NASA Astrophysics Data System (ADS)

Yitayew, M.; Didan, K.; Barreto-munoz, A.

2013-12-01

The Nile Basin is one of the world's water resources hotspot that is home to over 437 million people in ten riparian countries with 54% or 238 millions live directly within the basin. The basin like all other basins of the world is facing water resources challenges exacerbated by climate change and increased demand. Nowadays any water resource management action in the basin has to assess the impacts of climate change to be able to predict future water supply and also to help in the negotiation process. Presently, there is a lack of basin wide weather networks to understand sensitivity of the vegetation cover to the impacts of climate change. Vegetation plays major economic and ecological functions in the basin and provides key services ranging from pastoralism, agricultural production, firewood, habitat and food sources for the rich wildlife, as well as a major role in the carbon cycle and climate regulation of the region. Under the threat of climate change and the incessant anthropogenic pressure the distribution and services of the region's ecosystems are projected to change The goal of this work is to assess and characterize how the basin vegetation productivity, distribution, and phenology have changed over the last 30+ years and what are the key climatic drivers of this change. This work makes use of a newly generated multi-sensor long-term land surface data set about vegetation and phenology. Vegetation indices derived from remotely sensed surface reflectance data are commonly used to characterize phenology or vegetation dynamics accurately and with enough spatial and temporal resolution to support change detection. We used more than 30 years of vegetation index and growing season data from AVHRR and MODIS sensors compiled by the Vegetation Index and Phenology laboratory (VIP LAB) at the University of Arizona. Available climate data about precipitation and temperature for the corresponding 30 years period is also used for this analysis. We looked at the changes in the vegetation index signal and to a lesser degree the change in land cover and land use over the last 30 years. Using the climate data record we looked at the drivers of this change. The sensitivity of the basin to climate change was assessed using the multi-linear regression analysis on the covariance of the change in key phenology parameters and the two climate drivers considered here. The overall response was very complex owing to the complicated climate regime and topography of the region. Vegetation response was mostly stable in high lands with a slightly decreasing trend over low and mid-elevations. Over the same period we also observed an intensification of agriculture production corresponding to an increase in percent cover and productivity. We also observed a decrease in forest cover associated with land use conversion. These changes were mostly driven by the precipitation regimes with little impact of the temperature. Climate models project an eventual decrease in precipitation and increase in temperature over the basin. Coupled with these results and observations these projected changes point to major challenges to the vegetation cover, productivity, and associated ecosystem services of the Nile basin.

Citizen science: Plant and insect phenology with regards to degree-days

USDA-ARS?s Scientific Manuscript database

Daily minimum and maximum temperatures collected from grower-collaborators were used to calculate site specific degree-days. Using our new understanding of Sparganothis phenology, plant phenology were examined relative to moth phenology, allowing us to predict moth development in parallel with plant...

Flower power: tree flowering phenology as a settlement cue for migrating birds.

PubMed

McGrath, Laura J; van Riper, Charles; Fontaine, Joseph J

2009-01-01

1. Neotropical migrant birds show a clear preference for stopover habitats with ample food supplies; yet, the proximate cues underlying these decisions remain unclear. 2. For insectivorous migrants, cues associated with vegetative phenology (e.g. flowering, leaf flush, and leaf loss) may reliably predict the availability of herbivorous arthropods. Here we examined whether migrants use the phenology of five tree species to choose stopover locations, and whether phenology accurately predicts food availability. 3. Using a combination of experimental and observational evidence, we show migrant populations closely track tree phenology, particularly the flowering phenology of honey mesquite (Prosopis glandulosa), and preferentially forage in trees with more flowers. Furthermore, the flowering phenology of honey mesquite reliably predicts overall arthropod abundance as well as the arthropods preferred by migrants for food. 4. Together, these results suggest that honey mesquite flowering phenology is an important cue used by migrants to assess food availability quickly and reliably, while in transit during spring migration.

Flower power: Tree flowering phenology as a settlement cue for migrating birds

USGS Publications Warehouse

McGrath, L.J.; van Riper, Charles; Fontaine, J.J.

2009-01-01

1. Neotropical migrant birds show a clear preference for stopover habitats with ample food supplies; yet, the proximate cues underlying these decisions remain unclear. 2. For insectivorous migrants, cues associated with vegetative phenology (e.g. flowering, leaf flush, and leaf loss) may reliably predict the availability of herbivorous arthropods. Here we examined whether migrants use the phenology of five tree species to choose stopover locations, and whether phenology accurately predicts food availability. 3. Using a combination of experimental and observational evidence, we show migrant populations closely track tree phenology, particularly the flowering phenology of honey mesquite (Prosopis glandulosa), and preferentially forage in trees with more flowers. Furthermore, the flowering phenology of honey mesquite reliably predicts overall arthropod abundance as well as the arthropods preferred by migrants for food. 4. Together, these results suggest that honey mesquite flowering phenology is an important cue used by migrants to assess food availability quickly and reliably, while in transit during spring migration. ?? 2008 The Authors.

Linking spring phenology with mechanistic models of host movement to predict disease transmission risk

USGS Publications Warehouse

Merkle, Jerod A.; Cross, Paul C.; Scurlock, Brandon M.; Cole, Eric K.; Courtemanch, Alyson B.; Dewey, Sarah R.; Kauffman, Matthew J.

2018-01-01

Disease models typically focus on temporal dynamics of infection, while often neglecting environmental processes that determine host movement. In many systems, however, temporal disease dynamics may be slow compared to the scale at which environmental conditions alter host space-use and accelerate disease transmission.Using a mechanistic movement modelling approach, we made space-use predictions of a mobile host (elk [Cervus Canadensis] carrying the bacterial disease brucellosis) under environmental conditions that change daily and annually (e.g., plant phenology, snow depth), and we used these predictions to infer how spring phenology influences the risk of brucellosis transmission from elk (through aborted foetuses) to livestock in the Greater Yellowstone Ecosystem.Using data from 288 female elk monitored with GPS collars, we fit step selection functions (SSFs) during the spring abortion season and then implemented a master equation approach to translate SSFs into predictions of daily elk distribution for five plausible winter weather scenarios (from a heavy snow, to an extreme winter drought year). We predicted abortion events by combining elk distributions with empirical estimates of daily abortion rates, spatially varying elk seroprevelance and elk population counts.Our results reveal strong spatial variation in disease transmission risk at daily and annual scales that is strongly governed by variation in host movement in response to spring phenology. For example, in comparison with an average snow year, years with early snowmelt are predicted to have 64% of the abortions occurring on feedgrounds shift to occurring on mainly public lands, and to a lesser extent on private lands.Synthesis and applications. Linking mechanistic models of host movement with disease dynamics leads to a novel bridge between movement and disease ecology. Our analysis framework offers new avenues for predicting disease spread, while providing managers tools to proactively mitigate risks posed by mobile disease hosts. More broadly, we demonstrate how mechanistic movement models can provide predictions of ecological conditions that are consistent with climate change but may be more extreme than has been observed historically.

Influences of spawning timing, water temperature, and climatic warming on early life history phenology in western Alaska sockeye salmon

USGS Publications Warehouse

Sparks, Morgan M.; Falke, Jeffrey A.; Quinn, Thomas P.; Adkison, Milo D.; Schindler, Daniel E.; Bartz, Krista K.; Young, Daniel B.; Westley, Peter A. H.

2018-01-01

We applied an empirical model to predict hatching and emergence timing for 25 western Alaska sockeye salmon (Oncorhynchus nerka) populations in four lake-nursery systems to explore current patterns and potential responses of early life history phenology to warming water temperatures. Given experienced temperature regimes during development, we predicted hatching to occur in as few as 58 d to as many as 260 d depending on spawning timing and temperature. For a focal lake spawning population, our climate-lake temperature model predicted a water temperature increase of 0.7 to 1.4 °C from 2015 to 2099 during the incubation period, which translated to a 16 d to 30 d earlier hatching timing. The most extreme scenarios of warming advanced development by approximately a week earlier than historical minima and thus climatic warming may lead to only modest shifts in phenology during the early life history stage of this population. The marked variation in the predicted timing of hatching and emergence among populations in close proximity on the landscape may serve to buffer this metapopulation from climate change.

Oceanographic drivers and mistiming processes shape breeding success in a seabird

PubMed Central

2016-01-01

Understanding the processes driving seabirds' reproductive performance through trophic interactions requires the identification of seasonal pulses in marine productivity. We investigated the sequence of environmental and biological processes driving the reproductive phenology and performance of the storm petrel (Hydrobates pelagicus) in the Western Mediterranean. The enhanced light and nutrient availability at the onset of water stratification (late winter/early spring) resulted in annual consecutive peaks in relative abundance of phytoplankton, zooplankton and ichthyoplankton. The high energy-demanding period of egg production and chick rearing coincided with these successive pulses in food availability, pointing to a phenological adjustment to such seasonal patterns with important fitness consequences. Indeed, delayed reproduction with respect to the onset of water stratification resulted in both hatching and breeding failure. This pattern was observed at the population level, but also when confounding factors such as individuals' age or experience were also accounted for. We provide the first evidence of oceanographic drivers leading to the optimal time-window for reproduction in an inshore seabird at southern European latitudes, along with a suitable framework for assessing the impact of environmentally driven changes in marine productivity patterns in seabird performance. PMID:26962134

Oceanographic drivers and mistiming processes shape breeding success in a seabird.

PubMed

Ramírez, Francisco; Afán, Isabel; Tavecchia, Giacomo; Catalán, Ignacio A; Oro, Daniel; Sanz-Aguilar, Ana

2016-03-16

Understanding the processes driving seabirds' reproductive performance through trophic interactions requires the identification of seasonal pulses in marine productivity. We investigated the sequence of environmental and biological processes driving the reproductive phenology and performance of the storm petrel (Hydrobates pelagicus) in the Western Mediterranean. The enhanced light and nutrient availability at the onset of water stratification (late winter/early spring) resulted in annual consecutive peaks in relative abundance of phytoplankton, zooplankton and ichthyoplankton. The high energy-demanding period of egg production and chick rearing coincided with these successive pulses in food availability, pointing to a phenological adjustment to such seasonal patterns with important fitness consequences. Indeed, delayed reproduction with respect to the onset of water stratification resulted in both hatching and breeding failure. This pattern was observed at the population level, but also when confounding factors such as individuals' age or experience were also accounted for. We provide the first evidence of oceanographic drivers leading to the optimal time-window for reproduction in an inshore seabird at southern European latitudes, along with a suitable framework for assessing the impact of environmentally driven changes in marine productivity patterns in seabird performance. © 2016 The Author(s).

Detrimental effect of temperature increase on the fitness of an amphibian ( Lissotriton helveticus)

NASA Astrophysics Data System (ADS)

Galloy, Valérie; Denoël, Mathieu

2010-03-01

Increases of global temperatures have resulted in measurable shifts in the distribution, phenology and survival of some plant and animal species. However, the mechanisms showing links between global warming and biodiversity declines remain unclear. The aim of this study was to examine whether a key parameter of fitness, i.e. offspring number, could be affected by a temperature increase. To this end, we compared egg-laying traits at naturally occurring temperatures (14 °C, 18 °C and 22 °C) in palmate newts, Lissotriton helveticus. Our study suggests that water temperature increase has a negative effect on the fecundity of female newts. Females lay half as many eggs at high temperatures as they do at low temperatures, which results in a lower number of hatchlings. This study shows that global warming would affect amphibian populations. It complements other studies in pointing out that changes in phenology may not be driven only by warmer earlier temperatures but also by counter-selection during late-breeding, particularly in long-term breeders such as newts. More experimental studies should be carried out to understand the complex consequences of global warming and the proximate mechanisms of amphibian decline.

Delineating environmental control of phytoplankton biomass and phenology in the Southern Ocean

NASA Astrophysics Data System (ADS)

Ardyna, Mathieu; Claustre, Hervé; Sallée, Jean-Baptiste; D'Ovidio, Francesco; Gentili, Bernard; van Dijken, Gert; D'Ortenzio, Fabrizio; Arrigo, Kevin R.

2017-05-01

The Southern Ocean (SO), an area highly sensitive to climate change, is currently experiencing rapid warming and freshening. Such drastic physical changes might significantly alter the SO's biological pump. For more accurate predictions of the possible evolution of this pump, a better understanding of the environmental factors controlling SO phytoplankton dynamics is needed. Here we present a satellite-based study deciphering the complex environmental control of phytoplankton biomass (PB) and phenology (PH; timing and magnitude of phytoplankton blooms) in the SO. We reveal that PH and PB are mostly organized in the SO at two scales: a large latitudinal scale and a regional scale. Latitudinally, a clear gradient in the timing of bloom occurrence appears tightly linked to the seasonal cycle in irradiance, with some exceptions in specific light-limited regimes (i.e., well-mixed areas). Superimposed on this latitudinal scale, zonal asymmetries, up to 3 orders of magnitude, in regional-scale PB are mainly driven by local advective and iron supply processes. These findings provide a global understanding of PB and PH in the SO, which is of fundamental interest for identifying and explaining ongoing changes as well as predicting future changes in the SO biological pump.

Morton et al. Reply

NASA Technical Reports Server (NTRS)

Morton, Douglas C.; Nagol, Jyoteshwar; Carabajal, Claudia C.; Rosette, Jacqueline; Palace, Michael; Cook, Bruce D.; Vermote, Eric F.; Harding, David J.; North, Peter R. J.

2016-01-01

Multiple mechanisms could lead to up-regulation of dry-season photosynthesis in Amazon forests, including canopy phenology and illumination geometry. We specifically tested two mechanisms for phenology-driven changes in Amazon forests during dry-season months, and the combined evidence from passive optical and lidar satellite data was incompatible with large net changes in canopy leaf area or leaf reflectance suggested by previous studies. We therefore hypothesized that seasonal changes in the fraction of sunlit and shaded canopies, one aspect of bidirectional reflectance effects in Moderate Resolution Imaging Spectroradiometer (MODIS) data, could alter light availability for dry-season photosynthesis and the photosynthetic capacity of Amazon forests without large net changes in canopy composition. Subsequent work supports the hypothesis that seasonal changes in illumination geometry and diffuse light regulate light saturation in Amazon forests. These studies clarify the physical mechanisms that govern light availability in Amazon forests from seasonal variability in direct and diffuse illumination. Previously, in the debate over light limitation of Amazon forest productivity, seasonal changes in the distribution of light within complex Amazon forest canopies were confounded with dry-season increases in total incoming photosynthetically active radiation. In the accompanying Comment, Saleska et al. do not fully account for this confounding effect of forest structure on photosynthetic capacity.

Retrospective estimation of breeding phenology of American Goldfinch (Carduelis tristis) using pattern oriented modeling

EPA Science Inventory

Avian seasonal productivity is often modeled as a time-limited stochastic process. Many mathematical formulations have been proposed, including individual based models, continuous-time differential equations, and discrete Markov models. All such models typically include paramete...

Identifying and prioritizing phenological data products and tools

NASA Astrophysics Data System (ADS)

Enquist, Carolyn A. F.; Rosemartin, Alyssa; Schwartz, Mark D.

2012-09-01

USA National Phenology Network Research Coordination Network Meeting; Milwaukee, Wisconsin, 22-23 May 2012 Phenology is the study of reoccurring life cycle events in plants and animals, such as bird migrations, emergence from hibernation, flowering, and carbon cycling. Changes in the timing of phenological events are widely recognized as indicators of the effects of climate change on ecosystems. Phenological data can be used to inform wildlife management, wildfire and pollen forecasting, and the planning of events such as the National Cherry Blossom Festival. Until recently, collection of phenological data using standardized methods was relatively rare, limiting their use in science, management, and decision making.

Progress Towards an Interdisciplinary Science of Plant Phenology: Building Predictions Across Space, Time and Species Diversity

NASA Technical Reports Server (NTRS)

Wolkovich, Elizabeth M.; Cook, Benjamin I.; Davies, T. Jonathan

2013-01-01

Climate change has brought renewed interest in the study of plant phenology - the timing of life history events. Data on shifting phenologies with warming have accumulated rapidly, yet research has been comparatively slow to explain the diversity of phenological responses observed across latitudes, growing seasons and species. Here, we outline recent efforts to synthesize perspectives on plant phenology across the fields of ecology, climate science and evolution. We highlight three major axes that vary among these disciplines: relative focus on abiotic versus biotic drivers of phenology, on plastic versus genetic drivers of intraspecific variation, and on cross-species versus autecological approaches. Recent interdisciplinary efforts, building on data covering diverse species and climate space, have found a greater role of temperature in controlling phenology at higher latitudes and for early-flowering species in temperate systems. These efforts have also made progress in understanding the tremendous diversity of responses across species by incorporating evolutionary relatedness, and linking phenological flexibility to invasions and plant performance. Future research with a focus on data collection in areas outside the temperate mid-latitudes and across species' ranges, alongside better integration of how risk and investment shape plant phenology, offers promise for further progress.

Predictive models of moth development

USDA-ARS?s Scientific Manuscript database

Degree-day models link ambient temperature to insect life-stages, making such models valuable tools in integrated pest management. These models increase management efficacy by predicting pest phenology. In Wisconsin, the top insect pest of cranberry production is the cranberry fruitworm, Acrobasis v...

The influence of local spring temperature variance on temperature sensitivity of spring phenology.

PubMed

Wang, Tao; Ottlé, Catherine; Peng, Shushi; Janssens, Ivan A; Lin, Xin; Poulter, Benjamin; Yue, Chao; Ciais, Philippe

2014-05-01

The impact of climate warming on the advancement of plant spring phenology has been heavily investigated over the last decade and there exists great variability among plants in their phenological sensitivity to temperature. However, few studies have explicitly linked phenological sensitivity to local climate variance. Here, we set out to test the hypothesis that the strength of phenological sensitivity declines with increased local spring temperature variance, by synthesizing results across ground observations. We assemble ground-based long-term (20-50 years) spring phenology database (PEP725 database) and the corresponding climate dataset. We find a prevalent decline in the strength of phenological sensitivity with increasing local spring temperature variance at the species level from ground observations. It suggests that plants might be less likely to track climatic warming at locations with larger local spring temperature variance. This might be related to the possibility that the frost risk could be higher in a larger local spring temperature variance and plants adapt to avoid this risk by relying more on other cues (e.g., high chill requirements, photoperiod) for spring phenology, thus suppressing phenological responses to spring warming. This study illuminates that local spring temperature variance is an understudied source in the study of phenological sensitivity and highlight the necessity of incorporating this factor to improve the predictability of plant responses to anthropogenic climate change in future studies. © 2013 John Wiley & Sons Ltd.

Does climate change explain the decline of a trans-Saharan Afro-Palaearctic migrant?

PubMed

Pearce-Higgins, J W; Yalden, D W; Dougall, T W; Beale, C M

2009-03-01

There is an urgent need to understand how climate change will impact on demographic parameters of vulnerable species. Migrants are regarded as particularly vulnerable to climate change; phenological mismatch has resulted in the local decline of one passerine, whilst variations in the survival of others have been related to African weather conditions. However, there have been few demographic studies on trans-Saharan non-passerine migrants, despite these showing stronger declines across Europe than passerines. We therefore analyse the effects of climate on the survival and productivity of common sandpipers Actitis hypoleucos, a declining non-passerine long-distant migrant using 28 years' data from the Peak District, England. Adult survival rates were significantly negatively correlated with winter North Atlantic Oscillation (NAO), being lower when winters were warm and wet in western Europe and cool and dry in northwest Africa. Annual variation in the productivity of the population was positively correlated with June temperature, but not with an index of phenological mismatch. The 59% population decline appears largely to have been driven by reductions in adult survival, with local productivity poorly correlated with subsequent population change, suggesting a low degree of natal philopatry. Winter NAO was not significantly correlated with adult survival rates in a second, Scottish Borders population, studied for 12 years. Variation in climatic conditions alone does not therefore appear to be responsible for common sandpiper declines. Unlike some passerine migrants, there was no evidence for climate-driven reductions in productivity, although the apparent importance of immigration in determining local recruitment complicates the assessment of productivity effects. We suggest that further studies to diagnose common sandpiper declines should focus on changes in the condition of migratory stop-over or wintering locations. Where possible, these analyses should be repeated for other declining migrants.

Evolved Phenological Asynchrony as a Baseline for Climate-change Impacts. (Invited)

NASA Astrophysics Data System (ADS)

Singer, M. C.; Parmesan, C.

2010-12-01

Changing climate can disrupt existing phenological relations between interacting species. We might expect the historical baseline for these effects to be precise synchrony between the season at which a consumer most requires food and the time when its resources are most available. When this is the case, change in any direction would be detrimental to the consumer. But is baseline synchrony the appropriate assumption? Here, we develop the theme that the starting point for climate change impacts may often have been asynchrony or mismatch between consumer and resource. To the extent that this has been true, assumptions of baseline synchrony risk mis-detection, mis-estimation, and mis-attribution of climate change impacts. Natural selection can result in asynchrony between exploiter and victim when victims successfully evolve to occupy enemy-free time. Asynchrony can also result from life-history tradedoffs. We illustrate asynchrony arising from tradeoffs for two species: Edith’s checkerspot butterfly and the winter moth. Initial observations of phenological mismatch in both systems were made prior to the onset of major impacts of anthropogenically-driven climate change. Neither species can detect the phenological stage of its host plants with precision. In both species, evolution of life history has involved compromise between maximizing fecundity and minimizing mortality, with the outcome being superficially maladaptive strategies in which many or even most individuals die of starvation through poor synchrony with their host plants. Both species have evolved high-risk life history strategies. While winter moth eggs gamble with their own lives by hatching early, bay checkerspots gamble with the lives of their offspring by growing large and eclosing late as adults. In both cases the result is the evolution of populations in which large numbers of individuals die because, as individuals, they fail to fit their life cycles into the available timespan. Because such a population exists near the limits of its ecological tolerance, it is particularly vulnerable to impacts of climate change. This vulnerability probably contributed to the skewed geographical pattern of population extinctions in the butterfly, which drove a northward and upward range shift in this species in the late 20th century.

Understanding phenology and drought recovery in the Amboseli Basin of Kenya with MODIS Vegetation Indices

NASA Astrophysics Data System (ADS)

Williams, R. T.; Geddes, Q. A.; Baker, A.; Gao, M.; Voelker, E.; Oluwakonyinsola, A.

2013-12-01

The Amboseli Conservation Centre (ACC) has been gathering comprehensive field data for 47 years within the Amboseli Basin near Mount Kilimanjaro in Kenya. Over the past half century, the region has suffered from near complete deforestation and continues to suffer from land degradation due to the increasingly sedentary and segregated human and animal concentrations. Overall, Kenya has experienced a loss of over 50% of biodiversity countrywide since 1977. 30% of remaining biodiversity is found in protected areas, which take up only 8% of the country's total land area. The Amboseli National Park has been identified as having the highest level of habitat irreplaceability of all 33 protected areas in the Somali-Masai Ecoregion. The successional cycles between woody vegetation and grassland affect levels of biodiversity in the region, and are largely driven by the grazing and migratory activities of elephants, as well as human land use and land management practices. Understanding the dynamics of land cover change as a continuum is therefore critical to framing conservation objectives. Currently, few land cover classifications derived from remote sensing are consistent with ACC field data, specifically in terms of differentiation between woody versus grassland vegetation. The ACC is interested in refining these distinctions in the Basin and across the Kenya-Tanzania borderlands and identifying which vegetation types are suffering from degradation and where. Therefore, the goal of this project is to 1) establish phenological profiles of differing vegetation in the Kenya-Tanzania borderlands and 2) characterize trends and drought resilience across the landscape. By analyzing MODIS vegetation indices in 8-day time steps from 2002 to 2012, this study establishes phenological profiles of primary vegetation cover classes including woodlands, bushlands, grasslands, and swamps and identifies areas that are drought-resistant or drought-sensitive at a large scale. By enhancing the ACC's ability to explore and communicate important biological distinctions based on phenology, the project will not only develop a useful tool for the ACC, but further a variety of their conservation and research goals.

Separating temperature from other factors in phenological measurements

NASA Astrophysics Data System (ADS)

Schwartz, Mark D.; Hanes, Jonathan M.; Liang, Liang

2014-09-01

Phenological observations offer a simple and effective way to measure climate change effects on the biosphere. While some species in northern mixed forests show a highly sensitive site preference to microenvironmental differences (i.e., the species is present in certain areas and absent in others), others with a more plastic environmental response (e.g., Acer saccharum, sugar maple) allow provisional separation of the universal "background" phenological variation caused by in situ (possibly biological/genetic) variation from the microclimatic gradients in air temperature. Moran's I tests for spatial autocorrelation among the phenological data showed significant ( α ≤ 0.05) clustering across the study area, but random patterns within the microclimates themselves, with isolated exceptions. In other words, the presence of microclimates throughout the study area generally results in spatial autocorrelation because they impact the overall phenological development of sugar maple trees. However, within each microclimate (where temperature conditions are relatively uniform) there is little or no spatial autocorrelation because phenological differences are due largely to randomly distributed in situ factors. The phenological responses from 2008 and 2009 for two sugar maple phenological stages showed the relationship between air temperature degree-hour departure and phenological change ranged from 0.5 to 1.2 days earlier for each additional 100 degree-hours. Further, the standard deviations of phenological event dates within individual microclimates (for specific events and years) ranged from 2.6 to 3.8 days. Thus, that range of days is inferred to be the "background" phenological variation caused by factors other than air temperature variations, such as genetic differences between individuals.

Intra- and interspecific variation in tropical tree and liana phenology derived from Unmanned Aerial Vehicle images

NASA Astrophysics Data System (ADS)

Bohlman, S.; Park, J.; Muller-Landau, H. C.; Rifai, S. W.; Dandois, J. P.

2017-12-01

Phenology is a critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical tree and liana phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. Spectral, texture, and image information was extracted from the UAV images for individual tree crowns, which was then used as inputs for a machine learning algorithm to predict percent leaf and branch cover. We obtained the species identities of 2000 crowns in the images via field mapping. The objectives of this study are to (1) determined if machine learning algorithms, applied to UAV images, can effectively quantify changes in leaf cover, which we term "deciduousness; (2) determine how liana cover effects deciduousness and (3) test how well UAV-derived deciduousness patterns match satellite-derived temporal patterns. Machine learning algorithms trained on a variety of image parameters could effectively determine leaf cover, despite variation in lighting and viewing angles. Crowns with higher liana cover have less overall deciduousness (tree + liana together) than crowns with lower liana cover. Individual crown deciduousness, summed over all crowns measured in the 50-ha plot, showed a similar seasonal pattern as MODIS EVI composited over 10 years. However, MODIS EVI phenology was "greened" up earlier than UAV-based deciduousness, perhaps reflecting the new late dry season leaf flush that increases EVI but not overall leaf cover. We discuss how the potential mechanisms that explain variation among species and between trees and lianas and the consequences for these variation for ecosystem processes and modeling.

Perspectivs and challenges of phenology research on South America

NASA Astrophysics Data System (ADS)

Patrícia Morellato, Leonor

2017-04-01

Detecting plant responses to environmental changes across the Southern Hemisphere is an important question in the global agenda, as there is still a shortage of studies addressing phenological trends related to global warming. Here I bring a fresh perspective on the current knowledge of South America's phenology, and discusss the challenges and future research agendas for one of the most diverse regions of the world. I will syntethize: (i) What is the current focus of contemporany phenological research in South America? (ii) Is phenology contributing to the detection of trends and shifts related to climate or antropogenic changes? (iii) How has phenology been integrated to conservation, restoration, and management of natural vegetation and endangered species? (iv) What would be the main challenges and new avenues for South American phenological research in the 21st century? (v) Can we move towards phenology monitoring networks, linked to citizen science and education? My perspective is based on recent reviews addressing the Southeastern Hemisphere, South America, and Neotropical phenology; and on reviews and essays on the contribution of phenological research to biodiversity conservation, management, and ecological restoration, emphasizing tropical, species-rich ecosystems. Phenological research has grown at an unprecedented rate in the last 20 years, surpassing 100 articles per year after 2010. There is still a predominance of short-term studies (2-3 years) describing patterns and drivers for reproduction and leaf exchange. Only 10 long-term studies were found, based on direct observations or plant traps, and this number did not add much to the previous surveys. Therefore, we remain in need of more long-term studies to enhance the contribution of phenology to climate change research in South America. It is also mandatory to bring conservation issues to phenology research. The effects of climatic and antropogenic changes on plant phenology have been addressed rarely, but the few published studies have shown the importance of taking phenology into account for forest managment, restoration planning, and to assess plant responses to land-use changes. The main challange remains to establish successfull monitoring programs, which could be partially achieved using near remote phenology digital cameras or phenocams. Phenocams are a relative low-cost tool for taking photographs from vegetation on a daily basis, reducing manual labor. Furthermore, cameras can monitor several sites simultaneously, therefore increasinfg the spatial coverage of phenological moitoring. Phenocams are successfuly detecting leaf changes, but reproductive phenology is still an issue. Networks of phenocams already exist in north America and we are starting the first phenocam network for South America, but consistent financial support and an effective collaboration with the existing networks are to be sought for the success of this endeavour. The integrations of local populations on phenology data collection and observations would be a effective strategy to fill that gap and enroll citzens on scientific activities linked to conservation and education. Still, citizen science is largelly unexplored across South America, and remains as one of the most important goal in penology research for the next decades.

Phenology prediction component of GypsES

Treesearch

Jesse A. Logan; Lukas P. Schaub; F. William Ravlin

1991-01-01

Prediction of phenology is an important component of most pest management programs, and considerable research effort has been expended toward development of predictive tools for gypsy moth phenology. Although phenological prediction is potentially valuable for timing of spray applications (e.g. Bt, or Gypcheck) and other management activities (e.g. placement and...

Use of intraspecific variation in thermal responses for estimating an elevational cline in the timing of cold hardening in a sub-boreal conifer.

PubMed

Ishizuka, W; Ono, K; Hara, T; Goto, S

2015-01-01

To avoid winter frost damage, evergreen coniferous species develop cold hardiness with suitable phenology for the local climate regime. Along the elevational gradient, a genetic cline in autumn phenology is often recognised among coniferous populations, but further quantification of evolutionary adaptation related to the local environment and its responsible signals generating the phenological variation are poorly understood. We evaluated the timing of cold hardening among populations of Abies sachalinensis, based on time series freezing tests using trees derived from four seed source populations × three planting sites. Furthermore, we constructed a model to estimate the development of hardening from field temperatures and the intraspecific variations occurring during this process. An elevational cline was detected such that high-elevation populations developed cold hardiness earlier than low-elevation populations, representing significant genetic control. Because development occurred earlier at high-elevation planting sites, the genetic trend across elevation overlapped with the environmental trend. Based on the trade-off between later hardening to lengthen the active growth period and earlier hardening to avoid frost damage, this genetic cline would be adaptive to the local climate. Our modelling approach estimated intraspecific variation in two model components: the threshold temperature, which was the criterion for determining whether the trees accumulated the thermal value, and the chilling requirement for trees to achieve adequate cold hardiness. A higher threshold temperature and a lower chilling requirement could be responsible for the earlier phenology of the high-elevation population. These thermal responses may be one of the important factors driving the elevation-dependent adaptation of A. sachalinensis. © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands.

Physiology-phenology interactions in a productive semi-arid pine forest.

PubMed

Maseyk, Kadmiel S; Lin, Tongbao; Rotenberg, Eyal; Grünzweig, José M; Schwartz, Amnon; Yakir, Dan

2008-01-01

This study explored possible advantages conferred by the phase shift between leaf phenology and photosynthesis seasonality in a semi-arid Pinus halepensis forest system, not seen in temperate sites. Leaf-scale measurements of gas exchange, nitrogen and phenology were used on daily, seasonal and annual time-scales. Peak photosynthesis was in late winter, when high soil moisture, mild temperatures and low leaf vapour pressure deficit (D(L)) allowed high rates associated with high water- and nitrogen-use efficiencies. Self-sustained new needle growth through the dry and hot summer maximized photosynthesis in the following wet season, without straining carbon storage. Low rates of water loss were associated with increasing sensitivity of stomatal conductance (g(s)) to soil moisture below a relative extractable water (REW) of 0.4, and decreased g(s )sensitivity to D(L) below REW of approx. 0.2. This response was captured by the modified Ball-Berry (Leuning) model. While most physiological parameters and responses measured were typical of temperate pines, the photosynthesis-phenological phasing contributed to high productivity under warm-dry conditions. This contrasts with reported effects of short-term periodical droughts and could lead to different predictions of the effect of warming and drying climate on pine forest productivity.

Ecophysiological and phenological strategies in seasonally-dry ecosystems: an ecohydrological approach

NASA Astrophysics Data System (ADS)

Vico, Giulia; Manzoni, Stefano; Thompson, Sally; Molini, Annalisa; Porporato, Amilcare

2015-04-01

Seasonally-dry climates are particularly challenging for vegetation, as they are characterized by prolonged dry periods and often marked inter-annual variability. During the dry season plants face predictable physiological stress due to lack of water, whereas the inter-annual variability in rainfall timing and amounts requires plants to develop flexible adaptation strategies. The variety of strategies observed across seasonally-dry (Mediterranean and tropical) ecosystems is indeed wide - ranging from near-isohydric species that adjust stomatal conductance to avoid drought, to anisohydric species that maintain gas exchange during the dry season. A suite of phenological strategies are hypothesized to be associated to ecophysiological strategies. Here we synthetize current knowledge on ecophysiological and phenological adaptations through a comprehensive ecohydrological model linking a soil water balance to a vegetation carbon balance. Climatic regimes are found to select for different phenological strategies that maximize the long-term plant carbon uptake. Inter-annual variability of the duration of the wet season allows coexistence of different drought-deciduous strategies. In contrast, short dry seasons or access to groundwater favour evergreen species. Climatic changes causing more intermittent rainfall and/or shorter wet seasons are predicted to favour drought-deciduous species with opportunistic water use.

Warmest extreme year in U.S. history alters thermal requirements for tree phenology.

PubMed

Carter, Jacob M; Orive, Maria E; Gerhart, Laci M; Stern, Jennifer H; Marchin, Renée M; Nagel, Joane; Ward, Joy K

2017-04-01

The frequency of extreme warm years is increasing across the majority of the planet. Shifts in plant phenology in response to extreme years can influence plant survival, productivity, and synchrony with pollinators/herbivores. Despite extensive work on plant phenological responses to climate change, little is known about responses to extreme warm years, particularly at the intraspecific level. Here we investigate 43 populations of white ash trees (Fraxinus americana) from throughout the species range that were all grown in a common garden. We compared the timing of leaf emergence during the warmest year in U.S. history (2012) with relatively non-extreme years. We show that (a) leaf emergence among white ash populations was accelerated by 21 days on average during the extreme warm year of 2012 relative to non-extreme years; (b) rank order for the timing of leaf emergence was maintained among populations across extreme and non-extreme years, with southern populations emerging earlier than northern populations; (c) greater amounts of warming units accumulated prior to leaf emergence during the extreme warm year relative to non-extreme years, and this constrained the potential for even earlier leaf emergence by an average of 9 days among populations; and (d) the extreme warm year reduced the reliability of a relevant phenological model for white ash by producing a consistent bias toward earlier predicted leaf emergence relative to observations. These results demonstrate a critical need to better understand how extreme warm years will impact tree phenology, particularly at the intraspecific level.

Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations

NASA Astrophysics Data System (ADS)

de Moura, Yhasmin Mendes; Galvão, Lênio Soares; Hilker, Thomas; Wu, Jin; Saleska, Scott; do Amaral, Cibele Hummel; Nelson, Bruce Walker; Lopes, Aline Pontes; Wiedeman, Kenia K.; Prohaska, Neill; de Oliveira, Raimundo Cosme; Machado, Carolyne Bueno; Aragão, Luiz E. O. C.

2017-09-01

The association between spectral reflectance and canopy processes remains challenging for quantifying large-scale canopy phenological cycles in tropical forests. In this study, we used a tower-mounted hyperspectral camera in an eastern Amazon forest to assess how canopy spectral signals of three species are linked with phenological processes in the 2012 dry season. We explored different approaches to disentangle the spectral components of canopy phenology processes and analyze their variations over time using 17 images acquired by the camera. The methods included linear spectral mixture analysis (SMA); principal component analysis (PCA); continuum removal (CR); and first-order derivative analysis. In addition, three vegetation indices potentially sensitive to leaf flushing, leaf loss and leaf area index (LAI) were calculated: the Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI) and the entitled Green-Red Normalized Difference (GRND) index. We inspected also the consistency of the camera observations using Moderate Resolution Imaging Spectroradiometer (MODIS) and available phenological data on new leaf production and LAI of young, mature and old leaves simulated by a leaf demography-ontogeny model. The results showed a diversity of phenological responses during the 2012 dry season with related changes in canopy structure and greenness values. Because of the differences in timing and intensity of leaf flushing and leaf shedding, Erisma uncinatum, Manilkara huberi and Chamaecrista xinguensis presented different green vegetation (GV) and non-photosynthetic vegetation (NPV) SMA fractions; distinct PCA scores; changes in depth, width and area of the 681-nm chlorophyll absorption band; and variations over time in the EVI, GRND and NDVI. At the end of dry season, GV increased for Erisma uncinatum, while NPV increased for Chamaecrista xinguensis. For Manilkara huberi, the NPV first increased in the beginning of August and then decreased toward September with new foliage. Variations in red-edge position were not statistically significant between the species and across dates at the 95% confidence level. The camera data were affected by view-illumination effects, which reduced the SMA shade fraction over time. When MODIS data were corrected for these effects using the Multi-Angle Implementation of Atmospheric Correction Algorithm (MAIAC), we observed an EVI increase toward September that closely tracked the modeled LAI of mature leaves (3-5 months). Compared to the EVI, the GRND was a better indicator of leaf flushing because the modeled production of new leaves peaked in August and then declined in September following the GRND closely. While the EVI was more related to changes in mature leaf area, the GRND was more associated with new leaf flushing.

Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration

USGS Publications Warehouse

Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.

2015-01-01

Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.

Degree Day Requirements for Kudzu Bug (Hemiptera: Plataspidae), a Pest of Soybeans.

PubMed

Grant, Jessica I; Lamp, William O

2018-04-02

Understanding the phenology of a new potential pest is fundamental for the development of a management program. Megacopta cribraria Fabricius (Hemiptera: Plataspidae), kudzu bug, is a pest of soybeans first detected in the United States in 2009 and in Maryland in 2013. We observed the phenology of kudzu bug life stages in Maryland, created a Celsius degree-day (CDD) model for development, and characterized the difference between microhabitat and ambient temperatures of both kudzu, Pueraria montana (Lour.) Merr. (Fabales: Fabaceae) and soybeans, Glycine max (L.) Merrill (Fabales: Fabaceae). In 2014, low population numbers yielded limited resolution from field phenology observations. We observed kudzu bug populations persisting within Maryland; but between 2013 and 2016, populations were low compared to populations in the southeastern United States. Based on the degree-day model, kudzu bug eggs require 80 CDD at a minimum temperature of 14°C to hatch. Nymphs require 545 CDD with a minimum temperature of 16°C for development. The CDD model matches field observations when factoring a biofix date of April 1 and a minimum preoviposition period of 17 d. The model suggests two full generations per year in Maryland. Standard air temperature monitors do not affect model predictions for pest management, as microhabitat temperature differences did not show a clear trend between kudzu and soybeans. Ultimately, producers can predict the timing of kudzu bug life stages with the CDD model for the use of timing management plans in soybean fields.

The effect of winter length on duration of dormancy and survival of specialized herbivorous Rhagoletis fruit flies from high elevation environments with acyclic climatic variability.

PubMed

Rull, J; Tadeo, E; Lasa, R; Aluja, M

2017-09-19

Dormancy can be defined as a state of suppressed development allowing insects to cope with adverse conditions and plant phenology. Among specialized herbivorous insects exploiting seasonal resources, diapause frequently evolves as a strategy to adjust to predictable plant seasonal cycles. To cope with acyclic and unpredictable climatic events, it has been found for some insects that a proportion of the population undergoes prolonged dormancy. We compared the response of three species in the Rhagoletis cingulata species group exploiting plants differing in fruiting phenology from environments varying in frequency and timing of acyclic climatic catastrophic events (frost during flowering and fruit set) and varying also in the time of the onset of the rainy season. Small proportions (10 months), and large proportions of pupae died without emerging as adults. The number of days elapsed from the end of artificial winter and adult eclosion was longer for R. cingulata exploiting late fruiting Prunus serotina in Northeastern Mexico than for flies recovered from earlier fruiting plants in the central Altiplano. Rhagoletis turpiniae and northeastern R. cingulata pupae suffered high proportions of parasitism. Large proportions of R. cingulata from central Mexico engaging in prolonged dormancy may be explained by the fact that flowering and fruit set for its host, P. serotina var capuli, driven by the timing of maximum precipitation, matches a period of highest probability of frost often resulting in large areas with fruitless trees at unpredictable time intervals. As a consequence of differences in host plant fruiting phenology, central and northeastern Mexican R. cingulata were found to be allochronically isolated. Prolonged dormancy may have resulted in escape from parasitism.

Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index

Treesearch

Taehee Hwang; Conghe Song; James Vose; Lawrence Band

2011-01-01

Forest canopy phenology is an important constraint on annual water and carbon budgets, and responds to regional interannual climate variation. In steep terrain, there are complex spatial variations in phenology due to topographic influences on microclimate, community composition, and available soil moisture. In this study, we investigate spatial patterns of phenology...

USA National Phenology Network observational data documentation

USGS Publications Warehouse

Rosemartin, Alyssa H.; Denny, Ellen G.; Gerst, Katharine L.; Marsh, R. Lee; Posthumus, Erin E.; Crimmins, Theresa M.; Weltzin, Jake F.

2018-04-25

The goals of the USA National Phenology Network (USA-NPN, www.usanpn.org) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to advance the science of phenology and facilitate ecosystem stewardship by providing phenological information freely and openly. To accomplish these goals, the USA-NPN National Coordinating Office (NCO) delivers observational data on plant and animal phenology in several formats, including minimally processed status and intensity datasets and derived phenometrics for individual plants, sites, and regions. This document describes the suite of observational data products delivered by the USA National Phenology Network, covering the period 2009–present for the United States and accessible via the Phenology Observation Portal (http://dx.doi.org/10.5066/F78S4N1V) and via an Application Programming Interface. The data described here have been used in diverse research and management applications, including over 30 publications in fields such as remote sensing, plant evolution, and resource management.

Amphibian breeding phenology trends under climate change: predicting the past to forecast the future.

PubMed

Green, David M

2017-02-01

Global climate warming is predicted to hasten the onset of spring breeding by anuran amphibians in seasonal environments. Previous data had indicated that the breeding phenology of a population of Fowler's Toads (Anaxyrus fowleri) at their northern range limit had been progressively later in spring, contrary to generally observed trends in other species. Although these animals are known to respond to environmental temperature and the lunar cycle to commence breeding, the timing of breeding should also be influenced by the onset of overwintering animals' prior upward movement through the soil column from beneath the frost line as winter becomes spring. I used recorded weather data to identify four factors of temperature, rainfall and snowfall in late winter and early spring that correlated with the toads' eventual date of emergence aboveground. Estimated dates of spring emergence of the toads calculated using a predictive model based on these factors, as well as the illumination of the moon, were highly correlated with observed dates of emergence over 24 consecutive years. Using the model to estimate of past dates of spring breeding (i.e. retrodiction) indicated that even three decades of data were insufficient to discern any appreciable phenological trend in these toads. However, by employing weather data dating back to 1876, I detected a significant trend over 140 years towards earlier spring emergence by the toads by less than half a day/decade, while, over the same period of time, average annual air temperature and annual precipitation had both increased. Changes in the springtime breeding phenology for late-breeding species, such as Fowler's Toads, therefore may conform to expectations of earlier breeding under global warming. Improved understanding of the environmental cues that bring organisms out of winter dormancy will enable better interpretation of long-term phenological trends. © 2016 John Wiley & Sons Ltd.

Phenology Across the LTER Network: Initial Findings, Future Directions

NASA Astrophysics Data System (ADS)

Henebry, G. M.

2007-12-01

Phenology is, in the words of Aldo Leopold, a "horizontal science" that cuts across and binds together multiple biological disciplines. It is a far-reaching but poorly understood aspect of the environmental sciences. Phenological research has been a component of the Long Term Ecological Research (LTER) Network at several sites over the years. However, it has not received the attention or resources to bring it to the forefront as an effective theme for interdisciplinary and cross-site synthesis. With the recent establishment of the USA National Phenology Network (USA-NPN), it is appropriate to assess the status of phenological knowledge across the LTER Network. A workshop funded by the LTER Network Office took place at the Sevilleta Field Station during February 26 to March 2, 2007. From the workshop three main products emerged: (1) an inventory of LTER phenology datasets, (2) establishment of a website to facilitate information interchange, and (3) a white paper recommending next steps for the LTER Network to engage the USA-NPN. This poster relates the findings and recommendations of the workshop, including a summary of phenologically explicit and phenologically implicit LTER datasets and illustrations of how the climatic envelopes described by simple weather variables can provide context for phenological comparisons within and across sites.

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers.

PubMed

Gamon, John A; Huemmrich, K Fred; Wong, Christopher Y S; Ensminger, Ingo; Garrity, Steven; Hollinger, David Y; Noormets, Asko; Peñuelas, Josep

2016-11-15

In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying "photosynthetic phenology" from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as chlorophyll/carotenoid ratios, and evergreen photosynthetic activity, leading to a "chlorophyll/carotenoid index" (CCI) that tracks evergreen photosynthesis at multiple spatial scales. When calculated from NASA's Moderate Resolution Imaging Spectroradiometer satellite sensor, the CCI closely follows the seasonal patterns of daily gross primary productivity of evergreen conifer stands measured by eddy covariance. This discovery provides a way of monitoring evergreen photosynthetic activity from optical remote sensing, and indicates an important regulatory role for carotenoid pigments in evergreen photosynthesis. Improved methods of monitoring photosynthesis from space can improve our understanding of the global carbon budget in a warming world of changing vegetation phenology.

Climate warming: a loss of variation in populations can accompany reproductive shifts.

PubMed

Massot, Manuel; Legendre, Stéphane; Fédérici, Pierre; Clobert, Jean

2017-09-01

The most documented response of organisms to climate warming is a change in the average timing of seasonal activities (phenology). Although we know that these average changes can differ among species and populations, we do not know whether climate warming impacts within-population variation in phenology. Using data from five study sites collected during a 13-year survey, we found that the increase in spring temperatures is associated with a reproductive advance of 10 days in natural populations of common lizards (Zootoca vivipara). Interestingly, we show a correlated loss of variation in reproductive dates within populations. As illustrated by a model, this shortening of the reproductive period can have significant negative effects on population dynamics. Consequently, we encourage tests in other species to assess the generality of decreased variation in phenological responses to climate change. © 2017 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.

Review: advances in in situ and satellite phenological observations in Japan

NASA Astrophysics Data System (ADS)

Nagai, Shin; Nasahara, Kenlo Nishida; Inoue, Tomoharu; Saitoh, Taku M.; Suzuki, Rikie

2016-04-01

To accurately evaluate the responses of spatial and temporal variation of ecosystem functioning (evapotranspiration and photosynthesis) and services (regulating and cultural services) to the rapid changes caused by global warming, we depend on long-term, continuous, near-surface, and satellite remote sensing of phenology over wide areas. Here, we review such phenological studies in Japan and discuss our current knowledge, problems, and future developments. In contrast with North America and Europe, Japan has been able to evaluate plant phenology along vertical and horizontal gradients within a narrow area because of the country's high topographic relief. Phenological observation networks that support scientific studies and outreach activities have used near-surface tools such as digital cameras and spectral radiometers. Differences in phenology among ecosystems and tree species have been detected by analyzing the seasonal variation of red, green, and blue digital numbers (RGB values) extracted from phenological images, as well as spectral reflectance and vegetation indices. The relationships between seasonal variations in RGB-derived indices or spectral characteristics and the ecological and CO2 flux measurement data have been well validated. In contrast, insufficient satellite remote-sensing observations have been conducted because of the coarse spatial resolution of previous datasets, which could not detect the heterogeneous plant phenology that results from Japan's complex topography and vegetation. To improve Japanese phenological observations, multidisciplinary analysis and evaluation will be needed to link traditional phenological observations with "index trees," near-surface and satellite remote-sensing observations, "citizen science" (observations by citizens), and results published on the Internet.

Phenology of Spondias tuberosa Arruda (Anacardiaceae) under different landscape management regimes and a proposal for a rapid phenological diagnosis using local knowledge

PubMed Central

2013-01-01

Background Studies aimed at investigating the influence of habitat change on species phenology. Studies that investigate people's perceptions of the phenology of certain species still area few; yet this approach is important for effective decision-making for conservation. The aim of this study was to investigate the phenology of Spondias tuberosa Arruda (Anacardiaceae), a native species of economic and ecological importance in northeastern Brazil, in five landscape units (LUs) (Mountain, Mountain Base, Pasture, Cultivated Areas and Homegardens) of a Caatinga region in Altinho, Pernambuco, northeastern Brazil. These data could then be compared with local people's perceptions of the species’ phenophases. Method Collection of phenological data was carried out monthly from February 2007 to January 2009 and included activity, intensity and synchronization of reproductive and vegetative phenophases. Ethnobotanical data were gathered using a collaborative approach to access local people’s knowledge about the species’ phenological schedule. Results There were no significant differences in the intensity of phenophases among LUs, and there was a correspondence between people’s perception of phenophases and the phenological data collected. The data show that the different management practices for LUs did not influence the phenology of the species. Conclusion The main conclusion of this study is the use of traditional knowledge as interesting tool for rapid phenological diagnosis. However further studies need to be developed to test this tool in other environments and cultural contexts. PMID:23369197

How Can the USA National Phenology Network's Data Resource Benefit You? Recent Applications of the Phenology Data and Information Housed in the National Phenology Database

NASA Astrophysics Data System (ADS)

Crimmins, T. M.

2015-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) serves science and society by promoting a broad understanding of plant and animal phenology and the relationships among phenological patterns and all aspects of environmental change. The National Phenology Database, maintained by the USA-NPN, is experiencing steady growth in the number of data records it houses. Since 2009, over 5,500 participants in Nature's Notebook, the national-scale, multi-taxa phenology observation program coordinated by the USA-NPN, have contributed nearly 6 million observation records of plants and animals. The phenology data curated by the USA-NPN are being used in a rapidly growing number of applications for science, conservation and resource management. Data and data products generated by the USA-NPN have been used in 17 peer-reviewed publications to date. Additionally, phenology data collected via Nature's Notebook is actively informing decisions ranging from efficiently scheduling street-sweeping activities to keep dropped leaves from entering inland lakes, to timing the spread of herbicide or other restoration activities to maximize their efficacy. We demonstrate several types of questions that can be addressed with this observing system and the resultant data, and highlight several ongoing local- to national-scale projects as well as some recently published studies. Additional data-mining and exploration by interested researchers and resource managers will undoubtedly continue to demonstrate the value of these data.

Predictions of heading date in bread wheat (Triticum aestivum L.) using QTL-based parameters of an ecophysiological model

PubMed Central

Bogard, Matthieu; Ravel, Catherine; Paux, Etienne; Bordes, Jacques; Balfourier, François; Chapman, Scott C.; Le Gouis, Jacques; Allard, Vincent

2014-01-01

Prediction of wheat phenology facilitates the selection of cultivars with specific adaptations to a particular environment. However, while QTL analysis for heading date can identify major genes controlling phenology, the results are limited to the environments and genotypes tested. Moreover, while ecophysiological models allow accurate predictions in new environments, they may require substantial phenotypic data to parameterize each genotype. Also, the model parameters are rarely related to all underlying genes, and all the possible allelic combinations that could be obtained by breeding cannot be tested with models. In this study, a QTL-based model is proposed to predict heading date in bread wheat (Triticum aestivum L.). Two parameters of an ecophysiological model (V sat and P base, representing genotype vernalization requirements and photoperiod sensitivity, respectively) were optimized for 210 genotypes grown in 10 contrasting location × sowing date combinations. Multiple linear regression models predicting V sat and P base with 11 and 12 associated genetic markers accounted for 71 and 68% of the variance of these parameters, respectively. QTL-based V sat and P base estimates were able to predict heading date of an independent validation data set (88 genotypes in six location × sowing date combinations) with a root mean square error of prediction of 5 to 8.6 days, explaining 48 to 63% of the variation for heading date. The QTL-based model proposed in this study may be used for agronomic purposes and to assist breeders in suggesting locally adapted ideotypes for wheat phenology. PMID:25148833

Continuous but diverse advancement of spring-summer phenology in response to climate warming across the Qinghai-Tibetan Plateau

DOE PAGES

Zheng, Zhoutao; Zhu, Wenquan; Chen, Guangsheng; ...

2016-04-25

The Qinghai-Tibetan Plateau (QTP) is more vulnerable and sensitive to climate change than many other regions worldwide because of its high altitude, permafrost geography, and harsh physical environment. As a sensitive bio-indicator of climate change, plant phenology shift in this region has been intensively studied during the recent decades, primarily based on satellite-retrieved data. However, great controversy still exists regarding the change in direction and magnitudes of spring-summer phenology. Based on a large number (11,000+ records) of long-term and continuous ground observational data for various plant species, our study intended to more comprehensively assess the changing trends of spring-summer phenologymore » and their relationships with climatic change across the QTP. The results indicated a continuous advancement (–2.69 days decade –1) in spring-summer phenology from 1981 to 2011, with an even more rapid advancement during 2000–2011 (–3.13 days decade –1), which provided new field evidence for continuous advancement in spring-summer phenology across the QTP. However, diverse advancing rates in spring-summer phenology were observed for different vegetation types, thermal conditions, and seasons. The advancing trends matched well with the difference in sensitivity of spring-summer phenology to increasing temperature, implying that the sensitivity of phenology to temperature was one of the major factors influencing spring-summer phenology shifts. Besides, increased precipitation could advance the spring-summer phenology. As a result, the response of spring-summer phenology to temperature tended to be stronger from east to west across all species, while the response to precipitation showed no consistent spatial pattern.« less

Continuous but diverse advancement of spring-summer phenology in response to climate warming across the Qinghai-Tibetan Plateau

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Zhoutao; Zhu, Wenquan; Chen, Guangsheng

The Qinghai-Tibetan Plateau (QTP) is more vulnerable and sensitive to climate change than many other regions worldwide because of its high altitude, permafrost geography, and harsh physical environment. As a sensitive bio-indicator of climate change, plant phenology shift in this region has been intensively studied during the recent decades, primarily based on satellite-retrieved data. However, great controversy still exists regarding the change in direction and magnitudes of spring-summer phenology. Based on a large number (11,000+ records) of long-term and continuous ground observational data for various plant species, our study intended to more comprehensively assess the changing trends of spring-summer phenologymore » and their relationships with climatic change across the QTP. The results indicated a continuous advancement (–2.69 days decade –1) in spring-summer phenology from 1981 to 2011, with an even more rapid advancement during 2000–2011 (–3.13 days decade –1), which provided new field evidence for continuous advancement in spring-summer phenology across the QTP. However, diverse advancing rates in spring-summer phenology were observed for different vegetation types, thermal conditions, and seasons. The advancing trends matched well with the difference in sensitivity of spring-summer phenology to increasing temperature, implying that the sensitivity of phenology to temperature was one of the major factors influencing spring-summer phenology shifts. Besides, increased precipitation could advance the spring-summer phenology. As a result, the response of spring-summer phenology to temperature tended to be stronger from east to west across all species, while the response to precipitation showed no consistent spatial pattern.« less

Multi-Scale Analysis of Trends in Northeastern Temperate Forest Springtime Phenology

NASA Astrophysics Data System (ADS)

Moon, M.; Melaas, E. K.; Sulla-menashe, D. J.; Friedl, M. A.

2017-12-01

The timing of spring leaf emergence is highly variable in many ecosystems, exerts first-order control growing season length, and significantly modulates seasonally-integrated photosynthesis. Numerous studies have reported trends toward earlier spring phenology in temperate forests, with some papers indicating that this trend is also leading to increased carbon uptake. At broad spatial scales, however, most of these studies have used data from coarse spatial resolution instruments such as MODIS, which does not resolve ecologically important landscape-scale patterns in phenology. In this work, we examine how long-term trends in spring phenology differ across three data sources acquired at different scales of measurements at the Harvard Forest in central Massachusetts. Specifically, we compared trends in the timing of phenology based on long-term in-situ measurements of phenology, estimates based on eddy-covariance measurements of net carbon uptake transition dates, and from two sources of satellite-based remote sensing (MODIS and Landsat) land surface phenology (LSP) data. Our analysis focused on the flux footprint surrounding the Harvard Forest Environmental Measurements (EMS) tower. Our results reveal clearly defined trends toward earlier springtime phenology in Landsat LSP and in the timing of tower-based net carbon uptake. However, we find no statistically significant trend in springtime phenology measured from MODIS LSP data products, possibly because the time series of MODIS observations is relatively short (13 years). The trend in tower-based transition data exhibited a larger negative value than the trend derived from Landsat LSP data (-0.42 and -0.28 days per year for 21 and 28 years, respectively). More importantly, these results have two key implications regarding how changes in spring phenology are impacting carbon uptake at landscape-scale. First, long-term trends in spring phenology can be quite different, depending on what data source is used to estimate the trend, and 2) the response of carbon uptake to climate change may be more sensitive than the response of land surface phenology itself.

Effect of Climate Change on Vegetation Phenology of Different Land Cover Types on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cheng, M.; Jin, J.

2017-12-01

Vegetation phenology is one of the most sensitive bio-indicators of climate change, and it has received increasing interests in the context of global warming. As one of the most sensitive areas to global change, the Tibetan Plateau is a unique region to study the trends in vegetation phenology in response to climate change because of its unique vegetation composition, climate features and low-level human disturbance. Although some studies have aroused wide controversies about the actual plant phenology patterns in the Tibetan Plateau, yet the reasons remain unclear. In particular, the phenology characteristics of sparse herbaceous or sparse shrub and evergreen forest that are mostly located in the northwest and southeast of the Tibetan Plateau remain less studied. In this study, the spatio-temporal patterns of the start (SOS), end (EOS) and length (LOS) of the vegetation growing season for six vegetation types in the Tibetan Plateau, including evergreen broadleaf forests, evergreen coniferous forests, evergreen shrub, meadow, steppe and sparse herbaceous or sparse shrub, were quantified from 1982 to 2014 using NOAA/AVHRR NDVI data set at a spatial resolution of 0.05°×0.05° and 7-day intervals using NDVI relative change rate threshold and sixth order polynomial fit models. Assisted with the monthly precipitation and temperature data, the relative effects of changing climates on the variability of phenology were also examined. Diverse phenological changes were observed for different land cover types, with an advancing start of growing season (SOS), delaying end of growing season (EOS) and increasing length of growing season (LOS) in the eastern Tibetan Plateau where meadow was the dominant vegetation type, but with the opposite changes in the steppe and sparse herbaceous or sparse shrub regions which are mostly located in the northwestern and western edges of the Tibetan Plateau. Correlation analysis indicated that sufficient preseason precipitation may delay the SOS of evergreen forests in the southeastern Plateau and advance the SOS of steppe and sparse herbaceous or sparse shrub in relatively arid areas, while the advance of SOS in meadow areas could be related to higher preseason temperature.

Early forecasting of crop condition using an integrative remote sensing method for corn and soybeans in Iowa and Illinois, USA

NASA Astrophysics Data System (ADS)

Seo, Bumsuk; Lee, Jihye; Kang, Sinkyu

2017-04-01

The weather-related risks in crop production is not only crucial for farmers but also for market participants and policy makers since securing food supply is an important issue for society. While crop growth condition and phenology are essential information about such risks, the extensive observations on those are often non-existent in many parts of the world. In this study, we have developed a novel integrative approach to remotely sense crop growth condition and phenology at a large scale. For corn and soybeans in Iowa and Illinois of USA (2003-2014), we assessed crop growth condition and crop phenology by EO data and validated it against the United States Department of Agriculture (USDA) National Agriculture Statistics System (NASS) crop statistics. For growth condition, we used two distinguished approaches to acquire crop condition indicators: a process-based crop growth modelling and a satellite NDVI based method. Based on their pixel-wise historic distributions, we determined relative growth conditions and scaled-down to the state-level. For crop phenology, we calculated three crop phenology metrics [i.e., start of season (SOS), end of season (EOS), and peak of season (POS)] at the pixel level from MODIS 8-day Normalized Difference Vegetation Index (NDVI). The estimates were compared with the Crop Progress and Condition (CPC) data of NASS. For the condition, the state-level 10-day estimates showed a moderate agreement (RMSE < 15.0%) and the average accuracy of the normal/bad year classification was well (> 70%). Notably, the condition estimates corresponded to the severe soybeans disease in 2003 and the drought in 2012 for both crops. For the phenology, the average RMSE of the estimates was 8.6 day for the all three metrics. The average |ME| was smaller than 1.0 day after bias correction. The proposed method enables us to evaluate crop growth at any given period and place. Global climate changes are increasing the risk in agricultural production such as long-term drought. We hope that the presented remote sensing method for crop condition and crop phenology contributes to reducing the growing risk of crop production in the Earth.

A 280-Year Long Series of Phenological Observations of Cherry Tree Blossoming Dates for Switzerland

NASA Astrophysics Data System (ADS)

Rutishauser, T.; Luterbacher, J.; Wanner, H.

2003-04-01

Phenology is generally described as the timing of life cycle phases or activities of plants and animals in their temporal occurrence throughout the year (Lieth 1974). Recent studies have shown that meteorological and climatological impacts leave their 'fingerprints' across natural systems in general and strongly influence the seasonal activities of single animal and plant species. During the 20th century, phenological observation networks have been established around the world to document and analyze the influence of the globally changing climate to plants and wildlife. This work presents a first attempt of a unique 280-year long series of phenological observations of cherry tree blossoming dates for the Swiss plateau region. In Switzerland, a nation-wide phenological observation network has been established in 1951 currently documenting 69 phenophases of 26 different plant species. A guidebook seeks to increase objectiveness in the network observations. The observations of the blooming of the cherry tree (prunus avium) were chosen to calculate a mean series for the Swiss plateau region with observations from altitudes ranging between 370 and 860 asl. A total number of 737 observations from 21 stations were used. A linear regression was established between the mean blooming date and altitude in order to correct the data to a reference altitude level. Other ecological parameters were unaccounted for. The selected network data series from 1951 to 2000 was combined and prolonged with observations from various sources back to 1721. These include several historical observation series by farmers, clergymen and teachers, data from various stations collected at the newly established Swiss meteorological network from 1864 to 1873 and the single long series of observations from Liestal starting in 1894. The homogenized time series of observations will be compared with reconstructions of late winter temperatures as well as statistical estimations of blooming time based on long instrumental data from Europe. In addition, the series is one of the few historical phenological records to assess past climate and ecological changes. Lieth, H. (1974). Phenology and Seasonality Modeling. Berlin, Heidelberg, New York, Springer.

Incorporating Animals in Phenological Assessments: USA National Phenology Network Methods to Observe Animal Phenology

NASA Astrophysics Data System (ADS)

Miller-Rushing, A. J.; Weltzin, J. F.

2009-12-01

Many assessments of phenology, particularly those operating at large scales, focus on the phenology of plants, in part because of the relevance of plants in cycles of leaf greening and browning that are visible from satellite-based remote sensing, and because plants contribute significantly to global and regional biogeochemical cycles. The USA National Phenology Network (USA-NPN), a consortium of individuals, agencies, and organizations, promotes integrated assessments of both plant and animal phenology. The network is currently developing standard methods to add animal phenology to existing assessments of plant phenology. The first phase will of the standard methods will be implemented online in spring 2010. The methods for observing animals will be similar to the standard methods for making on-the-ground observations of plants—observers will be asked to monitor a fixed location regularly throughout the year. During each visit, observers will answer a series of “yes-no” questions that address the phenological state of the species of interest: Is the species present? Is it mating? Is it feeding? And so on. We are currently testing this method in several national parks in the northeastern United States, including Acadia National Park and the Appalachian Trail. By collecting new observations of this sort for a range of animals—amphibians, birds, fish, insects, mammals, and reptiles—we will greatly increase the ability of scientists and natural resource managers to understand how temporal relationships among these species and the plants on which they depend may be changing. To bolster the data available, we are collaborating with existing monitoring programs to develop common monitoring techniques, data sharing technologies, and visualizations. We are also beginning to collect legacy datasets, such as one from North American Bird Phenology Program that includes 90 years of observations of bird migration times from across the continent. We believe that increasing the amount of animal phenology data available for scientists, natural resource managers, and educators, will greatly advance our understanding of phenological changes and their causes and consequences, particularly in this time of rapid environmental change.

Refined shape model fitting methods for detecting various types of phenological information on major U.S. crops

NASA Astrophysics Data System (ADS)

Sakamoto, Toshihiro

2018-04-01

Crop phenological information is a critical variable in evaluating the influence of environmental stress on the final crop yield in spatio-temporal dimensions. Although the MODIS (Moderate Resolution Imaging Spectroradiometer) Land Cover Dynamics product (MCD12Q2) is widely used in place of crop phenological information, the definitions of MCD12Q2-derived phenological events (e.g. green-up date, dormancy date) were not completely consistent with those of crop development stages used in statistical surveys (e.g. emerged date, harvested date). It has been necessary to devise an alternative method focused on detecting continental-scale crop developmental stages using a different approach. Therefore, this study aimed to refine the Shape Model Fitting (SMF) method to improve its applicability to multiple major U.S. crops. The newly-refined SMF methods could estimate the timing of 36 crop-development stages of major U.S. crops, including corn, soybeans, winter wheat, spring wheat, barley, sorghum, rice, and cotton. The newly-developed calibration process did not require any long-term field observation data, and could calibrate crop-specific phenological parameters, which were used as coefficients in estimated equation, by using only freely accessible public data. The calibration of phenological parameters was conducted in two steps. In the first step, the national common phenological parameters, referred to as X0[base], were calibrated by using the statistical data of 2008. The SMF method coupled using X0[base] was named the rSMF[base] method. The second step was a further calibration to gain regionally-adjusted phenological parameters for each state, referred to as X0[local], by using additional statistical data of 2015 and 2016. The rSMF method using the X0[local] was named the rSMF[local] method. This second calibration process improved the estimation accuracy for all tested crops. When applying the rSMF[base] method to the validation data set (2009-2014), the root mean square error (RMSE) of the rSMF[base]-derived estimates ranged from 7.1 days (corn) to 15.7 days (winter wheat). When using the rSMF[local] method, the RMSE of the rSMF[local]-derived estimates improved and ranged from 5.6 days (corn) to 12.3 days (winter wheat). The results showed that the second calibration step for the rSMF[local] method could correct the region-dependent bias error between the rSMF[base]-derived estimates and the statistical data. A comparison between the performances of the refined SMF methods and the MCD12Q2 products, indicated that both of the rSMF methods were superior to the MCD12Q2 products in estimating all phenological stages, except for the case of the rSMF[base]-derived barley emerged stages. The phenological stages for which the rSMF[local] showed the best estimation accuracy were the corn silking stage (RMSE = 4.3 days); the soybeans dropping leaves stage (RMSE = 4.9 days); the headed stages of winter wheat (RMSE = 11.1 days), barley (RMSE = 6.1 days), and sorghum (RMSE = 9.5 days); the spring-wheat harvested stage (RMSE = 5.5 days); the rice emerged stage (RMSE = 5.5 days), and the cotton squaring stage (RMSE = 6.6 days). These were more accurate than the results achieved by the MCD12Q2 products. In addition, the rSMF[local]-derived estimates were superior in terms of the reproducibility of the annual variation range, particularly of the late reproductive stages, such as the mature and harvested stages. The crop phenology maps derived from the SMF [local] method were also in good agreement with the relevant maps derived from statistics, and could reveal the characteristic spatial pattern of the key phenological stages at the continental scale with fine spatial resolution. For example, the winter-wheat headed stage clearly became later from south to north. The cotton squaring stage became earlier from the central region towards both coastal regions.

National and international organization of phenology as a tool for science, management and education in a changing environment

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; National Coordinating Office Of Usa National Phenology Network

2010-12-01

Patterns of phenology for plants and animals control ecosystem processes, determine land surface properties, control biosphere-atmosphere interactions, and affect food production, health, conservation, and recreation. The USA National Phenology Network (USA-NPN; www.usanpn.org), established in 2007, is a national science and monitoring initiative focused on phenology as a tool to understand how plants, animals and landscapes respond to climatic variability and change. Core functions of the National Coordinating Office (NCO) of USA-NPN are to provide a national information management system including databases, develop and implement internationally standardized phenology monitoring protocols, create partnerships for implementation, facilitate research and the development of decision support tools, and promote education and outreach activities related to phenology and climate change. USA-NPN has a number of new tools to facilitate science, management and education related to phenology at local, regional and national scales. The information management system includes an advanced on-line user interface to facilitate entry and download of contemporary organismal phenology data into the National Phenology Database, access to important historic phenology datasets, and a metadata editor for description, registration and search of phenology datasets. An integrated animal and plant phenology monitoring program provides internationally standardized methods and monitoring protocols for over 400 animal and plant species, with additional species added upon demand. Monitoring methods are designed to facilitate collection of sampling intensity and absence data for both plants and animals, and the interface enables the capture of considerable metadata (at granularities including observer, site, organism, and observation). National scale, in-situ observations since 2009 are now available for land product parameterization and validation, and USA-NPN is participating in the Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) Phenology Focus Group. Partnerships with a variety of other organizations benefit from recent development and distribution of standard operating procedures (SOPs) and web services with data input and output functions. USA-NPN facilitates research and the development of decision support tools through provision of communication, coordination and collaboration in a data-rich environment. Education and outreach are facilitated by new on-line training materials, in-person and distance workshops, and a strategic education plan in development. Finally, USA-NPN is collaborating with other national phenology networks around the globe to create an international community of practice for phenology within the collaborative infrastructure created by Group on Earth Observations (GEO).

Models for forecasting the flowering of Cornicabra olive groves.

PubMed

Rojo, Jesús; Pérez-Badia, Rosa

2015-11-01

This study examined the impact of weather-related variables on flowering phenology in the Cornicabra olive tree and constructed models based on linear and Poisson regression to forecast the onset and length of the pre-flowering and flowering phenophases. Spain is the world's leading olive oil producer, and the Cornicabra variety is the second largest Spanish variety in terms of surface area. However, there has been little phenological research into this variety. Phenological observations were made over a 5-year period (2009-2013) at four sampling sites in the province of Toledo (central Spain). Results showed that the onset of the pre-flowering phase is governed largely by temperature, which displayed a positive correlation with the temperature in the start of dormancy (November) and a negative correlation during the months prior to budburst (January, February and March). A similar relationship was recorded for the onset of flowering. Other weather-related variables, including solar radiation and rainfall, also influenced the succession of olive flowering phenophases. Linear models proved the most suitable for forecasting the onset and length of the pre-flowering period and the onset of flowering. The onset and length of pre-flowering can be predicted up to 1 or 2 months prior to budburst, whilst the onset of flowering can be forecast up to 3 months beforehand. By contrast, a nonlinear model using Poisson regression was best suited to predict the length of the flowering period.

Interannual abundance changes of gelatinous carnivore zooplankton unveil climate-driven hydrographic variations in the Iberian Peninsula, Portugal.

PubMed

D'Ambrosio, Mariaelena; Molinero, Juan C; Azeiteiro, Ulisses M; Pardal, Miguel A; Primo, Ana L; Nyitrai, Daniel; Marques, Sónia C

2016-09-01

The persistent massive blooms of gelatinous zooplankton recorded during recent decades may be indicative of marine ecosystem changes. In this study, we investigated the potential influence of the North Atlantic climate (NAO) variability on decadal abundance changes of gelatinous carnivore zooplankton in the Mondego estuary, Portugal, over the period 2003-2013. During the 11-year study, the community of gelatinous carnivores encompassed a larger diversity of hydromedusae than siphonophores; the former dominated by Obelia spp., Lizzia blondina, Clythia hemisphaerica, Liriope tetraphylla and Solmaris corona, while the latter dominated by Muggiaea atlantica. Gelatinous carnivore zooplankton displayed marked interannual variability and mounting species richness over the period examined. Their pattern of abundance shifted towards larger abundances ca. 2007 and significant phenological changes. The latter included a shift in the mean annual pattern (from unimodal to bimodal peak, prior and after 2007 respectively) and an earlier timing of the first annual peak concurrent with enhanced temperatures. These changes were concurrent with the climate-driven environmental variability mainly controlled by the NAO, which displayed larger variance after 2007 along with an enhanced upwelling activity. Structural equation modelling allowed depicting cascading effects derived from the NAO influence on regional climate and upwelling variability further shaping water temperature. Such cascading effect percolated the structure and dynamics of the community of gelatinous carnivore zooplankton in the Mondego estuary. Copyright © 2016 Elsevier Ltd. All rights reserved.