Assessment of spore presence for Cercospora beticola as demonstrated by sentinel beets

USDA-ARS?s Scientific Manuscript database

Cercospora beticola, the causal agent of Cercospora leaf spot (CLS) in Beta vulgaris (sugar, table, and leaf beet), is an important pathogen globally. Disease forecasting models are widely used to aid in CLS management for sugar beet. Most models rely on weather data to predict infection periods but...

Constructing seasonal LAI trajectory by data-model fusion for global evergreen needle-leaf forests

NASA Astrophysics Data System (ADS)

Wang, R.; Chen, J.; Mo, G.

2010-12-01

For decades, advancements in optical remote sensors made it possible to produce maps of a biophysical parameter--the Leaf Area Index (LAI), which is critically necessary in regional and global modeling of exchanges of carbon, water, energy and other substances, across large areas in a fast way. Quite a few global LAI products have been generated since 2000, e.g. GLOBCARBON (Deng et al., 2006), MODIS Collection 5 (Shabanov et al., 2007), CYCLOPES (Baret et al., 2007), etc. Albeit these progresses, the basic physics behind the technology restrains it from accurate estimation of LAI in winter, especially for northern high-latitude evergreen needle-leaf forests. Underestimation of winter LAI in these regions has been reported in literature (Yang et al., 2000; Cohen et al., 2003; Tian et al., 2004; Weiss et al., 2007; Pisek et al., 2007), and the distortion is usually attributed to the variations of canopy reflectance caused by understory change (Weiss et al., 2007) as well as by the presence of ice and snow on leaves and ground (Cohen, 2003; Tian et al., 2004). Seasonal changes in leaf pigments can also be another reason for low LAI retrieved in winter. Low conifer LAI values in winter retrieved from remote sensing make them unusable for surface energy budget calculations. To avoid these drawbacks of remote sensing approaches, we attempt to reconstruct the seasonal LAI trajectory through model-data fusion. A 1-degree LAI map of global evergreen needle-leaf forests at 10-day interval is produced based on the carbon allocation principle in trees. With net primary productivity (NPP) calculated by the Boreal Ecosystems Productivity Simulator (BEPS) (Chen et al., 1999), carbon allocated to needles is quantitatively evaluated and then can be further transformed into LAI using the specific leaf area (SLA). A leaf-fall scheme is developed to mimic the carbon loss caused by falling needles throughout the year. The seasonally maximum LAI from remote sensing data for each pixel is used as an anchor point of the LAI trajectory. Ground data are used for validation. The resulting LAI does not show strong seasonality within a year, which is reasonable for evergreen needle-leaf forests with known leaf longevity.

Global variability in leaf respiration in relation to climate, plant functional types and leaf traits

Treesearch

Owen K. Atkin; Keith J. Bloomfield; Peter B. Reich; Mark G. Tjoelker; Gregory P. Asner; Damien Bonal; Gerhard Bonisch; Matt G. Bradford; Lucas A. Cernusak; Eric G. Cosio; Danielle Creek; Kristine Y. Crous; Tomas F. Domingues; Jeffrey S. Dukes; John J. G. Egerton; John R. Evans; Graham D. Farquhar; Nikolaos M. Fyllas; Paul P. G. Gauthier; Emanuel Gloor; Teresa E. Gimeno; Kevin L. Griffin; Rossella Guerrieri; Mary A. Heskel; Chris Huntingford; Franc_oise Yoko Ishida; Jens Kattge; Hans Lambers; Michael J. Liddell; Jon Lloyd; Christopher H. Lusk; Roberta E. Martin; Ayal P. Maksimov; Trofim C. Maximov; Yadvinder Malhi; Belinda E. Medlyn; Patrick Meir; Lina M. Mercado; Nicholas Mirotchnick; Desmond Ng; Ulo Niinemets; Odhran S. O’Sullivan; Oliver L. Phillips; Lourens Poorter; Pieter Poot; I. Colin Prentice; Norma Salinas; Lucy M. Rowland; Michael G. Ryan; Stephen Sitch; Martijn Slot; Nicholas G. Smith; Matthew H. Turnbull; Mark C. VanderWel; Fernando Valladares; Erik J. Veneklaas; Lasantha K. Weerasinghe; Christian Wirth; Ian J. Wright; Kirk R. Wythers; Jen Xiang; Shuang Xiang; Joana Zaragoza-Castells

2015-01-01

A challenge for the development of terrestrial biosphere models (TBMs) and associated land surface components of Earth system models (ESMs) is improving representation of carbon (C) exchange between terrestrial plants and the atmosphere, and incorporating biological variation arising from diversity in plant functional types (PFTs) and climate (Sitch et al.,...

Effects of foliage clumping on the estimation of global terrestrial gross primary productivity

NASA Astrophysics Data System (ADS)

Chen, Jing M.; Mo, Gang; Pisek, Jan; Liu, Jane; Deng, Feng; Ishizawa, Misa; Chan, Douglas

2012-03-01

Sunlit and shaded leaf separation proposed by Norman (1982) is an effective way to upscale from leaf to canopy in modeling vegetation photosynthesis. The Boreal Ecosystem Productivity Simulator (BEPS) makes use of this methodology, and has been shown to be reliable in modeling the gross primary productivity (GPP) derived from CO2flux and tree ring measurements. In this study, we use BEPS to investigate the effect of canopy architecture on the global distribution of GPP. For this purpose, we use not only leaf area index (LAI) but also the first ever global map of the foliage clumping index derived from the multiangle satellite sensor POLDER at 6 km resolution. The clumping index, which characterizes the degree of the deviation of 3-dimensional leaf spatial distributions from the random case, is used to separate sunlit and shaded LAI values for a given LAI. Our model results show that global GPP in 2003 was 132 ± 22 Pg C. Relative to this baseline case, our results also show: (1) global GPP is overestimated by 12% when accurate LAI is available but clumping is ignored, and (2) global GPP is underestimated by 9% when the effective LAI is available and clumping is ignored. The clumping effects in both cases are statistically significant (p < 0.001). The effective LAI is often derived from remote sensing by inverting the measured canopy gap fraction to LAI without considering the clumping. Global GPP would therefore be generally underestimated when remotely sensed LAI (actually effective LAI by our definition) is used. This is due to the underestimation of the shaded LAI and therefore the contribution of shaded leaves to GPP. We found that shaded leaves contribute 50%, 38%, 37%, 39%, 26%, 29% and 21% to the total GPP for broadleaf evergreen forest, broadleaf deciduous forest, evergreen conifer forest, deciduous conifer forest, shrub, C4 vegetation, and other vegetation, respectively. The global average of this ratio is 35%.

Global estimation of evapotranspiration using a leaf area index-based surface energy and water balance model

USDA-ARS?s Scientific Manuscript database

Studies of global hydrologic cycles, carbon cycles and climate change are greatly facilitated when global estimates of evapotranspiration (E) are available. We have developed an air-relative-humidity-based two-source (ARTS) E model that simulates the surface energy balance, soil water balance, and e...

Frost and leaf-size gradients in forests: global patterns and experimental evidence.

PubMed

Lusk, Christopher H; Clearwater, Michael J; Laughlin, Daniel C; Harrison, Sandy P; Prentice, Iain Colin; Nordenstahl, Marisa; Smith, Benjamin

2018-05-16

Explanations of leaf size variation commonly focus on water availability, yet leaf size also varies with latitude and elevation in environments where water is not strongly limiting. We provide the first conclusive test of a prediction of leaf energy balance theory that may explain this pattern: large leaves are more vulnerable to night-time chilling, because their thick boundary layers impede convective exchange with the surrounding air. Seedlings of 15 New Zealand evergreens spanning 12-fold variation in leaf width were exposed to clear night skies, and leaf temperatures were measured with thermocouples. We then used a global dataset to assess several climate variables as predictors of leaf size in forest assemblages. Leaf minus air temperature was strongly correlated with leaf width, ranging from -0.9 to -3.2°C in the smallest- and largest-leaved species, respectively. Mean annual temperature and frost-free period were good predictors of evergreen angiosperm leaf size in forest assemblages, but no climate variable predicted deciduous leaf size. Although winter deciduousness makes large leaves possible in strongly seasonal climates, large-leaved evergreens are largely confined to frost-free climates because of their susceptibility to radiative cooling. Evergreen leaf size data can therefore be used to enhance vegetation models, and to infer palaeotemperatures from fossil leaf assemblages. © 2018 The Authors New Phytologist © 2018 New Phytologist Trust.

A model using marginal efficiency of investment to analyse carbon and nitrogen interactions in forested ecosystems

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Williams, M.

2014-12-01

Carbon (C) and nitrogen (N) cycles are coupled in terrestrial ecosystems through multiple processes including photosynthesis, tissue allocation, respiration, N fixation, N uptake, and decomposition of litter and soil organic matter. Capturing the constraint of N on terrestrial C uptake and storage has been a focus of the Earth System modelling community. Here we explore the trade-offs and sensitivities of allocating C and N to different tissues in order to optimize the productivity of plants using a new, simple model of ecosystem C-N cycling and interactions (ACONITE). ACONITE builds on theory related to plant economics in order to predict key ecosystem properties (leaf area index, leaf C:N, N fixation, and plant C use efficiency) based on the optimization of the marginal change in net C or N uptake associated with a change in allocation of C or N to plant tissues. We simulated and evaluated steady-state and transient ecosystem stocks and fluxes in three different forest ecosystems types (tropical evergreen, temperate deciduous, and temperate evergreen). Leaf C:N differed among the three ecosystem types (temperate deciduous < tropical evergreen < temperature evergreen), a result that compared well to observations from a global database describing plant traits. Gross primary productivity (GPP) and net primary productivity (NPP) estimates compared well to observed fluxes at the simulation sites. A sensitivity analysis revealed that parameterization of the relationship between leaf N and leaf respiration had the largest influence on leaf area index and leaf C:N. Also, a widely used linear leaf N-respiration relationship did not yield a realistic leaf C:N, while a more recently reported non-linear relationship simulated leaf C:N that compared better to the global trait database than the linear relationship. Overall, our ability to constrain leaf area index and allow spatially and temporally variable leaf C:N can help address challenges simulating these properties in ecosystem and Earth System models. Furthermore, the simple approach with emergent properties based on coupled C-N dynamics has potential for use in research that uses data-assimilation methods to integrate data on both the C and N cycles to improve C flux forecasts.

Global remote sensing of water-chlorophyll ratio in terrestrial plant leaves.

PubMed

Kushida, Keiji

2012-10-01

I evaluated the use of global remote sensing techniques for estimating plant leaf chlorophyll a + b (C(ab); μg cm(-2)) and water (C(w); mg cm(-2)) concentrations as well as the ratio of C(w)/C(ab) with the PROSAIL model under possible distributions for leaf and soil spectra, leaf area index (LAI), canopy geometric structure, and leaf size. First, I estimated LAI from the normalized difference vegetation index. I found that, at LAI values <2, C(ab), C(w), and C(w)/C(ab) could not be reliably estimated. At LAI values >2, C(ab) and C(w) could be estimated for only restricted ranges of the canopy structure; however, the ratio of C(w)/C(ab) could be reliably estimated for a variety of possible canopy structures with coefficients of determination (R(2)) ranging from 0.56 to 0.90. The remote estimation of the C(w)/C(ab) ratio from satellites offers information on plant condition at a global scale.

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.

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.

Are trait-scaling relationships invariant across contrasting elevations in the widely distributed treeline species Nothofagus pumilio?

PubMed

Fajardo, Alex

2016-05-01

The study of scaling examines the relative dimensions of diverse organismal traits. Understanding whether global scaling patterns are paralleled within species is key to identify causal factors of universal scaling. I examined whether the foliage-stem (Corner's rules), the leaf size-number, and the leaf mass-leaf area scaling relationships remained invariant and isometric with elevation in a wide-distributed treeline species in the southern Chilean Andes. Mean leaf area, leaf mass, leafing intensity, and twig cross-sectional area were determined for 1-2 twigs of 8-15 Nothofagus pumilio individuals across four elevations (including treeline elevation) and four locations (from central Chile at 36°S to Tierra del Fuego at 54°S). Mixed effects models were fitted to test whether the interaction term between traits and elevation was nonsignificant (invariant). The leaf-twig cross-sectional area and the leaf mass-leaf area scaling relationships were isometric (slope = 1) and remained invariant with elevation, whereas the leaf size-number (i.e., leafing intensity) scaling was allometric (slope ≠ -1) and showed no variation with elevation. Leaf area and leaf number were consistently negatively correlated across elevation. The scaling relationships examined in the current study parallel those seen across species. It is plausible that the explanation of intraspecific scaling relationships, as trait combinations favored by natural selection, is the same as those invoked to explain across species patterns. Thus, it is very likely that the global interspecific Corner's rules and other leaf-leaf scaling relationships emerge as the aggregate of largely parallel intraspecific patterns. © 2016 Botanical Society of America.

Understanding of Leaf Development-the Science of Complexity.

PubMed

Malinowski, Robert

2013-06-25

The leaf is the major organ involved in light perception and conversion of solar energy into organic carbon. In order to adapt to different natural habitats, plants have developed a variety of leaf forms, ranging from simple to compound, with various forms of dissection. Due to the enormous cellular complexity of leaves, understanding the mechanisms regulating development of these organs is difficult. In recent years there has been a dramatic increase in the use of technically advanced imaging techniques and computational modeling in studies of leaf development. Additionally, molecular tools for manipulation of morphogenesis were successfully used for in planta verification of developmental models. Results of these interdisciplinary studies show that global growth patterns influencing final leaf form are generated by cooperative action of genetic, biochemical, and biomechanical inputs. This review summarizes recent progress in integrative studies on leaf development and illustrates how intrinsic features of leaves (including their cellular complexity) influence the choice of experimental approach.

Understanding of Leaf Development—the Science of Complexity

PubMed Central

Malinowski, Robert

2013-01-01

The leaf is the major organ involved in light perception and conversion of solar energy into organic carbon. In order to adapt to different natural habitats, plants have developed a variety of leaf forms, ranging from simple to compound, with various forms of dissection. Due to the enormous cellular complexity of leaves, understanding the mechanisms regulating development of these organs is difficult. In recent years there has been a dramatic increase in the use of technically advanced imaging techniques and computational modeling in studies of leaf development. Additionally, molecular tools for manipulation of morphogenesis were successfully used for in planta verification of developmental models. Results of these interdisciplinary studies show that global growth patterns influencing final leaf form are generated by cooperative action of genetic, biochemical, and biomechanical inputs. This review summarizes recent progress in integrative studies on leaf development and illustrates how intrinsic features of leaves (including their cellular complexity) influence the choice of experimental approach. PMID:27137383

Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison.

PubMed

Hu, Zhongmin; Shi, Hao; Cheng, Kaili; Wang, Ying-Ping; Piao, Shilong; Li, Yue; Zhang, Li; Xia, Jianyang; Zhou, Lei; Yuan, Wenping; Running, Steve; Li, Longhui; Hao, Yanbin; He, Nianpeng; Yu, Qiang; Yu, Guirui

2018-04-17

Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons. © 2018 John Wiley & Sons Ltd.

The potential impacts of climate change induced changes to tropical leaf albedo and its feedback on global climate

NASA Astrophysics Data System (ADS)

Doughty, C.; Shenkin, A.; Bentley, L. P.; Malhi, Y.

2017-12-01

Tropical forest leaf albedo plays a critical role in global climate by determining how much radiation the planet absorbs near the equator. However, little is known about how tropical leaf albedo could be affected by climate change and how any such changes in albedo could, in turn, impact global climate. Here we measure sunlit leaf albedo along two elevation temperature gradients (a 3000-meter gradient in Peru (10 plots) and a 1500 m gradient in Australia (10 plots) and along two wet to dry transects (a 2000 mm yr-1 gradient in Ghana (10 plots) and a 2000 mm yr-1 gradient in Brazil (10 plots). We found a highly significant increase in visible leaf albedo with wetness at both wet to dry gradients. We also found a marginally significant trend of increased albedo with warmer temperatures along one of the elevation gradients. Leaf albedo can also be impacted by changes in species composition, variations in interspecific variation, and changes in leaf chlorophyll concentrations. We removed the dominant two species from the basal area weighting for each plots but found no significant change, a directional change of interspecific variation could change albedo by 0.01 in the NIR, and changes in chlorophyll could decrease visible albedo by 0.005. We then simulated changes in tropical leaf albedo with a climate model and show that such changes could act as a small negative feedback on climate, but most likely will not have a large impact on future climate.

Spin-Up and Tuning of the Global Carbon Cycle Model Inside the GISS ModelE2 GCM

NASA Technical Reports Server (NTRS)

Aleinov, Igor; Kiang, Nancy Y.; Romanou, Anastasia

2015-01-01

Planetary carbon cycle involves multiple phenomena, acting at variety of temporal and spacial scales. The typical times range from minutes for leaf stomata physiology to centuries for passive soil carbon pools and deep ocean layers. So, finding a satisfactory equilibrium state becomes a challenging and computationally expensive task. Here we present the spin-up processes for different configurations of the GISS Carbon Cycle model from the model forced with MODIS observed Leaf Area Index (LAI) and prescribed ocean to the prognostic LAI and to the model fully coupled to the dynamic ocean and ocean biology. We investigate the time it takes the model to reach the equilibrium and discuss the ways to speed up this process. NASA Goddard Institute for Space Studies General Circulation Model (GISS ModelE2) is currently equipped with all major algorithms necessary for the simulation of the Global Carbon Cycle. The terrestrial part is presented by Ent Terrestrial Biosphere Model (Ent TBM), which includes leaf biophysics, prognostic phenology and soil biogeochemistry module (based on Carnegie-Ames-Stanford model). The ocean part is based on the NASA Ocean Biogeochemistry Model (NOBM). The transport of atmospheric CO2 is performed by the atmospheric part of ModelE2, which employs quadratic upstream algorithm for this purpose.

Fundamental trade-offs generating the worldwide leaf economics spectrum.

PubMed

Shipley, Bill; Lechowicz, Martin J; Wright, Ian; Reich, Peter B

2006-03-01

Recent work has identified a worldwide "economic" spectrum of correlated leaf traits that affects global patterns of nutrient cycling and primary productivity and that is used to calibrate vegetation-climate models. The correlation patterns are displayed by species from the arctic to the tropics and are largely independent of growth form or phylogeny. This generality suggests that unidentified fundamental constraints control the return of photosynthates on investments of nutrients and dry mass in leaves. Using novel graph theoretic methods and structural equation modeling, we show that the relationships among these variables can best be explained by assuming (1) a necessary trade-off between allocation to structural tissues versus liquid phase processes and (2) an evolutionary tradeoff between leaf photosynthetic rates, construction costs, and leaf longevity.

Reconciling leaf physiological traits and canopy flux data: Use of the TRY and FLUXNET databases in the Community Land Model version 4

NASA Astrophysics Data System (ADS)

Bonan, Gordon B.; Oleson, Keith W.; Fisher, Rosie A.; Lasslop, Gitta; Reichstein, Markus

2012-06-01

The Community Land Model version 4 overestimates gross primary production (GPP) compared with estimates from FLUXNET eddy covariance towers. The revised model of Bonan et al. (2011) is consistent with FLUXNET, but values for the leaf-level photosynthetic parameterVcmaxthat yield realistic GPP at the canopy-scale are lower than observed in the global synthesis of Kattge et al. (2009), except for tropical broadleaf evergreen trees. We investigate this discrepancy betweenVcmaxand canopy fluxes. A multilayer model with explicit calculation of light absorption and photosynthesis for sunlit and shaded leaves at depths in the canopy gives insight to the scale mismatch between leaf and canopy. We evaluate the model with light-response curves at individual FLUXNET towers and with empirically upscaled annual GPP. Biases in the multilayer canopy with observedVcmaxare similar, or improved, compared with the standard two-leaf canopy and its lowVcmax, though the Amazon is an exception. The difference relates to light absorption by shaded leaves in the two-leaf canopy, and resulting higher photosynthesis when the canopy scaling parameterKn is low, but observationally constrained. Larger Kndecreases shaded leaf photosynthesis and reduces the difference between the two-leaf and multilayer canopies. The low modelVcmaxis diagnosed from nitrogen reduction of GPP in simulations with carbon-nitrogen biogeochemistry. Our results show that the imposed nitrogen reduction compensates for deficiency in the two-leaf canopy that produces high GPP. Leaf trait databases (Vcmax), within-canopy profiles of photosynthetic capacity (Kn), tower fluxes, and empirically upscaled fields provide important complementary information for model evaluation.

Simulations of Seasonal and Latitudinal Variations in Leaf Inclination Angle Distribution: Implications for Remote Sensing

NASA Technical Reports Server (NTRS)

Huemmrich, Karl F.

2013-01-01

The leaf inclination angle distribution (LAD) is an important characteristic of vegetation canopy structure affecting light interception within the canopy. However, LADs are difficult and time consuming to measure. To examine possible global patterns of LAD and their implications in remote sensing, a model was developed to predict leaf angles within canopies. Canopies were simulated using the SAIL radiative transfer model combined with a simple photosynthesis model. This model calculated leaf inclination angles for horizontal layers of leaves within the canopy by choosing the leaf inclination angle that maximized production over a day in each layer. LADs were calculated for five latitude bands for spring and summer solar declinations. Three distinct LAD types emerged: tropical, boreal, and an intermediate temperate distribution. In tropical LAD, the upper layers have a leaf angle around 35 with the lower layers having horizontal inclination angles. While the boreal LAD has vertical leaf inclination angles throughout the canopy. The latitude bands where each LAD type occurred changed with the seasons. The different LADs affected the fraction of absorbed photosynthetically active radiation (fAPAR) and Normalized Difference Vegetation Index (NDVI) with similar relationships between fAPAR and leaf area index (LAI), but different relationships between NDVI and LAI for the different LAD types. These differences resulted in significantly different relationships between NDVI and fAPAR for each LAD type. Since leaf inclination angles affect light interception, variations in LAD also affect the estimation of leaf area based on transmittance of light or lidar returns.

Mathematical modeling on obligate mutualism: Interactions between leaf-cutter ants and their fungus garden.

PubMed

Kang, Yun; Clark, Rebecca; Makiyama, Michael; Fewell, Jennifer

2011-11-21

We propose a simple mathematical model by applying Michaelis-Menton equations of enzyme kinetics to study the mutualistic interaction between the leaf cutter ant and its fungus garden at the early stage of colony expansion. We derive sufficient conditions on the extinction and coexistence of these two species. In addition, we give a region of initial condition that leads to the extinction of two species when the model has an interior attractor. Our global analysis indicates that the division of labor by worker ants and initial conditions are two important factors that determine whether leaf cutter ants' colonies and their fungus garden can survive and grow or not. We validate the model by comparing model simulations and data on fungal and ant colony growth rates under laboratory conditions. We perform sensitive analysis of the model based on the experimental data to gain more biological insights on ecological interactions between leaf-cutter ants and their fungus garden. Finally, we give conclusions and discuss potential future work. Published by Elsevier Ltd.

Representing leaf and root physiological traits in CLM improves global carbon and nitrogen cycling predictions

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

Ghimire, Bardan; Riley, William J.; Koven, Charles D.

In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However, current Earth System Models (ESMs) do not mechanistically represent functional nitrogen allocation for photosynthesis or the linkage between nitrogen uptake and root traits. The current version of CLM (4.5) links nitrogen availability and plant productivity via (1) an instantaneous downregulation of potential photosynthesis rates based on soil mineral nitrogen availability, and (2) apportionment of soil nitrogen between plants and competing nitrogen consumers assumed to be proportional to their relative N demands. However, plants do not photosynthesize at potential rates and then downregulate; instead photosynthesis ratesmore » are governed by nitrogen that has been allocated to the physiological processes underpinning photosynthesis. Furthermore, the role of plant roots in nutrient acquisition has also been largely ignored in ESMs. We therefore present a new plant nitrogen model for CLM4.5 with (1) improved representations of linkages between leaf nitrogen and plant productivity based on observed relationships in a global plant trait database and (2) plant nitrogen uptake based on root-scale Michaelis-Menten uptake kinetics. Our model improvements led to a global bias reduction in GPP, LAI, and biomass of 70%, 11%, and 49%, respectively. Furthermore, water use efficiency predictions were improved conceptually, qualitatively, and in magnitude. The new model's GPP responses to nitrogen deposition, CO 2 fertilization, and climate also differed from the baseline model. The mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers led to overall improvements in global carbon cycling predictions.« less

Representing leaf and root physiological traits in CLM improves global carbon and nitrogen cycling predictions

DOE PAGES

Ghimire, Bardan; Riley, William J.; Koven, Charles D.; ...

2016-05-01

In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However, current Earth System Models (ESMs) do not mechanistically represent functional nitrogen allocation for photosynthesis or the linkage between nitrogen uptake and root traits. The current version of CLM (4.5) links nitrogen availability and plant productivity via (1) an instantaneous downregulation of potential photosynthesis rates based on soil mineral nitrogen availability, and (2) apportionment of soil nitrogen between plants and competing nitrogen consumers assumed to be proportional to their relative N demands. However, plants do not photosynthesize at potential rates and then downregulate; instead photosynthesis ratesmore » are governed by nitrogen that has been allocated to the physiological processes underpinning photosynthesis. Furthermore, the role of plant roots in nutrient acquisition has also been largely ignored in ESMs. We therefore present a new plant nitrogen model for CLM4.5 with (1) improved representations of linkages between leaf nitrogen and plant productivity based on observed relationships in a global plant trait database and (2) plant nitrogen uptake based on root-scale Michaelis-Menten uptake kinetics. Our model improvements led to a global bias reduction in GPP, LAI, and biomass of 70%, 11%, and 49%, respectively. Furthermore, water use efficiency predictions were improved conceptually, qualitatively, and in magnitude. The new model's GPP responses to nitrogen deposition, CO 2 fertilization, and climate also differed from the baseline model. The mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers led to overall improvements in global carbon cycling predictions.« less

Representing leaf and root physiological traits in CLM improves global carbon and nitrogen cycling predictions

NASA Astrophysics Data System (ADS)

Ghimire, Bardan; Riley, William J.; Koven, Charles D.; Mu, Mingquan; Randerson, James T.

2016-06-01

In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However, current Earth System Models (ESMs) do not mechanistically represent functional nitrogen allocation for photosynthesis or the linkage between nitrogen uptake and root traits. The current version of CLM (4.5) links nitrogen availability and plant productivity via (1) an instantaneous downregulation of potential photosynthesis rates based on soil mineral nitrogen availability, and (2) apportionment of soil nitrogen between plants and competing nitrogen consumers assumed to be proportional to their relative N demands. However, plants do not photosynthesize at potential rates and then downregulate; instead photosynthesis rates are governed by nitrogen that has been allocated to the physiological processes underpinning photosynthesis. Furthermore, the role of plant roots in nutrient acquisition has also been largely ignored in ESMs. We therefore present a new plant nitrogen model for CLM4.5 with (1) improved representations of linkages between leaf nitrogen and plant productivity based on observed relationships in a global plant trait database and (2) plant nitrogen uptake based on root-scale Michaelis-Menten uptake kinetics. Our model improvements led to a global bias reduction in GPP, LAI, and biomass of 70%, 11%, and 49%, respectively. Furthermore, water use efficiency predictions were improved conceptually, qualitatively, and in magnitude. The new model's GPP responses to nitrogen deposition, CO2 fertilization, and climate also differed from the baseline model. The mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers led to overall improvements in global carbon cycling predictions.

Evolutionary History Underlies Plant Physiological Responses to Global Change Since the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Becklin, K. M.; Medeiros, J. S.; Sale, K. R.; Ward, J. K.

2014-12-01

Assessing family and species-level variation in physiological responses to global change across geologic time is critical for understanding factors that underlie changes in species distributions and community composition. Ancient plant specimens preserved within packrat middens are invaluable in this context since they allow for comparisons between co-occurring plant lineages. Here we used modern and ancient plant specimens preserved within packrat middens from the Snake Range, NV to investigate the physiological responses of a mixed montane conifer community to global change since the last glacial maximum. We used a conceptual model to infer relative changes in stomatal conductance and maximum photosynthetic capacity from measures of leaf carbon isotopes, stomatal characteristics, and leaf nitrogen content. Our results indicate that most of the sampled taxa decreased stomatal conductance and/or photosynthetic capacity from glacial to modern times. However, plant families differed in the timing and magnitude of these physiological responses. Additionally, leaf-level responses were more similar within plant families than within co-occurring species assemblages. This suggests that adaptation at the level of leaf physiology may not be the main determinant of shifts in community composition, and that plant evolutionary history may drive physiological adaptation to global change over recent geologic time.

Mapping local and global variability in plant trait distributions

DOE PAGES

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc; ...

2017-12-01

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

Mapping local and global variability in plant trait distributions

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

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

Using the CARDAMOM framework to retrieve global terrestrial ecosystem functioning properties

NASA Astrophysics Data System (ADS)

Exbrayat, Jean-François; Bloom, A. Anthony; Smallman, T. Luke; van der Velde, Ivar R.; Feng, Liang; Williams, Mathew

2016-04-01

Terrestrial ecosystems act as a sink for anthropogenic emissions of fossil-fuel and thereby partially offset the ongoing global warming. However, recent model benchmarking and intercomparison studies have highlighted the non-trivial uncertainties that exist in our understanding of key ecosystem properties like plant carbon allocation and residence times. It leads to worrisome differences in terrestrial carbon stocks simulated by Earth system models, and their evolution in a warming future. In this presentation we attempt to provide global insights on these properties by merging an ecosystem model with remotely-sensed global observations of leaf area and biomass through a data-assimilation system: the CARbon Data MOdel fraMework (CARDAMOM). CARDAMOM relies on a Markov Chain Monte Carlo algorithm to retrieve confidence intervals of model parameters that regulate ecosystem properties independently of any prior land-cover information. The MCMC method thereby enables an explicit representation of the uncertainty in land-atmosphere fluxes and the evolution of terrestrial carbon stocks through time. Global experiments are performed for the first decade of the 21st century using a 1°×1° spatial resolution. Relationships emerge globally between key ecosystem properties. For example, our analyses indicate that leaf lifespan and leaf mass per area are highly correlated. Furthermore, there exists a latitudinal gradient in allocation patterns: high latitude ecosystems allocate more carbon to photosynthetic carbon (leaves) while plants invest more carbon in their structural parts (wood and root) in the wet tropics. Overall, the spatial distribution of these ecosystem properties does not correspond to usual land-cover maps and are also partially correlated with disturbance regimes. For example, fire-prone ecosystems present statistically significant higher values of carbon use efficiency than less disturbed ecosystems experiencing similar climatic conditions. These results raise concerns on the suitability of the plant functional type paradigm for terrestrial carbon cycling.

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.

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.

Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information

NASA Astrophysics Data System (ADS)

Harper, Anna B.; Cox, Peter M.; Friedlingstein, Pierre; Wiltshire, Andy J.; Jones, Chris D.; Sitch, Stephen; Mercado, Lina M.; Groenendijk, Margriet; Robertson, Eddy; Kattge, Jens; Bönisch, Gerhard; Atkin, Owen K.; Bahn, Michael; Cornelissen, Johannes; Niinemets, Ülo; Onipchenko, Vladimir; Peñuelas, Josep; Poorter, Lourens; Reich, Peter B.; Soudzilovskaia, Nadjeda A.; van Bodegom, Peter

2016-07-01

Dynamic global vegetation models are used to predict the response of vegetation to climate change. They are essential for planning ecosystem management, understanding carbon cycle-climate feedbacks, and evaluating the potential impacts of climate change on global ecosystems. JULES (the Joint UK Land Environment Simulator) represents terrestrial processes in the UK Hadley Centre family of models and in the first generation UK Earth System Model. Previously, JULES represented five plant functional types (PFTs): broadleaf trees, needle-leaf trees, C3 and C4 grasses, and shrubs. This study addresses three developments in JULES. First, trees and shrubs were split into deciduous and evergreen PFTs to better represent the range of leaf life spans and metabolic capacities that exists in nature. Second, we distinguished between temperate and tropical broadleaf evergreen trees. These first two changes result in a new set of nine PFTs: tropical and temperate broadleaf evergreen trees, broadleaf deciduous trees, needle-leaf evergreen and deciduous trees, C3 and C4 grasses, and evergreen and deciduous shrubs. Third, using data from the TRY database, we updated the relationship between leaf nitrogen and the maximum rate of carboxylation of Rubisco (Vcmax), and updated the leaf turnover and growth rates to include a trade-off between leaf life span and leaf mass per unit area.Overall, the simulation of gross and net primary productivity (GPP and NPP, respectively) is improved with the nine PFTs when compared to FLUXNET sites, a global GPP data set based on FLUXNET, and MODIS NPP. Compared to the standard five PFTs, the new nine PFTs simulate a higher GPP and NPP, with the exception of C3 grasses in cold environments and C4 grasses that were previously over-productive. On a biome scale, GPP is improved for all eight biomes evaluated and NPP is improved for most biomes - the exceptions being the tropical forests, savannahs, and extratropical mixed forests where simulated NPP is too high. With the new PFTs, the global present-day GPP and NPP are 128 and 62 Pg C year-1, respectively. We conclude that the inclusion of trait-based data and the evergreen/deciduous distinction has substantially improved productivity fluxes in JULES, in particular the representation of GPP. These developments increase the realism of JULES, enabling higher confidence in simulations of vegetation dynamics and carbon storage.

Mapping local and global variability in plant trait distributions.

PubMed

Butler, Ethan E; Datta, Abhirup; Flores-Moreno, Habacuc; Chen, Ming; Wythers, Kirk R; Fazayeli, Farideh; Banerjee, Arindam; Atkin, Owen K; Kattge, Jens; Amiaud, Bernard; Blonder, Benjamin; Boenisch, Gerhard; Bond-Lamberty, Ben; Brown, Kerry A; Byun, Chaeho; Campetella, Giandiego; Cerabolini, Bruno E L; Cornelissen, Johannes H C; Craine, Joseph M; Craven, Dylan; de Vries, Franciska T; Díaz, Sandra; Domingues, Tomas F; Forey, Estelle; González-Melo, Andrés; Gross, Nicolas; Han, Wenxuan; Hattingh, Wesley N; Hickler, Thomas; Jansen, Steven; Kramer, Koen; Kraft, Nathan J B; Kurokawa, Hiroko; Laughlin, Daniel C; Meir, Patrick; Minden, Vanessa; Niinemets, Ülo; Onoda, Yusuke; Peñuelas, Josep; Read, Quentin; Sack, Lawren; Schamp, Brandon; Soudzilovskaia, Nadejda A; Spasojevic, Marko J; Sosinski, Enio; Thornton, Peter E; Valladares, Fernando; van Bodegom, Peter M; Williams, Mathew; Wirth, Christian; Reich, Peter B

2017-12-19

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.

Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites

NASA Astrophysics Data System (ADS)

Zhou, Yanlian; Wu, Xiaocui; Ju, Weimin; Chen, Jing M.; Wang, Shaoqiang; Wang, Huimin; Yuan, Wenping; Andrew Black, T.; Jassal, Rachhpal; Ibrom, Andreas; Han, Shijie; Yan, Junhua; Margolis, Hank; Roupsard, Olivier; Li, Yingnian; Zhao, Fenghua; Kiely, Gerard; Starr, Gregory; Pavelka, Marian; Montagnani, Leonardo; Wohlfahrt, Georg; D'Odorico, Petra; Cook, David; Arain, M. Altaf; Bonal, Damien; Beringer, Jason; Blanken, Peter D.; Loubet, Benjamin; Leclerc, Monique Y.; Matteucci, Giorgio; Nagy, Zoltan; Olejnik, Janusz; Paw U, Kyaw Tha; Varlagin, Andrej

2016-04-01

Light use efficiency (LUE) models are widely used to simulate gross primary production (GPP). However, the treatment of the plant canopy as a big leaf by these models can introduce large uncertainties in simulated GPP. Recently, a two-leaf light use efficiency (TL-LUE) model was developed to simulate GPP separately for sunlit and shaded leaves and has been shown to outperform the big-leaf MOD17 model at six FLUX sites in China. In this study we investigated the performance of the TL-LUE model for a wider range of biomes. For this we optimized the parameters and tested the TL-LUE model using data from 98 FLUXNET sites which are distributed across the globe. The results showed that the TL-LUE model performed in general better than the MOD17 model in simulating 8 day GPP. Optimized maximum light use efficiency of shaded leaves (ɛmsh) was 2.63 to 4.59 times that of sunlit leaves (ɛmsu). Generally, the relationships of ɛmsh and ɛmsu with ɛmax were well described by linear equations, indicating the existence of general patterns across biomes. GPP simulated by the TL-LUE model was much less sensitive to biases in the photosynthetically active radiation (PAR) input than the MOD17 model. The results of this study suggest that the proposed TL-LUE model has the potential for simulating regional and global GPP of terrestrial ecosystems, and it is more robust with regard to usual biases in input data than existing approaches which neglect the bimodal within-canopy distribution of PAR.

Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites: TL-LUE Parameterization and Validation

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

Zhou, Yanlian; Wu, Xiaocui; Ju, Weimin

2016-04-06

Light use efficiency (LUE) models are widely used to simulate gross primary production (GPP). However, the treatment of the plant canopy as a big leaf by these models can introduce large uncertainties in simulated GPP. Recently, a two-leaf light use efficiency (TL-LUE) model was developed to simulate GPP separately for sunlit and shaded leaves and has been shown to outperform the big-leaf MOD17 model at 6 FLUX sites in China. In this study we investigated the performance of the TL-LUE model for a wider range of biomes. For this we optimized the parameters and tested the TL-LUE model using datamore » from 98 FLUXNET sites which are distributed across the globe. The results showed that the TL-LUE model performed in general better than the MOD17 model in simulating 8-day GPP. Optimized maximum light use efficiency of shaded leaves (εmsh) was 2.63 to 4.59 times that of sunlit leaves (εmsu). Generally, the relationships of εmsh and εmsu with εmax were well described by linear equations, indicating the existence of general patterns across biomes. GPP simulated by the TL-LUE model was much less sensitive to biases in the photosynthetically active radiation (PAR) input than the MOD17 model. The results of this study suggest that the proposed TL-LUE model has the potential for simulating regional and global GPP of terrestrial ecosystems and it is more robust with regard to usual biases in input data than existing approaches which neglect the bi-modal within-canopy distribution of PAR.« less

A potential to monitor nutrients as an indicator of rangeland quality using space borne remote sensing

NASA Astrophysics Data System (ADS)

Ramoelo, A.; Cho, M. A.; Madonsela, S.; Mathieu, R.; van der Korchove, R.; Kaszta, Z.; Wolf, E.

2014-02-01

Global change consisting of land use and climate change could have huge impacts on food security and the health of various ecosystems. Leaf nitrogen (N) is one of the key factors limiting agricultural production and ecosystem functioning. Leaf N can be used as an indicator of rangeland quality which could provide information for the farmers, decision makers, land planners and managers. Leaf N plays a crucial role in understanding the feeding patterns and distribution of wildlife and livestock. Assessment of this vegetation parameter using conventional methods at landscape scale level is time consuming and tedious. Remote sensing provides a synoptic view of the landscape, which engenders an opportunity to assess leaf N over wider rangeland areas from protected to communal areas. Estimation of leaf N has been successful during peak productivity or high biomass and limited studies estimated leaf N in dry season. The objective of this study is to monitor leaf N as an indicator of rangeland quality using WorldView 2 satellite images in the north-eastern part of South Africa. Series of field work to collect samples for leaf N were undertaken in the beginning of May (end of wet season) and July (dry season). Several conventional and red edge based vegetation indices were computed. Simple regression was used to develop prediction model for leaf N. Using bootstrapping, indicator of precision and accuracy were analyzed to select a best model for the combined data sets (May and July). The may model for red edge based simple ratio explained over 90% of leaf N variations. The model developed from the combined data sets with normalized difference vegetation index explained 62% of leaf N variation, and this is a model used to estimate and map leaf N for two seasons. The study demonstrated that leaf N could be monitored using high spatial resolution with the red edge band capability.

Successional change in photosynthetic capacities after wildfires across the North American boreal forests

NASA Astrophysics Data System (ADS)

Tahara, N.; Ueyama, M.; Iwata, H.; Ichii, K.; Harazono, Y.; Nagano, H.

2015-12-01

Wildfire is a major disturbance across the North American boreal forests. Canopy ecophysiology is important to understand recovery of carbon dioxide and water vapor fluxes after wildfires. We developed a big-leaf model coupled photosynthesis (Farquhar et al., 1980) and stomatal conductance (Ball et al., 1987) models. We inputted eddy covariance data from fire chronosequence across the North American boreal forests into the big-leaf model for optimizing parameters: maximum carboxylation rate at 25℃ (Vcmax25) and stomatal conductance parameters. The model was optimized with a global optimization technique: SCE-UA method (Duan et al., 1994). The estimated canopy-scale parameters were then downscaled into a leaf scale (vcmax25; values per sun leaf area) using a two-leaf radiation transfer model (de Pury and Farquhar, 1997) and leaf area index. We used 6 sites from two fire chronosequence in Alaska (1~, 3~, 5~, 15~ and 80~ years after fire; Liu et al., 2005; Iwata et al., 2011) and 6 sites from a Canadian chronosequence study (6~, 15~, 23~, 40~ and 74~ years after fire; Goulden et al., 2010). Preliminary results showed clear seasonal variations in canopy-scale Vcmax25 with the maximum during the summer. In Alaska, the downscaled vcmax25 for four years after fire exceeded those of mature forests, indicating that the photosynthetic capacity recovered quickly in the early successional stage. This quick recovery was not seen in gross primary productivity. We will show the variations of the ecophysiological parameters in terms of environment conditions and stand age. References Ball et al., 1987: In Progress in Photosynthesis Research, 221-224. de Pury and Farquhar, 1997: Plant, Cell and Environ., 20, 537-557. Duan et al., 1994: J. Hydrology, 158, 265-284. Farquhar et al., 1980: Planta, 149, 78-90. Goulden et al., 2010: Global Change Biol., 17, 855-871. Iwata et al., 2011: SOLA., 7, 105-108. Liu et al., 2005: J. Geophys. Res., 110, D13101.

Modelling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

NASA Astrophysics Data System (ADS)

Reichstein, M.; Rey, A.; Freibauer, A.; Tenhunen, J.; Valentini, R.; Soil Respiration Synthesis Team

2003-04-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, inter-annual and spatial variability of soil respiration as affected by water availability, temperature and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g. leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical non-linear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and inter-site variability of soil respiration with a mean absolute error of 0.82 µmol m-2 s-1. The parameterised model exhibits the following principal properties: 1) At a relative amount of upper-layer soil water of 16% of field capacity half-maximal soil respiration rates are reached. 2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. 3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly time-scale we employed the approach by Raich et al. (2002, Global Change Biol. 8, 800-812) that used monthly precipitation and air temperature to globally predict soil respiration (T&P-model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the inter-site variability, regardless whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly time scale we developed a simple T&P&LAI-model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time-step model and explained 50 % of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index.

Steady state estimation of soil organic carbon using satellite-derived canopy leaf area index

DOE PAGES

Fang, Yilin; Liu, Chongxuan; Huang, Maoyi; ...

2014-12-02

Soil organic carbon (SOC) plays a key role in the global carbon cycle that is important for decadal-to-century climate prediction. Estimation of soil organic carbon stock using model-based methods typically requires spin-up (time marching transient simulation) of the carbon-nitrogen (CN) models by performing hundreds to thousands years long simulations until the carbon-nitrogen pools reach dynamic steady-state. This has become a bottleneck for global modeling and analysis, especially when testing new physical and/or chemical mechanisms and evaluating parameter sensitivity. Here we report a new numerical approach to estimate global soil carbon stock that can avoid the long term spin-up of themore » CN model. The approach uses canopy leaf area index (LAI) from satellite data and takes advantage of a reaction-based biogeochemical module NGBGC (Next Generation BioGeoChemical Module) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as used in CLM4CN, it can be easily configured to run prognostic or steady state simulations. In this approach, monthly LAI from the multi-year Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to calculate potential annual average gross primary production (GPP) and leaf carbon for the period of the atmospheric forcing. The calculated potential annual average GPP and leaf C are then used by NGBGC to calculate the steady-state distributions of carbon and nitrogen in different vegetation and soil pools by solving the steady-state reaction-network in NGBGC using the Newton-Raphson method. The new approach was applied at point and global scales and compared with SOC derived from long spin-up by running NGBGC in prognostic mode, and SOC from the empirical data of the Harmonized World Soil Database (HWSD). The steady-state solution is comparable to the spin-up value when the MODIS LAI is close to the LAI from the spin-up solution, and largely captured the variability of the HWSD SOC across the different dominant plant functional types (PFTs) at global scale. The numerical correlation between the calculated and HWSD SOC was, however, weak at both point and global scales, suggesting that the models used in describing biogeochemical processes in CLM needs improvements and/or HWSD needs updating as suggested by other studies. Besides SOC, the steady state solution also includes all other state variables simulated by a spin-up run, such as NPP, GPP, total vegetation C etc., which makes the developed approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare different aspects simulated by different CN mechanisms in the model.« less

Advances in understanding, models and parameterisations of biosphere-atmosphere ammonia exchange

NASA Astrophysics Data System (ADS)

Flechard, C. R.; Massad, R.-S.; Loubet, B.; Personne, E.; Simpson, D.; Bash, J. O.; Cooter, E. J.; Nemitz, E.; Sutton, M. A.

2013-03-01

Atmospheric ammonia (NH3) dominates global emissions of total reactive nitrogen (Nr), while emissions from agricultural production systems contribute about two thirds of global NH3 emissions; the remaining third emanates from oceans, natural vegetation, humans, wild animals and biomass burning. On land, NH3 emitted from the various sources eventually returns to the biosphere by dry deposition to sink areas, predominantly semi-natural vegetation, and by wet and dry deposition as ammonium (NH4+) to all surfaces. However, the land/atmosphere exchange of gaseous NH3 is in fact bi-directional over unfertilized as well as fertilized ecosystems, with periods and areas of emission and deposition alternating in time (diurnal, seasonal) and space (patchwork landscapes). The exchange is controlled by a range of environmental factors, including meteorology, surface layer turbulence, thermodynamics, air and surface heterogeneous-phase chemistry, canopy geometry, plant development stage, leaf age, organic matter decomposition, soil microbial turnover, and, in agricultural systems, by fertilizer application rate, fertilizer type, soil type, crop type, and agricultural management practices. We review the range of processes controlling NH3 emission and uptake in the different parts of the soil-canopy-atmosphere continuum, with NH3 emission potentials defined at the substrate and leaf levels by different [NH4+] / [H+] ratios (Γ). Surface/atmosphere exchange models for NH3 are necessary to compute the temporal and spatial patterns of emissions and deposition at the soil, plant, field, landscape, regional and global scales, in order to assess the multiple environmental impacts of air-borne and deposited NH3 and NH4+. Models of soil/vegetation/atmosphereem NH3 exchange are reviewed from the substrate and leaf scales to the global scale. They range from simple steady-state, "big leaf" canopy resistance models, to dynamic, multi-layer, multi-process, multi-chemical species schemes. Their level of complexity depends on their purpose, the spatial scale at which they are applied, the current level of parameterisation, and the availability of the input data they require. State-of-the-art solutions for determining the emission/sink Γ potentials through the soil/canopy system include coupled, interactive chemical transport models (CTM) and soil/ecosystem modelling at the regional scale. However, it remains a matter for debate to what extent realistic options for future regional and global models should be based on process-based mechanistic versus empirical and regression-type models. Further discussion is needed on the extent and timescale by which new approaches can be used, such as integration with ecosystem models and satellite observations.

Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange

NASA Astrophysics Data System (ADS)

Flechard, C. R.; Massad, R.-S.; Loubet, B.; Personne, E.; Simpson, D.; Bash, J. O.; Cooter, E. J.; Nemitz, E.; Sutton, M. A.

2013-07-01

Atmospheric ammonia (NH3) dominates global emissions of total reactive nitrogen (Nr), while emissions from agricultural production systems contribute about two-thirds of global NH3 emissions; the remaining third emanates from oceans, natural vegetation, humans, wild animals and biomass burning. On land, NH3 emitted from the various sources eventually returns to the biosphere by dry deposition to sink areas, predominantly semi-natural vegetation, and by wet and dry deposition as ammonium (NH4+) to all surfaces. However, the land/atmosphere exchange of gaseous NH3 is in fact bi-directional over unfertilized as well as fertilized ecosystems, with periods and areas of emission and deposition alternating in time (diurnal, seasonal) and space (patchwork landscapes). The exchange is controlled by a range of environmental factors, including meteorology, surface layer turbulence, thermodynamics, air and surface heterogeneous-phase chemistry, canopy geometry, plant development stage, leaf age, organic matter decomposition, soil microbial turnover, and, in agricultural systems, by fertilizer application rate, fertilizer type, soil type, crop type, and agricultural management practices. We review the range of processes controlling NH3 emission and uptake in the different parts of the soil-canopy-atmosphere continuum, with NH3 emission potentials defined at the substrate and leaf levels by different [NH4+] / [H+] ratios (Γ). Surface/atmosphere exchange models for NH3 are necessary to compute the temporal and spatial patterns of emissions and deposition at the soil, plant, field, landscape, regional and global scales, in order to assess the multiple environmental impacts of airborne and deposited NH3 and NH4+. Models of soil/vegetation/atmosphere NH3 exchange are reviewed from the substrate and leaf scales to the global scale. They range from simple steady-state, "big leaf" canopy resistance models, to dynamic, multi-layer, multi-process, multi-chemical species schemes. Their level of complexity depends on their purpose, the spatial scale at which they are applied, the current level of parameterization, and the availability of the input data they require. State-of-the-art solutions for determining the emission/sink Γ potentials through the soil/canopy system include coupled, interactive chemical transport models (CTM) and soil/ecosystem modelling at the regional scale. However, it remains a matter for debate to what extent realistic options for future regional and global models should be based on process-based mechanistic versus empirical and regression-type models. Further discussion is needed on the extent and timescale by which new approaches can be used, such as integration with ecosystem models and satellite observations.

Global meta-analysis of leaf area index in wetlands indicates uncertainties in understanding of their ecosystem function

NASA Astrophysics Data System (ADS)

Dronova, I.; Taddeo, S.; Foster, K.

2017-12-01

Projecting ecosystem responses to global change relies on the accurate understanding of properties governing their functions in different environments. An important variable in models of ecosystem function is canopy leaf area index (LAI; leaf area per unit ground area) declared as one of the Essential Climate Variables in the Global Climate Observing System and extensively measured in terrestrial landscapes. However, wetlands have been largely under-represented in these efforts, which globally limits understanding of their contribution to carbon sequestration, climate regulation and resilience to natural and anthropogenic disturbances. This study provides a global synthesis of >350 wetland-specific LAI observations from 182 studies and compares LAI among wetland ecosystem and vegetation types, biomes and measurement approaches. Results indicate that most wetland types and even individual locations show a substantial local dispersion of LAI values (average coefficient of variation 65%) due to heterogeneity of environmental properties and vegetation composition. Such variation indicates that mean LAI values may not sufficiently represent complex wetland environments, and the use of this index in ecosystem function models needs to incorporate within-site variation in canopy properties. Mean LAI did not significantly differ between direct and indirect measurement methods on a pooled global sample; however, within some of the specific biomes and wetland types significant contrasts between these approaches were detected. These contrasts highlight unique aspects of wetland vegetation physiology and canopy structure affecting measurement principles that need to be considered in generalizing canopy properties in ecosystem models. Finally, efforts to assess wetland LAI using remote sensing strongly indicate the promise of this technology for cost-effective regional-scale modeling of canopy properties similar to terrestrial systems. However, such efforts urgently require more rigorous corrections for three-dimensional contributions of non-canopy material and non-vegetated surfaces to wetland canopy reflectance.

Plant leaf traits, canopy processes, and global atmospheric chemistry interactions.

NASA Astrophysics Data System (ADS)

Guenther, A. B.

2017-12-01

Plants produce and emit a diverse array of volatile metabolites into the atmosphere that participate in chemical reactions that influence distributions of air pollutants and short-lived climate forcers including organic aerosol, ozone and methane. It is now widely accepted that accurate estimates of these emissions are required as inputs for regional air quality and global climate models. Predicting these emissions is complicated by the large number of volatile organic compounds, driving variables (e.g., temperature, solar radiation, abiotic and biotic stresses) and processes operating across a range of scales. Modeling efforts to characterize emission magnitude and variations will be described along with an assessment of the observations available for parameterizing and evaluating these models including discussion of the limitations and challenges associated with existing model approaches. A new approach for simulating canopy scale organic emissions on regional to global scales will be described and compared with leaf, canopy and regional scale flux measurements. The importance of including additional compounds and processes as well as improving estimates of existing ones will also be discussed.

Weak leaf photosynthesis and nutrient content relationships from tropical vegetation

NASA Astrophysics Data System (ADS)

Domingues, T. F.; Ishida, F. Y.; Feldpaush, T.; Saiz, G.; Grace, J.; Meir, P.; Lloyd, J.

2015-12-01

Evergreen rain forests and savannas are the two major vegetations of tropical land ecosystems, in terms of land area, biomass, biodiversity, biogeochemical cycles and rates of land use change. Mechanistically understanding ecosystem functioning on such ecosystems is still far from complete, but important for generation of future vegetation scenarios in response to global changes. Leaf photosynthetic rates is a key processes usually represented on land surface-atmosphere models, although data from tropical ecosystems is scarce, considering the high biodiversity they contain. As a shortcut, models usually recur to relationships between leaf nutrient concentration and photosynthetic rates. Such strategy is convenient, given the possibility of global datasets on leave nutrients derived from hyperspectral remote sensing data. Given the importance of Nitrogen on enzyme composition, this nutrient is usually used to infer photosynthetic capacity of leaves. Our experience, based on individual measurements on 1809 individual leaves from 428 species of trees and shrubs naturally occurring on tropical forests and savannas from South America, Africa and Australia, indicates that the relationship between leaf nitrogen and its assimilation capacity is weak. Therefore, leaf Nitrogen alone is a poor predictor of photosynthetic rates of tropical vegetation. Phosphorus concentrations from tropical soils are usually low and is often implied that this nutrient limits primary productivity of tropical vegetation. Still, phosphorus (or other nutrients) did not exerted large influence over photosynthetic capacity, although potassium influenced vegetation structure and function. Such results draw attention to the risks of applying universal nitrogen-photosynthesis relationships on biogeochemical models. Moreover, our data suggests that affiliation of plant species within phylogenetic hierarchy is an important aspect in understanding leaf trait variation. The lack of a strong single predictor of leaf photosynthesis indicates that the importance of other factors such as secondary compounds, mesophyll conductance, Rubisco activation state, etc might be more influential than anticipated.

Mapping local and global variability in plant trait distributions

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

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc

2017-12-01

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusingmore » on a set of plant traits closely coupled to photosynthesis and foliar respiration—specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (N m) and phosphorus (P m), we characterize how traits vary within and among over 50,000 ~50×50-km cells across the entire vegetated land surface. We do this in several ways—without defining the PFT of each grid cell and using 4 or 14 PFTs; each model’s predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps further reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.« less

Performance of a two-leaf light use efficiency model for mapping gross primary productivity against remotely sensed sun-induced chlorophyll fluorescence data.

PubMed

Zan, Mei; Zhou, Yanlian; Ju, Weimin; Zhang, Yongguang; Zhang, Leiming; Liu, Yibo

2018-02-01

Estimating terrestrial gross primary production is an important task when studying the carbon cycle. In this study, the ability of a two-leaf light use efficiency model to simulate regional gross primary production in China was validated using satellite Global Ozone Monitoring Instrument - 2 sun-induced chlorophyll fluorescence data. The two-leaf light use efficiency model was used to estimate daily gross primary production in China's terrestrial ecosystems with 500-m resolution for the period from 2007 to 2014. Gross primary production simulated with the two-leaf light use efficiency model was resampled to a spatial resolution of 0.5° and then compared with sun-induced chlorophyll fluorescence. During the study period, sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf light use efficiency model exhibited similar spatial and temporal patterns in China. The correlation coefficient between sun-induced chlorophyll fluorescence and monthly gross primary production simulated by the two-leaf light use efficiency model was significant (p<0.05, n=96) in 88.9% of vegetated areas in China (average value 0.78) and varied among vegetation types. The interannual variations in monthly sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf light use efficiency model were similar in spring and autumn in most vegetated regions, but dissimilar in winter and summer. The spatial variability of sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf light use efficiency model was similar in spring, summer, and autumn. The proportion of spatial variations of sun-induced chlorophyll fluorescence and annual gross primary production simulated by the two-leaf light use efficiency model explained by ranged from 0.76 (2011) to 0.80 (2013) during the study period. Overall, the two-leaf light use efficiency model was capable of capturing spatial and temporal variations in gross primary production in China. However, the model needs further improvement to better simulate gross primary production in summer. Copyright © 2017 Elsevier B.V. All rights reserved.

Community-weighted mean of leaf traits and divergence of wood traits predict aboveground biomass in secondary subtropical forests.

PubMed

Ali, Arshad; Yan, En-Rong; Chang, Scott X; Cheng, Jun-Yang; Liu, Xiang-Yu

2017-01-01

Subtropical forests are globally important in providing ecological goods and services, but it is not clear whether functional diversity and composition can predict aboveground biomass in such forests. We hypothesized that high aboveground biomass is associated with high functional divergence (FDvar, i.e., niche complementarity) and community-weighted mean (CWM, i.e., mass ratio; communities dominated by a single plant strategy) of trait values. Structural equation modeling was employed to determine the direct and indirect effects of stand age and the residual effects of CWM and FDvar on aboveground biomass across 31 plots in secondary forests in subtropical China. The CWM model accounted for 78, 20, 6 and 2% of the variation in aboveground biomass, nitrogen concentration in young leaf, plant height and specific leaf area of young leaf, respectively. The FDvar model explained 74, 13, 7 and 0% of the variation in aboveground biomass, plant height, twig wood density and nitrogen concentration in young leaf, respectively. The variation in aboveground biomass, CWM of leaf nitrogen concentration and specific leaf area, and FDvar of plant height, twig wood density and nitrogen concentration in young leaf explained by the joint model was 86, 20, 13, 7, 2 and 0%, respectively. Stand age had a strong positive direct effect but low indirect positive effects on aboveground biomass. Aboveground biomass was negatively related to CWM of nitrogen concentration in young leaf, but positively related to CWM of specific leaf area of young leaf and plant height, and FDvar of plant height, twig wood density and nitrogen concentration in young leaf. Leaf and wood economics spectra are decoupled in regulating the functionality of forests, communities with diverse species but high nitrogen conservative and light acquisitive strategies result in high aboveground biomass, and hence, supporting both the mass ratio and niche complementarity hypotheses in secondary subtropical forests. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Global Climatic Controls On Leaf Size

NASA Astrophysics Data System (ADS)

Wright, I. J.; Prentice, I. C.; Dong, N.; Maire, V.

2015-12-01

Since the 1890s it's been known that the wet tropics harbour plants with exceptionally large leaves. Yet the observed latitudinal gradient of leaf size has never been fully explained: it is still unclear which aspects of climate are most important for understanding geographic trends in leaf size, a trait that varies many thousand-fold among species. The key is the leaf-to-air temperature difference, which depends on the balance of energy inputs (irradiance) and outputs (transpirational cooling, losses to the night sky). Smaller leaves track air temperatures more closely than larger leaves. Widely cited optimality-based theories predict an advantage for smaller leaves in dry environments, where transpiration is restricted, but are silent on the latitudinal gradient. We aimed to characterize and explain the worldwide pattern of leaf size. Across 7900 species from 651 sites, here we show that: large-leaved species predominate in wet, hot, sunny environments; smaller-leaved species typify hot, sunny environments only when arid; small leaves are required to avoid freezing in high latitudes and at high elevation, and to avoid overheating in dry environments. This simple pattern was unclear in earlier, more limited analyses. We present a simple but robust, fresh approach to energy-balance modelling for both day-time and night-time leaf-to-air temperature differences, and thus risk of overheating and of frost damage. Our analysis shows night-chilling is important as well as day-heating, and simplifies leaf temperature modelling. It provides both a framework for modelling leaf size constraints, and a solution to one of the oldest conundrums in ecology. Although the path forward is not yet fully clear, because of its role in controlling leaf temperatures we suggest that climate-related leaf size constraints could usefully feature in the next generation of land ecosystem models.

Leaf respiration ( GlobResp) - global trait database supports Earth System Models

DOE PAGES

Wullschleger, Stan D.; Warren, Jeffrey; Thornton, Peter E.

2015-03-20

Here we detail how Atkin and his colleagues compiled a global database (GlobResp) that details rates of leaf dark respiration and associated traits from sites that span Arctic tundra to tropical forests. This compilation builds upon earlier research (Reich et al., 1998; Wright et al., 2006) and was supplemented by recent field campaigns and unpublished data.In keeping with other trait databases, GlobResp provides insights on how physiological traits, especially rates of dark respiration, vary as a function of environment and how that variation can be used to inform terrestrial biosphere models and land surface components of Earth System Models. Althoughmore » an important component of plant and ecosystem carbon (C) budgets (Wythers et al., 2013), respiration has only limited representation in models. Seen through the eyes of a plant scientist, Atkin et al. (2015) give readers a unique perspective on the climatic controls on respiration, thermal acclimation and evolutionary adaptation of dark respiration, and insights into the covariation of respiration with other leaf traits. We find there is ample evidence that once large databases are compiled, like GlobResp, they can reveal new knowledge of plant function and provide a valuable resource for hypothesis testing and model development.« less

Inter- and intraspecific variation in leaf economic traits in wheat and maize

PubMed Central

Hale, Christine E; Cerabolini, Bruno E L; Cornelissen, Johannes H C; Craine, Joseph; Gough, William A; Kattge, Jens; Tirona, Cairan K F

2018-01-01

Abstract Leaf Economics Spectrum (LES) trait variation underpins multiple agroecological processes and many prominent crop yield models. While there are numerous independent studies assessing trait variation in crops, to date there have been no comprehensive assessments of intraspecific trait variation (ITV) in LES traits for wheat and maize: the world’s most widespread crops. Using trait databases and peer-reviewed literature, we compiled over 700 records of specific leaf area (SLA), maximum photosynthetic rates (Amax) and leaf nitrogen (N) concentrations, for wheat and maize. We evaluated intraspecific LES trait variation, and intraspecific trait–environment relationships. While wheat and maize occupy the upper 90th percentile of LES trait values observed across a global species pool, ITV ranged widely across the LES in wheat and maize. Fertilization treatments had strong impacts on leaf N, while plant developmental stage (here standardized as the number of days since planting) had strong impacts on Amax; days since planting, N fertilization and irrigation all influenced SLA. When controlling for these factors, intraspecific responses to temperature and precipitation explained 39.4 and 43.7 % of the variation in Amax and SLA, respectively, but only 5.4 % of the variation in leaf N. Despite a long history of domestication in these species, ITV in wheat and maize among and within cultivars remains large. Intraspecific trait variation is a critical consideration to refine regional to global models of agroecosystem structure, function and food security. Considerable opportunities and benefits exist for consolidating a crop trait database for a wider range of domesticated plant species. PMID:29484152

Inter- and intraspecific variation in leaf economic traits in wheat and maize.

PubMed

Martin, Adam R; Hale, Christine E; Cerabolini, Bruno E L; Cornelissen, Johannes H C; Craine, Joseph; Gough, William A; Kattge, Jens; Tirona, Cairan K F

2018-02-01

Leaf Economics Spectrum (LES) trait variation underpins multiple agroecological processes and many prominent crop yield models. While there are numerous independent studies assessing trait variation in crops, to date there have been no comprehensive assessments of intraspecific trait variation (ITV) in LES traits for wheat and maize: the world's most widespread crops. Using trait databases and peer-reviewed literature, we compiled over 700 records of specific leaf area (SLA), maximum photosynthetic rates ( A max ) and leaf nitrogen (N) concentrations, for wheat and maize. We evaluated intraspecific LES trait variation, and intraspecific trait-environment relationships. While wheat and maize occupy the upper 90th percentile of LES trait values observed across a global species pool, ITV ranged widely across the LES in wheat and maize. Fertilization treatments had strong impacts on leaf N, while plant developmental stage (here standardized as the number of days since planting) had strong impacts on A max ; days since planting, N fertilization and irrigation all influenced SLA. When controlling for these factors, intraspecific responses to temperature and precipitation explained 39.4 and 43.7 % of the variation in A max and SLA, respectively, but only 5.4 % of the variation in leaf N. Despite a long history of domestication in these species, ITV in wheat and maize among and within cultivars remains large. Intraspecific trait variation is a critical consideration to refine regional to global models of agroecosystem structure, function and food security. Considerable opportunities and benefits exist for consolidating a crop trait database for a wider range of domesticated plant species.

76 FR 33923 - Endangered and Threatened Wildlife and Plants; 12-Month Finding on a Petition To List Abronia...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-09

... Sipes 2006, p. 76). The leaf blades are succulent (fleshy) and oval or diamond-shaped with smooth edges... of climate model runs performed at modeling centers worldwide using 22 global climate models (Ray et...

Reducing the uncertainty in the projection of the terrestrial carbon cycle by fusing models with remote sensing data

NASA Astrophysics Data System (ADS)

Serbin, S.; Shiklomanov, A. N.; Viskari, T.; Desai, A. R.; Townsend, P. A.; Dietze, M.

2015-12-01

Modeling global change requires accurate representation of terrestrial carbon (C), energy and water fluxes. In particular, capturing the properties of vegetation canopies that describe the radiation regime are a key focus for global change research because the properties related to radiation utilization and penetration within plant canopies provide an important constraint on terrestrial ecosystem productivity, as well as the fluxes of water and energy from vegetation to the atmosphere. As such, optical remote sensing observations present an important, and as yet relatively untapped, source of observations that can be used to inform modeling activities. In particular, high-spectral resolution optical data at the leaf and canopy scales offers the potential for an important and direct data constraint on the parameterization and structure of the radiative transfer model (RTM) scheme within ecosystem models across diverse vegetation types, disturbance and management histories. In this presentation we highlight ongoing work to integrate optical remote sensing observations, specifically leaf and imaging spectroscopy (IS) data across a range of forest ecosystems, into complex ecosystem process models within an efficient computational assimilation framework as a means to improve the description of canopy optical properties, vegetation composition, and modeled radiation balance. Our work leverages the Predictive Ecosystem Analyzer (PEcAn; http://www.pecanproject.org/) ecoinformatics toolbox together with a RTM module designed for efficient assimilation of leaf and IS observations to inform vegetation optical properties as well as associated plant traits. Ultimately, an improved understanding of the radiation balance of ecosystems will provide a better constraint on model projections of energy balance, vegetation composition, and carbon pools and fluxes thus allowing for a better diagnosis of the vulnerability of terrestrial ecosystems in response to global change.

Global patterns in leaf 13C discrimination and implications for studies of past and future climate

PubMed Central

Diefendorf, Aaron F.; Mueller, Kevin E.; Wing, Scott. L.; Koch, Paul L.; Freeman, Katherine H.

2010-01-01

Fractionation of carbon isotopes by plants during CO2 uptake and fixation (Δleaf) varies with environmental conditions, but quantitative patterns of Δleaf across environmental gradients at the global scale are lacking. This impedes interpretation of variability in ancient terrestrial organic matter, which encodes climatic and ecological signals. To address this problem, we converted 3,310 published leaf δ13C values into mean Δleaf values for 334 woody plant species at 105 locations (yielding 570 species-site combinations) representing a wide range of environmental conditions. Our analyses reveal a strong positive correlation between Δleaf and mean annual precipitation (MAP; R2 = 0.55), mirroring global trends in gross primary production and indicating stomatal constraints on leaf gas-exchange, mediated by water supply, are the dominant control of Δleaf at large spatial scales. Independent of MAP, we show a lesser, negative effect of altitude on Δleaf and minor effects of temperature and latitude. After accounting for these factors, mean Δleaf of evergreen gymnosperms is lower (by 1–2.7‰) than for other woody plant functional types (PFT), likely due to greater leaf-level water-use efficiency. Together, environmental and PFT effects contribute to differences in mean Δleaf of up to 6‰ between biomes. Coupling geologic indicators of ancient precipitation and PFT (or biome) with modern Δleaf patterns has potential to yield more robust reconstructions of atmospheric δ13C values, leading to better constraints on past greenhouse-gas perturbations. Accordingly, we estimate a 4.6‰ decline in the δ13C of atmospheric CO2 at the onset of the Paleocene-Eocene Thermal Maximum, an abrupt global warming event ∼55.8 Ma. PMID:20231481

The decadal state of the terrestrial carbon cycle: Global retrievals of terrestrial carbon allocation, pools, and residence times

PubMed Central

Bloom, A. Anthony; Exbrayat, Jean-François; van der Velde, Ivar R.; Feng, Liang; Williams, Mathew

2016-01-01

The terrestrial carbon cycle is currently the least constrained component of the global carbon budget. Large uncertainties stem from a poor understanding of plant carbon allocation, stocks, residence times, and carbon use efficiency. Imposing observational constraints on the terrestrial carbon cycle and its processes is, therefore, necessary to better understand its current state and predict its future state. We combine a diagnostic ecosystem carbon model with satellite observations of leaf area and biomass (where and when available) and soil carbon data to retrieve the first global estimates, to our knowledge, of carbon cycle state and process variables at a 1° × 1° resolution; retrieved variables are independent from the plant functional type and steady-state paradigms. Our results reveal global emergent relationships in the spatial distribution of key carbon cycle states and processes. Live biomass and dead organic carbon residence times exhibit contrasting spatial features (r = 0.3). Allocation to structural carbon is highest in the wet tropics (85–88%) in contrast to higher latitudes (73–82%), where allocation shifts toward photosynthetic carbon. Carbon use efficiency is lowest (0.42–0.44) in the wet tropics. We find an emergent global correlation between retrievals of leaf mass per leaf area and leaf lifespan (r = 0.64–0.80) that matches independent trait studies. We show that conventional land cover types cannot adequately describe the spatial variability of key carbon states and processes (multiple correlation median = 0.41). This mismatch has strong implications for the prediction of terrestrial carbon dynamics, which are currently based on globally applied parameters linked to land cover or plant functional types. PMID:26787856

A Graphical User Interface for Parameterizing Biochemical Models of Photosynthesis and Chlorophyll Fluorescence

NASA Astrophysics Data System (ADS)

Kornfeld, A.; Van der Tol, C.; Berry, J. A.

2015-12-01

Recent advances in optical remote sensing of photosynthesis offer great promise for estimating gross primary productivity (GPP) at leaf, canopy and even global scale. These methods -including solar-induced chlorophyll fluorescence (SIF) emission, fluorescence spectra, and hyperspectral features such as the red edge and the photochemical reflectance index (PRI) - can be used to greatly enhance the predictive power of global circulation models (GCMs) by providing better constraints on GPP. The way to use measured optical data to parameterize existing models such as SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) is not trivial, however. We have therefore extended a biochemical model to include fluorescence and other parameters in a coupled treatment. To help parameterize the model, we then use nonlinear curve-fitting routines to determine the parameter set that enables model results to best fit leaf-level gas exchange and optical data measurements. To make the tool more accessible to all practitioners, we have further designed a graphical user interface (GUI) based front-end to allow researchers to analyze data with a minimum of effort while, at the same time, allowing them to change parameters interactively to visualize how variation in model parameters affect predicted outcomes such as photosynthetic rates, electron transport, and chlorophyll fluorescence. Here we discuss the tool and its effectiveness, using recently-gathered leaf-level data.

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

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

Unger, N.; Harper, K.; Zheng, Y.

2013-10-22

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar/Ball- Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the ratemore » of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present day climatic state that uses plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R 2 = 64-96 %) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr -1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.« less

Photosynthesis-dependent Isoprene Emission from Leaf to Planet in a Global Carbon-chemistry-climate Model

NASA Technical Reports Server (NTRS)

Unger, N.; Harper, K.; Zeng, Y.; Kiang, N. Y.; Alienov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.;

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

NASA Astrophysics Data System (ADS)

Unger, N.; Harper, K.; Zheng, Y.; Kiang, N. Y.; Aleinov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.; Heinesch, B.; Hewitt, C. N.; Karl, T.; Laffineur, Q.; Langford, B.; McKinney, K. A.; Misztal, P.; Potosnak, M.; Rinne, J.; Pressley, S.; Schoon, N.; Serça, D.

2013-10-01

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar-Ball-Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 = 64-96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr-1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

NASA Astrophysics Data System (ADS)

Unger, N.; Harper, K.; Zheng, Y.; Kiang, N. Y.; Aleinov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.; Heinesch, B.; Hewitt, C. N.; Karl, T.; Laffineur, Q.; Langford, B.; McKinney, K. A.; Misztal, P.; Potosnak, M.; Rinne, J.; Pressley, S.; Schoon, N.; Serça, D.

2013-07-01

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar/Ball-Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2= 64-96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 Tg C yr-1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Exploring Patterns of Soil Organic Matter Decomposition with Students through the Global Decomposition Project (GDP) and the Interactive Model of Leaf Decomposition (IMOLD)

NASA Astrophysics Data System (ADS)

Steiner, S. M.; Wood, J. H.

2015-12-01

As decomposition rates are affected by climate change, understanding crucial soil interactions that affect plant growth and decomposition becomes a vital part of contributing to the students' knowledge base. The Global Decomposition Project (GDP) is designed to introduce and educate students about soil organic matter and decomposition through a standardized protocol for collecting, reporting, and sharing data. The Interactive Model of Leaf Decomposition (IMOLD) utilizes animations and modeling to learn about the carbon cycle, leaf anatomy, and the role of microbes in decomposition. Paired together, IMOLD teaches the background information and allows simulation of numerous scenarios, and the GDP is a data collection protocol that allows students to gather usable measurements of decomposition in the field. Our presentation will detail how the GDP protocol works, how to obtain or make the materials needed, and how results will be shared. We will also highlight learning objectives from the three animations of IMOLD, and demonstrate how students can experiment with different climates and litter types using the interactive model to explore a variety of decomposition scenarios. The GDP demonstrates how scientific methods can be extended to educate broader audiences, and data collected by students can provide new insight into global patterns of soil decomposition. Using IMOLD, students will gain a better understanding of carbon cycling in the context of litter decomposition, as well as learn to pose questions they can answer with an authentic computer model. Using the GDP protocols and IMOLD provide a pathway for scientists and educators to interact and reach meaningful education and research goals.

Variations in the methane budget over the last two millennia

NASA Astrophysics Data System (ADS)

Derendorp, L.

2012-06-01

Leaf litter is available at the Earth’s surface in large quantities. During the decomposition of leaf litter, volatile compounds can be released into the atmosphere, where they potentially influence local air quality, atmospheric chemistry or the global climate. In this thesis the focus was on the emission of C2-C5 hydrocarbons, molecular hydrogen (H2), carbon monoxide (CO) and methyl chloride (CH3Cl) from leaf litter and the factors that control the emissions were investigated. For different plant species, the emission rates of several C2-C5 hydrocarbons increased with temperature between 20 and 100°C according to the Arrhenius relation. When leaf litter was irradiated with UV, the emission increased linearly with the intensity of the UV. UVB radiation was more efficient in the generation of hydrocarbons from leaf litter than UVA. A simple upscaling showed that C2-C5 hydrocarbon emissions from leaf litter are likely insignificant for their global budgets, but may have a small influence on atmospheric chemistry on the local scale. Senescent and dead plant material releases carbon monoxide (CO), methane and larger hydrocarbons upon heating or irradiation with UV, but emissions of hydrogen (H2) have not been reported. In this study, H2 was released from leaf litter of Sequoiadendron giganteum in detectable amounts at temperatures above 45°C, whereas CO was also emitted at ambient temperature. Leaf litter has been identified as a potentially important source of CH3Cl. However, the factors controlling the emissions are unclear. Laboratory experiments have been performed in which CH3Cl emissions were measured from leaf litter of different plant species. For each investigated plant species, the CH3Cl emission rate strongly increased with temperature according to the Arrhenius relation. However, at constant temperature, large differences between different plants were observed. Therefore, CH3Cl emissions were measured from halophyte leaf litter with a varying chloride content, but no significant correlation between the CH3Cl emission rate and the chloride content of the plant material was observed. A limited set of field experiments was performed in which CH3Cl emissions were measured. Leaf litter emitted CH3Cl, but only in periods with fresh leaf litter fall. Outside these periods, the flux from leaf litter was zero or even slightly negative. The CH3Cl emission rate increased with temperature, but the temperature increase did not follow the Arrhenius relation as was observed in the laboratory experiments. The global importance of leaf litter as a source of CH3Cl was investigated using the global chemistry transport model TM5. Forward simulations with different emission scenarios indicated that at station Trinidad Head (mid-latitudes of North America), a substantial seasonal emission from leaf litter was required to match the measured CH3Cl mixing ratios at this station. Inversions performed with the TM4-4D-Var system indicated that the main CH3Cl sources were located in the Tropics, whereas the mid- and high latitudes were only a minor source. Sensitivity studies performed to investigate the robustness of the optimized emissions indicated that more than 90% of the global net emissions was located in the Tropics.

Simulation of leaf area index on site scale based on model data fusion

NASA Astrophysics Data System (ADS)

Yang, Y.; Wang, J. B.

2017-12-01

The world's grassland area is about 24 × 108hm2, accounting for about one-fifth of the global land area. It is one of the most widely distributed terrestrial ecosystems on Earth. And currently, it is the most affected area of human activity. A considerable portion of the global CO2 emissions are fixed by grassland, and the grassland carbon cycle plays an important role in the global carbon cycle (Li Bo, Yongshen Peng, Li Yao, China's Prairie, 1990). In recent years, the carbon cycle and its influencing factors of grassland ecosystems have become one of the hotspots in ecology, geology, botany and agronomy under the background of global change ( Mu Shaojie, 2014) . And the model is now as a popular and effective method of research. However, there are still some uncertainties in this approach. CEVSA ( Carbon Exchange between Vegetation, Soil and Atmosphere) is a biogeochemical cycle model based on physiological and ecological processes to simulate plant-soil-atmosphere system energy exchange and water-carbon-nitrogen coupling cycles (Cao at al., 1998a; 1998b; Woodward et al., 1995). In this paper, the remote sensing observation data of leaf area index are integrated into the model, and the CEVSA model of site version is optimized by Markov chain-Monte Carlo method to achieve the purpose of increasing the accuracy of model results.

Global Land Carbon Uptake from Trait Distributions

NASA Astrophysics Data System (ADS)

Butler, E. E.; Datta, A.; Flores-Moreno, H.; Fazayeli, F.; Chen, M.; Wythers, K. R.; Banerjee, A.; Atkin, O. K.; Kattge, J.; Reich, P. B.

2016-12-01

Historically, functional diversity in land surface models has been represented through a range of plant functional types (PFTs), each of which has a single value for all of its functional traits. Here we expand the diversity of the land surface by using a distribution of trait values for each PFT. The data for these trait distributions is from a sub-set of the global database of plant traits, TRY, and this analysis uses three leaf traits: mass based nitrogen and phosphorus content and specific leaf area, which influence both photosynthesis and respiration. The data are extrapolated into continuous surfaces through two methodologies. The first, a categorical method, classifies the species observed in TRY into satellite estimates of their plant functional type abundances - analogous to how traits are currently assigned to PFTs in land surface models. Second, a Bayesian spatial method which additionally estimates how the distribution of a trait changes in accord with both climate and soil covariates. These two methods produce distinct patterns of diversity which are incorporated into a land surface model to estimate how the range of trait values affects the global land carbon budget.

Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison

DOE PAGES

Restrepo-Coupe, Natalia; Levine, Naomi M.; Christoffersen, Bradley O.; ...

2016-08-29

To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of othermore » fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ‘soil water stress’ and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.« less

Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison

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

Restrepo-Coupe, Natalia; Levine, Naomi M.; Christoffersen, Bradley O.

To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of othermore » fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ‘soil water stress’ and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.« less

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.

Modeling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

NASA Astrophysics Data System (ADS)

Reichstein, Markus; Rey, Ana; Freibauer, Annette; Tenhunen, John; Valentini, Riccardo; Banza, Joao; Casals, Pere; Cheng, Yufu; Grünzweig, Jose M.; Irvine, James; Joffre, Richard; Law, Beverly E.; Loustau, Denis; Miglietta, Franco; Oechel, Walter; Ourcival, Jean-Marc; Pereira, Joao S.; Peressotti, Alessandro; Ponti, Francesca; Qi, Ye; Rambal, Serge; Rayment, Mark; Romanya, Joan; Rossi, Federica; Tedeschi, Vanessa; Tirone, Giampiero; Xu, Ming; Yakir, Dan

2003-12-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, interannual and spatial variability of soil respiration as affected by water availability, temperature, and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g., leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical nonlinear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content, and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and intersite variability of soil respiration with a mean absolute error of 0.82 μmol m-2 s-1. The parameterized model exhibits the following principal properties: (1) At a relative amount of upper-layer soil water of 16% of field capacity, half-maximal soil respiration rates are reached. (2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. (3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly timescale, we employed the approach by [2002] that used monthly precipitation and air temperature to globally predict soil respiration (T&P model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the intersite variability, regardless of whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly timescale, we developed a simple T&P&LAI model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time step model and explained 50% of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index. Before application at the continental or global scale, this approach should be further tested in boreal, cold-temperate, and tropical biomes as well as for non-woody vegetation.

Leaf photosynthesis and respiration of three bioenergy crops in relation to temperature and leaf nitrogen: how conserved are biochemical model parameters among crop species?

PubMed Central

Archontoulis, S. V.; Yin, X.; Vos, J.; Danalatos, N. G.; Struik, P. C.

2012-01-01

Given the need for parallel increases in food and energy production from crops in the context of global change, crop simulation models and data sets to feed these models with photosynthesis and respiration parameters are increasingly important. This study provides information on photosynthesis and respiration for three energy crops (sunflower, kenaf, and cynara), reviews relevant information for five other crops (wheat, barley, cotton, tobacco, and grape), and assesses how conserved photosynthesis parameters are among crops. Using large data sets and optimization techniques, the C3 leaf photosynthesis model of Farquhar, von Caemmerer, and Berry (FvCB) and an empirical night respiration model for tested energy crops accounting for effects of temperature and leaf nitrogen were parameterized. Instead of the common approach of using information on net photosynthesis response to CO2 at the stomatal cavity (An–Ci), the model was parameterized by analysing the photosynthesis response to incident light intensity (An–Iinc). Convincing evidence is provided that the maximum Rubisco carboxylation rate or the maximum electron transport rate was very similar whether derived from An–Ci or from An–Iinc data sets. Parameters characterizing Rubisco limitation, electron transport limitation, the degree to which light inhibits leaf respiration, night respiration, and the minimum leaf nitrogen required for photosynthesis were then determined. Model predictions were validated against independent sets. Only a few FvCB parameters were conserved among crop species, thus species-specific FvCB model parameters are needed for crop modelling. Therefore, information from readily available but underexplored An–Iinc data should be re-analysed, thereby expanding the potential of combining classical photosynthetic data and the biochemical model. PMID:22021569

Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area

USGS Publications Warehouse

Greenwood, Sarah; Ruiz-Benito, Paloma; Martinez-Vilalta, Jordi; Lloret, Francisco; Kitzberger, Thomas; Allen, Craig D.; Fensham, Rod; Laughlin, Daniel C.; Kattge, Jens; Bönisch, Gerhard; Kraft, Nathan J. B.; Jump, Alistair S.

2017-01-01

Drought events are increasing globally, and reports of consequent forest mortality are widespread. However, due to a lack of a quantitative global synthesis, it is still not clear whether drought-induced mortality rates differ among global biomes and whether functional traits influence the risk of drought-induced mortality. To address these uncertainties, we performed a global meta-analysis of 58 studies of drought-induced forest mortality. Mortality rates were modelled as a function of drought, temperature, biomes, phylogenetic and functional groups and functional traits. We identified a consistent global-scale response, where mortality increased with drought severity [log mortality (trees trees−1 year−1) increased 0.46 (95% CI = 0.2–0.7) with one SPEI unit drought intensity]. We found no significant differences in the magnitude of the response depending on forest biomes or between angiosperms and gymnosperms or evergreen and deciduous tree species. Functional traits explained some of the variation in drought responses between species (i.e. increased from 30 to 37% when wood density and specific leaf area were included). Tree species with denser wood and lower specific leaf area showed lower mortality responses. Our results illustrate the value of functional traits for understanding patterns of drought-induced tree mortality and suggest that mortality could become increasingly widespread in the future.

Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area.

PubMed

Greenwood, Sarah; Ruiz-Benito, Paloma; Martínez-Vilalta, Jordi; Lloret, Francisco; Kitzberger, Thomas; Allen, Craig D; Fensham, Rod; Laughlin, Daniel C; Kattge, Jens; Bönisch, Gerhard; Kraft, Nathan J B; Jump, Alistair S

2017-04-01

Drought events are increasing globally, and reports of consequent forest mortality are widespread. However, due to a lack of a quantitative global synthesis, it is still not clear whether drought-induced mortality rates differ among global biomes and whether functional traits influence the risk of drought-induced mortality. To address these uncertainties, we performed a global meta-analysis of 58 studies of drought-induced forest mortality. Mortality rates were modelled as a function of drought, temperature, biomes, phylogenetic and functional groups and functional traits. We identified a consistent global-scale response, where mortality increased with drought severity [log mortality (trees trees -1  year -1 ) increased 0.46 (95% CI = 0.2-0.7) with one SPEI unit drought intensity]. We found no significant differences in the magnitude of the response depending on forest biomes or between angiosperms and gymnosperms or evergreen and deciduous tree species. Functional traits explained some of the variation in drought responses between species (i.e. increased from 30 to 37% when wood density and specific leaf area were included). Tree species with denser wood and lower specific leaf area showed lower mortality responses. Our results illustrate the value of functional traits for understanding patterns of drought-induced tree mortality and suggest that mortality could become increasingly widespread in the future. © 2017 John Wiley & Sons Ltd/CNRS.

On the use of tower-flux measurements to assess the performance of global ecosystem models

NASA Astrophysics Data System (ADS)

El Maayar, M.; Kucharik, C.

2003-04-01

Global ecosystem models are important tools for the study of biospheric processes and their responses to environmental changes. Such models typically translate knowledge, gained from local observations, into estimates of regional or even global outcomes of ecosystem processes. A typical test of ecosystem models consists of comparing their output against tower-flux measurements of land surface-atmosphere exchange of heat and mass. To perform such tests, models are typically run using detailed information on soil properties (texture, carbon content,...) and vegetation structure observed at the experimental site (e.g., vegetation height, vegetation phenology, leaf photosynthetic characteristics,...). In global simulations, however, earth's vegetation is typically represented by a limited number of plant functional types (PFT; group of plant species that have similar physiological and ecological characteristics). For each PFT (e.g., temperate broadleaf trees, boreal conifer evergreen trees,...), which can cover a very large area, a set of typical physiological and physical parameters are assigned. Thus, a legitimate question arises: How does the performance of a global ecosystem model run using detailed site-specific parameters compare with the performance of a less detailed global version where generic parameters are attributed to a group of vegetation species forming a PFT? To answer this question, we used a multiyear dataset, measured at two forest sites with contrasting environments, to compare seasonal and interannual variability of surface-atmosphere exchange of water and carbon predicted by the Integrated BIosphere Simulator-Dynamic Global Vegetation Model. Two types of simulations were, thus, performed: a) Detailed runs: observed vegetation characteristics (leaf area index, vegetation height,...) and soil carbon content, in addition to climate and soil type, are specified for model run; and b) Generic runs: when only observed climates and soil types at the measurement sites are used to run the model. The generic runs were performed for the number of years equal to the current age of the forests, initialized with no vegetation and a soil carbon density equal to zero.

Earth System Modeling Tested for CLM4.5 in a Costa Rican Tropical Montane Rainforest

NASA Astrophysics Data System (ADS)

Song, J.; Miller, G. R.; Cahill, A. T.; Aparecido, L. M. T.; Moore, G. W.

2017-12-01

Terrestrial ecosystems in the tropics are important for global carbon and water cycling, which makes modeling of their land-surface processes essential for accurate understanding of land-atmosphere interactions. However, modeling of tropical regions, especially mountainous ones, is known to be subject to significant errors in the prediction of evapotranspiration. Our previous work has highlighted the effects of the prolonged wetness experienced by such sites, focusing on carbon and water exchange at the leaf/stand level. Here, we explore the implications these findings have for modeling at the stand/canopy scale. This study examined the performance of the Community Land Model (CLM4.5) against measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4,000 mm of mean annual precipitation. Measurements include leaf temperatures, transpiration (sap flows), fluxes via eddy-covariance, and vertical profiles of H2O and CO2 concentrations, micrometeorological variables, and leaf wetness. In this work, results from point-scale CLM4.5 were compared to canopy data. The model fails to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). We found that soil and leaf temperatures were overestimated (≈ +2°C) at noon and underestimated (≈ -1°C) during the night; daily transpiration was approximately double than that observed. Simulated leaf wetness deviated significantly from the measurements, both in timing and extent, which affected temperatures and evapotranspiration partitioning. Slope effects appeared in the average diurnal variations of surface albedo and carbon flux from actual data but were not captured in CLM. Our investigation indicated that interception and aerodynamic resistance models contribute to model errors, suggesting potential improvements for modeling in very wet and/or mountainous regions.

Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

NASA Astrophysics Data System (ADS)

Quetin, G. R.; Swann, A. L. S.

2017-12-01

Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models.

A Novel Diffuse Fraction-Based Two-Leaf Light Use Efficiency Model: An Application Quantifying Photosynthetic Seasonality across 20 AmeriFlux Flux Tower Sites

NASA Astrophysics Data System (ADS)

Yan, Hao; Wang, Shao-Qiang; Yu, Kai-Liang; Wang, Bin; Yu, Qin; Bohrer, Gil; Billesbach, Dave; Bracho, Rosvel; Rahman, Faiz; Shugart, Herman H.

2017-10-01

Diffuse radiation can increase canopy light use efficiency (LUE). This creates the need to differentiate the effects of direct and diffuse radiation when simulating terrestrial gross primary production (GPP). Here, we present a novel GPP model, the diffuse-fraction-based two-leaf model (DTEC), which includes the leaf response to direct and diffuse radiation, and treats maximum LUE for shaded leaves (ɛmsh defined as a power function of the diffuse fraction (Df)) and sunlit leaves (ɛmsu defined as a constant) separately. An Amazonian rainforest site (KM67) was used to calibrate the model by simulating the linear relationship between monthly canopy LUE and Df. This showed a positive response of forest GPP to atmospheric diffuse radiation, and suggested that diffuse radiation was more limiting than global radiation and water availability for Amazon rainforest GPP on a monthly scale. Further evaluation at 20 independent AmeriFlux sites showed that the DTEC model, when driven by monthly meteorological data and MODIS leaf area index (LAI) products, explained 70% of the variability observed in monthly flux tower GPP. This exceeded the 51% accounted for by the MODIS 17A2 big-leaf GPP product. The DTEC model's explicit accounting for the impacts of diffuse radiation and soil water stress along with its parameterization for C4 and C3 plants was responsible for this difference. The evaluation of DTEC at Amazon rainforest sites demonstrated its potential to capture the unique seasonality of higher GPP during the diffuse radiation-dominated wet season. Our results highlight the importance of diffuse radiation in seasonal GPP simulation.