David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Maosheng Zhao; Steve W. Running; Steven C. Wofsy; Shawn Urbanski; Allison L. Dunn; J.W. Munger
2003-01-01
The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using...
Evaluation of MODIS NPP and GPP products across multiple biomes.
David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Steve W. Running; Maosheng Zhao; Marcos H. Costa; Al A. Kirschbaum; Jay M. Ham; Scott R. Saleska; Douglas E. Ahl
2006-01-01
Estimates of daily gross primary production (GPP) and annual net primary production (NPP) at the 1 km spatial resolution are now produced operationally for the global terrestrial surface using imagery from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. Ecosystem-level measurements of GPP at eddy covariance flux towers and plot-level measurements of...
How much do different global GPP products agree in distribution and magnitude of GPP extremes?
NASA Astrophysics Data System (ADS)
Kim, S.; Ryu, Y.; Jiang, C.
2016-12-01
To evaluate uncertainty of global Gross Primary Productivity (GPP) extremes, we compare three global GPP datasets derived from different data processing methods (e.g. MPI-BGC: machine-learning, MODIS GPP (MOD17): semi-empirical, Breathing Earth System Simulator (BESS): process based). We preprocess the datasets following the method from Zscheischler et al., (2012) to detect GPP extremes which occur in less than 1% of the number of whole pixels, and to identify 3D-connected spatiotemporal GPP extremes. We firstly analyze global patterns and the magnitude of GPP extremes with MPI-BGC, MOD17, and BESS over 2001-2011. For consistent analysis in the three products, spatial and temporal resolution were set at 50 km and a monthly scale, respectively. Our results indicated that the global patterns of GPP extremes derived from MPI-BGC and BESS agreed with each other by showing hotspots in Northeastern Brazil and Eastern Texas. However, the extreme events detected from MOD17 were concentrated in tropical forests (e.g. Southeast Asia and South America). The amount of GPP reduction caused by climate extremes considerably differed across the products. For example, Russian heatwave in 2010 led to 100 Tg C uncertainty (198.7 Tg C in MPI-BGC, 305.6 Tg C in MOD17, and 237.8 Tg C in BESS). Moreover, the duration of extreme events differ among the three GPP datasets for the Russian heatwave (MPI-BGC: May-Sep, MOD17: Jun-Aug, and BESS: May-Aug). To test whether Sun induced Fluorescence (SiF), a proxy of GPP, can capture GPP extremes, we investigate global distribution of GPP extreme events in BESS, MOD17 and GOME-2 SiF between 2008 and 2014 when SiF data is available. We found that extreme GPP events in GOME-2 SiF and MOD17 appear in tropical forests whereas those in BESS emerged in Northeastern Brazil and Eastern Texas. The GPP extremes by severe 2011 US drought were detected by BESS and MODIS, but not by SiF. Our findings highlight that different GPP datasets could result in varying
NASA Astrophysics Data System (ADS)
Rambal, S.; Lempereur, M.; Limousin, J. M.; Martin-StPaul, N. K.; Ourcival, J. M.; Rodríguez-Calcerrada, J.
2014-12-01
The partitioning of photosynthates toward biomass compartments plays a crucial role in the carbon (C) sink function of forests. Few studies have examined how carbon is allocated toward plant compartments in drought-prone forests. We analyzed the fate of gross primary production (GPP) in relation to yearly water deficit in an old evergreen Mediterranean Quercus ilex coppice severely affected by water limitations. Carbon fluxes between the ecosystem and the atmosphere were measured with an eddy covariance flux tower running continuously since 2001. Discrete measurements of litterfall, stem growth and fAPAR allowed us to derive annual productions of leaves, wood, flowers and acorns, and an isometric relationship between stem and belowground biomass has been used to estimate perennial belowground growth. By combining eddy covariance fluxes with annual net primary productions (NPP), we managed to close a C budget and derive values of autotrophic, heterotrophic respirations and carbon-use efficiency (CUE; the ratio between NPP and GPP). Average values of yearly net ecosystem production (NEP), GPP and Reco were 282, 1259 and 977 g C m-2. The corresponding aboveground net primary production (ANPP) components were 142.5, 26.4 and 69.6 g C m-2 for leaves, reproductive effort (flowers and fruits) and stems, respectively. NEP, GPP and Reco were affected by annual water deficit. Partitioning to the different plant compartments was also impacted by drought, with a hierarchy of responses going from the most affected - the stem growth - to the least affected - the leaf production. The average CUE was 0.40, which is well in the range for Mediterranean-type forest ecosystems. CUE tended to decrease less drastically in response to drought than GPP and NPP did, probably due to drought acclimation of autotrophic respiration. Overall, our results provide a baseline for modeling the inter-annual variations of carbon fluxes and allocation in this widespread Mediterranean ecosystem, and
NASA Technical Reports Server (NTRS)
Zhang, Qingyuan; Cheng, Yen-Ben; Lyapustin, Alexei I.; Wang, Yujie; Zhang, Xiaoyang; Suyker, Andrew; Verma, Shashi; Shuai, Yanmin; Middleton, Elizabeth M.
2015-01-01
Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the
A Model-based Approach to Scaling GPP and NPP in Support of MODIS Land Product Validation
NASA Astrophysics Data System (ADS)
Turner, D. P.; Cohen, W. B.; Gower, S. T.; Ritts, W. D.
2003-12-01
Global products from the Earth-orbiting MODIS sensor include land cover, leaf area index (LAI), FPAR, 8-day gross primary production (GPP), and annual net primary production (NPP) at the 1 km spatial resolution. The BigFoot Project was designed specifically to validate MODIS land products, and has initiated ground measurements at 9 sites representing a wide array of vegetation types. An ecosystem process model (Biome-BGC) is used to generate estimates of GPP and NPP for each 5 km x 5 km BigFoot site. Model inputs include land cover and LAI (from Landsat ETM+), daily meteorological data (from a centrally located eddy covariance flux tower), and soil characteristics. Model derived outputs are validated against field-measured NPP and flux tower-derived GPP. The resulting GPP and NPP estimates are then aggregated to the 1 km resolution for direct spatial comparison with corresponding MODIS products. At the high latitude sites (tundra and boreal forest), the MODIS GPP phenology closely tracks the BigFoot GPP, but there is a high bias in the MODIS GPP. In the temperate zone sites, problems with the timing and magnitude of the MODIS FPAR introduce differences in MODIS GPP compared to the validation data at some sites. However, the MODIS LAI/FPAR data are currently being reprocessed (=Collection 4) and new comparisons will be made for 2002. The BigFoot scaling approach permits precise overlap in spatial and temporal resolution between the MODIS products and BigFoot products, and thus permits the evaluation of specific components of the MODIS NPP algorithm. These components include meteorological inputs from the NASA Data Assimilation Office, LAI and FPAR from other MODIS algorithms, and biome-specific parameters for base respiration rate and light use efficiency.
NASA Astrophysics Data System (ADS)
Pankaew, Prasan; Milton, Edward; Dawson, Terry; Dash, Jadu
2013-04-01
Forests and woodlands play an important role in CO2 flux and in the storage of carbon, therefore it is important to be able to estimate gross primary productivity (GPP) and its change over time. The MODIS GPP product (MOD17) provides near-global GPP, but at relatively coarse spatial resolution (1km pixel size) and only every eight days. In order to study the dynamics of GPP over shorter time periods and over smaller areas it is necessary to make ground measurements or use a plant canopy model. The most reliable ground-based GPP data are those from the FLUXNET network, which comprises over 500 sites worldwide, each of which measures GPP using the eddy covariance method. Each FLUXNET measurement corresponds to GPP from an area around the sampling tower, the size and shape of which varies with weather conditions, notably wind speed and direction. The FLIGHT forest light simulation model (North, 1996) is a Monte Carlo based model to estimate the GPP from forest canopies, which does not take into account the spatial complexity of the site or the wind conditions at the time. Forests in southern England are small and embedded in a matrix of other land cover types (agriculture, urban etc.), so GPP estimated from FLIGHT needs to be adjusted to match that measured from a FLUXNET tower. The aim of this paper is to develop and test a method to adjust FLIGHT GPP so that it matches FLUXNET GPP. The advantage of this is that GPP can then be estimated over many other forests which do not possess FLUXNET sites. The study was based on data from two mixed broadleaf forests in southern England (Wytham Woods and Alice Holt forest), both of which have FLUXNET sites located within them. The FLUXNET meteorological data were prepared for use in the FLIGHT model by converting broadband irradiance to photosynthetically active radiance (PAR) and estimating diffuse PAR, using methods developed in previous work by the authors. The standard FLIGHT model tended to overestimate GPP in the winter
David P. Turner; William D. Ritts; Warren B. Cohen; Thomas K. Maeirsperger; Stith T. Gower; Al A. Kirschbaum; Steve W. Runnings; Maosheng Zhaos; Steven C. Wofsy; Allison L. Dunn; Beverly E. Law; John L. Campbell; Walter C. Oechel; Hyo Jung Kwon; Tilden P. Meyers; Eric E. Small; Shirley A. Kurc; John A. Gamon
2005-01-01
Operational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site-level studies across a range of biomes, with close attention to numerous scaling...
NASA Astrophysics Data System (ADS)
Ise, Takeshi; Litton, Creighton M.; Giardina, Christian P.; Ito, Akihiko
2010-12-01
Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long-lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning to leaves, stems, and roots varies consistently with GPP and that the ratio of net primary production (NPP) to GPP is conservative across environmental gradients. To examine influences of carbon partitioning schemes employed by global ecosystem models, we used this meta-analysis-based model and a satellite-based (MODIS) terrestrial GPP data set to estimate global woody NPP and equilibrium biomass, and then compared it to two process-based ecosystem models (Biome-BGC and VISIT) using the same GPP data set. We hypothesized that different carbon partitioning schemes would result in large differences in global estimates of woody NPP and equilibrium biomass. Woody NPP estimated by Biome-BGC and VISIT was 25% and 29% higher than the meta-analysis-based model for boreal forests, with smaller differences in temperate and tropics. Global equilibrium woody biomass, calculated from model-specific NPP estimates and a single set of tissue turnover rates, was 48 and 226 Pg C higher for Biome-BGC and VISIT compared to the meta-analysis-based model, reflecting differences in carbon partitioning to structural versus metabolically active tissues. In summary, we found that different carbon partitioning schemes resulted in large variations in estimates of global woody carbon flux and storage, indicating that stand-level controls on carbon partitioning are not yet accurately represented in ecosystem models.
Takeshi Ise; Creighton M. Litton; Christian P. Giardina; Akihiko Ito
2010-01-01
Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long�]lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning...
NASA Technical Reports Server (NTRS)
Zhang, Qingyuan; Cheng, Yen-Ben; Lyapustin, Alexei I.; Wang, Yujie; Xiao, Xiangming; Suyker, Andrew; Verma, Shashi; Tan, Bin; Middleton, Elizabeth M.
2014-01-01
Accurate estimation of gross primary production (GPP) is essential for carbon cycle and climate change studies. Three AmeriFlux crop sites of maize and soybean were selected for this study. Two of the sites were irrigated and the other one was rainfed. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the green band chlorophyll index (CIgreen), and the green band wide dynamic range vegetation index (WDRVIgreen) were computed from the moderate resolution imaging spectroradiometer (MODIS) surface reflectance data. We examined the impacts of the MODIS observation footprint and the vegetation bidirectional reflectance distribution function (BRDF) on crop daily GPP estimation with the four spectral vegetation indices (VIs - NDVI, EVI, WDRVIgreen and CIgreen) where GPP was predicted with two linear models, with and without offset: GPP = a × VI × PAR and GPP = a × VI × PAR + b. Model performance was evaluated with coefficient of determination (R2), root mean square error (RMSE), and coefficient of variation (CV). The MODIS data were filtered into four categories and four experiments were conducted to assess the impacts. The first experiment included all observations. The second experiment only included observations with view zenith angle (VZA) = 35? to constrain growth of the footprint size,which achieved a better grid cell match with the agricultural fields. The third experiment included only forward scatter observations with VZA = 35?. The fourth experiment included only backscatter observations with VZA = 35?. Overall, the EVI yielded the most consistently strong relationships to daily GPP under all examined conditions. The model GPP = a × VI × PAR + b had better performance than the model GPP = a × VI × PAR, and the offset was significant for most cases. Better performance was obtained for the irrigated field than its counterpart rainfed field. Comparison of experiment 2 vs. experiment 1 was used to examine the observation
Estimating Per-Pixel GPP of the Contiguous USA Directly from MODIS EVI Data
NASA Astrophysics Data System (ADS)
Rahman, A. F.; Sims, D. A.; El-Masri, B. Z.; Cordova, V. D.
2005-12-01
We estimated gross primary production (GPP) of the contiguous USA using enhanced vegetation index (EVI) data from NASA's moderate resolution imaging spectroradiometer (MODIS). Based on recently published values of correlation coefficients between EVI and GPP of North American vegetations, we derived GPP maps of the contiguous USA for 2001-2004, which included one La Nina year and three moderately El Nino years. The product was a truly per-pixel GPP estimate (named E-GPP), in contrast to the pseudo-continuous MOD17, the standard MODIS GPP product. We compared E-GPP with fine-scale experimental GPP data and MOD17 estimates from three Bigfoot experimental sites, and also with MOD17 estimates from the whole contiguous USA for the above-mentioned four years. For each of the '7 by 7' km Bigfoot experimental sites, E-GPP was able to track the primary production activity during the green-up period while MOD17 failed to do so. The E-GPP estimates during peak production season were similar to those from Bigfoot and MOD17 for most vegetation types except for the deciduous types, where it was lower. Annual E-GPP of the Bigfoot sites compared well with Bigfoot experimental GPP (r = 0.71) and MOD17 (r = 0.78). But for the contiguous USA for 2001-2004, annual E-GPP showed disagreement with MOD17 in both magnitude and seasonal trends for deciduous forests and grass lands. In this study we explored the reasons for this mismatch between E-GPP and MOD17 and also analyzed the uncertainties in E-GPP across multiple spatial scales. Our results show that the E-GPP, based on a simple regression model, can work as a robust alternative to MOD17 for large-area annual GPP estimation. The relative advantages of E-GPP are that it is truly per-pixel, solely dependent on remotely sensed data that is routinely available from NASA, easy to compute and has the potential of being used as an operational product.
NASA Astrophysics Data System (ADS)
Ise, T.; Litton, C. M.; Giardina, C. P.; Ito, A.
2009-12-01
Plant partitioning of carbon (C) to above- vs. belowground, to growth vs. respiration, and to short vs. long lived tissues exerts a large influence on ecosystem structure and function with implications for the global C budget. Importantly, outcomes of process-based terrestrial vegetation models are likely to vary substantially with different C partitioning algorithms. However, controls on C partitioning patterns remain poorly quantified, and studies have yielded variable, and at times contradictory, results. A recent meta-analysis of forest studies suggests that the ratio of net primary production (NPP) and gross primary production (GPP) is fairly conservative across large scales. To illustrate the effect of this unique meta-analysis-based partitioning scheme (MPS), we compared an application of MPS to a terrestrial satellite-based (MODIS) GPP to estimate NPP vs. two global process-based vegetation models (Biome-BGC and VISIT) to examine the influence of C partitioning on C budgets of woody plants. Due to the temperature dependence of maintenance respiration, NPP/GPP predicted by the process-based models increased with latitude while the ratio remained constant with MPS. Overall, global NPP estimated with MPS was 17 and 27% lower than the process-based models for temperate and boreal biomes, respectively, with smaller differences in the tropics. Global equilibrium biomass of woody plants was then calculated from the NPP estimates and tissue turnover rates from VISIT. Since turnover rates differed greatly across tissue types (i.e., metabolically active vs. structural), global equilibrium biomass estimates were sensitive to the partitioning scheme employed. The MPS estimate of global woody biomass was 7-21% lower than that of the process-based models. In summary, we found that model output for NPP and equilibrium biomass was quite sensitive to the choice of C partitioning schemes. Carbon use efficiency (CUE; NPP/GPP) by forest biome and the globe. Values are means
NASA Astrophysics Data System (ADS)
Aralova, Dildora; Jarihani, Ben; Khujanazarov, Timur; Toderich, Kristina; Gafurov, Dilshod; Gismatulina, Liliya
2017-04-01
Previous studies have shown that precipitation anomalies and raising of temperature trends were deteriorate affected on large-scale of vegetation surveys in Central Asia (CA). Nowadays, remote sensing techniques can provide estimation of Net and Gross Primary Productivity (NPP & GPP) for regional and global scales, and selected zones in CA (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan) dominated by C4 plants (biomes) what it reveals more accurately simulate C4 carbon. The estimation of NPP & GPP from source (MOD17A2/A3) would be beneficial to determine natural driver factors, whether on rangeland ecosystem is a carbon sink or source, such as a vast area of the selected zones incorporates exacerbate regional drought-risk factors nowadays. Generally, we have combined last available NPP & GPP (2000-2015) with 1 km resolution from MODIS, with investigation of long-term vegetation patterns under Normalized Difference Vegetation Indices (NDVI) with 8 km resolution from AVHRR-GIMMS 3g sources (2001-2015) within aim to estimate potential values of rangeland ecosystems. Interaction ratios of NPP/GPP are integrating more accurately describe carbon sink process under natural or anthropogenic factors, specifically last results of NDVI trends were described as decreasing trends due to climate anomalies, besides the eastern and northern parts of CA (mostly boreal forest zones) where accumulated or indicated of raising trends of NDVI in last three years (2012-2015). Results revealed that, in CA were averaged annually value NDVI ranges from 0.19-0.21; (Kyrgyzstan: 0.23-0.26; Kazakhstan: 0.21-0.24; Tajikistan: 0.19-0.21); and resting countries as low NDVI accumulated areas were Turkmenistan and Uzbekistan ranges 0.13-0.16; Comparing datasets of GPP given the response dynamic change structures of NDVI values and explicit carbon uptake (CO2) in arid ecosystems and average GPPyearlyin CA ranges 2.42 kg C/m2; including to Tajikistan, Uzbekistan (3.09 kg C/m2) and
Towards 250 m mapping of terrestrial primary productivity over Canada
NASA Astrophysics Data System (ADS)
Gonsamo, A.; Chen, J. M.
2011-12-01
Terrestrial ecosystems are an important part of the climate and global change systems. Their role in climate change and in the global carbon cycle is yet to be well understood. Dataset from satellite earth observation, coupled with numerical models provide the unique tools for monitoring the spatial and temporal dynamics of territorial carbon cycle. The Boreal Ecosystems Productivity Simulator (BEPS) is a remote sensing based approach to quantifying the terrestrial carbon cycle by that gross and net primary productivity (GPP and NPP) and terrestrial carbon sinks and sources expressed as net ecosystem productivity (NEP). We have currently implemented a scheme to map the GPP, NPP and NEP at 250 m for first time over Canada using BEPS model. This is supplemented by improved mapping of land cover and leaf area index (LAI) at 250 m over Canada from MODIS satellite dataset. The results from BEPS are compared with MODIS GPP product and further evaluated with estimated LAI from various sources to evaluate if the results capture the trend in amount of photosynthetic biomass distributions. Final evaluation will be to validate both BEPS and MODIS primary productivity estimates over the Fluxnet sites over Canada. The primary evaluation indicate that BEPS GPP estimates capture the over storey LAI variations over Canada very well compared to MODIS GPP estimates. There is a large offset of MODIS GPP, over-estimating the lower GPP value compared to BEPS GPP estimates. These variations will further be validated based on the measured values from the Fluxnet tower measurements over Canadian. The high resolution GPP (NPP) products at 250 m will further be used to scale the outputs between different ecosystem productivity models, in our case the Canadian carbon budget model of Canadian forest sector CBM-CFS) and the Integrated Terrestrial Ecosystem Carbon model (InTEC).
Observations-based GPP estimates
NASA Astrophysics Data System (ADS)
Joiner, J.; Yoshida, Y.; Jung, M.; Tucker, C. J.; Pinzon, J. E.
2017-12-01
We have developed global estimates of gross primary production based on a relatively simple satellite observations-based approach using reflectance data from the MODIS instruments in the form of vegetation indices that provide information about photosynthetic capacity at both high temporal and spatial resolution and combined with information from chlorophyll solar-induced fluorescence from the Global Ozone Monitoring Experiment-2 instrument that is noisier and available only at lower temporal and spatial scales. We compare our gross primary production estimates with those from eddy covariance flux towers and show that they are competitive with more complicated extrapolated machine learning gross primary production products. Our results provide insight into the amount of variance in gross primary production that can be explained with satellite observations data and also show how processing of the satellite reflectance data is key to using it for accurate GPP estimates.
Canopy and physiological controls of GPP during drought and heat wave
NASA Astrophysics Data System (ADS)
Zhang, Yao; Xiao, Xiangming; Zhou, Sha; Ciais, Philippe; McCarthy, Heather; Luo, Yiqi
2016-04-01
Vegetation indices (VIs) derived from satellite reflectance measurements are often used as proxies of canopy activity to evaluate the impacts of drought and heat wave on gross primary production (GPP) through production efficiency models. However, GPP is also regulated by physiological processes that cannot be directly detected using reflectance measurements. This study analyzes the co-limitation of canopy and plant physiology (represented by VIs and climate anomalies, respectively) on GPP during the 2003 European summer drought and heat wave for 15 Euroflux sites. During the entire drought period, spatial pattern of GPP anomalies can be quantified by relative changes in VIs. We also find that GPP sensitivity to relative canopy changes is higher for nonforest ecosystems (1.81 ± 0.32%GPP/%enhanced vegetation index), while GPP sensitivity to physiological changes is higher for forest ecosystems (-0.18 ± 0.05 g C m-2 d-1/hPa). A conceptual model is further built to better illustrate the canopy and physiological controls on GPP during drought periods.
The Regional Differences of Gpp Estimation by Solar Induced Fluorescence
NASA Astrophysics Data System (ADS)
Wang, X.; Lu, S.
2018-04-01
Estimating gross primary productivity (GPP) at large spatial scales is important for studying the global carbon cycle and global climate change. In this study, the relationship between solar-induced chlorophyll fluorescence (SIF) and GPP is analysed in different levels of annual average temperature and annual total precipitation respectively using simple linear regression analysis. The results showed high correlation between SIF and GPP, when the area satisfied annual average temperature in the range of -5 °C to 15 °C and the annual total precipitation is higher than 200 mm. These results can provide a basis for future estimation of GPP research.
The ratio of NPP to GPP: evidence of change over the course of stand development
Annikki Makela; Harry T. Valentine
2001-01-01
Using Scots pine (Pinus sylvestris L.) in Fenno-Scandia as a case study, we investigate whether net primary production (NPP) and maintenance respiration are constant fractions of gross primary production (GPP) as even-aged mono-specific stands progress from initiation to old age. A model of the ratio of NPP to GPP is developed based on (1) the...
Seasonal and interannual patterns in primary production ...
Measurements of primary production and respiration provide fundamental information about the trophic status of aquatic ecosystems, yet such measurements are logistically difficult and expensive to sustain as part of long-term monitoring programs. However, ecosystem metabolism parameters can be inferred from high frequency water quality data collections using autonomous logging instruments. For this study, we analyzed such time series datasets from three Gulf of Mexico estuaries: Grand Bay, MS, Weeks Bay AL and Apalachicola Bay FL. Data were acquired from NOAA's National Estuarine Research Reserve System Wide Monitoring Program and used to calculate gross primary production (GPP), ecosystem respiration (ER) and net ecosystem metabolism (NEM) using Odum's open water method. The three systems present a diversity of estuaries typical of the Gulf of Mexico region, varying by as much as 2 orders of magnitude in key physical characteristics, such as estuarine area, watershed area, freshwater flow, and nutrient loading. In all three systems, gross primary production (GPP) and ecosystem respiration (ER) displayed strong seasonality, peaking in summer and being lowest during winter. Peak rates of GPP and ER exceeded 200 mmol O2 m-2 d-1 52 in all three estuaries. To our knowledge, this is the only study examining long term trends in rates of GPP, ER and NEM in estuaries. Variability in metabolism tended to be small among sites within each estuary. Nitrogen loading was high
GPP in Loblolly Pine: A Monthly Comparison of Empirical and Process Models
Christopher Gough; John Seiler; Kurt Johnsen; David Arthur Sampson
2002-01-01
Monthly and yearly gross primary productivity (GPP) estimates derived from an empirical and two process based models (3PG and BIOMASS) were compared. Spatial and temporal variation in foliar gas photosynthesis was examined and used to develop GPP prediction models for fertilized nine-year-old loblolly pine (Pinus taeda) stands located in the North...
Primary Productivity in Meduxnekeag River, Maine, 2005
Goldstein, Robert M.; Schalk, Charles W.; Kempf, Joshua P.
2009-01-01
During August and September 2005, dissolved oxygen, temperature, pH, specific conductance, streamflow, and light intensity (LI) were determined continuously at six sites defining five reaches on Meduxnekeag River above and below Houlton, Maine. These data were collected as input for a dual-station whole-stream metabolism model to evaluate primary productivity in the river above and below Houlton. The river receives nutrients and organic matter from tributaries and the Houlton wastewater treatment plant (WWTP). Model output estimated gross and net primary productivity for each reach. Gross primary productivity (GPP) varied in each reach but was similar and positive among the reaches. GPP was correlated to LI in the four reaches above the WWTP but not in the reach below. Net primary productivity (NPP) decreased in each successive downstream reach and was negative in the lowest two reaches. NPP was weakly related to LI in the upper two reaches and either not correlated or negatively correlated in the lower three reaches. Relations among GPP, NPP, and LI indicate that the system is heterotrophic in the downstream reaches. The almost linear decrease in NPP (the increase in metabolism and respiration) indicates a cumulative effect of inputs of nutrients and organic matter from tributaries that drain agricultural land, the town of Houlton, and the discharges from the WWTP.
Multiscale analyses of solar-induced florescence and gross primary production
USDA-ARS?s Scientific Manuscript database
Remotely sensed solar induced fluorescence (SIF) has shown great promise for probing spatiotemporal variations in terrestrial gross primary production (GPP), the largest component flux of the global carbon cycle. However, scale mismatches between SIF and ground-based GPP have posed challenges toward...
NASA Astrophysics Data System (ADS)
Shim, C.
2013-12-01
The Moderate Resolution Imaging Radiometer (MODIS) Gross Primary Productivity (GPP)/Net Primary Productivity (NPP) has been widely used for the study on global terrestrial ecosystem and carbon cycle. The current MODIS product with ~ 1 km spatial resolution, however, has limitation on the information on local scale environment (< 1km), particularly on the regions with complex land-use types. Here we try to test the performance of MODIS annual GPP/NPP for a case of Korea, where the vegetation types are mostly heterogeneous within a size of MODIS products (~1km). We selected the sites where the ground/tower flux measurements and MODIS retrievals were simultaneously available and the land classification of sites agreed the forest type map (~71m) (1 site over Gwangneung flux tower (GDK) for 2006-2008 and 2 sites of ground measurements over Cheongju (CJ1 and CJ2) for 2011). The MODIS GPP are comparable to that of GDK (largely deciduous forest) within -6.3 ~ +2.3% of bias (-104.5 - 37.9 gCm-2yr-1). While the MODIS NPP of CJ1 at Cheongju (largely Larix leptolepis) underestimated NPP by 34% (-224.5 gCm-2yr-1), the MODIS NPP of CJ2 (largely Pinus densiflora) agreed well with -0.2% of bias (1.6 gCm-2yr-1). The fairly comparable values of the MODIS here however, cannot assure the quality of the MOD17 over the complex vegetation area of Korea since the ground measurements except the eddy covariance tower flux measurements are highly inconsistent. Therefore, the comprehensive experiments to represents GPP/NPP over diverse vegetation types for a comparable scale of MODIS with a consistent measurement technique are necessary in order to evaluate the MODIS vegetation productivity data over Korea, which contains a large portion of highly heterogeneous vegetation area.
NASA Astrophysics Data System (ADS)
Martínez, B.; Sanchez-Ruiz, S.; Gilabert, M. A.; Moreno, A.; Campos-Taberner, M.; García-Haro, F. J.; Trigo, I. F.; Aurela, M.; Brümmer, C.; Carrara, A.; De Ligne, A.; Gianelle, D.; Grünwald, T.; Limousin, J. M.; Lohila, A.; Mammarella, I.; Sottocornola, M.; Steinbrecher, R.; Tagesson, T.
2018-03-01
The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperature at 2 m (Ta) from ERA-Interim data. The GPP product (MSG GPP) was produced for 2012 and assessed by direct site-level comparison with GPP from eddy covariance data (EC GPP). MSG GPP presents relative bias errors lower than 40% for the most forest vegetation types with a high agreement (r > 0.7) when compared with EC GPP. For drylands, MSG GPP reproduces the seasonal variations related to water limitation in a good agreement with site level GPP estimates (RMSE = 2.11 g m-2 day-1; MBE = -0.63 g m-2 day-1), especially for the dry season. A consistency analysis against other GPP satellite products (MOD17A2 and FLUXCOM) reveals a high consistency among products (RMSD < 1.5 g m-2 day-1) over Europe, North and South Africa. The major GPP disagreement arises over moist biomes in central Africa (RMSD > 3.0 g m-2 day-1) and over dry biomes with MSG GPP estimates lower than FLUXCOM (MBD up to -3.0 g m-2 day-1). This newly derived product has the potential for analysing spatial patterns and temporal dynamics of GPP at the MSG spatial resolutions on a daily basis allowing to better capture the GPP dynamics and magnitude.
Remote sensing evaluation of CLM4 GPP for the period 2000 to 2009
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mao, Jiafu; Thornton, Peter E; Shi, Xiaoying
2012-01-01
The ability of a process-based ecosystem model like Version 4 of the Community Land Model (CLM4) to provide accurate estimates of CO2 flux is a top priority for researchers, modelers and policy makers. Remote sensing can provide long-term and large scale products suitable for ecosystem model evaluation. Global estimations of gross primary production (GPP) at the 1 km spatial resolution from years 2000 to 2009 from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor offer a unique opportunity for evaluating the temporal and spatial patterns of global GPP and its relationship with climate for CLM4. We compare monthly GPP simulated bymore » CLM4 at half-degree resolution with satellite estimates of GPP from the MODIS GPP (MOD17) dataset for the 10-yr period, January 2000 December 2009. The assessment is presented in terms of long-term mean carbon assimilation, seasonal mean distributions, amplitude and phase of the annual cycle, and intra-annual and inter-annual GPP variability and their responses to climate variables. For the long-term annual and seasonal means, major GPP patterns are clearly demonstrated by both products. Compared to the MODIS product, CLM4 overestimates the magnitude of GPP for tropical evergreen forests. CLM4 has longer carbon uptake period than MODIS for most plant functional types (PFTs) with an earlier onset of GPP in spring and later decline of GPP in autumn. Empirical Orthogonal Function (EOF) analysis of the monthly GPP changes indicates that on the intra-annual scale, both CLM4 and MODIS display similar spatial representations and temporal patterns for most terrestrial ecosystems except in northeast Russia and the very dry region in central Australia. For 2000-2009, CLM4 simulates increases in annual averaged GPP over both hemispheres, however estimates from MODIS suggest a reduction in the Southern Hemisphere (-0.2173 PgC/year) balancing the significant increase over the Northern Hemisphere (0.2157 PgC/year).« less
Aaron R. Weiskittel; Nicholas L. Crookston; Philip J. Radtke
2011-01-01
Assessing forest productivity is important for developing effective management regimes and predicting future growth. Despite some important limitations, the most common means for quantifying forest stand-level potential productivity is site index (SI). Another measure of productivity is gross primary production (GPP). In this paper, SI is compared with GPP estimates...
NASA Astrophysics Data System (ADS)
Hashimoto, H.; Wang, W.; Ganguly, S.; Li, S.; Michaelis, A.; Higuchi, A.; Takenaka, H.; Nemani, R. R.
2017-12-01
New geostationary sensors such as the AHI (Advanced Himawari Imager on Himawari-8) and the ABI (Advanced Baseline Imager on GOES-16) have the potential to advance ecosystem modeling particularly of diurnally varying phenomenon through frequent observations. These sensors have similar channels as in MODIS (MODerate resolution Imaging Spectroradiometer), and allow us to utilize the knowledge and experience in MODIS data processing. Here, we developed sub-hourly Gross Primary Production (GPP) algorithm, leverating the MODIS 17 GPP algorithm. We run the model at 1-km resolution over Japan and Australia using geo-corrected AHI data. Solar radiation was directly calculated from AHI using a neural network technique. The other necessary climate data were derived from weather stations and other satellite data. The sub-hourly estimates of GPP were first compared with ground-measured GPP at various Fluxnet sites. We also compared the AHI GPP with MODIS 17 GPP, and analyzed the differences in spatial patterns and the effect of diurnal changes in climate forcing. The sub-hourly GPP products require massive storage and strong computational power. We use NEX (NASA Earth Exchange) facility to produce the GPP products. This GPP algorithm can be applied to other geostationary satellites including GOES-16 in future.
Harris, B Z; Kaiser, D; Singer, M
1998-04-01
Guanosine 3'-di-5'-(tri)di-phosphate nucleotides [(p)ppGpp], synthesized in response to amino acid limitation, induce early gene expression leading to multicellular fruiting body formation in Myxococcus xanthus. A mutant (DK527) that fails to accumulate (p)ppGpp in response to starvation was found to be blocked in development prior to aggregation. By use of a series of developmentally regulated Tn5lac transcriptional fusion reporters, the time of developmental arrest in DK527 was narrowed to within the few hours of development, the period of starvation recognition. The mutant is also defective in the production of A-factor, an early extracellular cell-density signal. The relA gene from Escherichia coli, which encodes a ribosome-dependent (p)ppGpp synthetase, rescues this mutant. We also demonstrate that inactivation of the M. xanthus relA homolog blocks development and the accumulation of (p)ppGpp. Moreover, the wild-type allele of Myxococcus relA rescues DK527. These observations support a model in which accumulation of (p)ppGpp, in response to starvation, initiates the program of fruiting body development, including the production of A-factor.
Monitoring crop gross primary productivity using Landsat data (Invited)
NASA Astrophysics Data System (ADS)
Gitelson, A. A.; Peng, Y.; Keydan, G. P.; Masek, J.; Rundquist, D. C.; Verma, S. B.; Suyker, A. E.
2009-12-01
There is a growing interest in monitoring the gross primary productivity (GPP) of crops due mostly to their carbon sequestration potential. We presented a new technique for GPP estimation in irrigated and rainfed maize and soybeans based on the close and consistent relationship between GPP and crop chlorophyll content, and entirely on remotely sensed data. A recently proposed Green Chlorophyll Index (Green CI), which employs the green and the NIR spectral bands, was used to retrieve daytime GPP from Landsat ETM+ data. Due to its high spatial resolution (i.e., 30x30m/pixel), this satellite system is particularly appropriate for detecting not only between but also within field GPP variability during the growing season. The Green CI obtained using atmospherically corrected Landsat ETM+ data was found to be linearly related with crop GPP explaining about 90% of GPP variation. Green CI constitutes an accurate surrogate measure for GPP estimation. For comparison purposes, other vegetation indices were also tested. These results open new possibilities for analyzing the spatio-temporal variation of the GPP of crops using the extensive archive of Landsat imagery acquired since the early 1980s.
NASA Astrophysics Data System (ADS)
Cai, Wenwen; Yuan, Wenping; Liang, Shunlin; Zhang, Xiaotong; Dong, Wenjie; Xia, Jiangzhou; Fu, Yang; Chen, Yang; Liu, Dan; Zhang, Qiang
2014-01-01
Terrestrial vegetation gross primary production (GPP) is an important variable in determining the global carbon cycle as well as the interannual variability of the atmospheric CO2 concentration. The accuracy of GPP simulation is substantially affected by several critical model drivers, one of the most important of which is photosynthetically active radiation (PAR) which directly determines the photosynthesis processes of plants. In this study, we examined the impacts of uncertainties in radiation products on GPP estimates in China. Two satellite-based radiation products (GLASS and ISCCP), three reanalysis products (MERRA, ECMWF, and NCEP), and a blended product of reanalysis and observations (Princeton) were evaluated based on observations at hundreds of sites. The results revealed the highest accuracy for two satellite-based products over various temporal and spatial scales. The three reanalysis products and the Princeton product tended to overestimate radiation. The GPP simulation driven by the GLASS product exhibited the highest consistency with those derived from site observations. Model validation at 11 eddy covariance sites suggested the highest model performance when utilizing the GLASS product. Annual GPP in China driven by GLASS was 5.55 Pg C yr-1, which was 68.85%-94.87% of those derived from the other products. The results implied that the high spatial resolution, satellite-derived GLASS PAR significantly decreased the uncertainty of the GPP estimates at the regional scale.
Primary production of coral ecosystems in the Vietnamese coastal and adjacent marine waters
NASA Astrophysics Data System (ADS)
Tac-An, Nguyen; Minh-Thu, Phan; Cherbadji, I. I.; Propp, M. V.; Odintsov, V. S.; Propp, L. H.
2013-11-01
Coral reef ecosystems in coastal waters and islands of Vietnam have high primary production. Average gross primary production (GPP) in coral reef waters was 0.39 g C m-2 day-1. GPP of corals ranged from 3.12 to 4.37 g C m-2 day-1. GPP of benthic microalgae in coral reefs ranged from 2 to 10 g C m-2 day-1. GPP of macro-algae was 2.34 g C m-2 day-1. Therefore, the total of GPP of whole coral reef ecosystems could reach 7.85 to 17.10 g C m-2 day-1. Almost all values of the ratio of photosynthesis to respiration in the water bodies are higher than 1, which means these regions are autotrophic systems. Wire variation of GPP in coral reefs was contributed by species abundance of coral and organisms, nutrient supports and environmental characteristics of coral ecosystems. Coral reefs play an important ecological role of biogeochemical cycling of nutrients in waters around the reefs. These results contribute valuable information for the protection, conservation and sustainable exploitation of the natural resources in coral reef ecosystems in Vietnam.
Kevin Schaefer; Christopher R. Schwalm; Chris Williams; M. Altaf Arain; Alan Barr; Jing M. Chen; Kenneth J. Davis; Dimitre Dimitrov; Timothy W. Hilton; David Y. Hollinger; Elyn Humphreys; Benjamin Poulter; Brett M. Raczka; Andrew D. Richardson; Alok Sahoo; Peter Thornton; Rodrigo Vargas; Hans Verbeeck; Ryan Anderson; Ian Baker; T. Andrew Black; Paul Bolstad; Jiquan Chen; Peter S. Curtis; Ankur R. Desai; Michael Dietze; Danilo Dragoni; Christopher Gough; Robert F. Grant; Lianhong Gu; Atul Jain; Chris Kucharik; Beverly Law; Shuguang Liu; Erandathie Lokipitiya; Hank A. Margolis; Roser Matamala; J. Harry McCaughey; Russ Monson; J. William Munger; Walter Oechel; Changhui Peng; David T. Price; Dan Ricciuto; William J. Riley; Nigel Roulet; Hanqin Tian; Christina Tonitto; Margaret Torn; Ensheng Weng; Xiaolu Zhou
2012-01-01
Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States...
Constraining the SIF - GPP relationship via estimation of NPQ
NASA Astrophysics Data System (ADS)
Silva, C. E.; Yang, X.; Tang, J.; Lee, J. E.; Cushman, K.; Toh Yuan Kun, L.; Kellner, J. R.
2016-12-01
Airborne and satellite measurements of solar-induced fluorescence (SIF) have the potential to improve estimates of gross primary production (GPP). Plants dissipate absorbed photosynthetically active radiation (APAR) among three de-excitation pathways: SIF, photochemical quenching (PQ), which results in electron transport and the production of ATP and NADPH consumed during carbon fixation (i.e., GPP), and heat dissipation via conversion of xanthophyll pigments (non-photochemical quenching: NPQ). As a result, the relationship between SIF and GPP is a function of NPQ and may vary temporally and spatially with environmental conditions (e.g., light and water availability) and plant traits (e.g., leaf N content). Accurate estimates of any one of the de-excitation pathways require measurement of the other two. Here we combine half-hourly measurements of canopy APAR and SIF with eddy covariance estimates of GPP at Harvard Forest to close the canopy radiation budget and infer canopy NPQ throughout the 2013 growing season. We use molecular-level photosynthesis equations to compute PQ (umol photons m-2s-1) from GPP (umol CO2 m-2s-1) and invert an integrated canopy radiative transfer and leaf-level photosynthesis/fluorescence model (SCOPE) to quantify hemispherically and spectrally-integrated SIF emission (umol photons m-2s-1) from single band (760 nm) top-of-canopy SIF measurements. We estimate half-hourly NPQ as the residual required to close the radiation budget (NPQ = APAR - SIF - PQ). Our future work will test estimated NPQ against simultaneously acquired measurements of the photochemical reflectance index (PRI), a spectral index sensitive to xanthopyll pigments. By constraining two of the three de-excitation pathways, simultaneous SIF and PRI measurements are likely to improve GPP estimates, which are crucial to the study of climate - carbon cycle interactions.
Satellite Driven Estimation of Primary Productivity of Agroecosystems in India
NASA Astrophysics Data System (ADS)
Patel, N. R.; Dadhwal, V. K.; Agrawal, S.; Saha, S. K.
2011-08-01
Earth observation driven ecosystem modeling have played a major role in estimation of carbon budget components such as gross primary productivity (GPP) and net primary production (NPP) over terrestrial ecosystems, including agriculture. The present study therefore evaluate satellite-driven vegetation photosynthesis (VPM) model for GPP estimation over agro-ecosystems in India by using time series of the Normalized Difference Vegetation Index (NDVI) from SPOT-VEGETATION, cloud cover observation from MODIS, coarse-grid C3/C4 crop fraction and decadal grided databases of maximum and minimum temperatures. Parameterization of VPM parameters e.g. maximum light use efficiency (ɛ*) and Tscalar was done based on eddy-covariance measurements and literature survey. Incorporation of C3/C4 crop fraction is a modification to commonly used constant maximum LUE. Modeling results from VPM captured very well the geographical pattern of GPP and NPP over cropland in India. Well managed agro-ecosystems in Trans-Gangetic and upper Indo-Gangetic plains had the highest magnitude of GPP with peak GPP during kharif occurs in sugarcane-wheat system (western UP) and it occurs in rice-wheat system (Punjab) during Rabi season. Overall, croplands in these plains had more annual GPP (> 1000 g C m-2) and NPP (> 600 g C m-2) due to input-intensive cultivation. Desertic tracts of western Rajasthan showed the least GPP and NPP values. Country-level contribution of croplands to national GPP and NPP amounts to1.34 Pg C year-1 and 0.859 Pg C year-1, respectively. Modeled estimates of cropland NPP agrees well with ground-based estimates for north-western India (R2 = 0.63 and RMSE = 108 g C m-2). Future research will focus on evaluating the VPM model with medium resolution sensors such as AWiFS and MODIS for rice-wheat system and validating with eddy-covariance measurements.
NASA Astrophysics Data System (ADS)
Campioli, M.; Gielen, B.; Göckede, M.; Papale, D.; Bouriaud, O.; Granier, A.
2011-09-01
The allocation of carbon (C) taken up by the tree canopy for respiration and production of tree organs with different construction and maintenance costs, life span and decomposition rate, crucially affects the residence time of C in forests and their C cycling rate. The carbon-use efficiency, or ratio between net primary production (NPP) and gross primary production (GPP), represents a convenient way to analyse the C allocation at the stand level. In this study, we extend the current knowledge on the NPP-GPP ratio in forests by assessing the temporal variability of the NPP-GPP ratio at interannual (for 8 years) and seasonal (for 1 year) scales for a young temperate beech stand, reporting dynamics for both leaves and woody organs, in particular stems. NPP was determined with biometric methods/litter traps, whereas the GPP was estimated via the eddy covariance micrometeorological technique. The interannual variability of the proportion of C allocated to leaf NPP, wood NPP and leaf plus wood NPP (on average 11% yr-1, 29% yr-1 and 39% yr-1, respectively) was significant among years with up to 12% yr-1 variation in NPP-GPP ratio. Studies focusing on the comparison of NPP-GPP ratio among forests and models using fixed allocation schemes should take into account the possibility of such relevant interannual variability. Multiple linear regressions indicated that the NPP-GPP ratio of leaves and wood significantly correlated with environmental conditions. Previous year drought and air temperature explained about half of the NPP-GPP variability of leaves and wood, respectively, whereas the NPP-GPP ratio was not decreased by severe drought, with large NPP-GPP ratio on 2003 due mainly to low GPP. During the period between early May and mid June, the majority of GPP was allocated to leaf and stem NPP, whereas these sinks were of little importance later on. Improved estimation of seasonal GPP and of the contribution of previous-year reserves to stem growth, as well as reduction
Improved assessment of gross and net primary productivity of Canada's landmass
NASA Astrophysics Data System (ADS)
Gonsamo, Alemu; Chen, Jing M.; Price, David T.; Kurz, Werner A.; Liu, Jane; Boisvenue, Céline; Hember, Robbie A.; Wu, Chaoyang; Chang, Kuo-Hsien
2013-12-01
assess Canada's gross primary productivity (GPP) and net primary productivity (NPP) using boreal ecosystem productivity simulator (BEPS) at 250 m spatial resolution with improved input parameter and driver fields and phenology and nutrient release parameterization schemes. BEPS is a process-based two-leaf enzyme kinetic terrestrial ecosystem model designed to simulate energy, water, and carbon (C) fluxes using spatial data sets of meteorology, remotely sensed land surface variables, soil properties, and photosynthesis and respiration rate parameters. Two improved key land surface variables, leaf area index (LAI) and land cover type, are derived at 250 m from Moderate Resolution Imaging Spectroradiometer sensor. For diagnostic error assessment, we use nine forest flux tower sites where all measured C flux, meteorology, and ancillary data sets are available. The errors due to input drivers and parameters are then independently corrected for Canada-wide GPP and NPP simulations. The optimized LAI use, for example, reduced the absolute bias in GPP from 20.7% to 1.1% for hourly BEPS simulations. Following the error diagnostics and corrections, daily GPP and NPP are simulated over Canada at 250 m spatial resolution, the highest resolution simulation yet for the country or any other comparable region. Total NPP (GPP) for Canada's land area was 1.27 (2.68) Pg C for 2008, with forests contributing 1.02 (2.2) Pg C. The annual comparisons between measured and simulated GPP show that the mean differences are not statistically significant (p > 0.05, paired t test). The main BEPS simulation error sources are from the driver fields.
Regional contribution to variability and trends of global gross primary productivity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Min; Rafique, Rashid; Asrar, Ghassem R.
Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117±13 Pg C yr-1 (mean ± 1 standard deviation), whichmore » was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.« less
Regional contribution to variability and trends of global gross primary productivity
NASA Astrophysics Data System (ADS)
Chen, Min; Rafique, Rashid; Asrar, Ghassem R.; Bond-Lamberty, Ben; Ciais, Philippe; Zhao, Fang; Reyer, Christopher P. O.; Ostberg, Sebastian; Chang, Jinfeng; Ito, Akihiko; Yang, Jia; Zeng, Ning; Kalnay, Eugenia; West, Tristram; Leng, Guoyong; Francois, Louis; Munhoven, Guy; Henrot, Alexandra; Tian, Hanqin; Pan, Shufen; Nishina, Kazuya; Viovy, Nicolas; Morfopoulos, Catherine; Betts, Richard; Schaphoff, Sibyll; Steinkamp, Jörg; Hickler, Thomas
2017-10-01
Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117 ± 13 Pg C yr-1 (mean ± 1 standard deviation), which was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.
Large historical growth in global terrestrial gross primary production
Campbell, J. E.; Berry, J. A.; Seibt, U.; ...
2017-04-05
Growth in terrestrial gross primary production (GPP) may provide a negative feedback for climate change. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth. In consequence, model estimates of terrestrial carbon storage and carbon cycle –climate feedbacks remain poorly constrained. Here we present a global, measurement-based estimate of GPP growth during the twentieth century based on long-term atmospheric carbonyl sulphide (COS) records derived from ice core, firn, and ambient air samples. Here, we interpret these records using a model that simulates changes in COS concentration due to changes in its sources and sinks, including amore » large sink that is related to GPP. We find that the COS record is most consistent with climate-carbon cycle model simulations that assume large GPP growth during the twentieth century (31% ± 5%; mean ± 95% confidence interval). Finally, while this COS analysis does not directly constrain estimates of future GPP growth it provides a global-scale benchmark for historical carbon cycle simulations.« less
Large historical growth in global terrestrial gross primary production
DOE Office of Scientific and Technical Information (OSTI.GOV)
Campbell, J. E.; Berry, J. A.; Seibt, U.
Growth in terrestrial gross primary production (GPP) may provide a negative feedback for climate change. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth. In consequence, model estimates of terrestrial carbon storage and carbon cycle –climate feedbacks remain poorly constrained. Here we present a global, measurement-based estimate of GPP growth during the twentieth century based on long-term atmospheric carbonyl sulphide (COS) records derived from ice core, firn, and ambient air samples. Here, we interpret these records using a model that simulates changes in COS concentration due to changes in its sources and sinks, including amore » large sink that is related to GPP. We find that the COS record is most consistent with climate-carbon cycle model simulations that assume large GPP growth during the twentieth century (31% ± 5%; mean ± 95% confidence interval). Finally, while this COS analysis does not directly constrain estimates of future GPP growth it provides a global-scale benchmark for historical carbon cycle simulations.« less
Joint control of terrestrial gross primary productivity by plant phenology and physiology
Xia, Jianyang; Niu, Shuli; Ciais, Philippe; Janssens, Ivan A.; Chen, Jiquan; Ammann, Christof; Arain, Altaf; Blanken, Peter D.; Cescatti, Alessandro; Bonal, Damien; Buchmann, Nina; Curtis, Peter S.; Chen, Shiping; Dong, Jinwei; Flanagan, Lawrence B.; Frankenberg, Christian; Georgiadis, Teodoro; Gough, Christopher M.; Hui, Dafeng; Kiely, Gerard; Li, Jianwei; Lund, Magnus; Magliulo, Vincenzo; Marcolla, Barbara; Merbold, Lutz; Olesen, Jørgen E.; Piao, Shilong; Raschi, Antonio; Roupsard, Olivier; Suyker, Andrew E.; Vaccari, Francesco P.; Varlagin, Andrej; Vesala, Timo; Wilkinson, Matthew; Weng, Ensheng; Yan, Liming; Luo, Yiqi
2015-01-01
Terrestrial gross primary productivity (GPP) varies greatly over time and space. A better understanding of this variability is necessary for more accurate predictions of the future climate–carbon cycle feedback. Recent studies have suggested that variability in GPP is driven by a broad range of biotic and abiotic factors operating mainly through changes in vegetation phenology and physiological processes. However, it is still unclear how plant phenology and physiology can be integrated to explain the spatiotemporal variability of terrestrial GPP. Based on analyses of eddy–covariance and satellite-derived data, we decomposed annual terrestrial GPP into the length of the CO2 uptake period (CUP) and the seasonal maximal capacity of CO2 uptake (GPPmax). The product of CUP and GPPmax explained >90% of the temporal GPP variability in most areas of North America during 2000–2010 and the spatial GPP variation among globally distributed eddy flux tower sites. It also explained GPP response to the European heatwave in 2003 (r2 = 0.90) and GPP recovery after a fire disturbance in South Dakota (r2 = 0.88). Additional analysis of the eddy–covariance flux data shows that the interbiome variation in annual GPP is better explained by that in GPPmax than CUP. These findings indicate that terrestrial GPP is jointly controlled by ecosystem-level plant phenology and photosynthetic capacity, and greater understanding of GPPmax and CUP responses to environmental and biological variations will, thus, improve predictions of GPP over time and space. PMID:25730847
Vegetation canopy and physiological control of GPP decline during drought and heat wave
NASA Astrophysics Data System (ADS)
Zhang, Y.; Xiao, X.; Zhou, S.; McCarthy, H. R.; Ciais, P.; Luo, Y.
2015-12-01
Different vegetation indices derived from satellites were often used as a proxy of vegetation activity to monitor and evaluate the impacts of drought and heat wave on ecosystem carbon fluxes (gross primary production, respiration) through the production efficiency models (PEMs). However, photosynthesis is also regulated by a series of physiological processes which cannot be directly observed through satellites. In this study, we analyzed the response of drought and heat wave induced GPP and climate anomaly from 15 Euroflux sites and the corresponding vegetation indices from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. Correlation analysis suggests that the vegetation indices are more responsive to GPP variation in grasslands and open shrublands, but less responsive in forest ecosystems. Physiology control can be up to 20% of the total GPP during the drought period without changing the canopy structure. At temporal scale for each site, VPD and vegetation indices can be used to track the GPP for forest and non-forest, respectively. However, different stand characteristics should be taken into consideration for forest ecosystems. Based on the above findings, a conceptual model is built to illuminate the physiological and canopy control on the GPP during the drought period. Improvement for future PEMs should incorporate better indicators to deal with drought conditions for different ecosystems.
NASA Astrophysics Data System (ADS)
Ma, M., II; Yuan, W.; Dong, J.; Zhang, F.; Cai, W.; Li, H.
2017-12-01
Vegetation gross primary production (GPP) is an important variable for the carbon cycle on the Qinghai-Tibetan Plateau (QTP). Based on the measurements from twelve eddy covariance (EC) sites, we validated a light use efficiency model (i.e. EC-LUE) to evaluate the spatial-temporal patterns of GPP and the effect of environmental variables on QTP. The EC-LUE model explained 85.4% of the daily observed GPP variations through all of the twelve EC sites, and characterized very well the seasonal changes of GPP. Annual GPP over the entire QTP ranged from 575 to 703 Tg C, and showed a significantly increasing trend from 1982 to 2013. However, there were large spatial heterogeneities in long-term trends of GPP. Throughout the entire QTP, air temperature TA increase had a greater influence than solar radiation and PREC changes on productivity. Moreover, our results highlight the large uncertainties of previous GPP estimates due to insufficient parameterization and validations. When compared with GPP estimates of the EC-LUE model, most Coupled Model Intercomparison Project (CMIP5) GPP products overestimate the magnitude and increasing trends of regional GPP, which potentially impact the feedback of ecosystems to regional climate changes.
Wang, Fumin; Gonsamo, Alemu; Chen, Jing M; Black, T Andrew; Zhou, Bin
2014-11-01
Daily canopy photosynthesis is usually temporally upscaled from instantaneous (i.e., seconds) photosynthesis rate. The nonlinear response of photosynthesis to meteorological variables makes the temporal scaling a significant challenge. In this study, two temporal upscaling schemes of daily photosynthesis, the integrated daily model (IDM) and the segmented daily model (SDM), are presented by considering the diurnal variations of meteorological variables based on a coupled photosynthesis-stomatal conductance model. The two models, as well as a simple average daily model (SADM) with daily average meteorological inputs, were validated using the tower-derived gross primary production (GPP) to assess their abilities in simulating daily photosynthesis. The results showed IDM closely followed the seasonal trend of the tower-derived GPP with an average RMSE of 1.63 g C m(-2) day(-1), and an average Nash-Sutcliffe model efficiency coefficient (E) of 0.87. SDM performed similarly to IDM in GPP simulation but decreased the computation time by >66%. SADM overestimated daily GPP by about 15% during the growing season compared to IDM. Both IDM and SDM greatly decreased the overestimation by SADM, and improved the simulation of daily GPP by reducing the RMSE by 34 and 30%, respectively. The results indicated that IDM and SDM are useful temporal upscaling approaches, and both are superior to SADM in daily GPP simulation because they take into account the diurnally varying responses of photosynthesis to meteorological variables. SDM is computationally more efficient, and therefore more suitable for long-term and large-scale GPP simulations.
Spatiotemporal distribution and variation of GPP in the Greater Khingan Mountains from 1982 to 2015
NASA Astrophysics Data System (ADS)
Hu, L.; Fan, W.; Liu, S.; Ren, H.; Xu, X.
2017-12-01
GPP (Gross Primary Productivity) is an important index to reflect the productivity of plants because it refers to the organic accumulated by green plants on land through assimilating the carbon dioxide in the atmosphere by photosynthesis and a serial of physiological processes in plants. Therefore, GPP plays a significant role in studying the carbon sink of terrestrial ecosystem and plants' reaction to global climate change. Remote sensing provides an efficient way to estimate GPP at regional and global scales and its products can be used to monitor the spatiotemporal variation of terrestrial ecosystem.As the Greater Khingan Mountains is the only bright coniferous forest of cool temperate zone in China and accounts for about 30% of the forest in China. This region is sensitive to climate change, but its forest coverage presented a significant variation due to fire disasters, excessive deforestation and so on. Here, we aimed at studying the variation pattern of GPP in the Greater Khingan Mountains and further found impact factors for the change in order to improve the understanding of what have and will happen on plants and carbon cycle under climate change.Based on GPP product from the GLASS program, we first studied spatial distribution of plants in the Greater Khingan Mountains from 1982 to 2015. With a linear regression model, seasonal and inter-annual GPP variability were explored on pixel and regional scale. We analyzed some climatic factors (e.g. temperature and precipitation) and terrain in order to find the driven factors for the GPP variations. The Growing Season Length (GSL) was also regarded as a factor and was retrieved from GIMMS 3g NDVI datasets using dynamic threshold method. We found that GPP in study area linearly decreased with the increasing elevation. Both annual accumulated GPP (AAG) and maximum daily GPP (during mid-June to mid-July) gained obvious improvement over the past 34 years under climate warming and drying (Fig.1 and Fig.2). Further
A multi-sites analysis on the ozone effects on Gross Primary Production of European forests.
Proietti, C; Anav, A; De Marco, A; Sicard, P; Vitale, M
2016-06-15
Ozone (O3) is both a greenhouse gas and a secondary air pollutant causing adverse impacts on forests ecosystems at different scales, from cellular to ecosystem level. Specifically, the phytotoxic nature of O3 can impair CO2 assimilation that, in turn affects forest productivity. This study aims to evaluate the effects of tropospheric O3 on Gross Primary Production (GPP) at 37 European forest sites during the time period 2000-2010. Due to the lack of carbon assimilation data at O3 monitoring stations (and vice-versa) this study makes a first attempt to combine high resolution MODIS Gross Primary Production (GPP) estimates and O3 measurement data. Partial Correlations, Anomalies Analysis and the Random Forests Analysis (RFA) were used to quantify the effects of tropospheric O3 concentration and its uptake on GPP and to evaluate the most important factors affecting inter-annual GPP changes. Our results showed, along a North-West/South-East European transect, a negative impact of O3 on GPP ranging from 0.4% to 30%, although a key role of meteorological parameters respect to pollutant variables in affecting GPP was found. In particular, meteorological parameters, namely air temperature (T), soil water content (SWC) and relative humidity (RH) are the most important predictors at 81% of test sites. Moreover, it is interesting to highlight a key role of SWC in the Mediterranean areas (Spanish, Italian and French test sites) confirming that, soil moisture and soil water availability affect vegetation growth and photosynthesis especially in arid or semi-arid ecosystems such as the Mediterranean climate regions. Considering the pivotal role of GPP in the global carbon balance and the O3 ability to reduce primary productivity of the forests, this study can help in assessing the O3 impacts on ecosystem services, including wood production and carbon sequestration. Copyright © 2016 Elsevier B.V. All rights reserved.
Environmental controls on the increasing GPP of terrestrial vegetation across northern Eurasia
NASA Astrophysics Data System (ADS)
Dass, P.; Rawlins, M. A.; Kimball, J. S.; Kim, Y.
2016-01-01
Terrestrial ecosystems of northern Eurasia are demonstrating an increasing gross primary productivity (GPP), yet few studies have provided definitive attribution for the changes. While prior studies point to increasing temperatures as the principle environmental control, influences from moisture and other factors are less clear. We assess how changes in temperature, precipitation, cloudiness, and forest fires individually contribute to changes in GPP derived from satellite data across northern Eurasia using a light-use- efficiency-based model, for the period 1982-2010. We find that annual satellite-derived GPP is most sensitive to the temperature, precipitation and cloudiness of summer, which is the peak of the growing season and also the period of the year when the GPP trend is maximum. Considering the regional median, the summer temperature explains as much as 37.7 % of the variation in annual GPP, while precipitation and cloudiness explain 20.7 and 19.3 %. Warming over the period analysed, even without a sustained increase in precipitation, led to a significant positive impact on GPP for 61.7 % of the region. However, a significant negative impact on GPP was also found, for 2.4 % of the region, primarily the dryer grasslands in the south-west of the study area. For this region, precipitation positively correlates with GPP, as does cloudiness. This shows that the south-western part of northern Eurasia is relatively more vulnerable to drought than other areas. While our results further advance the notion that air temperature is the dominant environmental control for recent GPP increases across northern Eurasia, the role of precipitation and cloudiness can not be ignored.
Syal, Kirtimaan; Chatterji, Dipankar
2015-12-01
(p)ppGpp, a secondary messenger, is induced under stress and shows pleiotropic response. It binds to RNA polymerase and regulates transcription in Escherichia coli. More than 25 years have passed since the first discovery was made on the direct interaction of ppGpp with E. coli RNA polymerase. Several lines of evidence suggest different modes of ppGpp binding to the enzyme. Earlier cross-linking experiments suggested that the β-subunit of RNA polymerase is the preferred site for ppGpp, whereas recent crystallographic studies pinpoint the interface of β'/ω-subunits as the site of action. With an aim to validate the binding domain and to follow whether tetra- and pentaphosphate guanosines have different location on RNA polymerase, this work was initiated. RNA polymerase was photo-labeled with 8-azido-ppGpp/8-azido-pppGpp, and the product was digested with trypsin and subjected to mass spectrometry analysis. We observed three new peptides in the trypsin digest of the RNA polymerase labeled with 8-azido-ppGpp, of which two peptides correspond to the same pocket on β'-subunit as predicted by X-ray structural analysis, whereas the third peptide was mapped on the β-subunit. In the case of 8-azido-pppGpp-labeled RNA polymerase, we have found only one cross-linked peptide from the β'-subunit. However, we were unable to identify any binding site of pppGpp on the β-subunit. Interestingly, we observed that pppGpp at high concentration competes out ppGpp bound to RNA polymerase more efficiently, whereas ppGpp cannot titrate out pppGpp. The competition between tetraphosphate guanosine and pentaphosphate guanosine for E. coli RNA polymerase was followed by gel-based assay as well as by a new method known as DRaCALA assay. © 2015 The Molecular Biology Society of Japan and Wiley Publishing Asia Pty Ltd.
NASA Astrophysics Data System (ADS)
Guanter, L.; Zhang, Y.; Jung, M.; Joiner, J.; Voigt, M.; Huete, A. R.; Zarco-Tejada, P.; Frankenberg, C.; Lee, J.; Berry, J. A.; Moran, S. M.; Ponce-Campos, G.; Beer, C.; Camps-Valls, G.; Buchmann, N. C.; Gianelle, D.; Klumpp, K.; Cescatti, A.; Baker, J. M.; Griffis, T.
2013-12-01
Monitoring agricultural productivity is important for optimizing management practices in a world under a continuous increase of food and biofuel demand. We used new space measurements of sun-induced chlorophyll fluorescence (SIF), a vegetation parameter intrinsically linked to photosynthesis, to capture photosynthetic uptake of the crop belts in the north temperate region. The following data streams and procedures have been used in this analysis: (1) SIF retrievals have been derived from measurements of the MetOp-A / GOME-2 instrument in the 2007-2011 time period; (2) ensembles of process-based and data-driven biogeochemistry models have been analyzed in order to assess the capability of global models to represent crop gross primary production (GPP); (3) flux tower-based GPP estimates covering the 2007-2011 time period have been extracted over 18 cropland and grassland sites in the Midwest US and Western Europe from the Ameriflux and the European Fluxes Database networks; (4) large-scale NPP estimates have been derived by the agricultural inventory data sets developed by USDA-NASS and Monfreda et al. The strong linear correlation between the SIF space retrievals and the flux tower-based GPP, found to be significantly higher than that between reflectance-based vegetation indices (EVI, NDVI and MTCI) and GPP, has enabled the direct upscaling of SIF to cropland GPP maps at the synoptic scale. The new crop GPP estimates we derive from the scaling of SIF space retrievals are consistent with both flux tower GPP estimates and agricultural inventory data. These new GPP estimates show that crop productivity in the US Western Corn Belt, and most likely also in the rice production areas in the Indo-Gangetic plain and China, is up to 50-75% higher than estimates by state-of-the-art data-driven and process-oriented biogeochemistry models. From our analysis we conclude that current carbon models have difficulties in reproducing the special conditions of those highly productive
USDA-ARS?s Scientific Manuscript database
Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet, understanding of the relationship between GPP and remote sensing observations and how it changes as a function of factors such as scale, biophysical constraint, and vegetation ...
Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP
USDA-ARS?s Scientific Manuscript database
This study investigates the utility of in-situ and satellite-based leaf chlorophyll (Chl) estimates for quantifying leaf photosynthetic capacity and for constraining model simulations of Gross Primary Productivity (GPP) over a corn field in Maryland, U.S.A. The maximum rate of carboxylation (Vmax) r...
Heather L. Kimball; Paul C. Selmants; Alvaro Moreno; Steve W. Running; Christian P. Giardina; Benjamin Poulter
2017-01-01
Gross primary production (GPP) is the Earthâs largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the...
NASA Astrophysics Data System (ADS)
Xia, J.; McGuire, A. D.; Lawrence, D. M.; Burke, E.; Chen, X.; Delire, C. L.; Koven, C. D.; MacDougall, A. H.; Peng, S.; Rinke, A.; Saito, K.; Zhang, W.; Alkama, R.; Bohn, T. J.; Ciais, P.; Decharme, B.; Gouttevin, I.; Hajima, T.; Ji, D.; Krinner, G.; Lettenmaier, D. P.; Miller, P. A.; Moore, J. C.; Smith, B.; Sueyoshi, T.; Shi, Z.; Yan, L.; Liang, J.; Jiang, L.; Luo, Y.
2014-12-01
A more accurate prediction of future climate-carbon (C) cycle feedbacks requires better understanding and improved representation of the carbon cycle in permafrost regions within current earth system models. Here, we evaluated 10 terrestrial ecosystem models for their estimated net primary productivity (NPP) and its vulnerability to climate change in permafrost regions in the Northern Hemisphere. Those models were run retrospectively between 1960 and 2009. In comparison with MODIS satellite estimates, most models produce higher NPP (310 ± 12 g C m-2 yr-1) than MODIS (240 ± 20 g C m-2 yr-1) over the permafrost regions during 2000‒2009. The modeled NPP was then decomposed into gross primary productivity (GPP) and the NPP/GPP ratio (i.e., C use efficiency; CUE). By comparing the simulated GPP with a flux-tower-based database [Jung et al. Journal of Geophysical Research 116 (2011) G00J07] (JU11), we found although models only produce 10.6% higher mean GPP than JU11 over 1982‒2009, there was a two-fold disparity among models (397 to 830 g C m-2 yr-1). The model-to-model variation in GPP mainly resulted from the seasonal peak GPP and in low-latitudinal permafrost regions such as the Tibetan Plateau. Most models overestimate the CUE in permafrost regions in comparison to calculated CUE from the MODIS NPP and JU11 GPP products and observation-based estimates at 8 forest sites. The models vary in their sensitivities of NPP, GPP and CUE to historical changes in air temperature, atmospheric CO2 concentration and precipitation. For example, climate warming enhanced NPP in four models via increasing GPP but reduced NPP in two other models by decreasing both GPP and CUE. The results indicate that the model predictability of C cycle in permafrost regions can be improved by better representation of those processes controlling the seasonal maximum GPP and the CUE as well as their sensitivity to climate change.
Spatiotemporal patterns of terrestrial gross primary production: A review
NASA Astrophysics Data System (ADS)
Anav, Alessandro; Friedlingstein, Pierre; Beer, Christian; Ciais, Philippe; Harper, Anna; Jones, Chris; Murray-Tortarolo, Guillermo; Papale, Dario; Parazoo, Nicholas C.; Peylin, Philippe; Piao, Shilong; Sitch, Stephen; Viovy, Nicolas; Wiltshire, Andy; Zhao, Maosheng
2015-09-01
Great advances have been made in the last decade in quantifying and understanding the spatiotemporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric, and space observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available data sets predict the spatiotemporal patterns of GPP, identify the differences among data sets, and highlight the main advantages/disadvantages of each data set. We compare GPP estimates for the historical period (1990-2009) from two observation-based data sets (Model Tree Ensemble and Moderate Resolution Imaging Spectroradiometer) to coupled carbon-climate models and terrestrial carbon cycle models from the Fifth Climate Model Intercomparison Project and TRENDY projects and to a new hybrid data set (CARBONES). Results show a large range in the mean global GPP estimates. The different data sets broadly agree on GPP seasonal cycle in terms of phasing, while there is still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation-based data that show little IAV and trend, while the process-based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation-based data sets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.
Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.; ...
2017-06-23
Here, the maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr –1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated throughmore » to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.
Here, the maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr –1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated throughmore » to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.« less
NASA Astrophysics Data System (ADS)
Wang, H.; Jia, G.
2017-12-01
Accurate estimation of temporal continuous gross primary production (GPP) plays an important role in mechanistic understanding of global carbon budget and exchange between atmosphere and terrestrial ecosystems. Ground based PhenoCam can provide near surface observations of plant phenology with high temporal resolution and have great potential in modeling seasonal dynamics of GPP. However, due to the empirical approaches for estimating fAPAR, there still exist some uncertainties of adopting PhenoCam images in GPP modeling. In this study, we combined excess green index (EGI) derived from PhenoCam and EVI retrieved from MODIS to generate daily time-series of fAPAR (fAPARcam), and then to estimate daily GPP (GPPpre) with a light use efficiency model in semi-arid grassland from 2012 to 2014. Among the three continuous years, daily fAPARcam exhibited similar temporal behaviors with eddy covariance observed GPP (GPPobs). The overall determination coefficients (R2) were all greater than 0.81. GPPpre agreed well with GPPobs and these agreements showed highly statistically significant (p <0.01). R2 ranged from 0.80 to 0.87, RE ranged from -2.9% to 2.81% and RMSE ranged from 0.83 (gC/m2d-1) to 0.98 (gC/m2d-1). GPPpre was then further evaluated by comparing with MODIS GPP products and VPM modeled GPP. Validation showed the variance explained by GPPpre is still the highest. RMSE and RE were also lower than the other two in general. Explanatory power of inputs in GPP modeling was also explored: fAPAR is the most influential input and PAR takes the second place. Contributions of Tscalar and Wscalar are lower than PAR. These results highlight the potential of PhenoCam images in high temporal resolution GPP modeling. Our GPP modeling method will help to reduce uncertainties of using PhenoCam images in monitoring of seasonal development of vegetation production.
Estimating Urban Gross Primary Productivity at High Spatial Resolution
NASA Astrophysics Data System (ADS)
Miller, David Lauchlin
Gross primary productivity (GPP) is an important metric of ecosystem function and is the primary way carbon is transferred from the atmosphere to the land surface. Remote sensing techniques are commonly used to estimate regional and global GPP for carbon budgets. However, urban areas are typically excluded from such estimates due to a lack of parameters specific to urban vegetation and the modeling challenges that arise in mapping GPP across heterogeneous urban land cover. In this study, we estimated typical midsummer GPP within and among vegetation and land use types in the Minneapolis-Saint Paul, Minnesota metropolitan region by deriving light use efficiency parameters specific to urban vegetation types using in situ flux observations and WorldView-2 high spatial resolution satellite imagery. We produced a land cover classification using the satellite imagery, canopy height data from airborne lidar, and leaf-off color-infrared aerial orthophotos, and used regional GIS layers to mask certain land cover/land use types. The classification for built-up and vegetated urban land cover classes distinguished deciduous trees, evergreen trees, turf grass, and golf grass from impervious and soil surfaces, with an overall classification accuracy of 80% (kappa = 0.73). The full study area had 52.1% vegetation cover. The light use efficiency for each vegetation class, with the exception of golf grass, tended to be low compared to natural vegetation light use efficiencies in the literature. The mapped GPP estimates were within 11% of estimates from independent tall tower eddy covariance measurements. The order of the mapped vegetation classes for the full study area in terms of mean GPP from lowest to highest was: deciduous trees (2.52 gC m -2 d-1), evergreen trees (5.81 gC m-2 d-1), turf grass (6.05 gC m-2 d-1), and golf grass (11.77 gC m-2 d-1). Turf grass GPP had a larger coefficient of variation (0.18) than the other vegetation classes (˜0.10). Mean land use GPP for the
NASA Technical Reports Server (NTRS)
2002-01-01
NASA's new Moderate-resolution Imaging Spectroradiometer (MODIS) allows scientists to gauge our planet's metabolism on an almost daily basis. GPP, gross primary production, is the technical term for plant photosynthesis. This composite image over the continental United States, acquired during the period March 26-April 10, 2000, shows regions where plants were more or less productive-i.e., where they 'inhaled' carbon dioxide and then used the carbon from photosynthesis to build new plant structures. This false-color image provides a map of how much carbon was absorbed out of the atmosphere and fixed within land vegetation. Areas colored blue show where plants used as much as 60 grams of carbon per square meter. Areas colored green and yellow indicate a range of anywhere from 40 to 20 grams of carbon absorbed per square meter. Red pixels show an absorption of less than 10 grams of carbon per square meter and white pixels (often areas covered by snow or masked as urban) show little or no absorption. This is one of a number of new measurements that MODIS provides to help scientists understand how the Earth's landscapes are changing over time. Scientists' goal is use of these GPP measurements to refine computer models to simulate how the land biosphere influences the natural cycles of water, carbon, and energy throughout the Earth system. The GPP will be an integral part of global carbon cycle source and sink analysis, an important aspect of Kyoto Protocol assessments. This image is the first of its kind from the MODIS instrument, which launched in December 1999 aboard the Terra spacecraft. MODIS began acquiring scientific data on February 24, 2000, when it first opened its aperture door. The MODIS instrument and Terra spacecraft are both managed by NASA's Goddard Space Flight Center, Greenbelt, MD. Image courtesy Steven Running, MODIS Land Group Member, University of Montana
Christian P. Giardina; Michael G. Ryan; Dan Binkley; Dan Binkley; James H. Fownes
2003-01-01
Nutrient supply commonly limits aboveground plant productivity in forests, but the effects of an altered nutrient supply on gross primary production (GPP) and patterns of carbon (C) allocation remain poorly characterized. Increased nutrient supply may lead to a higher aboveground net primary production (ANPP), but a lower total belowground carbon allocation (TBCA),...
Scoarughi, G L; Cimmino, C; Donini, P
1995-01-01
The stringent halobacterial strain Haloferax volcanii was subjected to a set of physiological conditions different from amino acid starvation that are known to cause production of guanosine polyphosphates [(p)pp Gpp] in eubacteria via the relA-independent (spoT) pathway. The conditions used were temperature upshift, treatment with cyanide, and total starvation. Under none of these conditions were detectable levels of (p)ppGpp observed. This result, in conjunction with our previous finding that (p)ppGpp synthesis does not occur under amino acid starvation, leads to the conclusion that in halobacteria both growth rate control and stringency are probably governed by mechanisms that operate in the absence of ppGpp. During exponential growth, a low level of phosphorylated compounds with electrophoretic mobilities similar, but not identical, to that of (p)ppGpp were observed. The intracellular concentration of these compounds increased considerably during the stationary phase of growth and with all of the treatments used. The compounds were identified as short-chain polyphosphates identical to those found under similar conditions in Saccharomyces cerevisiae. PMID:7798153
Cui, Tianxiang; Wang, Yujie; Sun, Rui; Qiao, Chen; Fan, Wenjie; Jiang, Guoqing; Hao, Lvyuan; Zhang, Lei
2016-01-01
Estimating gross primary production (GPP) and net primary production (NPP) are significant important in studying carbon cycles. Using models driven by multi-source and multi-scale data is a promising approach to estimate GPP and NPP at regional and global scales. With a focus on data that are openly accessible, this paper presents a GPP and NPP model driven by remotely sensed data and meteorological data with spatial resolutions varying from 30 m to 0.25 degree and temporal resolutions ranging from 3 hours to 1 month, by integrating remote sensing techniques and eco-physiological process theories. Our model is also designed as part of the Multi-source data Synergized Quantitative (MuSyQ) Remote Sensing Production System. In the presented MuSyQ-NPP algorithm, daily GPP for a 10-day period was calculated as a product of incident photosynthetically active radiation (PAR) and its fraction absorbed by vegetation (FPAR) using a light use efficiency (LUE) model. The autotrophic respiration (Ra) was determined using eco-physiological process theories and the daily NPP was obtained as the balance between GPP and Ra. To test its feasibility at regional scales, our model was performed in an arid and semi-arid region of Heihe River Basin, China to generate daily GPP and NPP during the growing season of 2012. The results indicated that both GPP and NPP exhibit clear spatial and temporal patterns in their distribution over Heihe River Basin during the growing season due to the temperature, water and solar influx conditions. After validated against ground-based measurements, MODIS GPP product (MOD17A2H) and results reported in recent literature, we found the MuSyQ-NPP algorithm could yield an RMSE of 2.973 gC m(-2) d(-1) and an R of 0.842 when compared with ground-based GPP while an RMSE of 8.010 gC m(-2) d(-1) and an R of 0.682 can be achieved for MODIS GPP, the estimated NPP values were also well within the range of previous literature, which proved the reliability of our
Cui, Tianxiang; Wang, Yujie; Sun, Rui; Qiao, Chen; Fan, Wenjie; Jiang, Guoqing; Hao, Lvyuan; Zhang, Lei
2016-01-01
Estimating gross primary production (GPP) and net primary production (NPP) are significant important in studying carbon cycles. Using models driven by multi-source and multi-scale data is a promising approach to estimate GPP and NPP at regional and global scales. With a focus on data that are openly accessible, this paper presents a GPP and NPP model driven by remotely sensed data and meteorological data with spatial resolutions varying from 30 m to 0.25 degree and temporal resolutions ranging from 3 hours to 1 month, by integrating remote sensing techniques and eco-physiological process theories. Our model is also designed as part of the Multi-source data Synergized Quantitative (MuSyQ) Remote Sensing Production System. In the presented MuSyQ-NPP algorithm, daily GPP for a 10-day period was calculated as a product of incident photosynthetically active radiation (PAR) and its fraction absorbed by vegetation (FPAR) using a light use efficiency (LUE) model. The autotrophic respiration (Ra) was determined using eco-physiological process theories and the daily NPP was obtained as the balance between GPP and Ra. To test its feasibility at regional scales, our model was performed in an arid and semi-arid region of Heihe River Basin, China to generate daily GPP and NPP during the growing season of 2012. The results indicated that both GPP and NPP exhibit clear spatial and temporal patterns in their distribution over Heihe River Basin during the growing season due to the temperature, water and solar influx conditions. After validated against ground-based measurements, MODIS GPP product (MOD17A2H) and results reported in recent literature, we found the MuSyQ-NPP algorithm could yield an RMSE of 2.973 gC m-2 d-1 and an R of 0.842 when compared with ground-based GPP while an RMSE of 8.010 gC m-2 d-1 and an R of 0.682 can be achieved for MODIS GPP, the estimated NPP values were also well within the range of previous literature, which proved the reliability of our modelling
Wavelength-dependent ability of solar-induced chlorophyll fluorescence to estimate GPP
NASA Astrophysics Data System (ADS)
Liu, L.
2017-12-01
Recent studies have demonstrated that solar-induced chlorophyll fluorescence (SIF) can offer a new way for directly estimating the terrestrial gross primary production (GPP). In this paper, the wavelength-dependent ability of SIF to estimate GPP was investigated using both simulations by SCOPE model (Soil Canopy Observation, Photochemistry and Energy fluxes) and observations at the canopy level. Firstly, the response of the remotely sensed SIF at the canopy level to the absorbed photosynthetically active radiation (APAR ) was investigated. Both the simulations and observations confirm a linear relationship between canopy SIF and APAR, while it is species-specific and affected by biochemical components and canopy structure. The ratio of SIF to APAR varies greatly for different vegetation types, which is significant larger for canopy with horizontal structure than it with vertical structure. At red band, the ratio also decreases noticeable when chlorophyll content increases. Then, the performance of SIF to estimate GPP was investigated using diurnal observations of winter wheat at different grow stages. The results showed that the diurnal GPP could be robustly estimated from the SIF spectra for winter wheat at each growth stage, while the correlation weakened greatly at red band if all the observations made at different growth stages or all simulations with different LAI values were pooled together - a situation which did not occur at the far-red band. Finally, the SIF-based GPP models derived from the 2016 observations on winter wheat were well validated using the dataset from 2015, which give better performance for SIF at far-red band than that at red band. Therefore, it is very important to correct for reabsorption and scattering of the SIF radiative transfer from the photosystem to the canopy level before the remotely sensed SIF is linked to the GPP, especially at red band.
Seasonality of primary and secondary production in an Arctic river
NASA Astrophysics Data System (ADS)
Kendrick, M.; Huryn, A.; Deegan, L.
2011-12-01
Rivers and streams that freeze solid for 8-9 months each year provide excellent examples of the extreme seasonality of arctic habitats. The communities of organisms inhabiting these rivers must complete growth and development during summer, resulting in a rapid ramp-up and down of production over the short ice-free period. The effects of recent shifts in the timing of the spring thaw and autumn freeze-up on the duration and pattern of the period of active production are poorly understood. We are currently investigating: 1) the response of the biotic community of the Kuparuk River (Arctic Alaska) to shifts in the seasonality of the ice-free period, and 2) the community response to increases in phosphorous (P) supply anticipated as the volume of the permafrost active-layer increases in response to climate warming. Here algal production supports a 2-tier web of consumers. We tracked primary and secondary production from the spring thaw through mid-August in a reference reach and one receiving low-level P fertilization. Gross primary production/community respiration (GPP/R) ratios for both reaches were increasing through mid-July, with higher GPP/R in response to the P addition. Understanding the degree of synchrony between primary and secondary production in this Arctic river system will enhance further understanding of how shifts in seasonality affect trophic dynamics.
NASA Astrophysics Data System (ADS)
Mo, Xingguo; Chen, Xuejuan; Hu, Shi; Liu, Suxia; Xia, Jun
2017-01-01
Attributing changes in evapotranspiration (ET) and gross primary productivity (GPP) is crucial for impact and adaptation assessment of the agro-ecosystems to climate change. Simulations with the VIP model revealed that annual ET and GPP slightly increased from 1981 to 2013 over the North China Plain. The tendencies of both ET and GPP were upward in the spring season, while they were weak and downward in the summer season. A complete factor analysis illustrated that the relative contributions of climatic change, CO2 fertilization, and management to the ET (GPP) trend were 56 (-32) %, -28 (25) %, and 68 (108) %, respectively. The decline of global radiation resulted from deteriorated aerosol and air pollution was the principal cause of GPP decline in summer, while air warming intensified the water cycle and advanced the plant productivity in the spring season. Generally, agronomic improvements were the principal drivers of crop productivity enhancement.
Selmants, Paul C.; Moreno, Alvaro; Running, Steve W.; Giardina, Christian P.
2017-01-01
Gross primary production (GPP) is the Earth’s largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales. PMID:28886187
Kimball, Heather L.; Selmants, Paul; Moreno, Alvaro; Running Steve W,; Giardina, Christian P.
2017-01-01
Gross primary production (GPP) is the Earth’s largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales.
Kimball, Heather L; Selmants, Paul C; Moreno, Alvaro; Running, Steve W; Giardina, Christian P
2017-01-01
Gross primary production (GPP) is the Earth's largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales.
Barman, Rahul; Jain, Atul K; Liang, Miaoling
2014-05-01
We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis-driven GPP bias was significantly positive with respect to the observed meteorology-driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m(-2) yr(-1) across sites (ca. 15% of site level GPP). At the northern mid-/high-latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20-30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short-wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site-level reanalysis-driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate-driven uncertainties in carbon, energy, and water fluxes
Cassels, R; Oliva, B; Knowles, D
1995-01-01
The stringent response in Escherichia coli and many other organisms is regulated by the nucleotides ppGpp and pppGpp. We show here for the first time that at least six staphylococcal species also synthesize ppGpp and pppGpp upon induction of the stringent response by mupirocin. Spots corresponding to ppGpp and pppGpp on thin-layer chromatograms suggest that pppGpp is the principal regulatory nucleotide synthesized by staphylococci in response to mupirocin, rather than ppGpp as in E. coli. PMID:7665499
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xia, Jingfeng; Zhuang, Qianlai; Law, Beverly E.
The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide rangemore » of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km x 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr{sup -1} for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were
Hongqing Wanga; Charles A.S. Halla; Frederick N. Scatenab; Ned Fetcherc; Wei Wua
2003-01-01
There are few studies that have examined the spatial variability of forest productivity over an entire tropical forested landscape. In this study, we used a spatially-explicit forest productivity model, TOPOPROD, which is based on the FORESTBGC model, to simulate spatial patterns of gross primary productivity (GPP), net primary productivity (NPP), and respiration over...
The ratio of NPP to GPP: evidence of change over the course of stand development.
Mäkelä, A; Valentine, H T
2001-09-01
Using Scots pine (Pinus sylvestris L.) in Fenno-Scandia as a case study, we investigate whether net primary production (NPP) and maintenance respiration are constant fractions of gross primary production (GPP) as even-aged mono-specific stands progress from initiation to old age. A model of the ratio of NPP to GPP is developed based on (1) the classical model of respiration, which divides total respiration into construction and maintenance components, and (2) a process-based model, which derives respiration from processes including construction, nitrate uptake and reduction, ion uptake, phloem loading and maintenance. Published estimates of specific respiration and production rates, and some recent measurements of components of dry matter in stands of different ages, are used to quantify the two approaches over the course of stand development in an average environment. Both approaches give similar results, showing a decrease in the NPP/GPP ratio with increasing tree height. In addition, we show that stand-growth models fitted under three different sets of assumptions-(i) annual specific rates of maintenance respiration of sapwood (mW) and photosynthesis (sC) are constant; (ii) m(W) is constant, but sC decreases with increasing tree height; and (iii) total maintenance respiration is a constant fraction of GPP and s(C) decreases with increasing tree height-can lead to nearly identical model projections that agree with empirical observations of NPP and stand-growth variables. Remeasurements of GPP and respiration over time in chronosequences of stands may be needed to discern which set of assumptions is correct. Total (construction + maintenance) sapwood respiration per unit mass of sapwood (kg C (kg C year)-1) decreased with increasing stand age, sapwood stock, and average tree height under all three assumptions. However, total sapwood respiration (kg C (ha year)-1) increased over the course of stand development under (i) and (ii), contributing to a downward trend in
Evaluating post-disaster ecosystem resilience using MODIS GPP data
NASA Astrophysics Data System (ADS)
Frazier, Amy E.; Renschler, Chris S.; Miles, Scott B.
2013-04-01
An integrated community resilience index (CRI) quantifies the status, exposure, and recovery of the physical, economic, and socio-cultural capital for a specific target community. However, most CRIs do not account for the recovery of ecosystem functioning after extreme events, even though many aspects of a community depend on the services provided by the natural environment. The primary goal of this study was to monitor the recovery of ecosystem functionality (ecological capital) using remote sensing-derived gross primary production (GPP) as an indicator of 'ecosystem-wellness' and assess the effect of resilience of ecological capital on the recovery of a community via an integrated CRI. We developed a measure of ecosystem resilience using remotely sensed GPP data and applied the modeling prototype ResilUS in a pilot study for a four-parish coastal community in southwestern Louisiana, USA that was impacted by Hurricane Rita in 2005. The results illustrate that after such an extreme event, the recovery of ecological capital varies according to land use type and may take many months to return to full functionality. This variable recovery can potentially impact the recovery of certain businesses that rely heavily on ecosystem services such as agriculture, forestry, fisheries, and tourism.
NASA Astrophysics Data System (ADS)
Kimball, H.; Selmants, P. C.; Running, S. W.; Moreno, A.; Giardina, C. P.
2016-12-01
In this study we evaluate the influence of spatial data product accuracy and resolution on the application of global models for smaller scale heterogeneous landscapes. In particular, we assess the influence of locally specific land cover and high-resolution climate data products on estimates of Gross Primary Production (GPP) for the Hawaiian Islands using the MOD17 model. The MOD17 GPP algorithm uses a measure of the fraction of absorbed photosynthetically active radiation from the National Aeronautics and Space Administration's Earth Observation System. This direct measurement is combined with global land cover (500-m resolution) and climate models ( 1/2-degree resolution) to estimate GPP. We first compared the alignment between the global land cover model used in MOD17 with a Hawaii specific land cover data product. We found that there was a 51.6% overall agreement between the two land cover products. We then compared four MOD17 GPP models: A global model that used the global land cover and low-resolution global climate data products, a model produced using the Hawaii specific land cover and low-resolution global climate data products, a model with global land cover and high-resolution climate data products, and finally, a model using both Hawaii specific land cover and high-resolution climate data products. We found that including either the Hawaii specific land cover or the high-resolution Hawaii climate data products with MOD17 reduced overall estimates of GPP by 8%. When both were used, GPP estimates were reduced by 16%. The reduction associated with land cover is explained by a reduction of the total area designated as evergreen broad leaf forest and an increase in the area designated as barren or sparsely vegetated in the Hawaii land cover product as compared to the global product. The climate based reduction is explained primarily by the spatial resolution and distribution of solar radiation in the Hawaiian Islands. This study highlights the importance of
NASA Astrophysics Data System (ADS)
Minaya, Veronica; Corzo, Gerald; van der Kwast, Johannes; Mynett, Arthur
2016-04-01
Many terrestrial biogeochemistry process models have been applied around the world at different scales and for a large range of ecosystems. Grasslands, and in particular the ones located in the Andean Region are essential ecosystems that sustain important ecological processes; however, just a few efforts have been made to estimate the gross primary production (GPP) and the hydrological budgets for this specific ecosystem along an altitudinal gradient. A previous study, which is one of the few available in the region, considered the heterogeneity of the main properties of the páramo vegetation and showed significant differences in plant functional types, site/soil parameters and daily meteorology. This study extends the work above mentioned and uses spatio-temporal analysis of the BIOME-BGC model results. This was done to simulate the GPP and the water fluxes in space and time, by applying altitudinal analysis. The catchment located at the southwestern slope of the Antisana volcano in Ecuador was selected as a representative area of the Andean páramos and its hydrological importance as one of the main sources of a water supply reservoir in the region. An accurate estimation of temporal changes in GPP in the region is important for carbon budget assessments, evaluation of the impact of climate change and biomass productivity. This complex and yet interesting problem was integrated by the ecosystem process model BIOME-BGC, the results were evaluated and associated to the land cover map where the growth forms of vegetation were identified. The responses of GPP and the water fluxes were not only dependent on the environmental drivers but also on the ecophysiology and the site specific parameters. The model estimated that the GPP at lower elevations doubles the amount estimated at higher elevations, which might have a large implication during extrapolations at larger spatio-temporal scales. The outcomes of the stand hydrological processes demonstrated a wrong
Zhang, Li; Wylie, Bruce K.; Loveland, Thomas R.; Fosnight, Eugene A.; Tieszen, Larry L.; Ji, Lei; Gilmanov, Tagir
2007-01-01
Two spatially-explicit estimates of gross primary production (GPP) are available for the Northern Great Plains. An empirical piecewise regression (PWR) GPP model was developed from flux tower measurements to map carbon flux across the region. The Moderate Resolution Imaging Spectrometer (MODIS) GPP model is a process-based model that uses flux tower data to calibrate its parameters. Verification and comparison of the regional PWR GPP and the global MODIS GPP are important for the modeling of grassland carbon flux. This study compared GPP estimates from PWR and MODIS models with five towers in the grasslands. Among them, PWR GPP and MODIS GPP showed a good agreement with tower-based GPP at three towers. The global MODIS GPP, however, did not agree well with tower-based GPP at two other towers, probably because of the insensitivity of MODIS model to regional ecosystem and climate change and extreme soil moisture conditions. Cross-validation indicated that the PWR model is relatively robust for predicting regional grassland GPP. However, the PWR model should include a wide variety of flux tower data as the training data sets to obtain more accurate results.In addition, GPP maps based on the PWR and MODIS models were compared for the entire region. In the northwest and south, PWR GPP was much higher than MODIS GPP. These areas were characterized by the higher water holding capacity with a lower proportion of C4 grasses in the northwest and a higher proportion of C4 grasses in the south. In the central and southeastern regions, PWR GPP was much lower than MODIS GPP under complicated conditions with generally mixed C3/C4 grasses. The analysis indicated that the global MODIS GPP model has some limitations on detecting moisture stress, which may have been caused by the facts that C3 and C4 grasses are not distinguished, water stress is driven by vapor pressure deficit (VPD) from coarse meteorological data, and MODIS land cover data are unable to differentiate the sub
NASA Astrophysics Data System (ADS)
Nicholson, David P.; Wilson, Samuel T.; Doney, Scott C.; Karl, David M.
2015-05-01
Using autonomous underwater gliders, we quantified diurnal periodicity in dissolved oxygen, chlorophyll, and temperature in the subtropical North Pacific near the Hawaii Ocean Time-series (HOT) Station ALOHA during summer 2012. Oxygen optodes provided sufficient stability and precision to quantify diel cycles of average amplitude of 0.6 µmol kg-1. A theoretical diel curve was fit to daily observations to infer an average mixed layer gross primary productivity (GPP) of 1.8 mmol O2 m-3 d-1. Cumulative net community production (NCP) over 110 days was 500 mmol O2 m-2 for the mixed layer, which averaged 57 m in depth. Both GPP and NCP estimates indicated a significant period of below-average productivity at Station ALOHA in 2012, an observation confirmed by 14C productivity incubations and O2/Ar ratios. Given our success in an oligotrophic gyre where biological signals are small, our diel GPP approach holds promise for remote characterization of productivity across the spectrum of marine environments.
NASA Astrophysics Data System (ADS)
Zhang, Yao; Xiao, Xiangming; Guanter, Luis; Zhou, Sha; Ciais, Philippe; Joiner, Joanna; Sitch, Stephen; Wu, Xiaocui; Nabel, Julia; Dong, Jinwei; Kato, Etsushi; Jain, Atul K.; Wiltshire, Andy; Stocker, Benjamin D.
2016-12-01
Carbon uptake by terrestrial ecosystems is increasing along with the rising of atmospheric CO2 concentration. Embedded in this trend, recent studies suggested that the interannual variability (IAV) of global carbon fluxes may be dominated by semi-arid ecosystems, but the underlying mechanisms of this high variability in these specific regions are not well known. Here we derive an ensemble of gross primary production (GPP) estimates using the average of three data-driven models and eleven process-based models. These models are weighted by their spatial representativeness of the satellite-based solar-induced chlorophyll fluorescence (SIF). We then use this weighted GPP ensemble to investigate the GPP variability for different aridity regimes. We show that semi-arid regions contribute to 57% of the detrended IAV of global GPP. Moreover, in regions with higher GPP variability, GPP fluctuations are mostly controlled by precipitation and strongly coupled with evapotranspiration (ET). This higher GPP IAV in semi-arid regions is co-limited by supply (precipitation)-induced ET variability and GPP-ET coupling strength. Our results demonstrate the importance of semi-arid regions to the global terrestrial carbon cycle and posit that there will be larger GPP and ET variations in the future with changes in precipitation patterns and dryland expansion.
NASA Technical Reports Server (NTRS)
Zhang, Yao; Xiao, Xiangming; Guanter, Luis; Zhou, Sha; Ciais, Philippe; Joiner, Joanna; Sitch, Stephen; Wu, Xiaocui; Nabel, Julian; Dong, Jinwei;
2016-01-01
Carbon uptake by terrestrial ecosystems is increasing along with the rising of atmospheric CO2 concentration. Embedded in this trend, recent studies suggested that the interannual variability (IAV) of global carbon fluxes may be dominated by semi-arid ecosystems, but the underlying mechanisms of this high variability in these specific regions are not well known. Here we derive an ensemble of gross primary production (GPP) estimates using the average of three data-driven models and eleven process-based models. These models are weighted by their spatial representativeness of the satellite-based solar-induced chlorophyll fluorescence (SIF). We then use this weighted GPP ensemble to investigate the GPP variability for different aridity regimes. We show that semi-arid regions contribute to 57% of the detrended IAV of global GPP. Moreover, in regions with higher GPP variability, GPP fluctuations are mostly controlled by precipitation and strongly coupled with evapotranspiration (ET). This higher GPP IAV in semi-arid regions is co-limited by supply (precipitation)-induced ET variability and GPP-ET coupling strength. Our results demonstrate the importance of semi-arid regions to the global terrestrial carbon cycle and posit that there will be larger GPP and ET variations in the future with changes in precipitation patterns and dryland expansion.
Danelichen, Victor H M; Biudes, Marcelo S; Velasque, Maísa C S; Machado, Nadja G; Gomes, Raphael S R; Vourlitis, George L; Nogueira, José S
2015-09-01
The acceleration of the anthropogenic activity has increased the atmospheric carbon concentration, which causes changes in regional climate. The Gross Primary Production (GPP) is an important variable in the global carbon cycle studies, since it defines the atmospheric carbon extraction rate from terrestrial ecosystems. The objective of this study was to estimate the GPP of the Amazon-Cerrado Transitional Forest by the Vegetation Photosynthesis Model (VPM) using local meteorological data and remote sensing data from MODIS and Landsat 5 TM reflectance from 2005 to 2008. The GPP was estimated using Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) calculated by MODIS and Landsat 5 TM images. The GPP estimates were compared with measurements in a flux tower by eddy covariance. The GPP measured in the tower was consistent with higher values during the wet season and there was a trend to increase from 2005 to 2008. The GPP estimated by VPM showed the same increasing trend observed in measured GPP and had high correlation and Willmott's coefficient and low error metrics in comparison to measured GPP. These results indicated high potential of the Landsat 5 TM images to estimate the GPP of Amazon-Cerrado Transitional Forest by VPM.
Novel (p)ppGpp Binding and Metabolizing Proteins of Escherichia coli.
Zhang, Yong; Zborníková, Eva; Rejman, Dominik; Gerdes, Kenn
2018-03-06
The alarmone (p)ppGpp plays pivotal roles in basic bacterial stress responses by increasing tolerance of various nutritional limitations and chemical insults, including antibiotics. Despite intensive studies since (p)ppGpp was discovered over 4 decades ago, (p)ppGpp binding proteins have not been systematically identified in Escherichia coli We applied DRaCALA ( d ifferential ra dial c apillary a ction of l igand a ssay) to identify (p)ppGpp-protein interactions. We discovered 12 new (p)ppGpp targets in E. coli that, based on their physiological functions, could be classified into four major groups, involved in (i) purine nucleotide homeostasis (YgdH), (ii) ribosome biogenesis and translation (RsgA, Era, HflX, and LepA), (iii) maturation of dehydrogenases (HypB), and (iv) metabolism of (p)ppGpp (MutT, NudG, TrmE, NadR, PhoA, and UshA). We present a comprehensive and comparative biochemical and physiological characterization of these novel (p)ppGpp targets together with a comparative analysis of relevant, known (p)ppGpp binding proteins. Via this, primary targets of (p)ppGpp in E. coli are identified. The GTP salvage biosynthesis pathway and ribosome biogenesis and translation are confirmed as targets of (p)ppGpp that are highly conserved between E. coli and Firmicutes In addition, an alternative (p)ppGpp degradative pathway, involving NudG and MutT, was uncovered. This report thus significantly expands the known cohort of (p)ppGpp targets in E. coli IMPORTANCE Antibiotic resistance and tolerance exhibited by pathogenic bacteria have resulted in a global public health crisis. Remarkably, almost all bacterial pathogens require the alarmone (p)ppGpp to be virulent. Thus, (p)ppGpp not only induces tolerance of nutritional limitations and chemical insults, including antibiotics, but is also often required for induction of virulence genes. However, understanding of the molecular targets of (p)ppGpp and the mechanisms by which (p)ppGpp influences bacterial physiology
Feng, X; Liu, G; Chen, J M; Chen, M; Liu, J; Ju, W M; Sun, R; Zhou, W
2007-11-01
The terrestrial carbon cycle is one of the foci in global climate change research. Simulating net primary productivity (NPP) of terrestrial ecosystems is important for carbon cycle research. In this study, China's terrestrial NPP was simulated using the Boreal Ecosystem Productivity Simulator (BEPS), a carbon-water coupled process model based on remote sensing inputs. For these purposes, a national-wide database (including leaf area index, land cover, meteorology, vegetation and soil) at a 1 km resolution and a validation database were established. Using these databases and BEPS, daily maps of NPP for the entire China's landmass in 2001 were produced, and gross primary productivity (GPP) and autotrophic respiration (RA) were estimated. Using the simulated results, we explore temporal-spatial patterns of China's terrestrial NPP and the mechanisms of its responses to various environmental factors. The total NPP and mean NPP of China's landmass were 2.235 GtC and 235.2 gCm(-2)yr(-1), respectively; the total GPP and mean GPP were 4.418 GtC and 465 gCm(-2)yr(-1); and the total RA and mean RA were 2.227 GtC and 234 gCm(-2)yr(-1), respectively. On average, NPP was 50.6% of GPP. In addition, statistical analysis of NPP of different land cover types was conducted, and spatiotemporal patterns of NPP were investigated. The response of NPP to changes in some key factors such as LAI, precipitation, temperature, solar radiation, VPD and AWC are evaluated and discussed.
Walker, Anthony P; Quaife, Tristan; van Bodegom, Peter M; De Kauwe, Martin G; Keenan, Trevor F; Joiner, Joanna; Lomas, Mark R; MacBean, Natasha; Xu, Chongang; Yang, Xiaojuan; Woodward, F Ian
2017-09-01
The maximum photosynthetic carboxylation rate (V cmax ) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr -1 , 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes. © 2017 UT-Battelle LLC. New Phytologist © 2017 New Phytologist Trust.
High sensitivity of gross primary production in the Rocky Mountains to summer rain
Berkelhammer, M.; Stefanescu, I.C.; Joiner, J.; Anderson, Lesleigh
2017-01-01
In the catchments of the Rocky Mountains, peak snowpack is declining in response to warmer spring temperatures. To understand how this will influence terrestrial gross primary production (GPP), we compared precipitation data across the intermountain west with satellite retrievals of solar-induced fluorescence (SIF), a proxy for GPP. Annual precipitation patterns explained most of the spatial and temporal variability of SIF, but the slope of the response was dependent on site to site differences in the proportion of snowpack to summer rain. We separated the response of SIF to different seasonal precipitation amounts and found that SIF was approximately twice as sensitive to variations in summer rain than snowpack. The response of peak GPP to a secular decline in snowpack will likely be subtle, whereas a change in summer rain amount will have precipitous effects on GPP. The study suggests that the rain use efficiency of Rocky Mountain ecosystems is strongly dependent on precipitation form and timing.
Climate data induced uncertainty in model-based estimations of terrestrial primary productivity
NASA Astrophysics Data System (ADS)
Wu, Zhendong; Ahlström, Anders; Smith, Benjamin; Ardö, Jonas; Eklundh, Lars; Fensholt, Rasmus; Lehsten, Veiko
2017-06-01
Model-based estimations of historical fluxes and pools of the terrestrial biosphere differ substantially. These differences arise not only from differences between models but also from differences in the environmental and climatic data used as input to the models. Here we investigate the role of uncertainties in historical climate data by performing simulations of terrestrial gross primary productivity (GPP) using a process-based dynamic vegetation model (LPJ-GUESS) forced by six different climate datasets. We find that the climate induced uncertainty, defined as the range among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 11 Pg C yr-1 globally (9% of mean GPP). We also assessed a hypothetical maximum climate data induced uncertainty by combining climate variables from different datasets, which resulted in significantly larger uncertainties of 41 Pg C yr-1 globally or 32% of mean GPP. The uncertainty is partitioned into components associated to the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (climate data range) and the apparent sensitivity of the modeled GPP to the driver (apparent model sensitivity). We find that LPJ-GUESS overestimates GPP compared to empirically based GPP data product in all land cover classes except for tropical forests. Tropical forests emerge as a disproportionate source of uncertainty in GPP estimation both in the simulations and empirical data products. The tropical forest uncertainty is most strongly associated with shortwave radiation and precipitation forcing, of which climate data range contributes higher to overall uncertainty than apparent model sensitivity to forcing. Globally, precipitation dominates the climate induced uncertainty over nearly half of the vegetated land area, which is mainly due
NASA Astrophysics Data System (ADS)
Loehman, R.; Heinsch, F. A.; Mills, J. N.; Wagoner, K.; Running, S.
2003-12-01
Recent predictive models for hantavirus pulmonary syndrome (HPS) have used remotely sensed spectral reflectance data to characterize risk areas with limited success. We present an alternative method using gross primary production (GPP) from the MODIS sensor to estimate the effects of biomass accumulation on population density of Peromyscus maniculatus (deer mouse), the principal reservoir species for Sin Nombre virus (SNV). The majority of diagnosed HPS cases in North America are attributed to SNV, which is transmitted to humans through inhalation of excretions and secretions from infected rodents. A logistic model framework is used to evaluate MODIS GPP, temperature, and precipitation as predictors of P. maniculatus density at established trapping sites across the western United States. Rodent populations are estimated using monthly minimum number alive (MNA) data for 2000 through 2002. Both local meteorological data from nearby weather stations and 1.25 degree x 1 degree gridded data from the NASA DAO were used in the regression model to determine the spatial sensitivity of the response. MODIS eight-day GPP data (1-km resolution) were acquired and binned to monthly average and monthly sum GPP for 3km x 3km grids surrounding each rodent trapping site. The use of MODIS GPP to forecast HPS risk may result in a marked improvement over past reflectance-based risk area characterizations. The MODIS GPP product provides a vegetation dynamics estimate that is unique to disease models, and targets the fundamental ecological processes responsible for increased rodent density and amplified disease risk.
Hall, Robert O.; Yackulic, Charles B.; Kennedy, Theodore A.; Yard, Michael D.; Rosi-Marshall, Emma J.; Voichick, Nicholas; Behn, Kathrine E.
2015-01-01
Dams and river regulation greatly alter the downstream environment for gross primary production (GPP) because of changes in water clarity, flow, and temperature regimes. We estimated reach-scale GPP in five locations of the regulated Colorado River in Grand Canyon using an open channel model of dissolved oxygen. Benthic GPP dominates in Grand Canyon due to fast transport times and low pelagic algal biomass. In one location, we used a 738 days time series of GPP to identify the relative contribution of different physical controls of GPP. We developed both linear and semimechanistic time series models that account for unmeasured temporal covariance due to factors such as algal biomass dynamics. GPP varied from 0 g O2 m−2 d−1 to 3.0 g O2 m−2 d−1 with a relatively low annual average of 0.8 g O2 m−2d−1. Semimechanistic models fit the data better than linear models and demonstrated that variation in turbidity primarily controlled GPP. Lower solar insolation during winter and from cloud cover lowered GPP much further. Hydropeaking lowered GPP but only during turbid conditions. Using the best model and parameter values, the model accurately predicted seasonal estimates of GPP at 3 of 4 upriver sites and outperformed the linear model at all sites; discrepancies were likely from higher algal biomass at upstream sites. This modeling approach can predict how changes in physical controls will affect relative rates of GPP throughout the 385 km segment of the Colorado River in Grand Canyon and can be easily applied to other streams and rivers.
NASA Astrophysics Data System (ADS)
Smith, W. K.; Biederman, J. A.; Scott, R. L.; Moore, D. J. P.; He, M.; Kimball, J. S.; Yan, D.; Hudson, A.; Barnes, M. L.; MacBean, N.; Fox, A. M.; Litvak, M. E.
2018-01-01
Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet understanding of the relationship between GPP and remote sensing observations and how it changes with factors such as scale, biophysical constraint, and vegetation type remains limited. This knowledge gap is especially apparent for dryland ecosystems, which have characteristic high spatiotemporal variability and are under-represented by long-term field measurements. Here we utilize an eddy covariance (EC) data synthesis for southwestern North America in an assessment of how accurately satellite-derived vegetation proxies capture seasonal to interannual GPP dynamics across dryland gradients. We evaluate the enhanced vegetation index, solar-induced fluorescence (SIF), and the photochemical reflectivity index. We find evidence that SIF is more accurately capturing seasonal GPP dynamics particularly for evergreen-dominated EC sites and more accurately estimating the full magnitude of interannual GPP dynamics for all dryland EC sites. These results suggest that incorporation of SIF could significantly improve satellite-based GPP estimates.
A statistical light use efficiency model explains 85% variations in global GPP
NASA Astrophysics Data System (ADS)
Jiang, C.; Ryu, Y.
2016-12-01
Photosynthesis is a complicated process whose modeling requires different levels of assumptions, simplification, and parameterization. Among models, light use efficiency (LUE) model is highly compact but powerful in monitoring gross primary production (GPP) from satellite data. Most of LUE models adopt a multiplicative from of maximum LUE, absorbed photosynthetically active radiation (APAR), and temperature and water stress functions. However, maximum LUE is a fitting parameter with large spatial variations, but most studies only use several biome dependent constants. In addition, stress functions are empirical and arbitrary in literatures. Moreover, meteorological data used are usually coarse-resolution, e.g., 1°, which could cause large errors. Finally, sunlit and shade canopy have completely different light responses but little considered. Targeting these issues, we derived a new statistical LUE model from a process-based and satellite-driven model, the Breathing Earth System Simulator (BESS). We have already derived a set of global radiation (5-km resolution), carbon and water fluxes (1-km resolution) products from 2000 to 2015 from BESS. By exploring these datasets, we found strong correlation between APAR and GPP for sunlit (R2=0.84) and shade (R2=0.96) canopy, respectively. A simple model, only driven by sunlit and shade APAR, was thus built based on linear relationships. The slopes of the linear function act as effective LUE of global ecosystem, with values of 0.0232 and 0.0128 umol C/umol quanta for sunlit and shade canopy, respectively. When compared with MPI-BGC GPP products, a global proxy of FLUXNET data, BESS-LUE achieved an overall accuracy of R2 = 0.85, whereas original BESS was R2 = 0.83 and MODIS GPP product was R2 = 0.76. We investigated spatiotemporal variations of the effective LUE. Spatially, the ratio of sunlit to shade values ranged from 0.1 (wet tropic) to 4.5 (dry inland). By using maps of sunlit and shade effective LUE the accuracy of
NASA Astrophysics Data System (ADS)
Raj, R.; Hamm, N. A. S.; van der Tol, C.; Stein, A.
2015-08-01
Gross primary production (GPP), separated from flux tower measurements of net ecosystem exchange (NEE) of CO2, is used increasingly to validate process-based simulators and remote sensing-derived estimates of simulated GPP at various time steps. Proper validation should include the uncertainty associated with this separation at different time steps. This can be achieved by using a Bayesian framework. In this study, we estimated the uncertainty in GPP at half hourly time steps. We used a non-rectangular hyperbola (NRH) model to separate GPP from flux tower measurements of NEE at the Speulderbos forest site, The Netherlands. The NRH model included the variables that influence GPP, in particular radiation, and temperature. In addition, the NRH model provided a robust empirical relationship between radiation and GPP by including the degree of curvature of the light response curve. Parameters of the NRH model were fitted to the measured NEE data for every 10-day period during the growing season (April to October) in 2009. Adopting a Bayesian approach, we defined the prior distribution of each NRH parameter. Markov chain Monte Carlo (MCMC) simulation was used to update the prior distribution of each NRH parameter. This allowed us to estimate the uncertainty in the separated GPP at half-hourly time steps. This yielded the posterior distribution of GPP at each half hour and allowed the quantification of uncertainty. The time series of posterior distributions thus obtained allowed us to estimate the uncertainty at daily time steps. We compared the informative with non-informative prior distributions of the NRH parameters. The results showed that both choices of prior produced similar posterior distributions GPP. This will provide relevant and important information for the validation of process-based simulators in the future. Furthermore, the obtained posterior distributions of NEE and the NRH parameters are of interest for a range of applications.
Assessing the relationship between microwave vegetation optical depth and gross primary production
NASA Astrophysics Data System (ADS)
Teubner, Irene E.; Forkel, Matthias; Jung, Martin; Liu, Yi Y.; Miralles, Diego G.; Parinussa, Robert; van der Schalie, Robin; Vreugdenhil, Mariette; Schwalm, Christopher R.; Tramontana, Gianluca; Camps-Valls, Gustau; Dorigo, Wouter A.
2018-03-01
At the global scale, the uptake of atmospheric carbon dioxide by terrestrial ecosystems through photosynthesis is commonly estimated through vegetation indices or biophysical properties derived from optical remote sensing data. Microwave observations of vegetated areas are sensitive to different components of the vegetation layer than observations in the optical domain and may therefore provide complementary information on the vegetation state, which may be used in the estimation of Gross Primary Production (GPP). However, the relation between GPP and Vegetation Optical Depth (VOD), a biophysical quantity derived from microwave observations, is not yet known. This study aims to explore the relationship between VOD and GPP. VOD data were taken from different frequencies (L-, C-, and X-band) and from both active and passive microwave sensors, including the Advanced Scatterometer (ASCAT), the Soil Moisture Ocean Salinity (SMOS) mission, the Advanced Microwave Scanning Radiometer for Earth Observation System (AMSR-E) and a merged VOD data set from various passive microwave sensors. VOD data were compared against FLUXCOM GPP and Solar-Induced chlorophyll Fluorescence (SIF) from the Global Ozone Monitoring Experiment-2 (GOME-2). FLUXCOM GPP estimates are based on the upscaling of flux tower GPP observations using optical satellite data, while SIF observations present a measure of photosynthetic activity and are often used as a proxy for GPP. For relating VOD to GPP, three variables were analyzed: original VOD time series, temporal changes in VOD (ΔVOD), and positive changes in VOD (ΔVOD≥0). Results show widespread positive correlations between VOD and GPP with some negative correlations mainly occurring in dry and wet regions for active and passive VOD, respectively. Correlations between VOD and GPP were similar or higher than between VOD and SIF. When comparing the three variables for relating VOD to GPP, correlations with GPP were higher for the original VOD time
NASA Astrophysics Data System (ADS)
Wu, X.; Xiao, X.; Zhang, Y.; Zhang, G.
2016-12-01
By offsetting one-third of anthropogenic carbon emissions, terrestrial carbon uptake mitigates atmospheric CO2 concentration and consequent global warming. However, the current global warming trend is inducing more climate extremes, which in turn cause large changes in terrestrial carbon uptake. Here we report the seasonal and regional anomalies of gross primary productivity (GPP) across the conterminous USA (CONUS) in response to two contrasting climate extremes: the cool and wet 2009 versus the warm and dry 2012. We used the Vegetation Photosynthesis Model (VPM, Xiao et al., 2006), MODIS images and NCEP/NARR climate data to estimate GPP from 2009-2014, and evaluated the VPM-predicted GPP with the estimated GPP from the CO2 eddy flux tower sites (24 sites). We analyze the correlation between the anomalies of the continental GPP and the anomalies of temperature and precipitation. The results show a substantial, negative GPP anomaly in 2009, in addition to the positive GPP anomaly in 2012, which was already reported in a previous study (Wolf et al., 2016). We also found that GPP anomalies of different climate regions in four seasons are controlled by either temperature or precipitation. Our study shows the robustness of the VPM to simulate GPP under the condition of climate extremes, and highlights the need of investigating the impacts of cooling events on the terrestrial carbon cycle. Our finding also suggests that there is no uniform pattern for terrestrial ecosystems responding to climate extremes, and that climate extremes should be studied in a case-by-case, location-based approach.
MODIS-Derived Terrestrial Primary Production
NASA Astrophysics Data System (ADS)
Zhao, Maosheng; Running, Steven; Heinsch, Faith Ann; Nemani, Ramakrishna
Temporal and spatial changes in terrestrial biological productivity have a large impact on humankind because terrestrial ecosystems not only create environments suitable for human habitation, but also provide materials essential for survival, such as food, fiber and fuel. A recent study estimated that consumption of terrestrial net primary production (NPP; a list of all the acronyms is available in the appendix at the end of the chapter) by the human population accounts for about 14-26% of global NPP (Imhoff et al. 2004). Rapid global climate change is induced by increased atmospheric greenhouse gas concentration, especially CO2, which results from human activities such as fossil fuel combustion and deforestation. This directly impacts terrestrial NPP, which continues to change in both space and time (Melillo et al. 1993; Prentice et al. 2001; Nemani et al. 2003), and ultimately impacts the well-being of human society (Milesi et al. 2005). Additionally, substantial evidence show that the oceans and the biosphere, especially terrestrial ecosystems, currently play a major role in reducing the rate of the atmospheric CO2 increase (Prentice et al. 2001; Schimel et al. 2001). NPP is the first step needed to quantify the amount of atmospheric carbon fixed by plants and accumulated as biomass. Continuous and accurate measurements of terrestrial NPP at the global scale are possible using satellite data. Since early 2000, for the first time, the MODIS sensors onboard the Terra and Aqua satellites, have operationally provided scientists with near real-time global terrestrial gross primary production (GPP) and net photosynthesis (PsnNet) data. These data are provided at 1 km spatial resolution and an 8-day interval, and annual NPP covers 109,782,756 km2 of vegetated land. These GPP, PsnNet and NPP products are collectively known as MOD17 and are part of a larger suite of MODIS land products (Justice et al. 2002), one of the core Earth System or Climate Data Records (ESDR or
NASA Astrophysics Data System (ADS)
Jin, C.; Xiao, X.; Wagle, P.
2014-12-01
Accurate estimation of crop Gross Primary Production (GPP) is important for food securityand terrestrial carbon cycle. Numerous publications have reported the potential of the satellite-based Production Efficiency Models (PEMs) to estimate GPP driven by in-situ climate data. Simulations of the PEMs often require surface reanalysis climate data as inputs, for example, the North America Regional Reanalysis datasets (NARR). These reanalysis datasets showed certain biases from the in-situ climate datasets. Thus, sensitivity analysis of the PEMs to the climate inputs is needed before their application at the regional scale. This study used the satellite-based Vegetation Photosynthesis Model (VPM), which is driven by solar radiation (R), air temperature (T), and the satellite-based vegetation indices, to quantify the causes and degree of uncertainties in crop GPP estimates due to different meteorological inputs at the 8-day interval (in-situ AmeriFlux data and NARR surface reanalysis data). The NARR radiation (RNARR) explained over 95% of the variability in in-situ RAF and TAF measured from AmeriFlux. The bais of TNARR was relatively small. However, RNARR had a systematical positive bias of ~3.5 MJ m-2day-1 from RAF. A simple adjustment based on the spatial statistic between RNARR and RAF produced relatively accurate radiation data for all crop site-years by reducing RMSE from 4 to 1.7 MJ m-2day-1. The VPM-based GPP estimates with three climate datasets (i.e., in-situ, and NARR before and after adjustment, GPPVPM,AF, GPPVPM,NARR, and GPPVPM,adjNARR) showed good agreements with the seasonal dynamics of crop GPP derived from the flux towers (GPPAF). The GPPVPM,AF differed from GPPAF by 2% for maize, and -8% to -12% for soybean on the 8-day interval. The positive bias of RNARR resulted in an overestimation of GPPVPM,NARR at both maize and soybean systems. However, GPPVPM,adjNARR significantly reduced the uncertainties of the maize GPP from 25% to 2%. The results from this
NASA Technical Reports Server (NTRS)
Walker, Anthony P.; Quaife, Tristan; Van Bodegom, Peter M.; De Kauwe, Martin G.; Keenan, Trevor F.; Joiner, Joanna; Lomas, Mark R.; MacBean, Natasha; Xu, Chongang; Yang, Xiaojuan;
2017-01-01
The maximum photosynthetic carboxylation rate (V (sub cmax)) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V(sub cmax) distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 petagrams of Carbon (PgC) per year, 65 percent of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27percent coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r equals 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V(sub cmax) variation in the field, particularly in northern latitudes.
NASA Astrophysics Data System (ADS)
Walker, Anthony P.; Carter, Kelsey R.; Gu, Lianhong; Hanson, Paul J.; Malhotra, Avni; Norby, Richard J.; Sebestyen, Stephen D.; Wullschleger, Stan D.; Weston, David J.
2017-05-01
Sphagnum mosses are the keystone species of peatland ecosystems. With rapid rates of climate change occurring in high latitudes, vast reservoirs of carbon accumulated over millennia in peatland ecosystems are potentially vulnerable to rising temperature and changing precipitation. We investigate the seasonal drivers of Sphagnum gross primary production (GPP)—the entry point of carbon into wetland ecosystems. Continuous flux measurements and flux partitioning show a seasonal cycle of Sphagnum GPP that peaked in the late summer, well after the peak in photosynthetically active radiation. Wavelet analysis showed that water table height was the key driver of weekly variation in Sphagnum GPP in the early summer and that temperature was the primary driver of GPP in the late summer and autumn. Flux partitioning and a process-based model of Sphagnum photosynthesis demonstrated the likelihood of seasonally dynamic maximum rates of photosynthesis and a logistic relationship between the water table and photosynthesizing tissue area when the water table was at the Sphagnum surface. The model also suggested that variability in internal resistance to CO2 transport, a function of Sphagnum water content, had minimal effect on GPP. To accurately model Sphagnum GPP, we recommend the following: (1) understanding seasonal photosynthetic trait variation and its triggers in Sphagnum; (2) characterizing the interaction of Sphagnum photosynthesizing tissue area with water table height; (3) modeling Sphagnum as a "soil" layer for consistent simulation of water dynamics; and (4) measurement of Sphagnum "canopy" properties: extinction coefficient (k), clumping (Ω), and maximum stem area index (SAI).
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%.
NASA Astrophysics Data System (ADS)
Carvalho, Matheus C.; Schulz, Kai G.; Eyre, Bradley D.
2017-06-01
New respiration (Rnew, of freshly fixated carbon) and old respiration (Rold, of storage carbon) were estimated for different regions of the global surface ocean using published data on simultaneous measurements of the following: (1) primary productivity using 14C (14PP); (2) gross primary productivity (GPP) based on 18O or O2; and (3) net community productivity (NCP) using O2. The ratio Rnew/GPP in 24 h incubations was typically between 0.1 and 0.3 regardless of depth and geographical area, demonstrating that values were almost constant regardless of large variations in temperature (0 to 27°C), irradiance (surface to 100 m deep), nutrients (nutrient-rich and nutrient-poor waters), and community composition (diatoms, flagellates, etc,). As such, between 10 and 30% of primary production in the surface ocean is respired in less than 24 h, and most respiration (between 55 and 75%) was of older carbon. Rnew was most likely associated with autotrophs, with minor contribution from heterotrophic bacteria. Patterns were less clear for Rold. Short 14C incubations are less affected by respiratory losses. Global oceanic GPP is estimated to be between 70 and 145 Gt C yr-1.
Varik, Vallo; Oliveira, Sofia Raquel Alves; Hauryliuk, Vasili; Tenson, Tanel
2017-09-08
Here we describe an HPLC-based method to quantify bacterial housekeeping nucleotides and the signaling messengers ppGpp and pppGpp. We have replicated and tested several previously reported HPLC-based approaches and assembled a method that can process 50 samples in three days, thus making kinetically resolved experiments feasible. The method combines cell harvesting by rapid filtration, followed by acid extraction, freeze-drying with chromatographic separation. We use a combination of C18 IPRP-HPLC (GMP unresolved and co-migrating with IMP; GDP and GTP; AMP, ADP and ATP; CTP; UTP) and SAX-HPLC in isocratic mode (ppGpp and pppGpp) with UV detection. The approach is applicable to bacteria without the requirement of metabolic labelling with 32P-labelled radioactive precursors. We applied our method to quantify nucleotide pools in Escherichia coli BW25113 K12-strain both throughout the growth curve and during acute stringent response induced by mupirocin. While ppGpp and pppGpp levels vary drastically (40- and ≥8-fold, respectively) these changes are decoupled from the quotients of the housekeeping pool and guanosine and adenosine housekeeping nucleotides: NTP/NDP/NMP ratio remains stable at 6/1/0.3 during both normal batch culture growth and upon acute amino acid starvation.
NASA Astrophysics Data System (ADS)
Wang, H.; Li, X.; Xiao, J.; Ma, M.
2017-12-01
Arid and semi-arid ecosystems cover more than one-third of the Earth's land surface, it is of great important to the global carbon cycle. However, the magnitude of carbon sequestration and its contribution to global atmospheric carbon cycle is poorly understood due to the worldwide paucity of measurements of carbon exchange in the arid ecosystems. Accurate and continuous monitoring the production of arid ecosystem is of great importance for regional carbon cycle estimation. The MOD17A2 product provides high frequency observations of terrestrial Gross Primary Productivity (GPP) over the world. Although there have been plenty of studies to validate the MODIS GPP products with ground based measurements over a range of biome types, few have comprehensively validated the performance of MODIS estimates in arid and semi-arid ecosystems. Thus, this study examined the performance of the MODIS-derived GPP comparing with the EC observed GPP at different timescales for the main arid ecosystems in the arid and semi-arid ecosystems in China, and optimized the performance of the MODIS GPP calculations by using the in-situ metrological forcing data, and optimization of biome-specific parameters with the Bayesian approach. Our result revealed that the MOD17 algorithm could capture the broad trends of GPP at 8-day time scales for all investigated sites on the whole. However, the GPP product was underestimated in most ecosystems in the arid region, especially the irrigated cropland and forest ecosystems, while the desert ecosystem was overestimated in the arid region. On the annual time scale, the best performance was observed in grassland and cropland, followed by forest and desert ecosystems. On the 8-day timescale, the RMSE between MOD17 products and in-situ flux observations of all sites was 2.22 gC/m2/d, and R2 was 0.69. By using the in-situ metrological data driven, optimizing the biome-based parameters of the algorithm, we improved the performances of the MODIS GPP calculation
Ogutu, Booker O; Dash, Jadunandan; Dawson, Terence P
2013-09-01
This article develops a new carbon exchange diagnostic model [i.e. Southampton CARbon Flux (SCARF) model] for estimating daily gross primary productivity (GPP). The model exploits the maximum quantum yields of two key photosynthetic pathways (i.e. C3 and C4 ) to estimate the conversion of absorbed photosynthetically active radiation into GPP. Furthermore, this is the first model to use only the fraction of photosynthetically active radiation absorbed by photosynthetic elements of the canopy (i.e. FAPARps ) rather than total canopy, to predict GPP. The GPP predicted by the SCARF model was comparable to in situ GPP measurements (R(2) > 0.7) in most of the evaluated biomes. Overall, the SCARF model predicted high GPP in regions dominated by forests and croplands, and low GPP in shrublands and dry-grasslands across USA and Europe. The spatial distribution of GPP from the SCARF model over Europe and conterminous USA was comparable to those from the MOD17 GPP product except in regions dominated by croplands. The SCARF model GPP predictions were positively correlated (R(2) > 0.5) to climatic and biophysical input variables indicating its sensitivity to factors controlling vegetation productivity. The new model has three advantages, first, it prescribes only two quantum yield terms rather than species specific light use efficiency terms; second, it uses only the fraction of PAR absorbed by photosynthetic elements of the canopy (FAPARps ) hence capturing the actual PAR used in photosynthesis; and third, it does not need a detailed land cover map that is a major source of uncertainty in most remote sensing based GPP models. The Sentinel satellites planned for launch in 2014 by the European Space Agency have adequate spectral channels to derive FAPARps at relatively high spatial resolution (20 m). This provides a unique opportunity to produce global GPP operationally using the Southampton CARbon Flux (SCARF) model at high spatial resolution. © 2013 John Wiley & Sons
Modeling the Impacts of Long-Term Warming Trends on Gross Primary Productivity Across North America
NASA Astrophysics Data System (ADS)
Mekonnen, Z. A.; Grant, R. F.
2014-12-01
There is evidence of warming over recent decades in most regions of North America (NA) that affects ecosystem productivity and the past decade has been the warmest since instrumental records of global surface temperatures began. In this study, we examined the spatial and temporal variability and trends of warming across NA using climate data from the North America Regional Reanalysis (NARR) from 1979 to 2010 with a 3-hourly time-step and 0.250 x 0.250 spatial resolution as part of the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). A comprehensive mathematical process model, ecosys was used to simulate impacts of this variability in warming on gross primary productivity (GPP). In a test of model results, annual GPP modeled for pixels which corresponded to the locations of 25 eddy covariance towers correlated well (R2=0.76) with annual GPP derived from the flux towers in 2005. At the continental scale long-term (2000 - 2010) annual average modeled GPP for NA correlated well (geographically weighed regression R2 = 0.8) with MODIS GPP, demonstrating close similarities in spatial patterns. Results from the NARR indicated that most areas of NA, particularly high latitude regions, have experienced warming but changes in precipitation vary spatially over the last three decades. GPP modeled in most areas with lower mean annual air temperature (Ta), such as those in boreal climate zones, increased due to early spring and late autumn warming observed in NARR. However modeled GPP declined in most southwestern regions of NA, due to water stress from rising Ta and declining precipitation. Overall, GPP modeled across NA had a positive trend of +0.025 P g C yr-1 with a range of -1.16 to 0.87 P g C yr-1 from the long-term mean. Interannual variability of GPP was the greatest in southwest of US and part of the Great Plains, which could be as a result of frequent El Niño-Southern Oscillation' (ENSO) events that led to major droughts.
NASA Astrophysics Data System (ADS)
Madani, Nima; Kimball, John S.; Running, Steven W.
2017-11-01
In the light use efficiency (LUE) approach of estimating the gross primary productivity (GPP), plant productivity is linearly related to absorbed photosynthetically active radiation assuming that plants absorb and convert solar energy into biomass within a maximum LUE (LUEmax) rate, which is assumed to vary conservatively within a given biome type. However, it has been shown that photosynthetic efficiency can vary within biomes. In this study, we used 149 global CO2 flux towers to derive the optimum LUE (LUEopt) under prevailing climate conditions for each tower location, stratified according to model training and test sites. Unlike LUEmax, LUEopt varies according to heterogeneous landscape characteristics and species traits. The LUEopt data showed large spatial variability within and between biome types, so that a simple biome classification explained only 29% of LUEopt variability over 95 global tower training sites. The use of explanatory variables in a mixed effect regression model explained 62.2% of the spatial variability in tower LUEopt data. The resulting regression model was used for global extrapolation of the LUEopt data and GPP estimation. The GPP estimated using the new LUEopt map showed significant improvement relative to global tower data, including a 15% R2 increase and 34% root-mean-square error reduction relative to baseline GPP calculations derived from biome-specific LUEmax constants. The new global LUEopt map is expected to improve the performance of LUE-based GPP algorithms for better assessment and monitoring of global terrestrial productivity and carbon dynamics.
Impacts of climate extremes on gross primary production under global warming
Williams, I. N.; Torn, M. S.; Riley, W. J.; ...
2014-09-24
The impacts of historical droughts and heat-waves on ecosystems are often considered indicative of future global warming impacts, under the assumption that water stress sets in above a fixed high temperature threshold. Historical and future (RCP8.5) Earth system model (ESM) climate projections were analyzed in this study to illustrate changes in the temperatures for onset of water stress under global warming. The ESMs examined here predict sharp declines in gross primary production (GPP) at warm temperature extremes in historical climates, similar to the observed correlations between GPP and temperature during historical heat-waves and droughts. However, soil moisture increases at themore » warm end of the temperature range, and the temperature at which soil moisture declines with temperature shifts to a higher temperature. The temperature for onset of water stress thus increases under global warming and is associated with a shift in the temperature for maximum GPP to warmer temperatures. Despite the shift in this local temperature optimum, the impacts of warm extremes on GPP are approximately invariant when extremes are defined relative to the optimal temperature within each climate period. The GPP sensitivity to these relative temperature extremes therefore remains similar between future and present climates, suggesting that the heat- and drought-induced GPP reductions seen recently can be expected to be similar in the future, and may be underestimates of future impacts given model projections of increased frequency and persistence of heat-waves and droughts. The local temperature optimum can be understood as the temperature at which the combination of water stress and light limitations is minimized, and this concept gives insights into how GPP responds to climate extremes in both historical and future climate periods. Both cold (temperature and light-limited) and warm (water-limited) relative temperature extremes become more persistent in future climate
Impacts of climate extremes on gross primary production under global warming
DOE Office of Scientific and Technical Information (OSTI.GOV)
Williams, I. N.; Torn, M. S.; Riley, W. J.
The impacts of historical droughts and heat-waves on ecosystems are often considered indicative of future global warming impacts, under the assumption that water stress sets in above a fixed high temperature threshold. Historical and future (RCP8.5) Earth system model (ESM) climate projections were analyzed in this study to illustrate changes in the temperatures for onset of water stress under global warming. The ESMs examined here predict sharp declines in gross primary production (GPP) at warm temperature extremes in historical climates, similar to the observed correlations between GPP and temperature during historical heat-waves and droughts. However, soil moisture increases at themore » warm end of the temperature range, and the temperature at which soil moisture declines with temperature shifts to a higher temperature. The temperature for onset of water stress thus increases under global warming and is associated with a shift in the temperature for maximum GPP to warmer temperatures. Despite the shift in this local temperature optimum, the impacts of warm extremes on GPP are approximately invariant when extremes are defined relative to the optimal temperature within each climate period. The GPP sensitivity to these relative temperature extremes therefore remains similar between future and present climates, suggesting that the heat- and drought-induced GPP reductions seen recently can be expected to be similar in the future, and may be underestimates of future impacts given model projections of increased frequency and persistence of heat-waves and droughts. The local temperature optimum can be understood as the temperature at which the combination of water stress and light limitations is minimized, and this concept gives insights into how GPP responds to climate extremes in both historical and future climate periods. Both cold (temperature and light-limited) and warm (water-limited) relative temperature extremes become more persistent in future climate
Satellite-based modeling of gross primary production in an evergreen needleleaf forest
Xiangming Xiao; David Hollinger; John Aber; Mike Goltz; Eric A. Davidson; Qingyuan Zhang; Berrien Moore III
2004-01-01
The eddy covariance technique provides valuable information on net ecosystem exchange (NEE) of CO2, between the atmosphere and terrestrial ecosystems, ecosystem respiration, and gross primary production (GPP) at a variety of C02 eddy flux tower sites. In this paper, we develop a new, satellite-based Vegetation Photosynthesis Model (VPM) to estimate the seasonal dynamcs...
NASA Astrophysics Data System (ADS)
Kim, J.; Ryu, Y.; Dechant, B.; Cho, S.; Kim, H. S.; Yang, K.
2017-12-01
The emerging technique of remotely sensed sun-induced fluorescence (SIF) has advanced our ability to estimate plant photosynthetic activity at regional and global scales. Continuous observations of SIF and gross primary productivity (GPP) at the canopy scale in evergreen needleleaf forests, however, have not yet been presented in the literature so far. Here, we report a time series of near-surface measurements of canopy-scale SIF, hyperspectral reflectance and GPP during the senescence period in an evergreen needleleaf forest in South Korea. Mean canopy height was 30 m and a hyperspectrometer connected with a single fiber and rotating prism, which measures bi-hemispheric irradiance, was installed 20 m above the canopy. SIF was retrieved in the spectral range 740-790 nm at a temporal resolution of 1 min. We tested different SIF retrieval methods, such as Fraunhofer line depth (FLD), spectral fitting method (SFM) and singular vector decomposition (SVD) against GPP estimated by eddy covariance and absorbed photosynthetically active radiation (APAR). We found that the SVD-retrieved SIF signal shows linear relationships with GPP (R2 = 0.63) and APAR (R2 = 0.52) while SFM- and FLD-retrieved SIF performed poorly. We suspect the larger influence of atmospheric oxygen absorption between the sensor and canopy might explain why SFM and FLD methods showed poor results. Data collection will continue and the relationships between SIF, GPP and APAR will be studied during the senescence period.
NASA Astrophysics Data System (ADS)
Barnes, M.; Moore, D. J.; Scott, R. L.; MacBean, N.; Ponce-Campos, G. E.; Breshears, D. D.
2017-12-01
Both satellite observations and eddy covariance estimates provide crucial information about the Earth's carbon, water and energy cycles. Continuous measurements from flux towers facilitate exploration of the exchange of carbon dioxide, water and energy between the land surface and the atmosphere at fine temporal and spatial scales, while satellite observations can fill in the large spatial gaps of in-situ measurements and provide long-term temporal continuity. The Southwest (Southwest United States and Northwest Mexico) and other semi-arid regions represent a key uncertainty in interannual variability in carbon uptake. Comparisons of existing global upscaled gross primary production (GPP) products with flux tower data at sites across the Southwest show widespread mischaracterization of seasonality in vegetation carbon uptake, resulting in large (up to 200%) errors in annual carbon uptake estimates. Here, remotely sensed and distributed meteorological inputs are used to upscale GPP estimates from 25 Ameriflux towers across the Southwest to the regional scale using a machine learning approach. Our random forest model incorporates two novel features that improve the spatial and temporal variability in GPP. First, we incorporate a multi-scalar drought index at multiple timescales to account for differential seasonality between ecosystem types. Second, our machine learning algorithm was trained on twenty five ecologically diverse sites to optimize both the monthly variability in and the seasonal cycle of GPP. The product and its components will be used to examine drought impacts on terrestrial carbon cycling across the Southwest including the effects of drought seasonality and on carbon uptake. Our spatially and temporally continuous upscaled GPP product drawing from both ground and satellite data over the Southwest region helps us understand linkages between the carbon and water cycles in semi-arid ecosystems and informs predictions of vegetation response to future
NASA Astrophysics Data System (ADS)
Halubok, M.; Yang, Z. L.
2016-12-01
This study investigates how gross primary production (GPP) estimates can be improved with the use of solar-induced chlorophyll fluorescence (SIF) and presents an effort to produce GPP predictions based on the interdependence between SIF, precipitation, soil moisture and GPP using Global Ozone Monitoring Experiment-2 (GOME-2), Tropical Rainfall Measuring Mission (TRMM), European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) datasets and FLUXNET observations. We found that considering the relationships between SIF, precipitation and soil moisture, isolating SIF-GPP relationships for different plant functional types (PFTs), and using precipitation and soil moisture conditions pertinent to the continental US provides the most accurate GPP estimates over the Great Plains and Texas. We found that there exists a lag between a precipitation event and corresponding fluorescence levels, ranging from about 2 weeks for grasses to a month for crops. Using these lead-lag relationships, we estimate GPP using SIF, precipitation and soil moisture data for two different PFTs (C3 non-arctic grass and crop) over the US applying the multiple linear regression technique. GPP values estimated from our lead-lag based SIF show the closest possible match with the observational data from the FLUXNET stations. During the drought 2011 year over Texas, our GPP values show a decrease by 100 gC/m2/month as compared to the reference year of 2007. In 2012 (drought year over the Great Plains), we observe significant decrease in GPP, especially in the area of high production (>500 gC/m2/month) that is reduced in July and August 2012. Hence, estimating GPP using specific SIF-GPP relationships, considering the differences in biomes and their interactions with precipitation and soil moisture pertinent to a certain region can detect the drought trends and produce reasonable GPP estimates. Thus, this simple and computationally efficient method based on derived linear equations can be
NASA Astrophysics Data System (ADS)
Lin, S.; Li, J.; Liu, Q.
2018-04-01
Satellite remote sensing data provide spatially continuous and temporally repetitive observations of land surfaces, and they have become increasingly important for monitoring large region of vegetation photosynthetic dynamic. But remote sensing data have their limitation on spatial and temporal scale, for example, higher spatial resolution data as Landsat data have 30-m spatial resolution but 16 days revisit period, while high temporal scale data such as geostationary data have 30-minute imaging period, which has lower spatial resolution (> 1 km). The objective of this study is to investigate whether combining high spatial and temporal resolution remote sensing data can improve the gross primary production (GPP) estimation accuracy in cropland. For this analysis we used three years (from 2010 to 2012) Landsat based NDVI data, MOD13 vegetation index product and Geostationary Operational Environmental Satellite (GOES) geostationary data as input parameters to estimate GPP in a small region cropland of Nebraska, US. Then we validated the remote sensing based GPP with the in-situ measurement carbon flux data. Results showed that: 1) the overall correlation between GOES visible band and in-situ measurement photosynthesis active radiation (PAR) is about 50 % (R2 = 0.52) and the European Center for Medium-Range Weather Forecasts ERA-Interim reanalysis data can explain 64 % of PAR variance (R2 = 0.64); 2) estimating GPP with Landsat 30-m spatial resolution data and ERA daily meteorology data has the highest accuracy(R2 = 0.85, RMSE < 3 gC/m2/day), which has better performance than using MODIS 1-km NDVI/EVI product import; 3) using daily meteorology data as input for GPP estimation in high spatial resolution data would have higher relevance than 8-day and 16-day input. Generally speaking, using the high spatial resolution and high frequency satellite based remote sensing data can improve GPP estimation accuracy in cropland.
NASA Astrophysics Data System (ADS)
Raj, Rahul; Hamm, Nicholas Alexander Samuel; van der Tol, Christiaan; Stein, Alfred
2016-03-01
Gross primary production (GPP) can be separated from flux tower measurements of net ecosystem exchange (NEE) of CO2. This is used increasingly to validate process-based simulators and remote-sensing-derived estimates of simulated GPP at various time steps. Proper validation includes the uncertainty associated with this separation. In this study, uncertainty assessment was done in a Bayesian framework. It was applied to data from the Speulderbos forest site, The Netherlands. We estimated the uncertainty in GPP at half-hourly time steps, using a non-rectangular hyperbola (NRH) model for its separation from the flux tower measurements. The NRH model provides a robust empirical relationship between radiation and GPP. It includes the degree of curvature of the light response curve, radiation and temperature. Parameters of the NRH model were fitted to the measured NEE data for every 10-day period during the growing season (April to October) in 2009. We defined the prior distribution of each NRH parameter and used Markov chain Monte Carlo (MCMC) simulation to estimate the uncertainty in the separated GPP from the posterior distribution at half-hourly time steps. This time series also allowed us to estimate the uncertainty at daily time steps. We compared the informative with the non-informative prior distributions of the NRH parameters and found that both choices produced similar posterior distributions of GPP. This will provide relevant and important information for the validation of process-based simulators in the future. Furthermore, the obtained posterior distributions of NEE and the NRH parameters are of interest for a range of applications.
A Global Study of GPP focusing on Light Use Efficiency in a Random Forest Regression Model
NASA Astrophysics Data System (ADS)
Fang, W.; Wei, S.; Yi, C.; Hendrey, G. R.
2016-12-01
Light use efficiency (LUE) is at the core of mechanistic modeling of global gross primary production (GPP). However, most LUE estimates in global models are satellite-based and coarsely measured with emphasis on environmental variables. Others are from eddy covariance towers with much greater spatial and temporal data quality and emphasis on mechanistic processes, but in a limited number of sites. In this paper, we conducted a comprehensive global study of tower-based LUE from 237 FLUXNET towers, and scaled up LUEs from in-situ tower level to global biome level. We integrated key environmental and biological variables into the tower-based LUE estimates, at 0.5o x 0.5o grid-cell resolution, using a random forest regression (RFR) approach. We then developed an RFR-LUE-GPP model using the grid-cell LUE data, and compared it to a tower-LUE-GPP model by the conventional way of treating LUE as a series of biome-specific constants. In order to calibrate the LUE models, we developed a data-driven RFR-GPP model using a random forest regression method. Our results showed that LUE varies largely with latitude. We estimated a global area-weighted average of LUE at 1.21 gC m-2 MJ-1 APAR, which led to an estimated global GPP of 102.9 Gt C /year from 2000 to 2005. The tower-LUE-GPP model tended to overestimate forest GPP in tropical and boreal regions. Large uncertainties exist in GPP estimates over sparsely vegetated areas covered by savannas and woody savannas around the middle to low latitudes (i.g. 20oS to 40oS and 5oN to 15oN) due to lack of available data. Model results were improved by incorporating Köppen climate types to represent climate /meteorological information in machine learning modeling. This shed new light on the recognized issues of climate dependence of spring onset of photosynthesis and the challenges in modeling the biome GPP of evergreen broad leaf forests (EBF) accurately. The divergent responses of GPP to temperature and precipitation at mid
NASA Technical Reports Server (NTRS)
Zhang, Yao; Xiao, Xiangming; Jin, Cui; Dong, Jinwei; Zhou, Sha; Wagle, Pradeep; Joiner, Joanna; Guanter, Luis; Zhang, Yongguang; Zhang , Geli;
2016-01-01
Accurate estimation of the gross primary production (GPP) of terrestrial ecosystems is vital for a better understanding of the spatial-temporal patterns of the global carbon cycle. In this study,we estimate GPP in North America (NA) using the satellite-based Vegetation Photosynthesis Model (VPM), MODIS (Moderate Resolution Imaging Spectrometer) images at 8-day temporal and 500 meter spatial resolutions, and NCEP-NARR (National Center for Environmental Prediction-North America Regional Reanalysis) climate data. The simulated GPP (GPP (sub VPM)) agrees well with the flux tower derived GPP (GPPEC) at 39 AmeriFlux sites (155 site-years). The GPP (sub VPM) in 2010 is spatially aggregated to 0.5 by 0.5-degree grid cells and then compared with sun-induced chlorophyll fluorescence (SIF) data from Global Ozone Monitoring Instrument 2 (GOME-2), which is directly related to vegetation photosynthesis. Spatial distribution and seasonal dynamics of GPP (sub VPM) and GOME-2 SIF show good consistency. At the biome scale, GPP (sub VPM) and SIF shows strong linear relationships (R (sup 2) is greater than 0.95) and small variations in regression slopes ((4.60-5.55 grams Carbon per square meter per day) divided by (milliwatts per square meter per nanometer per square radian)). The total annual GPP (sub VPM) in NA in 2010 is approximately 13.53 petagrams Carbon per year, which accounts for approximately 11.0 percent of the global terrestrial GPP and is within the range of annual GPP estimates from six other process-based and data-driven models (11.35-22.23 petagrams Carbon per year). Among the seven models, some models did not capture the spatial pattern of GOME-2 SIF data at annual scale, especially in Midwest cropland region. The results from this study demonstrate the reliable performance of VPM at the continental scale, and the potential of SIF data being used as a benchmark to compare with GPP models.
NASA Astrophysics Data System (ADS)
Chiwara, P.; Dash, J.; Ardö, J.; Ogutu, B. O.; Milton, E. J.; Saunders, M. J.; Nicolini, G.
2016-12-01
Accurate knowledge about the amount and dynamics of terrestrial gross primary productivity is an important component for understanding of ecosystem functioning and processes. Recently a new diagnostic model, Southampton Carbon Flux (SCARF), was developed to predict terrestrial gross primary productivity at regional to global scale based on a chlorophyll index derived from MERIS data. The model aims at mitigating some shortcomings in traditional light-use-efficiency based models by (i) using the fraction of photosynthetic active radiation absorbed only by the photosynthetic components of the canopy (FAPARps) and (ii) using the intrinsic quantum yields of C3 and C4 photosynthesis thereby reducing errors from land cover misclassification. Initial evaluation of the model in northern higher latitude ecosystems shows good agreement with in situ measurements. The current study calibrated and validated the model for a diversity of vegetation types across Africa in order to test its performance over a water limiting environment. The validation was based on GPP measurements from seven eddy flux towers across Africa. Sensitivity and uncertainty analyses were also performed to determine the importance of key biophysical and meteorological input parameters.Overall, modelled GPP values show good agreement with in situ measured GPP at most sites except tropical rainforest site. Mean daily GPP varied significantly across sites depending on the vegetation types and climate; from a minimum of -0.12 gC m2 day-1 for the semi-arid savannah to a maximum of 7.30 gC m2 day-1 for tropical rain forest ecosystems at Ankasa (Ghana). The model results have modest to very strong positive agreement with observed GPP at most sites (R2 values ranging from 0.60 for Skukuza in South Africa) and 0.85 for Mongu in Zambia) except tropical rain forest ecosystem (R2=0.34). Overall, the model has a stronger across-site coefficient of determination (R2=0.78) than MOD17 GPP product (R2=0.68). PAR and VPD
Sebestyen, Stephen D.; Norby, Richard J.; Hanson, Paul J.; ...
2017-04-18
Sphagnum mosses are the keystone species of peatland ecosystems. With rapid rates of climate change occurring in high latitudes, vast reservoirs of carbon accumulated over millennia in peatland ecosystems are potentially vulnerable to rising temperature and changing precipitation. We investigate the seasonal drivers of Sphagnum gross primary production (GPP)—the entry point of carbon into wetland ecosystems. Continuous flux measurements and flux partitioning show a seasonal cycle of Sphagnum GPP that peaked in the late summer, well after the peak in photosynthetically active radiation. Wavelet analysis showed that water table height was the key driver of weekly variation in Sphagnum GPPmore » in the early summer and that temperature was the primary driver of GPP in the late summer and autumn. Flux partitioning and a process-based model of Sphagnum photosynthesis demonstrated the likelihood of seasonally dynamic maximum rates of photosynthesis and a logistic relationship between the water table and photosynthesizing tissue area when the water table was at the Sphagnum surface. Here, the model also suggested that variability in internal resistance to CO 2 transport, a function of Sphagnum water content, had minimal effect on GPP. To accurately model Sphagnum GPP, we recommend the following: (1) understanding seasonal photosynthetic trait variation and its triggers in Sphagnum; (2) characterizing the interaction of Sphagnum photosynthesizing tissue area with water table height; (3) modeling Sphagnum as a “soil” layer for consistent simulation of water dynamics; and (4) measurement of Sphagnum “canopy” properties: extinction coefficient (k), clumping (Ω), and maximum stem area index (SAI).« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sebestyen, Stephen D.; Norby, Richard J.; Hanson, Paul J.
Sphagnum mosses are the keystone species of peatland ecosystems. With rapid rates of climate change occurring in high latitudes, vast reservoirs of carbon accumulated over millennia in peatland ecosystems are potentially vulnerable to rising temperature and changing precipitation. We investigate the seasonal drivers of Sphagnum gross primary production (GPP)—the entry point of carbon into wetland ecosystems. Continuous flux measurements and flux partitioning show a seasonal cycle of Sphagnum GPP that peaked in the late summer, well after the peak in photosynthetically active radiation. Wavelet analysis showed that water table height was the key driver of weekly variation in Sphagnum GPPmore » in the early summer and that temperature was the primary driver of GPP in the late summer and autumn. Flux partitioning and a process-based model of Sphagnum photosynthesis demonstrated the likelihood of seasonally dynamic maximum rates of photosynthesis and a logistic relationship between the water table and photosynthesizing tissue area when the water table was at the Sphagnum surface. Here, the model also suggested that variability in internal resistance to CO 2 transport, a function of Sphagnum water content, had minimal effect on GPP. To accurately model Sphagnum GPP, we recommend the following: (1) understanding seasonal photosynthetic trait variation and its triggers in Sphagnum; (2) characterizing the interaction of Sphagnum photosynthesizing tissue area with water table height; (3) modeling Sphagnum as a “soil” layer for consistent simulation of water dynamics; and (4) measurement of Sphagnum “canopy” properties: extinction coefficient (k), clumping (Ω), and maximum stem area index (SAI).« less
NASA Astrophysics Data System (ADS)
Doughty, R.; Xiao, X.; Qin, Y.; Wu, X.; Zhang, Y.; Zou, Z.; Bajgain, R.; Zhou, Y.; Basara, J. B.; McCarthy, H. R.; Friedman, J. R.
2017-12-01
To accurately estimate carbon cycling and food production, it is essential to understand how gross primary production (GPP) of irrigated and non-irrigated grasslands and croplands respond to drought and pluvial conditions. Oklahoma experienced extreme drought in 2011 and record-breaking precipitation in 2015, thus providing an opportunity to study such changes in GPP of grasslands and croplands. This study analyzes annual GPP of irrigation-permitted and non-permitted grasslands, winter wheat, other C3 croplands, and C4 croplands in Caddo County of western Oklahoma from 2010 through 2016. For each land class, annual GPP from the 2011 drought and pluvial 2015 were compared with the combined, 5-year mean GPP from the other years of the study period. The results show that for the 2011 drought: 1) non-permitted C4 croplands had the largest percentage decrease (-41%) in GPP from the 5-year mean, but irrigation-permitted C4 croplands had no significant decrease; 2) GPP was significantly lower than the 5-year mean for all non-C4 vegetation types, regardless of water rights; 3) non-permitted lands were more sensitive to drought than irrigation-permitted lands, except for grasslands, which had similar percentage reductions in GPP (-35%). Results for the pluvial year 2015 indicate that: 1) GPP was significantly higher for grasslands, winter wheat, and non-permitted C3 croplands than the 5-year mean; 2) there was no significant difference in GPP for irrigation-permitted C3 croplands or non-permitted C4 croplands; 3) GPP for C4 irrigation-permitted croplands was 9% lower than the 5-year mean.
Investigating smoke's influence on primary production throughout the Amazon
NASA Astrophysics Data System (ADS)
Flanner, M. G.; Mahowald, N. M.; Zender, C. S.; Randerson, J. T.; Tosca, M. G.
2007-12-01
Smoke from annual burning in the Amazon causes large reduction in surface insolation and increases the diffuse fraction of photosynthetically-active radiation (PAR). These effects have competing influence on gross primary production (GPP). Recent studies indicate that the sign of net influence depends on aerosol optical depth, but the magnitude of smoke's effect on continental-scale carbon cycling is very poorly constrained and may constitute an important term of fire's net impact on carbon storage. To investigate widespread effects of Amazon smoke on surface radiation properties, we apply a version of the NCAR Community Atmosphere Model with prognostic aerosol transport, driven with re-analysis winds. Carbon aerosol emissions are derived from the Global Fire Emissions Database (GFED). We use AERONET observations to identify model biases in aerosol optical depth, single-scatter albedo, and surface radiative forcing, and prescribe new aerosol optical properties based on field observations to improve model agreement with AERONET data. Finally, we quantify a potential range of smoke-induced change in large-scale GPP based on: 1) ground measurements of GPP in the Amazon as a function of aerosol optical depth and diffuse fraction of PAR, and 2) empirical functions of ecosystem-scale photosynthesis rates currently employed in models such as the Community Land Model (CLM).
Reimer, Janet J; Vargas, Rodrigo; Rivas, David; Gaxiola-Castro, Gilberto; Hernandez-Ayon, J Martin; Lara-Lara, Ruben
2015-01-01
Some land and ocean processes are related through connections (and synoptic-scale teleconnections) to the atmosphere. Synoptic-scale atmospheric (El Niño/Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO], and North Atlantic Oscillation [NAO]) decadal cycles are known to influence the global terrestrial carbon cycle. Potentially, smaller scale land-ocean connections influenced by coastal upwelling (changes in sea surface temperature) may be important for local-to-regional water-limited ecosystems where plants may benefit from air moisture transported from the ocean to terrestrial ecosystems. Here we use satellite-derived observations to test potential connections between changes in sea surface temperature (SST) in regions with strong coastal upwelling and terrestrial gross primary production (GPP) across the Baja California Peninsula. This region is characterized by an arid/semiarid climate along the southern California Current. We found that SST was correlated with the fraction of photosynthetic active radiation (fPAR; as a proxy for GPP) with lags ranging from 0 to 5 months. In contrast ENSO was not as strongly related with fPAR as SST in these coastal ecosystems. Our results show the importance of local-scale changes in SST during upwelling events, to explain the variability in GPP in coastal, water-limited ecosystems. The response of GPP to SST was spatially-dependent: colder SST in the northern areas increased GPP (likely by influencing fog formation), while warmer SST at the southern areas was associated to higher GPP (as SST is in phase with precipitation patterns). Interannual trends in fPAR are also spatially variable along the Baja California Peninsula with increasing secular trends in subtropical regions, decreasing trends in the most arid region, and no trend in the semi-arid regions. These findings suggest that studies and ecosystem process based models should consider the lateral influence of local-scale ocean processes that could
Reimer, Janet J.; Vargas, Rodrigo; Rivas, David; Gaxiola-Castro, Gilberto; Hernandez-Ayon, J. Martin; Lara-Lara, Ruben
2015-01-01
Some land and ocean processes are related through connections (and synoptic-scale teleconnections) to the atmosphere. Synoptic-scale atmospheric (El Niño/Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO], and North Atlantic Oscillation [NAO]) decadal cycles are known to influence the global terrestrial carbon cycle. Potentially, smaller scale land-ocean connections influenced by coastal upwelling (changes in sea surface temperature) may be important for local-to-regional water-limited ecosystems where plants may benefit from air moisture transported from the ocean to terrestrial ecosystems. Here we use satellite-derived observations to test potential connections between changes in sea surface temperature (SST) in regions with strong coastal upwelling and terrestrial gross primary production (GPP) across the Baja California Peninsula. This region is characterized by an arid/semiarid climate along the southern California Current. We found that SST was correlated with the fraction of photosynthetic active radiation (fPAR; as a proxy for GPP) with lags ranging from 0 to 5 months. In contrast ENSO was not as strongly related with fPAR as SST in these coastal ecosystems. Our results show the importance of local-scale changes in SST during upwelling events, to explain the variability in GPP in coastal, water-limited ecosystems. The response of GPP to SST was spatially-dependent: colder SST in the northern areas increased GPP (likely by influencing fog formation), while warmer SST at the southern areas was associated to higher GPP (as SST is in phase with precipitation patterns). Interannual trends in fPAR are also spatially variable along the Baja California Peninsula with increasing secular trends in subtropical regions, decreasing trends in the most arid region, and no trend in the semi-arid regions. These findings suggest that studies and ecosystem process based models should consider the lateral influence of local-scale ocean processes that could
NASA Astrophysics Data System (ADS)
Cooper, L. Annie; Ballantyne, Ashley P.; Holden, Zachary A.; Landguth, Erin L.
2017-04-01
Forest disturbances influence forest structure, composition, and function and may impact climate through changes in net radiation or through shifts in carbon exchange. Climate impacts vary depending on environmental variables and disturbance characteristics, yet few studies have investigated disturbance impacts over large, environmentally heterogeneous, regions. We used satellite data to objectively determine the impacts of fire, bark beetles, defoliators, and "unidentified disturbances" (UDs) on land surface temperature (LST) and gross primary productivity (GPP) across the western United States (U.S.). We investigated immediate disturbance impacts, the drivers of those impacts, and long-term postdisturbance LST and GPP recovery patterns. All disturbance types caused LST increases (°C; fire: 3.45 ± 3.02, bark beetles: 0.76 ± 3.04, defoliators: 0.49 ± 3.12, and UD: 0.76 ± 3.03). Fire and insects resulted in GPP declines (%; fire: -25.05 ± 21.67, bark beetles: -2.84 ± 21.06, defoliators: -0.23 ± 15.40), while UDs resulted in slightly enhanced GPP (1.89 ± 24.20%). Disturbance responses also varied between ecoregions. Severity and interannual changes in air temperature were the primary drivers of short-term disturbance responses, and severity also had a strong impact on long-term recovery patterns. These results suggest a potential climate feedback due to disturbance-induced biophysical changes that may strengthen as disturbance regimes shift due to climate change.
NASA Technical Reports Server (NTRS)
Cui, Yaoping; Xiao, Xiangmin; Zhang, Yao; Dong, Jinwei; Qin, Yuanwei; Doughty, Russell B.; Zhang, Geli; Wang, Jie; Wu, Xiaocui; Qin, Yaochen;
2017-01-01
The gross primary production (GPP) of vegetation in urban areas plays an important role in the study of urban ecology. It is difficult however, to accurately estimate GPP in urban areas, mostly due to the complexity of impervious land surfaces, buildings, vegetation, and management. Recently, we used the Vegetation Photosynthesis Model (VPM), climate data, and satellite images to estimate the GPP of terrestrial ecosystems including urban areas. Here, we report VPM-based GPP (GPPvpm) estimates for the world's ten most populous megacities during 2000-2014. The seasonal dynamics of GPPvpm during 2007-2014 in the ten megacities track well that of the solar-induced chlorophyll fluorescence (SIF) data from GOME-2 at 0.5deg x 0.5deg resolution. Annual GPPvpm during 2000-2014 also shows substantial variation among the ten megacities, and year-to-year trends show increases, no change, and decreases. Urban expansion and vegetation collectively impact GPP variations in these megacities. The results of this study demonstrate the potential of a satellite-based vegetation photosynthesis model for diagnostic studies of GPP and the terrestrial carbon cycle in urban areas.
NASA Astrophysics Data System (ADS)
Brilli, L.; Chiesi, M.; Maselli, F.; Moriondo, M.; Gioli, B.; Toscano, P.; Zaldei, A.; Bindi, M.
2013-08-01
We developed and tested a methodology to estimate olive (Olea europaea L.) gross primary production (GPP) combining ground and multi-sensor satellite data. An eddy-covariance station placed in an olive grove in central Italy provided carbon and water fluxes over two years (2010-2011), which were used as reference to evaluate the performance of a GPP estimation methodology based on a Monteith type model (modified C-Fix) and driven by meteorological and satellite (NDVI) data. A major issue was related to the consideration of the two main olive grove components, i.e. olive trees and inter-tree ground vegetation: this issue was addressed by the separate simulation of carbon fluxes within the two ecosystem layers, followed by their recombination. In this way the eddy covariance GPP measurements were successfully reproduced, with the exception of two periods that followed tillage operations. For these periods measured GPP could be approximated by considering synthetic NDVI values which simulated the expected response of inter-tree ground vegetation to tillages.
USDA-ARS?s Scientific Manuscript database
To accurately estimate carbon cycling and food production, it is essential to understand how gross primary production (GPP) of irrigated and non-irrigated grasslands and croplands respond to drought and pluvial events. Oklahoma experienced extreme drought in 2011 and record-breaking precipitation in...
Zhang, Fang-Min; Ju, Wei-Min; Chen, Jing-Ming; Wang, Shao-Qiang; Yu, Gui-Rui; Han, Shi-Jie
2012-02-01
Based on the bi-linearly interpolated meteorological reanalysis data from National Centers for Environmental Prediction, USA and by using the leaf area index data derived from the GIMMS NDVI to run the process-based Boreal Ecosystems Productivity Simulator (BEPS) model, this paper simulated and analyzed the spatiotemporal characteristics of the terrestrial ecosystem gross primary productivity (GPP) and net primary productivity (NPP) in East Asia in 2000-2005. Before regional simulating and calculating, the observation GPP data of different terrestrial ecosystem in 15 experimental stations of AsiaFlux network and the inventory measurements of NPP at 1300 sampling sites were applied to validate the BEPS GPP and NPP. The results showed that BEPS could well simulate the changes in GPP and NPP of different terrestrial ecosystems, with the R2 ranging from 0.86 to 0.99 and the root mean square error (RMSE) from 0.2 to 1.2 g C x m(-2) x d(-1). The simulated values by BEPS could explain 78% of the changes in annual NPP, and the RMSE was 118 g C x m(-2) x a(-1). In 2000-2005, the averaged total GPP and total NPP of the terrestrial ecosystems in East Asia were 21.7 and 10.5 Pg C x a(-1), respectively, and the GPP and NPP exhibited similar spatial and temporal variation patterns. During the six years, the total NPP of the terrestrial ecosystems varied from 10.2 to 10.7 Pg C x a(-1), with a coefficient of variation being 2. 2%. High NPP (above 1000 g C x m(-2) x a(-1)) occurred in the southeast island countries, while low NPP (below 30 g C x m(-2) x a(-1)) occurred in the desert area of Northwest China. The spatial patterns of NPP were mainly attributed to the differences in the climatic variables across East Asia. The NPP per capita also varied greatly among different countries, which was the highest (70217 kg C x a(-1)) in Mongolia, far higher than that (1921 kg C x a(-1)) in China, and the lowest (757 kg C x a(-1)) in India.
USDA-ARS?s Scientific Manuscript database
The utilization of remotely sensed observations for light use efficiency (LUE) and tower-based gross primary production (GPP) estimates was studied in a USDA cornfield. Nadir hyperspectral reflectance measurements were acquired at canopy level during a collaborative field campaign conducted in four ...
Patterns of NPP, GPP, respiration, and NEP during boreal forest succession
Goulden, M.L.; Mcmillan, A.M.S.; Winston, G.C.; Rocha, A.V.; Manies, K.L.; Harden, J.W.; Bond-Lamberty, B. P.
2011-01-01
We combined year-round eddy covariance with biometry and biomass harvests along a chronosequence of boreal forest stands that were 1, 6, 15, 23, 40, 74, and 154 years old to understand how ecosystem production and carbon stocks change during recovery from stand-replacing crown fire. Live biomass (Clive) was low in the 1 and 6 year old stands, and increased following a logistic pattern to high levels in the 74 and 154year old stands. Carbon stocks in the forest floor (Cforest floor) and coarse woody debris (CCWD) were comparatively high in the 1year old stand, reduced in the 6 through 40year old stands, and highest in the 74 and 154year old stands. Total net primary production (TNPP) was reduced in the 1 and 6year old stands, highest in the 23 through 74year old stands and somewhat reduced in the 154year old stand. The NPP decline at the 154year old stand was related to increased autotrophic respiration rather than decreased gross primary production (GPP). Net ecosystem production (NEP), calculated by integrated eddy covariance, indicated the 1 and 6 year old stands were losing carbon, the 15year old stand was gaining a small amount of carbon, the 23 and 74year old stands were gaining considerable carbon, and the 40 and 154year old stands were gaining modest amounts of carbon. The recovery from fire was rapid; a linear fit through the NEP observations at the 6 and 15year old stands indicated the transition from carbon source to sink occurred within 11-12 years. The NEP decline at the 154year old stand appears related to increased losses from Clive by tree mortality and possibly from Cforest floor by decomposition. Our findings support the idea that NPP, carbon production efficiency (NPP/GPP), NEP, and carbon storage efficiency (NEP/TNPP) all decrease in old boreal stands. ?? 2010 Blackwell Publishing Ltd.
Ma, Jun; Xiao, Xiangming; Zhang, Yao; Doughty, Russell; Chen, Bangqian; Zhao, Bin
2018-10-15
Accurately estimating spatial-temporal patterns of gross primary production (GPP) is important for the global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatial-temporal dynamics of GPP. However, the accuracy assessment of GPP simulations from LUE models at both spatial and temporal scales remains a challenge. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images with 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPP VPM ) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPP VPM and SIF data over a single year (2010) and multiple years (2007-2014) in most areas of China. GPP VPM is also significantly positive correlated with GOME-2 SIF (R 2 > 0.43) spatially for seasonal scales. However, poor consistency was detected between GPP VPM and SIF data at yearly scale. GPP dynamic trends have high spatial-temporal variation in China during 2007-2014. Temperature, leaf area index (LAI), and precipitation are the most important factors influence GPP VPM in the regions of East Qinghai-Tibet Plateau, Loss Plateau, and Southwestern China, respectively. The results of this study indicate that GPP VPM is temporally and spatially in line with GOME-2 SIF data, and space-borne SIF data have great potential for evaluating LUE-based GPP models. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Moore, Caitlin E.; Beringer, Jason; Evans, Bradley; Hutley, Lindsay B.; Tapper, Nigel J.
2017-01-01
The coexistence of trees and grasses in savanna ecosystems results in marked phenological dynamics that vary spatially and temporally with climate. Australian savannas comprise a complex variety of life forms and phenologies, from evergreen trees to annual/perennial grasses, producing a boom-bust seasonal pattern of productivity that follows the wet-dry seasonal rainfall cycle. As the climate changes into the 21st century, modification to rainfall and temperature regimes in savannas is highly likely. There is a need to link phenology cycles of different species with productivity to understand how the tree-grass relationship may shift in response to climate change. This study investigated the relationship between productivity and phenology for trees and grasses in an Australian tropical savanna. Productivity, estimated from overstory (tree) and understory (grass) eddy covariance flux tower estimates of gross primary productivity (GPP), was compared against 2 years of repeat time-lapse digital photography (phenocams). We explored the phenology-productivity relationship at the ecosystem scale using Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and flux tower GPP. These data were obtained from the Howard Springs OzFlux/Fluxnet site (AU-How) in northern Australia. Two greenness indices were calculated from the phenocam images: the green chromatic coordinate (GCC) and excess green index (ExG). These indices captured the temporal dynamics of the understory (grass) and overstory (trees) phenology and were correlated well with tower GPP for understory (r2 = 0.65 to 0.72) but less so for the overstory (r2 = 0.14 to 0.23). The MODIS enhanced vegetation index (EVI) correlated well with GPP at the ecosystem scale (r2 = 0.70). Lastly, we used GCC and EVI to parameterise a light use efficiency (LUE) model and found it to improve the estimates of GPP for the overstory, understory and ecosystem. We conclude that phenology is an important parameter to
NASA Astrophysics Data System (ADS)
Saberi, S. J.; Weathers, K. C.; Norouzi, H.; Prakash, S.; Solomon, C.; Boucher, J. M.
2016-12-01
Lakes contribute to local and regional climate conditions, cycle nutrients, and are viable indicators of climate change due to their sensitivity to disturbances in their water and airsheds. Utilizing spaceborne remote sensing (RS) techniques has considerable potential in studying lake dynamics because it allows for coherent and consistent spatial and temporal observations as well as estimates of lake functions without in situ measurements. However, in order for RS products to be useful, algorithms that relate in situ measurements to RS data must be developed. Estimates of lake metabolic rates are of particular scientific interest since they are indicative of lakes' roles in carbon cycling and ecological function. Currently, there are few existing algorithms relating remote sensing products to in-lake estimates of metabolic rates and more in-depth studies are still required. Here we use satellite surface temperature observations from Moderate Resolution Imaging Spectroradiometer (MODIS) product (MYD11A2) and published in-lake gross primary production (GPP) estimates for eleven globally distributed lakes during a one-year period to produce a univariate quadratic equation model. The general model was validated using other lakes during an equivalent one-year time period (R2=0.76). The statistical analyses reveal significant positive relationships between MODIS temperature data and the previously modeled in-lake GPP. Lake-specific models for Lake Mendota (USA), Rotorua (New Zealand), and Taihu (China) showed stronger relationships than the general combined model, pointing to local influences such as watershed characteristics on in-lake GPP in some cases. These validation data suggest that the developed algorithm has a potential to predict lake GPP on a global scale.
USDA-ARS?s Scientific Manuscript database
To accurately estimate carbon cycling and food production, it is essential to understand how gross primary production (GPP) of irrigated and non-irrigated grasslands and croplands respond to drought and pluvial events. Oklahoma experienced extreme drought in 2011 and record-breaking precipitation in...
NASA Astrophysics Data System (ADS)
Samal, N. R.; Pierson, D. C.; Staehr, P. A.; Pradhanang, S. M.; Smith, D. G.
2013-12-01
Episodic inputs of dissolved and particulate material during storm events can have important effects on lake and reservoir ecosystem function and also impact reservoir drinking water quality. We evaluate the impacts of storm events using vertical profiles of temperature, dissolved oxygen, turbidity, conductivity and chlorophyll automatically collected at 6 hour intervals in Ashokan Reservoir, which is a part of the New York City drinking water supply. Storm driven inputs to the reservoir periodically result in large input of suspended sediments that result in reservoir turbidity levels exceeding 25 NTU, and substantial reductions in the euphotic depth. Dissolved materials associated with these same storms would be expected to stimulate bacterial production. This study involves the use of a conceptual model to calculate depth specific estimates of gross primary production (GPP) and ecosystem respiration (R) using three years of data that included 777 events that increased reservoir turbidity levels to over 25 NTU. Using data from before, during and after storm events, we examine how the balance between GPP and R is influenced by storm related increases in turbidity and dissolved organic matter, which would in turn influence light attenuation and bacterial production. Key words: metabolism, primary production, GPP, respiration, euphotic depth, storm event, reservoir
The Potential of Carbonyl Sulfide as a Tracer for Gross Primary Productivity at Flux Tower Sites
USDA-ARS?s Scientific Manuscript database
Regional/continental scale studies of atmospheric carbonyl sulfide (OCS) seasonal dynamics and leaf level studies of plant OCS uptake have shown a close relationship to CO2 dynamics and uptake, suggesting potential for OCS as a tracer for gross primary productivity (GPP). Canopy CO2 and OCS differen...
NASA Astrophysics Data System (ADS)
Han, J.; Zhang, L.; Li, S.
2017-12-01
The mid-subtropical forests in East Asia monsoon zone act as an important carbon sink. Planted coniferous forests are important vegetation types in this area. However, we lack an in-depth understanding of both controlling mechanisms of environmental and biotic factors in gross primary productivity (GPP) and their timescale effects. Based on eddy covariance carbon flux data and micro-meteorological data (2003-2015) observed at a mid-subtropical planted coniferous forest in Qianyanzhou, along with leaf area index derived from MODIS products, we used the path analysis mothed to quantify standardized total effects (STE) of environmental factors on GPP and their variabilities at different timescales. We found that GPP was mainly affected by photosynthetically active radiation (PAR) at half-hour scale. Furthermore, GPP under cloudy weather conditions was greater than under sunny weather conditions across seasons. From daily to yearly scales, PAR had the positive STE with GPP, but such STE was gradually reduced toward yearly scale; diffuse radiation or air temperature had the positive STE with GPP at daily and monthly scales, while negative STE occurred at seasonal and yearly scales. Vapor pressure deficit exhibited the negative STE with GPP at all timescales, and such STE increased gradually toward the yearly scale. Therefore, on one hand, GPP was controlled by light conditions, but on the other hand, high air temperature in summer and water availability had a significant restraining effect over GPP, and such effect increased with the timescales from day to year. Based on the simulation results by the light use efficiency (LUE) model, it indicated that modelled GPP agreed well with the measurements when the influence of the seasonal variations of LUE and diffuse radiation were incorporated into the model, especially at the yearly scale. This further indicated that diffuse radiation, together with changes in air temperature and water supply, had a significant effect on
Novel pppGpp binding site at the C-terminal region of the Rel enzyme from Mycobacterium smegmatis.
Syal, Kirtimaan; Joshi, Himanshu; Chatterji, Dipankar; Jain, Vikas
2015-10-01
Mycobacterium tuberculosis elicits the stringent response under unfavorable growth conditions, such as those encountered by the pathogen inside the host. The hallmark of this response is production of guanosine tetra- and pentaphosphates, collectively termed (p)ppGpp, which have pleiotropic effects on the bacterial physiology. As the stringent response is connected to survival under stress, it is now being targeted for developing inhibitors against bacterial persistence. The Rel enzyme in mycobacteria has two catalytic domains at its N-terminus that are involved in the synthesis and hydrolysis of (p)ppGpp, respectively. However, the function of the C-terminal region of the protein remained unknown. Here, we have identified a binding site for pppGpp in the C-terminal region of Rel. The binding affinity of pppGpp was quantified by isothermal titration calorimetry. The binding site was determined by crosslinking using the nucleotide analog azido-pppGpp, and examining the crosslink product by mass spectrometry. Additionally, mutations in the Rel protein were created to confirm the site of pppGpp binding by isothermal titration calorimetry. These mutants showed increased pppGpp synthesis and reduced hydrolytic activity. We believe that binding of pppGpp to Rel provides a feedback mechanism that allows the protein to detect and adjust the (p)ppGpp level in the cell. Our work suggests that such sites should also be considered while designing inhibitors to target the stringent response. © 2015 FEBS.
NASA Astrophysics Data System (ADS)
van Leth, Thomas C.; Verstraeten, Willem W.; Sanders, Abram F. J.
2014-05-01
Mapping terrestrial chlorophyll fluorescence is a crucial activity to obtain information on the functional status of vegetation and to improve estimates of light-use efficiency (LUE) and global primary productivity (GPP). GPP quantifies carbon fixation by plant ecosystems and is therefore an important parameter for budgeting terrestrial carbon cycles. Satellite remote sensing offers an excellent tool for investigating GPP in a spatially explicit fashion across different scales of observation. The GPP estimates, however, still remain largely uncertain due to biotic and abiotic factors that influence plant production. Sun-induced fluorescence has the ability to enhance our knowledge on how environmentally induced changes affect the LUE. This can be linked to optical derived remote sensing parameters thereby reducing the uncertainty in GPP estimates. Satellite measurements provide a relatively new perspective on global sun-induced fluorescence, enabling us to quantify spatial distributions and changes over time. Techniques have recently been developed to retrieve fluorescence emissions from hyperspectral satellite measurements. We use data from the Global Ozone Monitoring Instrument 2 (GOME2) to infer terrestrial fluorescence. The spectral signatures of three basic components atmospheric: absorption, surface reflectance, and fluorescence radiance are separated using reference measurements of non-fluorescent surfaces (desserts, deep oceans and ice) to solve for the atmospheric absorption. An empirically based principal component analysis (PCA) approach is applied similar to that of Joiner et al. (2013, ACP). Here we show our first global maps of the GOME2 retrievals of chlorophyll fluorescence. First results indicate fluorescence distributions that are similar with that obtained by GOSAT and GOME2 as reported by Joiner et al. (2013, ACP), although we find slightly higher values. In view of optimizing the fluorescence retrieval, we will show the effect of the references
Liu, Dan; Cai, Wenwen; Xia, Jiangzhou; Dong, Wenjie; Zhou, Guangsheng; Chen, Yang; Zhang, Haicheng; Yuan, Wenping
2014-01-01
Gross Primary Production (GPP) is the largest flux in the global carbon cycle. However, large uncertainties in current global estimations persist. In this study, we examined the performance of a process-based model (Integrated BIosphere Simulator, IBIS) at 62 eddy covariance sites around the world. Our results indicated that the IBIS model explained 60% of the observed variation in daily GPP at all validation sites. Comparison with a satellite-based vegetation model (Eddy Covariance-Light Use Efficiency, EC-LUE) revealed that the IBIS simulations yielded comparable GPP results as the EC-LUE model. Global mean GPP estimated by the IBIS model was 107.50±1.37 Pg C year(-1) (mean value ± standard deviation) across the vegetated area for the period 2000-2006, consistent with the results of the EC-LUE model (109.39±1.48 Pg C year(-1)). To evaluate the uncertainty introduced by the parameter Vcmax, which represents the maximum photosynthetic capacity, we inversed Vcmax using Markov Chain-Monte Carlo (MCMC) procedures. Using the inversed Vcmax values, the simulated global GPP increased by 16.5 Pg C year(-1), indicating that IBIS model is sensitive to Vcmax, and large uncertainty exists in model parameterization.
Benthic Light Availability Improves Predictions of Riverine Primary Production
NASA Astrophysics Data System (ADS)
Kirk, L.; Cohen, M. J.
2017-12-01
Light is a fundamental control on photosynthesis, and often the only control strongly correlated with gross primary production (GPP) in streams and rivers; yet it has received far less attention than nutrients. Because benthic light is difficult to measure in situ, surrogates such as open sky irradiance are often used. Several studies have now refined methods to quantify canopy and water column attenuation of open sky light in order to estimate the amount of light that actually reaches the benthos. Given the additional effort that measuring benthic light requires, we should ask if benthic light always improves our predictions of GPP compared to just open sky irradiance. We use long-term, high-resolution dissolved oxygen, turbidity, dissolved organic matter (fDOM), and irradiance data from streams and rivers in north-central Florida, US across gradients of size and color to build statistical models of benthic light that predict GPP. Preliminary results on a large, clear river show only modest model improvements over open sky irradiance, even in heavily canopied reaches with pulses of tannic water. However, in another spring-fed river with greater connectivity to adjacent wetlands - and hence larger, more frequent pulses of tannic water - the model improved dramatically with the inclusion of fDOM (model R2 improved from 0.28 to 0.68). River shade modeling efforts also suggest that knowing benthic light will greatly enhance our ability to predict GPP in narrower, forested streams flowing in particular directions. Our objective is to outline conditions where an assessment of benthic light conditions would be necessary for riverine metabolism studies or management strategies.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wagle, Pradeep; Xiao, Xiangming; Torn, Margaret S.
2014-09-01
Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index, LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production (GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled GPP (GPPVPM) was compared withmore » the GPP (GPPEC) derived from eddy covariance measurements. Precipitation at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006), while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function (Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal dynamics of GPPVPM agreed reasonably well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.« less
Marotta, H; Enrich-Prast, A
2015-11-01
Dredging is a catastrophic disturbance that directly affects key biological processes in aquatic ecosystems, especially in those small and shallow. In the tropics, metabolic responses could still be enhanced by the high temperatures and solar incidence. Here, we assessed changes in the aquatic primary production along a small section of low-flow tropical downstream (Imboassica Stream, Brazil) after dredging. Our results suggested that these ecosystems may show catastrophic shifts between net heterotrophy and autotrophy in waters based on three short-term stages following the dredging: (I) a strongly heterotrophic net primary production -NPP- coupled to an intense respiration -R- likely supported by high resuspended organic sediments and nutrients from the bottom; (II) a strongly autotrophic NPP coupled to an intense gross primary production -GPP- favored by the high nutrient levels and low solar light attenuation from suspended solids or aquatic macrophytes; and (III) a NPP near to the equilibrium coupled to low GPP and R rates following, respectively, the shading by aquatic macrophytes and high particulate sedimentation. In conclusion, changes in aquatic primary production could be an important threshold for controlling drastic shifts in the organic matter cycling and the subsequent silting up of small tropical streams after dredging events.
Climate data induced uncertainty in model based estimations of terrestrial primary productivity
NASA Astrophysics Data System (ADS)
Wu, Z.; Ahlström, A.; Smith, B.; Ardö, J.; Eklundh, L.; Fensholt, R.; Lehsten, V.
2016-12-01
Models used to project global vegetation and carbon cycle differ in their estimates of historical fluxes and pools. These differences arise not only from differences between models but also from differences in the environmental and climatic data that forces the models. Here we investigate the role of uncertainties in historical climate data, encapsulated by a set of six historical climate datasets. We focus on terrestrial gross primary productivity (GPP) and analyze the results from a dynamic process-based vegetation model (LPJ-GUESS) forced by six different climate datasets and two empirical datasets of GPP (derived from flux towers and remote sensing). We find that the climate induced uncertainty, defined as the difference among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 33 Pg C yr-1 globally (19% of mean GPP). The uncertainty is partitioned into the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (the data range) and the sensitivity of the modeled GPP to the driver (the ecosystem sensitivity). The analysis is performed globally and stratified into five land cover classes. We find that the dynamic vegetation model overestimates GPP, compared to empirically based GPP data over most areas, except for the tropical region. Both the simulations and empirical estimates agree that the tropical region is a disproportionate source of uncertainty in GPP estimation. This is mainly caused by uncertainties in shortwave radiation forcing, of which climate data range contributes slightly higher uncertainty than ecosystem sensitivity to shortwave radiation. We also find that precipitation dominated the climate induced uncertainty over nearly half of terrestrial vegetated surfaces, which is mainly due to large ecosystem sensitivity to
Sun, Jinwei; Wu, Jiabing; Guan, Dexin; Yao, Fuqi; Yuan, Fenghui; Wang, Anzhi; Jin, Changjie
2014-01-01
Leaf respiration is an important component of carbon exchange in terrestrial ecosystems, and estimates of leaf respiration directly affect the accuracy of ecosystem carbon budgets. Leaf respiration is inhibited by light; therefore, gross primary production (GPP) will be overestimated if the reduction in leaf respiration by light is ignored. However, few studies have quantified GPP overestimation with respect to the degree of light inhibition in forest ecosystems. To determine the effect of light inhibition of leaf respiration on GPP estimation, we assessed the variation in leaf respiration of seedlings of the dominant tree species in an old mixed temperate forest with different photosynthetically active radiation levels using the Laisk method. Canopy respiration was estimated by combining the effect of light inhibition on leaf respiration of these species with within-canopy radiation. Leaf respiration decreased exponentially with an increase in light intensity. Canopy respiration and GPP were overestimated by approximately 20.4% and 4.6%, respectively, when leaf respiration reduction in light was ignored compared with the values obtained when light inhibition of leaf respiration was considered. This study indicates that accurate estimates of daytime ecosystem respiration are needed for the accurate evaluation of carbon budgets in temperate forests. In addition, this study provides a valuable approach to accurately estimate GPP by considering leaf respiration reduction in light in other ecosystems. PMID:25419844
NASA Astrophysics Data System (ADS)
Li, X.; Xiao, J.; He, B.
2017-12-01
Solar-induced chlorophyll fluorescence (SIF) opens a new perspective on the monitoring of vegetation photosynthesis from space, and has been recently used to estimate gross primary productivity (GPP). However, previous studies on SIF were mainly based on satellite observations from the Greenhouse Gases Observing Satellite (GOSAT) and Global Ozone Monitoring Experiment-2 (GOME-2), and the evaluation of these coarse-resolution SIF measurements using GPP derived from eddy covariance (EC) flux towers has been hindered by the scale mismatch between satellite and tower footprints. We use new far-red SIF observations from the Orbiting Carbon Observatory-2 (OCO-2) satellite with much finer spatial resolution and GPP data from EC flux towers from 2014 to 2016 to examine the relationship between GPP and SIF for temperate forests. The OCO-2 SIF tracked tower GPP fairly well, and had strong correlation with tower GPP at both retrieval bands (757nm and 771nm) and both instantaneous (mid-day) and daily timescales. Daily SIF at 757nm (SIF757) exhibited much stronger correlation with tower GPP compared to MODIS enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) derived from either Terra or Aqua and had a similarly strong relationship as EVI based on the bidirectional reflectance distribution function (BRDF) corrected reflectance product (Terra+Aqua). Absorbed photosynthetically active radiation (APAR) explained 85% of the variance in SIF757, while the product of APAR and two environmental scalars - fTmin and fVPD (representing minimum temperature stress and water stress) explained slightly higher variance (92%) in SIF757. This suggests that SIF mainly depends on APAR and also contains information on light use efficiency (LUE) reflecting environmental stresses and physiological or biochemical variations of vegetation. The hyperbolic model based on SIF757 estimated GPP well (R2=0.81, p<0.0001; RMSE=1.11 gC m-2 d-1), and its performance was comparable
Gitelson, Anatoly A; Peng, Yi; Arkebauer, Timothy J; Suyker, Andrew E
2015-04-01
Vegetation productivity metrics such as gross primary production (GPP) at the canopy scale are greatly affected by the efficiency of using absorbed radiation for photosynthesis, or light use efficiency (LUE). Thus, close investigation of the relationships between canopy GPP and photosynthetically active radiation absorbed by vegetation is the basis for quantification of LUE. We used multiyear observations over irrigated and rainfed contrasting C3 (soybean) and C4 (maize) crops having different physiology, leaf structure, and canopy architecture to establish the relationships between canopy GPP and radiation absorbed by vegetation and quantify LUE. Although multiple LUE definitions are reported in the literature, we used a definition of efficiency of light use by photosynthetically active "green" vegetation (LUE(green)) based on radiation absorbed by "green" photosynthetically active vegetation on a daily basis. We quantified, irreversible slowly changing seasonal (constitutive) and rapidly day-to-day changing (facultative) LUE(green), as well as sensitivity of LUE(green) to the magnitude of incident radiation and drought events. Large (2-3-fold) variation of daily LUE(green) over the course of a growing season that is governed by crop physiological and phenological status was observed. The day-to-day variations of LUE(green) oscillated with magnitude 10-15% around the seasonal LUE(green) trend and appeared to be closely related to day-to-day variations of magnitude and composition of incident radiation. Our results show the high variability of LUE(green) between C3 and C4 crop species (1.43 g C/MJ vs. 2.24 g C/MJ, respectively), as well as within single crop species (i.e., maize or soybean). This implies that assuming LUE(green) as a constant value in GPP models is not warranted for the crops studied, and brings unpredictable uncertainties of remote GPP estimation, which should be accounted for in LUE models. The uncertainty of GPP estimation due to facultative and
NASA Astrophysics Data System (ADS)
He, M.; Kimball, J. S.; Running, S. W.; Ballantyne, A.; Guan, K.; Huemmrich, K. F.
2016-12-01
Satellite remote sensing provides continuous observations of vegetation properties that can be used to estimate ecosystem gross primary production (GPP). The Photochemical Reflectance Index (PRI) has been shown to be sensitive to photosynthetic light use efficiency (LUE), GPP and canopy water-stress. The NASA EOS MODIS (Moderate Resolution Imaging Spectroradiometer) sensor provides potential PRI estimation globally at daily time step and 1-km spatial resolution for more than 10 years. Here, we use the MODIS based PRI with eddy covariance CO2 flux measurements and meteorological observations from 20 tower sites representing 5 major plant functional types (PFT) within the continental USA (CONUS) to assess GPP sensitivity to seasonal water supply variability. The sPRI (scaled PRI) derived using MODIS band 13 as a reference band (sPRI13) generally shows higher correspondence with tower GPP observations than other potential MODIS reference bands (MODIS band 1, 4, 10 and 12). The sPRI13 was used to represent soil moisture related water supply constraints to LUE within a terrestrial carbon flux model to estimate GPP (GPPPRI). The GPPPRI calculations show generally strong relationships with tower GPP observations (0.457 ≤ R2 ≤ 0.818), except for lower GPPPRI performance over evergreen needleleaf forest (ENF) sites. A regional model sensitivity analysis using the sPRI13 as a proxy for soil moisture related water supply limits indicated that water restrictions limit GPP over more than 21% of the CONUS domain, particularly in northwest and southwest CONUS subregions, and drier climate areas where atmospheric moisture deficits (VPD) alone are insufficient to represent both atmosphere demand and soil water supply controls affecting productivity. Our results indicate strong potential of the MODIS sPRI13 to represent GPP sensitivity to seasonal soil moisture related water supply variability, with enhanced (1-km resolution) delineation of these processes closer to the scale of
NASA Astrophysics Data System (ADS)
Wang, S.; Bandini, F.; Jakobsen, J.; J Zarco-Tejada, P.; Liu, X.; Haugård Olesen, D.; Ibrom, A.; Bauer-Gottwein, P.; Garcia, M.
2017-12-01
Model prediction of evapotranspiration (ET) and gross primary productivity (GPP) using optical and thermal satellite imagery is biased towards clear-sky conditions. Unmanned Aerial Systems (UAS) can collect optical and thermal signals at unprecedented very high spatial resolution (< 1 meter) under sunny and cloudy weather conditions. However, methods to obtain model outputs between image acquisitions are still needed. This study uses UAS based optical and thermal observations to continuously estimate daily ET and GPP in a Danish willow forest for an entire growing season of 2016. A hexacopter equipped with multispectral and thermal infrared cameras and a real-time kinematic Global Navigation Satellite System was used. The Normalized Differential Vegetation Index (NDVI) and the Temperature Vegetation Dryness Index (TVDI) were used as proxies for leaf area index and soil moisture conditions, respectively. To obtain continuously daily records between UAS acquisitions, UAS surface temperature was assimilated by the ensemble Kalman filter into a prognostic land surface model (Noilhan and Planton, 1989), which relies on the force-restore method, to simulate the continuous land surface temperature. NDVI was interpolated into daily time steps by the cubic spline method. Using these continuous datasets, a joint ET and GPP model, which combines the Priestley-Taylor Jet Propulsion Laboratory ET model (Fisher et al., 2008; Garcia et al., 2013) and the Light Use Efficiency GPP model (Potter et al., 1993), was applied. The simulated ET and GPP were compared with the footprint of eddy covariance observations. The simulated daily ET has a RMSE of 14.41 W•m-2 and a correlation coefficient of 0.83. The simulated daily GPP has a root mean square error (RMSE) of 1.56 g•C•m-2•d-1 and a correlation coefficient of 0.87. This study demonstrates the potential of UAS based multispectral and thermal mapping to continuously estimate ET and GPP for both sunny and cloudy weather
Fan, Zhaosheng; Neff, Jason C.; Wieder, William R.
2016-02-10
We investigated several key limiting factors that control alpine tundra productivity by developing an ecosystem biogeochemistry model. The model simulates the coupled cycling of carbon (C), nitrogen (N), and phosphorus (P) and their interactions with gross primary production (GPP). It was parameterized with field observations from an alpine dry meadow ecosystem using a global optimization strategy to estimate the unknown parameters. The model, along with the estimated parameters, was first validated against independent data and then used to examine the environmental controls over plant productivity. Our results show that air temperature is the strongest limiting factor to GPP in themore » early growing season, N availability becomes important during the middle portion of the growing season, and soil moisture is the strongest limiting factors by late in the growing season. Overall, the controls over GPP during the growing season, from strongest to weakest, are soil moisture content, air temperature, N availability, and P availability. This simulation provides testable predictions of the shifting nature of physical and nutrient limitations on plant growth. The model also indicates that changing environmental conditions in the alpine will likely lead to changes in productivity. For example, warming eliminates the control of P availability on GPP and makes N availability surpass air temperature to become the second strongest limiting factor. In contrast, an increase in atmospheric nutrient deposition eliminates the control of N availability and enhances the importance of P availability. Furthermore, these analyses provide a quantitative and conceptual framework that can be used to test predictions and refine ecological analyses at this long-term ecological research site.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fan, Zhaosheng; Neff, Jason C.; Wieder, William R.
We investigated several key limiting factors that control alpine tundra productivity by developing an ecosystem biogeochemistry model. The model simulates the coupled cycling of carbon (C), nitrogen (N), and phosphorus (P) and their interactions with gross primary production (GPP). It was parameterized with field observations from an alpine dry meadow ecosystem using a global optimization strategy to estimate the unknown parameters. The model, along with the estimated parameters, was first validated against independent data and then used to examine the environmental controls over plant productivity. Our results show that air temperature is the strongest limiting factor to GPP in themore » early growing season, N availability becomes important during the middle portion of the growing season, and soil moisture is the strongest limiting factors by late in the growing season. Overall, the controls over GPP during the growing season, from strongest to weakest, are soil moisture content, air temperature, N availability, and P availability. This simulation provides testable predictions of the shifting nature of physical and nutrient limitations on plant growth. The model also indicates that changing environmental conditions in the alpine will likely lead to changes in productivity. For example, warming eliminates the control of P availability on GPP and makes N availability surpass air temperature to become the second strongest limiting factor. In contrast, an increase in atmospheric nutrient deposition eliminates the control of N availability and enhances the importance of P availability. Furthermore, these analyses provide a quantitative and conceptual framework that can be used to test predictions and refine ecological analyses at this long-term ecological research site.« less
NASA Astrophysics Data System (ADS)
Ma, J.; Xiao, X.; Zhang, Y.; Chen, B.; Zhao, B.
2017-12-01
Great significance exists in accurately estimating spatial-temporal patterns of gross primary production (GPP) because of its important role in global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatially time-sires GPP. However, the estimation of the accuracy of GPP simulations from LUE at both spatial and temporal scales is still a challenging work. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images of 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPPVPM) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPPVPM and SIF data over both single year (2010) and multiple years (2007-2014) in China. Annual GPPVPM is significantly positive correlated with SIF (R2>0.43) spatially for all years during 2007-2014 and all seasons in 2010 (R2>0.37). GPP dynamic trends is high spatial-temporal heterogeneous in China during 2007-2014. The results of this study indicate that GPPVPM is temporally and spatially in line with SIF data, and space-borne SIF data have great potential in validating and parameterizing GPP estimation of LUE-based models.
NASA Astrophysics Data System (ADS)
Ryan, E.; Ogle, K.; Peltier, D.; Williams, D. G.; Pendall, E.
2014-12-01
The goal of this study was to quantify interannual variation of gross primary production (GPP) and evaluate potential drivers of GPP with global change using the Prairie Heating and CO2 Enrichment (PHACE) experiment in semiarid grassland in southeastern Wyoming. PHACE consists of the treatments: control, warming only, elevated CO2 (eCO2) only, eCO2 and warming, and irrigation only. We expected that GPP would be most strongly influenced by interannual variability in precipitation under all PHACE treatments, soil water availability under eCO2, and nitrogen availability. GPP data were obtained from paired measurements of net ecosystem exchange (NEE) and ecosystem respiration (Reco; GPP = Reco - NEE) made on 2-4 week intervals over six growing seasons (2007-2012). Soil temperature (T), soil water content (SWC), vapor pressure deficit (VPD), and photosynthetically active radiation (PAR) were continuously recorded at the plot (T, SWC) and site (VPD, PAR) scales. Annual, plot-level aboveground plant nitrogen content (N) was measured during peak biomass. We fit a non-linear light-response model to the GPP data within a Bayesian framework, and modeled the maximum GPP rate (Gmax) and canopy light-use efficiency (Q) as functions of N and current and antecedent SWC, T, and VPD. The model fit the GPP data well (R2 = 0.64), and regardless of the PHACE treatment the most important drivers of GPP were N (for Gmax), VPD (Gmax and Q), antecedent T (Gmax), and antecedent VPD (Q). Model simulations predicted that annual GPP increased on average by about 16% with eCO2, 14% with warming, 12% with eCO2 and warming, and 23% with irrigation. For four of the six years, annual GPP was significantly affected by either eCO2 alone or when combined with warming. The increase in annual GPP under irrigation was similar to the increase under eCO2 during a dry year (2012), but irrigation stimulated GPP to a greater degree than eCO2 during wet years (2008, 2009). Hence, increases in GPP under eCO2
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ryan, Edmund M.; Ogle, Kiona; Peltier, Drew
Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO2 (eCO2) and warming requires accurate quantification of gross primary production (GPP), the largest flux of C in the global C cycle. We evaluated six years (2007-2012) of flux-derived GPP data from the Prairie Heating and CO2 Enrichment (PHACE) experiment, situated in a mixed prairie grassland in Wyoming (USA). The GPP data were fitted to a mixed effects model that extended a light response model to include the effects of environmental (soil water content, vegetation greenness, nitrogen) and meteorological datamore » (air temperature, vapor pressure deficit, photosynthetically active radiation) at current and past times. The stimulation of the cumulative six-year GPP by warming (20%, P=0.06) and eCO2 (19%, P=0.14) were primarily driven by enhanced C uptake during spring (96%, P=0.003) and fall (115%, P=0.001), respectively. These enhancements were consistent across each year, suggesting mechanisms for extending the growing season. Vapor pressure deficit from 1-3 days prior was the most significant predictor of temporalvariability in GPP and for explaining treatment differences in GPP, suggesting that atmospheric drought plays an important role for predicting GPP now and under future climate conditions.« less
Ryan, Edmund M.; Ogle, Kiona; Peltier, Drew; ...
2016-12-19
Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO2 (eCO2) and warming requires accurate quantification of gross primary production (GPP), the largest flux of C in the global C cycle. We evaluated six years (2007-2012) of flux-derived GPP data from the Prairie Heating and CO2 Enrichment (PHACE) experiment, situated in a mixed prairie grassland in Wyoming (USA). The GPP data were fitted to a mixed effects model that extended a light response model to include the effects of environmental (soil water content, vegetation greenness, nitrogen) and meteorological datamore » (air temperature, vapor pressure deficit, photosynthetically active radiation) at current and past times. The stimulation of the cumulative six-year GPP by warming (20%, P=0.06) and eCO2 (19%, P=0.14) were primarily driven by enhanced C uptake during spring (96%, P=0.003) and fall (115%, P=0.001), respectively. These enhancements were consistent across each year, suggesting mechanisms for extending the growing season. Vapor pressure deficit from 1-3 days prior was the most significant predictor of temporalvariability in GPP and for explaining treatment differences in GPP, suggesting that atmospheric drought plays an important role for predicting GPP now and under future climate conditions.« less
Within and beyond the stringent response-RSH and (p)ppGpp in plants.
Boniecka, Justyna; Prusińska, Justyna; Dąbrowska, Grażyna B; Goc, Anna
2017-11-01
Plant RSH proteins are able to synthetize and/or hydrolyze unusual nucleotides called (p)ppGpp or alarmones. These molecules regulate nuclear and chloroplast transcription, chloroplast translation and plant development and stress response. Homologs of bacterial RelA/SpoT proteins, designated RSH, and products of their activity, (p)ppGpp-guanosine tetra-and pentaphosphates, have been found in algae and higher plants. (p)ppGpp were first identified in bacteria as the effectors of the stringent response, a mechanism that orchestrates pleiotropic adaptations to nutritional deprivation and various stress conditions. (p)ppGpp accumulation in bacteria decreases transcription-with exception to genes that help to withstand or overcome current stressful situations, which are upregulated-and translation as well as DNA replication and eventually reduces metabolism and growth but promotes adaptive responses. In plants, RSH are nuclei-encoded and function in chloroplasts, where alarmones are produced and decrease transcription, translation, hormone, lipid and metabolites accumulation and affect photosynthetic efficiency and eventually plant growth and development. During senescence, alarmones coordinate nutrient remobilization and relocation from vegetative tissues into seeds. Despite the high conservancy of RSH protein domains among bacteria and plants as well as the bacterial origin of plant chloroplasts, in plants, unlike in bacteria, (p)ppGpp promote chloroplast DNA replication and division. Next, (p)ppGpp may also perform their functions in cytoplasm, where they would promote plant growth inhibition. Furthermore, (p)ppGpp accumulation also affects nuclear gene expression, i.a., decreases the level of Arabidopsis defense gene transcripts, and promotes plants susceptibility towards Turnip mosaic virus. In this review, we summarize recent findings that show the importance of RSH and (p)ppGpp in plant growth and development, and open an area of research aiming to understand the
Cytosolic ppGpp accumulation induces retarded plant growth and development.
Ihara, Yuta; Masuda, Shinji
2016-01-01
In bacteria a second messenger, guanosine 5'-diphosphate 3'-diphosphate (ppGpp), synthesized upon nutrient starvation, controls many gene expressions and enzyme activities, which is necessary for growth under changeable environments. Recent studies have shown that ppGpp synthase and hydrolase are also conserved in eukaryotes, although their functions are not well understood. We recently showed that ppGpp-overaccumulation in Arabidopsis chloroplasts results in robust growth under nutrient-limited conditions, demonstrating that the bacterial-like stringent response at least functions in plastids. To test if ppGpp also functions in the cytosol, we constructed the transgenic Arabidopsis expressing Bacillus subtilis ppGpp synthase gene yjbM. Upon induction of the gene, the mutant synthesizes ∼10-20-fold higher levels of ppGpp, and its fresh weight was reduced to ˜80% that of the wild type. These results indicate that cytosolic ppGpp negatively regulates plant growth and development.
USDA-ARS?s Scientific Manuscript database
Quantifying global carbon and water balances requires accurate estimation of gross primary production (GPP) and evapotranspiration (ET), respectively, across space and time. Models that are based on the theory of light use efficiency (LUE) and water use efficiency (WUE) have emerged as efficient met...
NASA Astrophysics Data System (ADS)
Bowling, D. R.; Blanken, P.; Burns, S. P.; Frankenberg, C.; Grossman, K.; Lin, J. C.; Logan, B. A.; Magney, T. S.; Richardson, A. D.; Stutz, J.; Aubrecht, D.
2017-12-01
Temperate and boreal conifer forests are dormant for many months during the cold season, during which they continue to absorb solar radiation. Thus they exhibit a marked seasonal change in light-use efficiency, challenging our ability to monitor gross primary productivity (GPP) from remote sensing platforms. We are studying the factors limiting the seasonality of photosynthesis of a high-elevation subalpine forest in Colorado. Using in-situ thermal imagery, we find that foliage in winter is sometimes near the optimum temperature for photosynthesis, but photosynthesis is shut down for most of the cold season. Water transport is limited by blockage of sap transport by frozen boles, but not by frozen soils. Foliar carotenoid content exhibits strong upregulation during winter, driven largely by increase in the pool size of the photoprotective xanthophyll cycle, but with no seasonal change in chlorophyll content. The seasonality of GPP is strongly linked to xanthophyll cycle conversion state and thawing of boles. Ongoing research includes examination of leaf-level chlorophyll fluorescence emission and gas exchange, combined with measurement of canopy-level spectral reflectance and solar-induced fluorescence (SIF) at high spatio-temporal resolution using a custom tower-based PhotoSpec scanning spectrometer system. These results will be synthesized in the context of using SIF as a metric for GPP.
Regional crop gross primary production and yield estimation using fused Landsat-MODIS data
NASA Astrophysics Data System (ADS)
He, M.; Kimball, J. S.; Maneta, M. P.; Maxwell, B. D.; Moreno, A.
2017-12-01
Accurate crop yield assessments using satellite-based remote sensing are of interest for the design of regional policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations are generally too coarse to capture cropland heterogeneity. Merging information from sensors with reciprocal spatial and temporal resolution can improve the accuracy of these retrievals. In this study, we estimate annual crop yields for seven important crop types -alfalfa, barley, corn, durum wheat, peas, spring wheat and winter wheat over Montana, United States (U.S.) from 2008 to 2015. Yields are estimated as the product of gross primary production (GPP) and a crop-specific harvest index (HI) at 30 m spatial resolution. To calculate GPP we used a modified form of the MOD17 LUE algorithm driven by a 30 m 8-day fused NDVI dataset constructed by blending Landsat (5 or 7) and MODIS Terra reflectance data. The fused 30-m NDVI record shows good consistency with the original Landsat and MODIS data, but provides better spatiotemporal information on cropland vegetation growth. The resulting GPP estimates capture characteristic cropland patterns and seasonal variations, while the estimated annual 30 m crop yield results correspond favorably with county-level crop yield data (r=0.96, p<0.05). The estimated crop yield performance was generally lower, but still favorable in relation to field-scale crop yield surveys (r=0.42, p<0.01). Our methods and results are suitable for operational applications at regional scales.
Impacts of Light Use Efficiency and fPAR Parameterization on Gross Primary Production Modeling
NASA Technical Reports Server (NTRS)
Cheng, Yen-Ben; Zhang, Qingyuan; Lyapustin, Alexei I.; Wang, Yujie; Middleton, Elizabeth M.
2014-01-01
This study examines the impact of parameterization of two variables, light use efficiency (LUE) and the fraction of absorbed photosynthetically active radiation (fPAR or fAPAR), on gross primary production(GPP) modeling. Carbon sequestration by terrestrial plants is a key factor to a comprehensive under-standing of the carbon budget at global scale. In this context, accurate measurements and estimates of GPP will allow us to achieve improved carbon monitoring and to quantitatively assess impacts from cli-mate changes and human activities. Spaceborne remote sensing observations can provide a variety of land surface parameterizations for modeling photosynthetic activities at various spatial and temporal scales. This study utilizes a simple GPP model based on LUE concept and different land surface parameterizations to evaluate the model and monitor GPP. Two maize-soybean rotation fields in Nebraska, USA and the Bartlett Experimental Forest in New Hampshire, USA were selected for study. Tower-based eddy-covariance carbon exchange and PAR measurements were collected from the FLUXNET Synthesis Dataset. For the model parameterization, we utilized different values of LUE and the fPAR derived from various algorithms. We adapted the approach and parameters from the MODIS MOD17 Biome Properties Look-Up Table (BPLUT) to derive LUE. We also used a site-specific analytic approach with tower-based Net Ecosystem Exchange (NEE) and PAR to estimate maximum potential LUE (LUEmax) to derive LUE. For the fPAR parameter, the MODIS MOD15A2 fPAR product was used. We also utilized fAPAR chl, a parameter accounting for the fAPAR linked to the chlorophyll-containing canopy fraction. fAPAR chl was obtained by inversion of a radiative transfer model, which used the MODIS-based reflectances in bands 1-7 produced by Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. fAPAR chl exhibited seasonal dynamics more similar with the flux tower based GPP than MOD15A2 fPAR, especially
NASA Astrophysics Data System (ADS)
Norton, A.; Rayner, P. J.; Scholze, M.; Koffi, E. N. D.
2016-12-01
The intercomparison study CMIP5 among other studies (e.g. Bodman et al., 2013) has shown that the land carbon flux contributes significantly to the uncertainty in projections of future CO2 concentration and climate (Friedlingstein et al., 2014)). The main challenge lies in disaggregating the relatively well-known net land carbon flux into its component fluxes, gross primary production (GPP) and respiration. Model simulations of these processes disagree considerably, and accurate observations of photosynthetic activity have proved a hindrance. Here we build upon the Carbon Cycle Data Assimilation System (CCDAS) (Rayner et al., 2005) to constrain estimates of one of these uncertain fluxes, GPP, using satellite observations of Solar Induced Fluorescence (SIF). SIF has considerable benefits over other proxy observations as it tracks not just the presence of vegetation but actual photosynthetic activity (Walther et al., 2016; Yang et al., 2015). To combine these observations with process-based simulations of GPP we have coupled the model SCOPE with the CCDAS model BETHY. This provides a mechanistic relationship between SIF and GPP, and the means to constrain the processes relevant to SIF and GPP via model parameters in a data assimilation system. We ingest SIF observations from NASA's Orbiting Carbon Observatory 2 (OCO-2) for 2015 into the data assimilation system to constrain estimates of GPP in space and time, while allowing for explicit consideration of uncertainties in parameters and observations. Here we present first results of the assimilation with SIF. Preliminary results indicate a constraint on global annual GPP of at least 75% when using SIF observations, reducing the uncertainty to < 3 PgC yr-1. A large portion of the constraint is propagated via parameters that describe leaf phenology. These results help to bring together state-of-the-art observations and model to improve understanding and predictive capability of GPP.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jin, Cui; Xiao, Xiangming; Wagle, Pradeep
2015-11-01
Satellite-based Production Efficiency Models (PEMs) often require meteorological reanalysis data such as the North America Regional Reanalysis (NARR) by the National Centers for Environmental Prediction (NCEP) as model inputs to simulate Gross Primary Production (GPP) at regional and global scales. This study first evaluated the accuracies of air temperature (TNARR) and downward shortwave radiation (RNARR) of the NARR by comparing with in-situ meteorological measurements at 37 AmeriFlux non-crop eddy flux sites, then used one PEM – the Vegetation Photosynthesis Model (VPM) to simulate 8-day mean GPP (GPPVPM) at seven AmeriFlux crop sites, and investigated the uncertainties in GPPVPM from climatemore » inputs as compared with eddy covariance-based GPP (GPPEC). Results showed that TNARR agreed well with in-situ measurements; RNARR, however, was positively biased. An empirical linear correction was applied to RNARR, and significantly reduced the relative error of RNARR by ~25% for crop site-years. Overall, GPPVPM calculated from the in-situ (GPPVPM(EC)), original (GPPVPM(NARR)) and adjusted NARR (GPPVPM(adjNARR)) climate data tracked the seasonality of GPPEC well, albeit with different degrees of biases. GPPVPM(EC) showed a good match with GPPEC for maize (Zea mays L.), but was slightly underestimated for soybean (Glycine max L.). Replacing the in-situ climate data with the NARR resulted in a significant overestimation of GPPVPM(NARR) (18.4/29.6% for irrigated/rainfed maize and 12.7/12.5% for irrigated/rainfed soybean). GPPVPM(adjNARR) showed a good agreement with GPPVPM(EC) for both crops due to the reduction in the bias of RNARR. The results imply that the bias of RNARR introduced significant uncertainties into the PEM-based GPP estimates, suggesting that more accurate surface radiation datasets are needed to estimate primary production of terrestrial ecosystems at regional and global scales.« less
NASA Astrophysics Data System (ADS)
Park, Haemi; Im, Jungho; Kim, Miae
2016-04-01
Photosynthesis of plants is the main mechanism of carbon absorption from the atmosphere into the terrestrial ecosystem and it contributes to remove greenhouse gases such as carbon dioxide. Annually, 120 Gt of C is supposed to be assimilated through photosynthetic activity of plants as the gross primary production (GPP) over global land area. In terms of climate change, GPP modelling is essential to understand carbon cycle and the balance of carbon budget over various ecosystems. One of the GPP modelling approaches uses light use efficiency that each vegetation type has a specific efficiency for consuming solar radiation related with temperature and humidity. Satellite data can be used to measure various meteorological and biophysical factors over vast areas, which can be used to quantify GPP. NASA Earth Observing System (EOS) program provides Moderate Resolution Imaging Spectroradiometer (MODIS)-derived global GPP product, namely MOD17A2H, on a daily basis. However, significant underestimation of MOD17A2H has been reported in Eastern Asia due to its dense forest distribution and humid condition during monsoon rainy season in summer. The objective of this study was to improve underestimation of MODIS GPP (MOD17A2H) by incorporating meteorological data-temperature, relative humidity, and solar radiation-of higher spatial resolution than data used in MOD17A2H. Landsat-based land cover maps of finer resolution observation and monitoring - global land cover (FROM-GLC) at 30m resolution were used for selection of light use efficiency (LUE). GPP (eq1. GPP = APAR×LUE) is computed by multiplication of APAR (IPAR×fPAR) and LUE (ɛ= ɛmax×T(°C)scalar×VPD(Pa)scalar, where, T is temperature, VPD is vapour pressure deficit) in this study. Meteorological data of Japanese 55-year Reanalysis (JRA-55, 0.56° grid, 3hr) were used for calculation of GPP in East Asia, including Eastern part of China, Korean peninsula, and Japan. Results were validated using flux tower-observed GPP
Understanding the output of a Smith-Root GPP electrofisher
Miranda, L.E.; Spencer, A.B.
2005-01-01
There is confusion among biologists about the use of the percent of range control in the GPP series of Smith-Root electrofishers. We evaluated the output of a GPP 7.5 electrofisher to examine how adjustments to the percent of range control affect voltage, pulse width, duty cycle, and waveform. We found that contrary to how most users interpret the labels on the GPP unit, adjustments to the percent of range control are linked only indirectly to changes in peak voltage. Suggestions for dealing with the restrictions of the GPP units are offered. ?? Copyright by the American Fisheries Society 2005.
NASA Astrophysics Data System (ADS)
Smith, W. K.; Biederman, J. A.; Scott, R. L.; Moore, D. J.; Kimball, J. S.; He, M.; Yan, D.; Hudson, A.; Barnes, M.; MacBean, N.; Fox, A. M.; Litvak, M. E.
2017-12-01
Satellite remote sensing provides unmatched spatiotemporal information on multiple facets of vegetation dynamics including seasonal to interannual total photosynthesis, termed gross primary productivity (GPP). Yet, our understanding of the relationship between GPP and remote sensing observations - and how this relationship changes with scale, biophysical constraint, vegetation type, etc. - remains limited. This knowledge gap is especially apparent for dryland ecosystems, which have high spatial and temporal variability and are under-represented by long-term, continuous field measurements. Here, utilizing a new synthesis of eddy covariance flux tower data for southwestern North America, we present a first assessment of the ability of novel satellite remote sensing vegetation proxies to accurately capture seasonal to interannual GPP dynamics across the region. We evaluate the greenness-based Enhanced Vegetation Index (EVI) and emerging proxies linked to plant physiological function, Solar-Induced Fluorescence (SIF) and Photochemical Reflectivity Index (PRI). We find that SIF observations more consistently correlate with seasonal GPP dynamics (R = 0.90) compared to EVI (R = 0.85) and PRI (R = 0.78). More, we find that SIF observations are also more sensitive to interannual GPP variability (linear slope = 0.80) relative to EVI (linear slope = 0.63) and PRI (linear slope = 0.35). This is likely due to increased sensitivity of SIF to GPP during periods of decoupling between greenness and photosynthesis due to water-limitation / stomatal closure. Conversely, EVI and PRI observations better capture spatial GPP variability between flux tower sites. These results suggest that combinations of these independent vegetation growth proxies could yield synergistic improvements in satellite-based GPP estimates.
Assessment of SMAP soil moisture for global simulation of gross primary production
NASA Astrophysics Data System (ADS)
He, Liming; Chen, Jing M.; Liu, Jane; Bélair, Stéphane; Luo, Xiangzhong
2017-07-01
In this study, high-quality soil moisture data derived from the Soil Moisture Active Passive (SMAP) satellite measurements are evaluated from a perspective of improving the estimation of the global gross primary production (GPP) using a process-based ecosystem model, namely, the Boreal Ecosystem Productivity Simulator (BEPS). The SMAP soil moisture data are assimilated into BEPS using an ensemble Kalman filter. The correlation coefficient (
USDA-ARS?s Scientific Manuscript database
Extreme climatic events, such as droughts and heat stress induce anomalies in ecosystem-atmosphere CO2 fluxes, such as gross primary production (GPP) and ecosystem respiration (Reco), and, hence, can change the net ecosystem carbon balance. However, despite our increasing understanding of the underl...
SPRUCE S1 Bog Sphagnum CO2 Flux Measurements and Partitioning into Re and GPP
Walker, A. P. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Carter, K. R. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Hanson, P. J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Nettles, W. R. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Philips, J. R. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Sebestyen, S. D. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Weston, D. J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.
2015-06-01
This data set provides (1) the results of in-situ Sphagnum-peat hourly net ecosystem exchange (NEE) measured using a LICOR 8100 gas exchange system and (2) the component fluxes -- gross primary production (GPP) and ecosystem respiration (Re), derived using empirical regressions.NEE measurements were made from 6 June to 6 November 2014 and 20 March to 10 May 2015. Three 8100 chambers per dominant species (S. magellanicum or S. fallax) were placed in the S1 Bog in relatively open ground where there was no obvious hummock-hollow microtopography. The 8100 chambers were not located in the SPRUCE experimental enclosures.
Interplay of drought and tropical cyclone activity in SE U.S. gross primary productivity
NASA Astrophysics Data System (ADS)
Lowman, Lauren E. L.; Barros, Ana P.
2016-06-01
Tropical cyclones (TCs), often associated with massive flooding and landslides in the Southeast U.S. (SE U.S.), provide a significant input of freshwater to the hydrologic system, and their timing and trajectory significantly impact drought severity and persistence. This manuscript investigates the sensitivity of gross primary productivity (GPP) in the SE U.S. to TC activity using the 1-D column implementation of the Duke Coupled Hydrology Model with Vegetation (DCHM-V) including coupled water and energy cycles and a biochemical representation of photosynthesis. Decadal-scale simulations of water, energy, and carbon fluxes were conducted at high temporal (30 min) and spatial (4 km) resolution over the period 2002-2012. At local scales, model results without calibration compare well against AmeriFlux tower data. At regional scales, differences between the DCHM-V estimates and the Moderate Resolution Imaging Spectroradiometer GPP product reflect the spatial organization of soil hydraulic properties and soil moisture dynamics by physiographic region, highlighting the links between the water and carbon cycles. To isolate the contribution of TC precipitation to SE U.S. productivity, control forcing simulations are contrasted with simulations where periods of TC activity in the atmospheric forcing data were replaced with climatology. During wet years, TC activity impacts productivity in 40-50% of the SE U.S. domain and explains a regional GPP increase of 3-5 Mg C/m2 that is 9% of the warm season total. In dry years, 23-34% of the domain exhibits a smaller positive response that corresponds to 4-8% of the seasonal carbon uptake, depending on TC timing and trajectory.
NASA Astrophysics Data System (ADS)
Dodds, W. K.; Tromboni, F.; Neres-Lima, V.; Zandoná, E.; Moulton, T. P.
2016-12-01
While whole-stream measures of metabolism and uptake have become common methods to characterize biogeochemical transport and processing, less is known about how nitrogen (N) uptake, gross primary production (GPP) and ecosystem respiration (ER) covary among different stream substrata as smaller scales. We measured 15N ammonium and nitrate uptake seperately, and GPP and ER of ecosystem compartments (leaves, epilithon, sand-associated biota and macrophytes) in closed circulating chambers in three streams/ rivers of varied size. The streams drain pristine Brazilian Atlantic Rainforest watersheds and are all within a few km of eachother. The smallest stream had dense forest canopy cover; the largest river was almost completely open. GPP could not be detected in the closed canopy stream. Epilithon (biofilms on rocks) was a dominant compartment for GPP and N uptake in the two open streams, and macrophytes rivaled epilithon GPP and N uptake rates in the most open stream. Even though leaves covered only 1-3% of the stream bottom, they could account for around half of all the ER in the streams but almost no N uptake. Sand had minimal rates of N uptake, GPP and R associated with it in all streams due to relatively low organic material content. The data suggest that N uptake, GPP and ER of different substrata are not closely linked over relatively small spatial (dm) scales, and that different biogeochemical processes may map to different hot and cool spots for ecosystem rates.
NASA Astrophysics Data System (ADS)
Cicuéndez, Víctor; Huesca, Margarita; Rodriguez-Rastrero, Manuel; Litago, Javier; Recuero, Laura; Merino de Miguel, Silvia; Palacios Orueta, Alicia
2014-05-01
Agroforestry ecosystems have a significant social, economic and environmental impact on the development of many regions of the world. In the Iberian Peninsula the agroforestry oak forest called "Dehesa" or "Montado" is considered as the extreme case of transformation of a Mediterranean forest by the management of human to provide a wide range of natural resources. The high variability of the Mediterranean climate and the different extensive management practices which human realized on the Dehesa result in a high spatial and temporal dynamics of the ecosystem. This leads to a complex pattern in CO2 exchange between the atmosphere and the ecosystem, i.e. in ecosystem's production. Thus, it is essential to assess Dehesa's carbon cycle to reach maximum economic benefits ensuring environmental sustainability. In this sense, the availability of high frequency Remote Sensing (RS) time series allows the assessment of ecosystem evolution at different temporal and spatial scales. Extensive research has been conducted to estimate production from RS data in different ecosystems. However, there are few studies on the Dehesa type ecosystems, probably due to their complexity in terms of spatial arrangement and temporal dynamics. In this study our overall objective is to assess the Gross Primary Production (GPP) dynamics of a Dehesa ecosystem situated in Central Spain by analyzing time series (2004-2008) of two models: (1) GPP provided by Remote Sensing Images of sensor MODIS (MOD17A2 product) and (2) GPP estimated by the implementation of a Site Specific Light Use Efficiency model based as MODIS model on Monteith equation (1972), but taking into account local ecological and meteorological parameters. Both models have been compared with the Production provided by an Eddy Covariance (EC) flux Tower that is located in our study area. In addition, dynamic relationships between models of GPP with Precipitation and Soil Water Content have been investigated by means of cross
Yuan, W.; Liu, S.; Yu, G.; Bonnefond, J.-M.; Chen, J.; Davis, K.; Desai, A.R.; Goldstein, Allen H.; Gianelle, D.; Rossi, F.; Suyker, A.E.; Verma, S.B.
2010-01-01
The simulation of gross primary production (GPP) at various spatial and temporal scales remains a major challenge for quantifying the global carbon cycle. We developed a light use efficiency model, called EC-LUE, driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux. The EC-LUE model may have the most potential to adequately address the spatial and temporal dynamics of GPP because its parameters (i.e., the potential light use efficiency and optimal plant growth temperature) are invariant across the various land cover types. However, the application of the previous EC-LUE model was hampered by poor prediction of Bowen ratio at the large spatial scale. In this study, we substituted the Bowen ratio with the ratio of evapotranspiration (ET) to net radiation, and revised the RS-PM (Remote Sensing-Penman Monteith) model for quantifying ET. Fifty-four eddy covariance towers, including various ecosystem types, were selected to calibrate and validate the revised RS-PM and EC-LUE models. The revised RS-PM model explained 82% and 68% of the observed variations of ET for all the calibration and validation sites, respectively. Using estimated ET as input, the EC-LUE model performed well in calibration and validation sites, explaining 75% and 61% of the observed GPP variation for calibration and validation sites respectively.Global patterns of ET and GPP at a spatial resolution of 0.5° latitude by 0.6° longitude during the years 2000–2003 were determined using the global MERRA dataset (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate Resolution Imaging Spectroradiometer). The global estimates of ET and GPP agreed well with the other global models from the literature, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas. However, comparisons with observed
Christina, Mathias; Le Maire, Guerric; Battie-Laclau, Patricia; Nouvellon, Yann; Bouillet, Jean-Pierre; Jourdan, Christophe; de Moraes Gonçalves, José Leonardo; Laclau, Jean-Paul
2015-05-01
Global climate change is expected to increase the length of drought periods in many tropical regions. Although large amounts of potassium (K) are applied in tropical crops and planted forests, little is known about the interaction between K nutrition and water deficit on the physiological mechanisms governing plant growth. A process-based model (MAESPA) parameterized in a split-plot experiment in Brazil was used to gain insight into the combined effects of K deficiency and water deficit on absorbed radiation (aPAR), gross primary productivity (GPP), and light-use efficiency for carbon assimilation and stem biomass production (LUEC and LUEs ) in Eucalyptus grandis plantations. The main-plot factor was the water supply (undisturbed rainfall vs. 37% of throughfall excluded) and the subplot factor was the K supply (with or without 0.45 mol K m(-2 ) K addition). Mean GPP was 28% lower without K addition over the first 3 years after planting whether throughfall was partly excluded or not. K deficiency reduced aPAR by 20% and LUEC by 10% over the whole period of growth. With K addition, throughfall exclusion decreased GPP by 25%, resulting from a 21% decrease in LUEC at the end of the study period. The effect of the combination of K deficiency and water deficit was less severe than the sum of the effects of K deficiency and water deficit individually, leading to a reduction in stem biomass production, gross primary productivity and LUE similar to K deficiency on its own. The modeling approach showed that K nutrition and water deficit influenced absorbed radiation essentially through changes in leaf area index and tree height. The changes in gross primary productivity and light-use efficiency were, however, driven by a more complex set of tree parameters, especially those controlling water uptake by roots and leaf photosynthetic capacities. © 2014 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Bacour, C.; Maignan, F.; Porcar-Castell, A.; MacBean, N.; Goulas, Y.; Flexas, J.; Guanter, L.; Joiner, J.; Peylin, P.
2016-12-01
A new era for improving our knowledge of the terrestrial carbon cycle at the global scale has begun with recent studies on the relationships between remotely sensed Sun Induce Fluorescence (SIF) and plant photosynthetic activity (GPP), and the availability of such satellite-derived products now "routinely" produced from GOSAT, GOME-2, or OCO-2 observations. Assimilating SIF data into terrestrial ecosystem models (TEMs) represents a novel opportunity to reduce the uncertainty of their prediction with respect to carbon-climate feedbacks, in particular the uncertainties resulting from inaccurate parameter values. A prerequisite is a correct representation in TEMs of the several drivers of plant fluorescence from the leaf to the canopy scale, and in particular the competing processes of photochemistry and non photochemical quenching (NPQ).In this study, we present the first results of a global scale assimilation of GOME-2 SIF products within a new version of the ORCHIDEE land surface model including a physical module of plant fluorescence. At the leaf level, the regulation of fluorescence yield is simulated both by the photosynthesis module of ORCHIDEE to calculate the photochemical yield and by a parametric model to estimate NPQ. The latter has been calibrated on leaf fluorescence measurements performed for boreal coniferous and Mediterranean vegetation species. A parametric representation of the SCOPE radiative transfer model is used to model the plant fluorescence fluxes for PSI and PSII and the scaling up to the canopy level. The ORCHIDEE-FluOR model is firstly evaluated with respect to in situ measurements of plant fluorescence flux and photochemical yield for scots pine and wheat. The potentials of SIF data to constrain the modelled GPP are evaluated by assimilating one year of GOME-2-SIF products within ORCHIDEE-FluOR. We investigate in particular the changes in the spatial patterns of GPP following the optimization of the photosynthesis and phenology parameters
Sinsabaugh, Robert L; Moorhead, Daryl L; Xu, Xiaofeng; Litvak, Marcy E
2017-06-01
The carbon use efficiency of plants (CUE a ) and microorganisms (CUE h ) determines rates of biomass turnover and soil carbon sequestration. We evaluated the hypothesis that CUE a and CUE h counterbalance at a large scale, stabilizing microbial growth (μ) as a fraction of gross primary production (GPP). Collating data from published studies, we correlated annual CUE a , estimated from satellite imagery, with locally determined soil CUE h for 100 globally distributed sites. Ecosystem CUE e , the ratio of net ecosystem production (NEP) to GPP, was estimated for each site using published models. At the ecosystem scale, CUE a and CUE h were inversely related. At the global scale, the apparent temperature sensitivity of CUE h with respect to mean annual temperature (MAT) was similar for organic and mineral soils (0.029°C -1 ). CUE a and CUE e were inversely related to MAT, with apparent sensitivities of -0.009 and -0.032°C -1 , respectively. These trends constrain the ratio μ : GPP (= (CUE a × CUE h )/(1 - CUE e )) with respect to MAT by counterbalancing the apparent temperature sensitivities of the component processes. At the ecosystem scale, the counterbalance is effected by modulating soil organic matter stocks. The results suggest that a μ : GPP value of c. 0.13 is a homeostatic steady state for ecosystem carbon fluxes at a large scale. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
Molecular mechanism and evolution of guanylate kinase regulation by (p)ppGpp
Liu, Kuanqing; Myers, Angela R.; Pisithkul, Tippapha; ...
2015-02-05
The nucleotide (p)ppGpp mediates bacterial stress responses, but its targets and underlying mechanisms of action vary among bacterial species and remain incompletely understood. In this paper, we characterize the molecular interaction between (p)ppGpp and guanylate kinase (GMK), revealing the importance of this interaction in adaptation to starvation. Combining structural and kinetic analyses, we show that (p)ppGpp binds the GMK active site and competitively inhibits the enzyme. The (p)ppGpp-GMK interaction prevents the conversion of GMP to GDP, resulting in GMP accumulation upon amino acid downshift. Abolishing this interaction leads to excess (p)ppGpp and defective adaptation to amino acid starvation. A surveymore » of GMKs from phylogenetically diverse bacteria shows that the (p)ppGpp-GMK interaction is conserved in members of Firmicutes, Actinobacteria, and Deinococcus-Thermus, but not in Proteobacteria, where (p)ppGpp regulates RNA polymerase (RNAP). Finally, we propose that GMK is an ancestral (p)ppGpp target and RNAP evolved more recently as a direct target in Proteobacteria.« less
Huang, Shengli; Liu, Heping; Dahal, Devendra; Jin, Suming; Welp, Lisa R.; Liu, Jinxun; Liu, Shuguang
2013-01-01
In interior Alaska, wildfires change gross primary production (GPP) after the initial disturbance. The impact of fires on GPP is spatially heterogeneous, which is difficult to evaluate by limited point-based comparisons or is insufficient to assess by satellite vegetation index. The direct prefire and postfire comparison is widely used, but the recovery identification may become biased due to interannual climate variability. The objective of this study is to propose a method to quantify the spatially explicit GPP change caused by fires and succession. We collected three Landsat images acquired on 13 July 2004, 5 August 2004, and 6 September 2004 to examine the GPP recovery of burned area from 1987 to 2004. A prefire Landsat image acquired in 1986 was used to reconstruct satellite images assuming that the fires of 1987–2004 had not occurred. We used a light-use efficiency model to estimate the GPP. This model was driven by maximum light-use efficiency (Emax) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR). We applied this model to two scenarios (i.e., an actual postfire scenario and an assuming-no-fire scenario), where the changes in Emax and FPAR were taken into account. The changes in Emax were represented by the change in land cover of evergreen needleleaf forest, deciduous broadleaf forest, and shrub/grass mixed, whose Emax was determined from three fire chronosequence flux towers as 1.1556, 1.3336, and 0.5098 gC/MJ PAR. The changes in FPAR were inferred from NDVI change between the actual postfire NDVI and the reconstructed NDVI. After GPP quantification for July, August, and September 2004, we calculated the difference between the two scenarios in absolute and percent GPP changes. Our results showed rapid recovery of GPP post-fire with a 24% recovery immediately after burning and 43% one year later. For the fire scars with an age range of 2–17 years, the recovery rate ranged from 54% to 95%. In addition to the averaging
Yuan, W.; Liu, S.; Zhou, G.; Tieszen, L.L.; Baldocchi, D.; Bernhofer, C.; Gholz, H.; Goldstein, Allen H.; Goulden, M.L.; Hollinger, D.Y.; Hu, Y.; Law, B.E.; Stoy, Paul C.; Vesala, T.; Wofsy, S.C.
2007-01-01
The quantitative simulation of gross primary production (GPP) at various spatial and temporal scales has been a major challenge in quantifying the global carbon cycle. We developed a light use efficiency (LUE) daily GPP model from eddy covariance (EC) measurements. The model, called EC-LUE, is driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux (used to calculate moisture stress). The EC-LUE model relies on two assumptions: First, that the fraction of absorbed PAR (fPAR) is a linear function of NDVI; Second, that the realized light use efficiency, calculated from a biome-independent invariant potential LUE, is controlled by air temperature or soil moisture, whichever is most limiting. The EC-LUE model was calibrated and validated using 24,349 daily GPP estimates derived from 28 eddy covariance flux towers from the AmeriFlux and EuroFlux networks, covering a variety of forests, grasslands and savannas. The model explained 85% and 77% of the observed variations of daily GPP for all the calibration and validation sites, respectively. A comparison with GPP calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS) indicated that the EC-LUE model predicted GPP that better matched tower data across these sites. The realized LUE was predominantly controlled by moisture conditions throughout the growing season, and controlled by temperature only at the beginning and end of the growing season. The EC-LUE model is an alternative approach that makes it possible to map daily GPP over large areas because (1) the potential LUE is invariant across various land cover types and (2) all driving forces of the model can be derived from remote sensing data or existing climate observation networks.
Impact of Chromophoric Dissolved Organic Matter on UV Inhibition of Primary Productivity in the Sea
NASA Technical Reports Server (NTRS)
Arrigo, Kevin R.; Brown, Christopher W.
1996-01-01
A model was developed to assess the impact of chromophoric dissolved organic matter (CDOM) on phytoplankton production within the euphotic zone. The rate of depth-integrated daily gross primary productivity within the euphotic zone was evaluated as a function of date, latitude, CDONI absorption characteristics, chlorophyll a (chl a) concentration, vertical stratification, and phytoplankton sensitivity to UV radiation (UVR). Results demonstrated that primary production was enhanced in the upper 30 m of the water column by the presence of CDOM, where predicted increases in production due to the removal of damaging UVR more than offset its reduction resulting from the absorption of photosynthetically usable radiation. At greater depths, where little UVR remained, primary production was always reduced due to removal by CDOM of photosynthetically usable radiation. When CDOM was distributed homogeneously within the euphotic zone, the integral over z [(GPP)(sub ez)], was reduced under most bio-optical (i.e. solar zenith angle, and CDOM absorption, and ozone concentration) and photophysiological production at depth was greater than the enhancement of production at the surface.
NASA Technical Reports Server (NTRS)
Cheng, Yen-Ben; Middleton, Elizabeth M.; Zhang, Qingyuan; Huemmrich, Karl F.; Campbell, Petya K. E.; Corp, Lawrence A.; Cook, Bruce D.; Kustas, William P.; Daughtry, Criag S.
2013-01-01
The utilization of remotely sensed observations for light use efficiency (LUE) and tower-based gross primary production (GPP) estimates was studied in a USDA cornfield. Nadir hyperspectral reflectance measurements were acquired at canopy level during a collaborative field campaign conducted in four growing seasons. The Photochemical Reflectance Index (PRI) and solar induced chlorophyll fluorescence (SIF), were derived. SIF retrievals were accomplished in the two telluric atmospheric oxygen absorption features centered at 688 nm (O2-B) and 760 nm (O2-A). The PRI and SIF were examined in conjunction with GPP and LUE determined by flux tower-based measurements. All of these fluxes, environmental variables, and the PRI and SIF exhibited diurnal as well as day-to-day dynamics across the four growing seasons. Consistent with previous studies, the PRI was shown to be related to LUE (r2 = 0.54 with a logarithm fit), but the relationship varied each year. By combining the PRI and SIF in a linear regression model, stronger performances for GPP estimation were obtained. The strongest relationship (r2 = 0.80, RMSE = 0.186 mg CO2/m2/s) was achieved when using the PRI and SIF retrievals at 688 nm. Cross-validation approaches were utilized to demonstrate the robustness and consistency of the performance. This study highlights a GPP retrieval method based entirely on hyperspectral remote sensing observations.
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.
NASA Astrophysics Data System (ADS)
Blonquist, J. M.; Wingate, L.; Ogeé, J.; Bowling, D. R.
2011-12-01
The stable carbon isotope composition of atmospheric CO2 (δ13Ca) can provide useful information on water use efficiency (WUE) dynamics of terrestrial ecosystems and potentially constrain models of CO2 and water fluxes at the land surface. This is due to the leaf-level relationship between photosynthetic 13CO2 discrimination (Δ), which influences δ13Ca, and the ratio of leaf intercellular to atmospheric CO2 mole fractions (Ci / Ca), which is related to WUE and is determined by the balance between C assimilation (CO2 demand) and stomatal conductance (CO2 supply). We used branch-scale Δ derived from tunable diode laser absorption spectroscopy measurements collected in a Maritime pine forest to estimate Ci / Ca variations over an entire growing season. We combined Ci / Ca estimates with rates of gross primary production (GPP) derived from eddy covariance (EC) to estimate canopy-scale stomatal conductance (Gs) and transpiration (T). Estimates of T were highly correlated to T estimates derived from sapflow data (y = 1.22x + 0.08; r2 = 0.61; slope P < 0.001) and T predictions from an ecosystem model (MuSICA) (y = 0.88x - 0.05; r2 = 0.64; slope P < 0.001). As an alternative to estimating T, Δ measurements can be used to estimate GPP by combining Ci / Ca estimates with Gs estimates from sapflow data. Estimates of GPP were determined in this fashion and were highly correlated to GPP values derived from EC (y = 0.82 + 0.07; r2 = 0.61; slope P < 0.001) and GPP predictions from MuSICA (y = 1.10 + 0.42; r2 = 0.50; slope P < 0.001). Results demonstrate that the leaf-level relationship between Δ and Ci / Ca can be extended to the canopy-scale and that Δ measurements have utility for partitioning ecosystem-scale CO2 and water fluxes.
NASA Astrophysics Data System (ADS)
Lowman, L.; Barros, A.
2015-12-01
Tropical cyclones (TCs) are an important source of freshwater input to the SE US eco-hydrologic function. Soil moisture, a temporal integral of precipitation, is critical to plant photosynthesis and carbon assimilation. In this study, we investigate the impact TCs have on gross primary productivity (GPP) in the SE US using the physically-based Duke Coupled Hydrology Model with Vegetation (DCHM-V) which includes coupled water and energy cycles and a biochemical representation of photosynthesis. A parsimonious evaluation of model-estimated GPP against all available AmeriFlux data in the SE US is presented. We characterize the seasonality of vegetation activity in the SE US by simulating water, energy, and carbon fluxes using the DCHM-V at high spatial (4 km) and temporal (30-min) resolution over the period 2002 - 2012. The model is run offline using atmospheric forcing data from NLDAS-2, precipitation from StageIV, and phenology indices from MODIS FPAR/LAI. Analysis of model results show the tendency for low GPP to occur in the Appalachian Mountains during peak summer months when water stress limits stomatal function. We contrast these simulations with model runs where periods of TC activity are replaced with the monthly climatological diurnal cycle from NARR. Results show that the timing and trajectory of TCs are key to understanding their impact on GPP across the SE US. Specifically: 1) Timing of moisture input from TCs greatly influences the vegetation response. TCs during peak summer months increase GPP and years with TCs falling in peak summer months see much higher annual GPP averages; 2) Years of drought and low plant productivity (2006-2007, 2011-2012) in the SE US tend to have TCs that fall later in the year when the additional moisture input does not have a significant impact on vegetation activity; and 3) TC path impacts regional GPP averages. The mountain region shows large inter- and intra-annual variability in plant productivity and high sensitivity to
NASA Astrophysics Data System (ADS)
He, W.; Ju, W.; Chen, H.; Peters, W.; van der Velde, I.; Baker, I. T.; Andrews, A. E.; Zhang, Y.; Launois, T.; Campbell, J. E.; Suntharalingam, P.; Montzka, S. A.
2016-12-01
Carbonyl sulfide (OCS) is a promising novel atmospheric tracer for studying carbon cycle processes. OCS shares a similar pathway as CO2 during photosynthesis but not released through a respiration-like process, thus could be used to partition Gross Primary Production (GPP) from Net Ecosystem-atmosphere CO2 Exchange (NEE). This study uses joint atmospheric observations of OCS and CO2 to constrain GPP and ecosystem respiration (Re). Flask data from tower and aircraft sites over North America are collected. We employ our recently developed CarbonTracker (CT)-Lagrange carbon assimilation system, which is based on the CT framework and the Weather Research and Forecasting - Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model, and the Simple Biosphere model with simulated OCS (SiB3-OCS) that provides prior GPP, Re and plant uptake fluxes of OCS. Derived plant OCS fluxes from both process model and GPP-scaled model are tested in our inversion. To investigate the ability of OCS to constrain GPP and understand the uncertainty propagated from OCS modeling errors to constrained fluxes in a dual-tracer system including OCS and CO2, two inversion schemes are implemented and compared: (1) a two-step scheme, which firstly optimizes GPP using OCS observations, and then simultaneously optimizes GPP and Re using CO2 observations with OCS-constrained GPP in the first step as prior; (2) a joint scheme, which simultaneously optimizes GPP and Re using OCS and CO2 observations. We will evaluate the result using an estimated GPP from space-borne solar-induced fluorescence observations and a data-driven GPP upscaled from FLUXNET data with a statistical model (Jung et al., 2011). Preliminary result for the year 2010 shows the joint inversion makes simulated mole fractions more consistent with observations for both OCS and CO2. However, the uncertainty of OCS simulation is larger than that of CO2. The two-step and joint schemes perform similarly in improving the consistence with
Comparisons of MODIS vegetation index products with biophysical and flux tower measurements
NASA Astrophysics Data System (ADS)
Sirikul, Natthanich
Vegetation indices (VI) play an important role in studies of global climate and biogeochemical cycles, and are also positively related to many biophysical parameters and satellite products, such as leaf area index (LAI), gross primary production (GPP), land surface water index (LSWI) and land surface temperature (LST). In this study we found that VI's had strong relationships with some biophysical products, such as gross primary production, yet were less well correlated with biophysical structural parameters, such as leaf area index. The relationships between MODIS VI's and biophysical field measured LAI showed poor correlation at semi-arid land and broadleaf forest land cover type whereas cropland showed stronger correlations than the other vegetation types. In addition, the relationship between the enhanced vegetation index (EVI)-LAI and normalized difference vegetation index (NDVI)-LAI did not show significant differences. Comparisons of the relationships between the EVI and NDVI with tower-measured GPP from 11 flux towers in North America, showed that MODIS EVI had much stronger relationships with tower-GPP than did NDVI, and EVI was better correlated with the seasonal dynamics of GPP than was NDVI. In addition, there were no significant differences among the 1x1, 3x3 and 7x7 pixel sample sizes. The comparisons of VIs from the 3 MODIS products from which VI's are generated (Standard VI (MOD13)), Nadir Adjusted Surface Reflectance (NBAR (MOD43)), and Surface Reflectance (MOD09)), showed that MODIS NBAR-EVI (MOD43) was best correlated with GPP compared with the other VI products. In addition, the MODIS VI - tower GPP relationships were significantly improved using NBAR-EVI over the more complex canopy structures, such as the broadleaf and needleleaf forests. The relationship of tower-GPP with other MODIS products would be useful in more thorough characterization of some land cover types in which the VI's have encountered problems. The land surface temperature
Fernández-Martínez, Marcos; Vicca, Sara; Janssens, Ivan A; Espelta, Josep Maria; Peñuelas, Josep
2017-01-01
Fruit production (NPP f ), the amount of photosynthates allocated to reproduction (%GPP f ) and their controls for spatial and species-specific variability (e.g. nutrient availability, climate) have been poorly studied in forest ecosystems. We characterized fruit production and its temporal behaviour for several tree species and resolved the effects of gross primary production (GPP), climate and foliar nutrient concentrations. We used data for litterfall and foliar nutrient concentration from 126 European forests and related them to climatic data. GPP was estimated for each forest using a regression model. Mean NPP f ranged from c. 10 to 40 g C m -2 yr -1 and accounted for 0.5-3% of GPP. Forests with higher GPPs produced larger fruit crops. Foliar zinc (Zn) and phosphorus (P) concentrations were associated positively with NPP f , whereas foliar Zn and potassium (K) were negatively related to its temporal variability. Maximum NPP f and interannual variability of NPP f were higher in Fagaceae than in Pinaceae species. NPP f and %GPP f were similar amongst the studied species despite the different reproductive temporal behaviour of Fagaceae and Pinaceae species. We report that foliar concentrations of P and Zn are associated with %GPP f , NPP f and its temporal behaviour. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
Global relation between microwave satellite vegetation products and vegetation productivity
NASA Astrophysics Data System (ADS)
Teubner, Irene E.; Forkel, Matthias; Jung, Martin; Miralles, Diego G.; Dorigo, Wouter A.
2017-04-01
The occurrence of unfavourable environmental conditions like droughts commonly reduces the photosynthetic activity of ecosystems and, hence, their potential to take up carbon from the atmosphere. Ecosystem photosynthetic activity is commonly determined using remote sensing observations in the optical domain, which however have limitations particularly in regions of frequent cloud cover, e.g. the tropics. In this study, we explore the potential of vegetation optical depth (VOD) from microwave satellite observations as an alternative source for assessing vegetation productivity. VOD serves as an estimate for vegetation density and water content, which has an impact on plant physiological processes and hence should potentially provide a link to gross primary production (GPP). However, to date, it is unclear how microwave-retrieved VOD data and GPP data are related. We compare seasonal dynamics and anomalies of VOD retrievals from different satellite sensors and microwave frequencies with site level and global GPP estimates. We use VOD observations from active (ASCAT) and passive microwave sensors (AMSR-E, SMOS). We include eddy covariance measurements from the FLUXNET2015 dataset to assess the VOD products at site level. For a global scale analysis, we use the solar-induced chlorophyll fluorescence (SIF) observations from GOME-2 as a proxy for GPP and the FLUXCOM GPP product, which presents an upscaling of site measurements based on remote sensing data. Our results demonstrate that in general a good agreement between VOD and GPP or SIF exists. However, the strength of these relations depends on the microwave frequency, land cover type, and the time within the growing season. Correlations between anomalies of VOD and GPP or SIF support the assumption that microwave-derived VOD can be used to monitor vegetation productivity dynamics. The study is performed as part of the EOWAVE project funded by the Vienna University of Technology (http://eowave.geo.tuwien.ac.at/) and
NASA Astrophysics Data System (ADS)
Kwon, Youngsang
As evidence of global warming continues to increase, being able to predict the relationship between forest growth rate and climate factors will be vital to maintain the sustainability and productivity of forests. Comprehensive analyses of forest primary production across the eastern US were conducted using remotely sensed MODIS and field-based FIA datasets. This dissertation primarily explored spatial patterns of gross and net carbon uptake in the eastern USA, and addressed three objectives. 1) Examine the use of pixel- and plot-scale screening variables to validate MODIS GPP predictions with Forest Inventory and Analysis (FIA) NPP measures. 2) Assess the net primary production (NPP) from MODIS and FIA at increasing levels of spatial aggregation using a hexagonal tiling system. 3) Assess the carbon use efficiency (CUE) calculated using a direct ratio of MODIS NPP to MODIS GPP and a standardized ratio of FIA NPP to MODIS GPP. The first objective was analyzed using total of 54,969 MODIS pixels and co-located FIA plots to validate MODIS GPP estimates. Eight SVs were used to test six hypotheses about the conditions under which MODIS GPP would be most strongly validated. SVs were assessed in terms of the tradeoff between improved relations and reduced number of samples. MODIS seasonal variation and FIA tree density were the two most efficient SVs followed by basic quality checks for each data set. The sequential application of SVs provided an efficient dataset of 17,090 co-located MODIS pixels and FIA plots, that raised the Pearson's correlation coefficient from 0.01 for the complete dataset of 54,969 plots to 0.48 for this screened subset of 17,090 plots. The second objective was addressed by aggregating data over increasing spatial extents so as to not lose plot- and pixel-level information. These data were then analyzed to determine the optimal scale with which to represent the spatial pattern of NPP. The results suggested an optimal scale of 390 km2. At that scale
NASA Astrophysics Data System (ADS)
Zhao, M.; Running, S.; Heinsch, F. A.
2006-12-01
Since the first Earth Observing System (EOS) satellite Terra was launched in December 1999 and Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard Terra began to provide data in February 2000, we have had six-year MODIS global 1-km terrestrial Gross and Net Primary Production (GPP &NPP) datasets. In this article, we present the variations (seasonality and inter-annual variability) of global GPP/NPP from the latest improved Collection 4.8 (C4.8) MODIS datasets for the past six-year (2000 - 2005), as well as improvements of the algorithm, validations of GPP and NPP. Validation results show that the C4.8 data have higher accuracy and quality than the previous version. Analyses of the variations in GPP/NPP show that GPP not only can reflect strong seasonality of photosynthesis activities by plants in mid- and high-latitude, but importantly, can reveal enhanced growth of Amazon rainforests during dry season, consistent with the reports by Huete et al. (2006) on GRL. Spatially, plants over mid- and high-latitude (north to 22.5°N) are the major contributor of global GPP seasonality. Inter-annual variability of MODIS NPP for 2000 - 2005 reveals the negative effects of major droughts on carbon sequestration at the regional and continental scales. A striking phenomenon is that the severe drought in 2005 over Amazon reduced NPP, indicating water availability becomes the dominant limiting factor rather than solar radiation under normal conditions. GMAO and NCEP driven global total NPPs have the similar interannual anomalies, and they generally follow the inverted CO2 growth rate anomaly with correlation of 0.85 and 0.91, respectively, which are higher than the correlation of 0.7 found by Nemani et al. (2003) on Science. Though there are only 6 years of MODIS data, results show that global NPP decreased from 2000 to 2005, and spatially most decreased NPP areas are in tropic and south hemisphere.
NASA Astrophysics Data System (ADS)
Tsujimoto, K.; Kato, T.; Hirano, T.; Saitoh, T. M.; Nagai, S.; Akitsu, T.; Nasahara, K. N.
2015-12-01
Chlorophyll fluorescence (ChlF) is emitted from chlorophyll a and b to release the excess sun-light energy. Recently, ChlF has been utilized to represent the ecosystem photosynthetic activity, i.e. gross primary production (GPP), by the satellite remote-sensing studies (e.g. Frankenberg et al., 2011). Despite its high expectation, small number of ecosystem-level ChlF observation at the ground reduces its availability. The aim of this study is to clarify the relationships between ChlF, and photosynthesis and light use efficiency (LUE) by the ground based measurement in the forest. The observations were carried out in the evergreen coniferous forest in Takayama, Japan, from March 2008 to February 2009. Downward and upward spectral radiances were measured with hemispherical spectroradiometer (MS-700, Eko Instruments, Japan) mounted at 30m-high above the ground surface. We calculated Sun-Induced fluorescence (FS) around the O2-A band (760 nm) from the spectral data with the Fraunhofer Line Depth method. The GPP was calculated from the carbon fluxes measured with eddy covariance at the top of the tower. FS showed the strong correlation to GPP linearly in the diurnal course (sunny day (8 August, 2008): r2 = 0.81, cloudy day (28 July, 2008): r2 = 0.87). In addition, GPP was fitted against FS by rectangular hyperbolic curve. (r2 = 0.87 (daily)). We also investigated the relationship between FS and LUE in daily averages. The FS-LUE relationship could be regressed by logarithm curve for each month (r2 = 0.46 ˜0.95). The seasonal changes in the regression coefficients for FS-GPP and FS-LUE curves were thought to be induced by the seasonal variation in the temperature-dependency of photosynthesis and the phenology. We conclude that FS can be utilized to estimate GPP and LUE in evergreen forest, and that relationship between FS and GPP is influenced by environmental factors such as PAR and air temperature.Chlorophyll fluorescence (ChlF) is emitted from chlorophyll a and b to
Ryan, Edmund M; Ogle, Kiona; Peltier, Drew; Walker, Anthony P; De Kauwe, Martin G; Medlyn, Belinda E; Williams, David G; Parton, William; Asao, Shinichi; Guenet, Bertrand; Harper, Anna B; Lu, Xingjie; Luus, Kristina A; Zaehle, Sönke; Shu, Shijie; Werner, Christian; Xia, Jianyang; Pendall, Elise
2017-08-01
Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO 2 (eCO 2 ) and warming requires accurate quantification of gross primary production (GPP), the largest flux of C in the global C cycle. We evaluated 6 years (2007-2012) of flux-derived GPP data from the Prairie Heating and CO 2 Enrichment (PHACE) experiment, situated in a grassland in Wyoming, USA. The GPP data were used to calibrate a light response model whose basic formulation has been successfully used in a variety of ecosystems. The model was extended by modeling maximum photosynthetic rate (A max ) and light-use efficiency (Q) as functions of soil water, air temperature, vapor pressure deficit, vegetation greenness, and nitrogen at current and antecedent (past) timescales. The model fits the observed GPP well (R 2 = 0.79), which was confirmed by other model performance checks that compared different variants of the model (e.g. with and without antecedent effects). Stimulation of cumulative 6-year GPP by warming (29%, P = 0.02) and eCO 2 (26%, P = 0.07) was primarily driven by enhanced C uptake during spring (129%, P = 0.001) and fall (124%, P = 0.001), respectively, which was consistent across years. Antecedent air temperature (Tair ant ) and vapor pressure deficit (VPD ant ) effects on A max (over the past 3-4 days and 1-3 days, respectively) were the most significant predictors of temporal variability in GPP among most treatments. The importance of VPD ant suggests that atmospheric drought is important for predicting GPP under current and future climate; we highlight the need for experimental studies to identify the mechanisms underlying such antecedent effects. Finally, posterior estimates of cumulative GPP under control and eCO 2 treatments were tested as a benchmark against 12 terrestrial biosphere models (TBMs). The narrow uncertainties of these data-driven GPP estimates suggest that they could be useful semi
NASA Technical Reports Server (NTRS)
Zhang, Qingyuan; Middleton, Elizabeth M.; Cheng, Yen-Ben; Huemmrich, K. Fred; Cook, Bruce D.; Corp, Lawrence A.; Kustas, William P.; Russ, Andrew L.; Prueger, John H.; Yao, Tian
2016-01-01
The concept of light use efficiency (Epsilon) and the concept of fraction of photosynthetically active ration (PAR) absorbed for vegetation photosynthesis (PSN), i.e., fAPAR (sub PSN), have been widely utilized to estimate vegetation gross primary productivity (GPP). It has been demonstrated that the photochemical reflectance index (PRI) is empirically related to e. An experimental US Department of Agriculture (USDA) cornfield in Maryland was selected as our study field. We explored the potential of integrating fAPAR(sub chl) (defined as the fraction of PAR absorbed by chlorophyll) and nadir PRI (PRI(sub nadir)) to predict cornfield daily GPP. We acquired nadir or near-nadir EO-1/Hyperion satellite images that covered the cornfield and took nadir in-situ field spectral measurements. Those data were used to derive the PRI(sub nadir) and fAPAR (sub chl). The fAPAR (sub chl) is retrieved with the advanced radiative transfer model PROSAIL2 and the Metropolis approach, a type of Markov Chain Monte Carlo (MCMC) estimation procedure. We define chlorophyll light use efficiency Epsilon (sub chl) as the ratio of vegetation GPP as measured by eddy covariance techniques to PAR absorbed by chlorophyll (Epsilon(sub chl) = GPP/APAR (sub chl). Daily Epsilon (sub chl) retrieved with the EO-1 Hyperion images was regressed with a linear equation of PRI (sub nadir) Epsilon (sub chl) = Alpha × PRI (sub nadir) + Beta). The satellite Epsilon(sub chl- PRI (sub nadir) linear relationship for the cornfield was implemented to develop an integrated daily GPP model [GPP = (Alpha × PRI(sub nadir) + Beta) × fAPAR (sub chl) × PAR], which was evaluated with fAPAR (sub chl) and PRI (sub nadir) retrieved from field measurements. Daily GPP estimated with this fAPAR (sub chl-) PRI (nadir) integration model was strongly correlated with the observed tower in-situ daily GPP (R(sup 2) = 0.93); with a root mean square error (RMSE) of 1.71 g C mol-(sup -1) PPFD and coefficient of variation (CV) of 16
NASA Astrophysics Data System (ADS)
Rodeghiero, Mirco; Martinez, Cristina; Gianelle, Damiano; Camin, Federica; Zanotelli, Damiano; Magnani, Federico
2013-04-01
Terrestrial plant carbon partitioning to above- and below-ground compartments can be better understood by integrating studies on biomass allocation and estimates of root carbon input based on the use of stable isotopes. These experiments are essential to model ecosystem's metabolism and predict the effects of global change on carbon cycling. Using in-growth soil cores in conjunction with the 13C natural abundance method we quantified net plant-derived root carbon input into the soil, which has been pointed out as the main unaccounted NPP (net primary productivity) component. Four land use types located in the Trentino Region (northern Italy) and representing a range of aboveground net primary productivity (ANPP) values (155-868 gC m-2 y-1) were investigated: conifer forest, apple orchard, vineyard and grassland. Cores, filled with soil of a known C4 isotopic signature were inserted at 18 sampling points for each site and left in place for twelve months. After extraction, cores were analysed for %C and d13C, which were used to calculate the proportion of new plant-derived root C input by applying a mass balance equation. The GPP (gross primary productivity) of each ecosystem was determined by the eddy covariance technique whereas ANPP was quantified with a repeated inventory approach. We found a strong and significant relationship (R2 = 0.93; p=0.03) between ANPP and the fraction of GPP transferred to the soil as root C input across the investigated sites. This percentage varied between 10 and 25% of GPP with the grassland having the lowest value and the apple orchard the highest. Mechanistic ecosystem carbon balance models could benefit from this general relationship since ANPP is routinely and easily measured at many sites. This result also suggests that by quantifying site-specific ANPP, root carbon input can be reliably estimated, as opposed to using arbitrary root/shoot ratios which may under- or over-estimate C partitioning.
NASA Astrophysics Data System (ADS)
Miller, D. L.; Roberts, D. A.; Clarke, K. C.; Peters, E. B.; Menzer, O.; Lin, Y.; McFadden, J. P.
2017-12-01
Gross primary productivity (GPP) is commonly estimated with remote sensing techniques over large regions of Earth; however, urban areas are typically excluded due to a lack of light use efficiency (LUE) parameters specific to urban vegetation and challenges stemming from the spatial heterogeneity of urban land cover. In this study, we estimated GPP during the middle of the growing season, both within and among vegetation and land use types, in the Minneapolis-Saint Paul, Minnesota metropolitan region (52.1% vegetation cover). We derived LUE parameters for specific urban vegetation types using estimates of GPP from eddy covariance and tree sap flow-based CO2 flux observations and fraction of absorbed photosynthetically active radiation derived from 2-m resolution WorldView-2 satellite imagery. We produced a pixel-based hierarchical land cover classification of built-up and vegetated urban land cover classes distinguishing deciduous broadleaf trees, evergreen needleleaf trees, turf grass, and golf course grass from impervious and soil surfaces. The overall classification accuracy was 80% (kappa = 0.73). The mapped GPP estimates were within 12% of estimates from independent tall tower eddy covariance measurements. Mean GPP estimates ( ± standard deviation; g C m-2 day-1) for the entire study area from highest to lowest were: golf course grass (11.77 ± 1.20), turf grass (6.05 ± 1.07), evergreen needleleaf trees (5.81 ± 0.52), and deciduous broadleaf trees (2.52 ± 0.25). Turf grass GPP had a larger coefficient of variation (0.18) than the other vegetation classes ( 0.10). Mean land use GPP for the full study area varied as a function of percent vegetation cover. Urban GPP in general, both including and excluding non-vegetated areas, was less than half that of literature estimates for nearby natural forests and grasslands.
NASA Astrophysics Data System (ADS)
Ichii, K.; Kondo, M.; Ueyama, M.; Kato, T.; Ito, A.; Sasai, T.; Sato, H.; Kobayashi, H.; Saigusa, N.
2014-12-01
Long term record of satellite-based terrestrial vegetation are important to evaluate terrestrial carbon cycle models. In this study, we demonstrate how multiple satellite observation can be used for evaluating past changes in gross primary productivity (GPP) and detecting robust anomalies in terrestrial carbon cycle in Asia through our model-data synthesis analysis, Asia-MIP. We focused on the two different temporal coverages: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2011; data intensive period) scales. We used a NOAA/AVHRR NDVI record for long-term analysis and multiple satellite data and products (e.g. Terra-MODIS, SPOT-VEGETATION) as historical satellite data, and multiple terrestrial carbon cycle models (e.g. BEAMS, Biome-BGC, ORCHIDEE, SEIB-DGVM, and VISIT). As a results of long-term (30 years) trend analysis, satellite-based time-series data showed that approximately 40% of the area has experienced a significant increase in the NDVI, while only a few areas have experienced a significant decreasing trend over the last 30 years. The increases in the NDVI were dominant in the sub-continental regions of Siberia, East Asia, and India. Simulations using the terrestrial biosphere models also showed significant increases in GPP, similar to the results for the NDVI, in boreal and temperate regions. A modeled sensitivity analysis showed that the increases in GPP are explained by increased temperature and precipitation in Siberia. Precipitation, solar radiation, CO2fertilization and land cover changes are important factors in the tropical regions. However, the relative contributions of each factor to GPP changes are different among the models. Year-to-year variations of terrestrial GPP were overall consistently captured by the satellite data and terrestrial carbon cycle models if the anomalies are large (e.g. 2003 summer GPP anomalies in East Asia and 2002 spring GPP anomalies in mid to high latitudes). The behind mechanisms can be consistently
Du, Ling; Mikle, Nathaniel; Zou, Zhenhua; Huang, Yuanyuan; Shi, Zheng; Jiang, Lifen; McCarthy, Heather R; Liang, Junyi; Luo, Yiqi
2018-07-01
Quantifying the ecological patterns of loss of ecosystem function in extreme drought is important to understand the carbon exchange between the land and atmosphere. Rain-use efficiency [RUE; gross primary production (GPP)/precipitation] acts as a typical indicator of ecosystem function. In this study, a novel method based on maximum rain-use efficiency (RUE max ) was developed to detect losses of ecosystem function globally. Three global GPP datasets from the MODIS remote sensing data (MOD17), ground upscaling FLUXNET observations (MPI-BGC), and process-based model simulations (BESS), and a global gridded precipitation product (CRU) were used to develop annual global RUE datasets for 2001-2011. Large, well-known extreme drought events were detected, e.g. 2003 drought in Europe, 2002 and 2011 drought in the U.S., and 2010 drought in Russia. Our results show that extreme drought-induced loss of ecosystem function could impact 0.9% ± 0.1% of earth's vegetated land per year and was mainly distributed in semi-arid regions. The reduced carbon uptake caused by functional loss (0.14 ± 0.03 PgC/yr) could explain >70% of the interannual variation in GPP in drought-affected areas (p ≤ 0.001). Our results highlight the impact of ecosystem function loss in semi-arid regions with increasing precipitation variability and dry land expansion expected in the future. Copyright © 2018 Elsevier B.V. All rights reserved.
Alemohammad, Seyed Hamed; Fang, Bin; Konings, Alexandra G; Aires, Filipe; Green, Julia K; Kolassa, Jana; Miralles, Diego; Prigent, Catherine; Gentine, Pierre
2017-01-01
A new global estimate of surface turbulent fluxes, latent heat flux (LE) and sensible heat flux (H), and gross primary production (GPP) is developed using a machine learning approach informed by novel remotely sensed Solar-Induced Fluorescence (SIF) and other radiative and meteorological variables. This is the first study to jointly retrieve LE, H and GPP using SIF observations. The approach uses an artificial neural network (ANN) with a target dataset generated from three independent data sources, weighted based on triple collocation (TC) algorithm. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides estimates of LE, H and GPP from 2007 to 2015 at 1° × 1° spatial resolution and on monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are evaluated using eddy covariance tower estimates from FLUXNET network across various climates and conditions. When compared to eddy covariance estimates, WECANN typically outperforms other products, particularly for sensible and latent heat fluxes. Analysing WECANN retrievals across three extreme drought and heatwave events demonstrates the capability of the retrievals in capturing the extent of these events. Uncertainty estimates of the retrievals are analysed and the inter-annual variability in average global and regional fluxes show the impact of distinct climatic events - such as the 2015 El Niño - on surface turbulent fluxes and GPP.
NASA Astrophysics Data System (ADS)
Liu, S.; Zhuang, Q.
2016-12-01
Climatic change affects the plant physiological and biogeochemistry processes, and therefore on the ecosystem water use efficiency (WUE). Therefore, a comprehensive understanding of WUE would help us understand the adaptability of ecosystem to variable climate conditions. Tree ring data have great potential in addressing the forest response to climatic changes compared with mechanistic model simulations, eddy flux measurement and manipulative experiments. Here, we collected the tree ring isotopic carbon data in 12 boreal forest sites to develop a multiple linear regression model, and the model was extrapolated to the whole boreal region to obtain the WUE spatial and temporal variation from 1948 to 2010. Two algorithms were also used to estimate the inter-annual gross primary productivity (GPP) based on our derived WUE. Our results demonstrated that most of boreal regions showed significant increasing WUE trend during the period except parts of Alaska. The spatial averaged annual mean WUE was predicted to increase by 13%, from 2.3±0.4 g C kg-1 H2O at 1948 to 2.6±0.7 g C kg-1 H2O at 2012, which was much higher than other land surface models. Our predicted GPP by the WUE definition algorithm was comparable with site observation, while for the revised light use efficiency algorithm, GPP estimation was higher than site observation as well as than land surface models. In addition, the increasing GPP trends by two algorithms were similar with land surface model simulations. This is the first study to evaluate regional WUE and GPP in forest ecosystem based on tree ring data and future work should consider other variables (elevation, nitrogen deposition) that influence tree ring isotopic signals and the dual-isotope approach may help improve predicting the inter-annual WUE variation.
NASA Astrophysics Data System (ADS)
Hu, Z.
2017-12-01
Climate change is predicted to cause dramatic variability in precipitation regime, not only in terms of change in annual precipitation amount, but also in precipitation seasonal distribution and precipitation event characteristics (high frenquency extrem precipitation, larger but fewer precipitation events), which combined to influence productivity of grassland in arid and semiarid regions. In this study, combining remote sensing products with in-situ measurements of aboveground net primary productivity (ANPP) and gross primary productivity (GPP) data from eddy covariance system in grassland of northern China, we quantified the effects of spatio-temporal vairation in precipitation on productivity from local sites to region scale. We found that, for an individual precipitation event, the duration of GPP-response to the individual precipitation event and the maximum absolute GPP response induced by the individual precipitation event increased linearly with the size of precipitation events. Comparison of the productivity-precipitation relationships between multi-sites determined that the predominant characteristics of precipitation events (PEC) that affected GPP differed remarkably between the water-limited temperate steppe and the temperature-limited alpine meadow. The number of heavy precipitation events (>10 mm d-1) was the most important PEC to impact GPP in the temperate steppe through affecting soil moisture at different soil profiles, while precipitation interval was the factor that affected GPP most in the alpine meadow via its effects on temperature. At the region scale, shape of ANPP-precipitation relationship varies with distinct spatial scales, and besides annual precipitation, precipitation seasonal distribution also has comparable impacts on spatial variation in ANPP. Temporal variability in ANPP was lower at both the dry and wet end, and peaked at a precipitation of 243.1±3.5mm, which is the transition region between typical steppe and desert steppe
NASA Astrophysics Data System (ADS)
Verma, Manish; Schimel, David; Evans, Bradley; Frankenberg, Christian; Beringer, Jason; Drewry, Darren T.; Magney, Troy; Marang, Ian; Hutley, Lindsay; Moore, Caitlin; Eldering, Annmarie
2017-03-01
Recent studies have utilized coarse spatial and temporal resolution remotely sensed solar-induced fluorescence (SIF) for modeling terrestrial gross primary productivity (GPP) at regional scales. Although these studies have demonstrated the potential of SIF, there have been concerns about the ecophysiological basis of the relationship between SIF and GPP in different environmental conditions. Launched in 2014, the Orbiting Carbon Observatory-2 (OCO-2) has enabled fine-scale (1.3 by 2.5 km) retrievals of SIF that are comparable with measurements recorded at eddy covariance towers. In this study, we examine the effect of environmental conditions on the relationship of OCO-2 SIF with tower GPP over the course of a growing season at a well-characterized natural grassland site. Combining OCO-2 SIF and eddy covariance tower data with a canopy radiative transfer and an ecosystem model, we also assess the potential of OCO-2 SIF to constrain the estimates of Vcmax, one of the most important parameters in ecosystem models. Based on the results, we suggest that although environmental conditions play a role in determining the nature of relationship between SIF and GPP, overall, the linear relationship is more robust at ecosystem scale than the theory based on leaf-level processes might suggest. Our study also shows that the ability of SIF to constrain Vcmax is weak at the selected site.
From COS ecosystem fluxes to GPP: integrating soil, branch and ecosystem fluxes.
NASA Astrophysics Data System (ADS)
Kooijmans, L.; Maseyk, K. S.; Vesala, T.; Mammarella, I.; Baker, I. T.; Seibt, U.; Sun, W.; Aalto, J.; Franchin, A.; Kolari, P.; Keskinen, H.; Levula, J.; Chen, H.
2016-12-01
The close coupling of Carbonyl Sulfide (COS) and CO2 due to a similar uptake pathway into plant stomata makes COS a promising new tracer that can potentially be used to partition the Net Ecosystem Exchange into gross primary production (GPP) and respiration. Although ecosystem-scale measurements have been made at several sites, the contribution of different ecosystem components to the total COS budget is often unknown. Besides that, the average Leaf Relative Uptake (LRU) ratio needs to be better determined to accurately translate COS ecosystem fluxes into GPP estimates when the simple linear correlation between GPP estimates and COS plant uptake is used. We performed two campaigns in the summer of 2015 and 2016 at the SMEAR II site in Hyytiälä, Finland to provide better constrained COS flux data for boreal forests. A combination of COS measurements were made during both years, i.e. atmospheric profile concentrations up to 125 m, eddy-covariance fluxes and soil chamber fluxes. In addition to these, branch chamber measurements were done in 2016 in an attempt to observe the LRU throughout the whole season. The LRU ratio shows an exponential correlation with photosynthetic active radiation (PAR) but is constant for PAR levels above 500 µmol m-2 s-1. Mid-day LRU values are 1.0 (aspen) and 1.5 (pine). The correlation between LRU and PAR can be explained by the fact that COS is hydrolyzed with the presence of the enzyme carbonic anhydrase, and is not light dependent, whereas the photosynthetic uptake of CO2 is. We observed nighttime fluxes on the order of 25-30 % of the daily maximum COS uptake. Soils are a small sink of COS and contribute to 3 % of the total ecosystem COS flux during daytime. In a comparison between observed and simulated fluxes from the Simple Biosphere (SiB) model, the modelled COS and CO2 ecosystem fluxes are on average 40 % smaller than the observed fluxes, however, the Ecosystem Relative Uptake (ERU) ratios are identical at a value of 1.9 ± 0
NASA Astrophysics Data System (ADS)
Jaafar, H. H.; Ahmad, F. A.
2015-04-01
In semi-arid areas within the MENA region, food security problems are the main problematic imposed. Remote sensing can be a promising too early diagnose food shortages and further prevent the population from famine risks. This study is aimed at examining the possibility of forecasting yield before harvest from remotely sensed MODIS-derived Enhanced Vegetation Index (EVI), Net photosynthesis (net PSN), and Gross Primary Production (GPP) in semi-arid and arid irrigated agro-ecosystems within the conflict affected country of Syria. Relationships between summer yield and remotely sensed indices were derived and analyzed. Simple regression spatially-based models were developed to predict summer crop production. The validation of these models was tested during conflict years. A significant correlation (p<0.05) was found between summer crop yield and EVI, GPP and net PSN. Results indicate the efficiency of remotely sensed-based models in predicting summer yield, mostly for cotton yields and vegetables. Cumulative summer EVI-based model can predict summer crop yield during crisis period, with deviation less than 20% where vegetables are the major yield. This approach prompts to an early assessment of food shortages and lead to a real time management and decision making, especially in periods of crisis such as wars and drought.
Barbosa, Jomar M; Asner, Gregory P; Hughes, R Flint; Johnson, M Tracy
2017-03-01
Plant invasion typically occurs within a landscape-scale framework of abiotic and biotic conditions, often resulting in emergent feedbacks among environment, ecosystem functions, and the dominance of invasive species. Understanding the mechanisms underlying successful invasions is an important component of conservation and management efforts, but this has been poorly investigated in a spatially explicit manner. Knowing where and why invasion patterns change throughout the landscape enables managers to use context-specific controls on the spread of invasive species. Using high-resolution airborne imaging spectroscopy, we studied plant performance in growth within and across landscapes to examine the dominance and spatial distribution of an invasive tree, Psidium cattleianum (strawberry guava), in heterogeneous environmental conditions of a submontane Hawaiian tropical forest. We assessed invader performance using the GPP ratio index, which is the relative difference in remotely sensed estimates of gross primary productivity between canopies of guava and canopies of the invaded plant community. In addition, we used airborne LiDAR data to evaluate the impacts of guava invasion on the forest aboveground carbon density in different environments. Structural equation modeling revealed that substrate type and elevation above sea level interact and amplify landscape-scale differences in productivity between the invasive species and the host plant community (GPP ratio); differences that ultimately control levels of dominance of guava. We found shifts in patterns of forest carbon storage based on both gradual increase of invader dominance and changes in environmental conditions. Overall, our results demonstrate that the remotely sensed index defined as the GPP ratio provided an innovative spatially explicit approach to track and predict the success of invasive plants based in their canopy productivity, particularly within a landscape-scale framework of varying environmental
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
NASA Astrophysics Data System (ADS)
von Buttlar, Jannis; Zscheischler, Jakob; Rammig, Anja; Sippel, Sebastian; Reichstein, Markus; Knohl, Alexander; Jung, Martin; Menzer, Olaf; Altaf Arain, M.; Buchmann, Nina; Cescatti, Alessandro; Gianelle, Damiano; Kiely, Gerard; Law, Beverly E.; Magliulo, Vincenzo; Margolis, Hank; McCaughey, Harry; Merbold, Lutz; Migliavacca, Mirco; Montagnani, Leonardo; Oechel, Walter; Pavelka, Marian; Peichl, Matthias; Rambal, Serge; Raschi, Antonio; Scott, Russell L.; Vaccari, Francesco P.; van Gorsel, Eva; Varlagin, Andrej; Wohlfahrt, Georg; Mahecha, Miguel D.
2018-03-01
Extreme climatic events, such as droughts and heat stress, induce anomalies in ecosystem-atmosphere CO2 fluxes, such as gross primary production (GPP) and ecosystem respiration (Reco), and, hence, can change the net ecosystem carbon balance. However, despite our increasing understanding of the underlying mechanisms, the magnitudes of the impacts of different types of extremes on GPP and Reco within and between ecosystems remain poorly predicted. Here we aim to identify the major factors controlling the amplitude of extreme-event impacts on GPP, Reco, and the resulting net ecosystem production (NEP). We focus on the impacts of heat and drought and their combination. We identified hydrometeorological extreme events in consistently downscaled water availability and temperature measurements over a 30-year time period. We then used FLUXNET eddy covariance flux measurements to estimate the CO2 flux anomalies during these extreme events across dominant vegetation types and climate zones. Overall, our results indicate that short-term heat extremes increased respiration more strongly than they downregulated GPP, resulting in a moderate reduction in the ecosystem's carbon sink potential. In the absence of heat stress, droughts tended to have smaller and similarly dampening effects on both GPP and Reco and, hence, often resulted in neutral NEP responses. The combination of drought and heat typically led to a strong decrease in GPP, whereas heat and drought impacts on respiration partially offset each other. Taken together, compound heat and drought events led to the strongest C sink reduction compared to any single-factor extreme. A key insight of this paper, however, is that duration matters most: for heat stress during droughts, the magnitude of impacts systematically increased with duration, whereas under heat stress without drought, the response of Reco over time turned from an initial increase to a downregulation after about 2 weeks. This confirms earlier theories that
DOE Office of Scientific and Technical Information (OSTI.GOV)
Alemohammad, Seyed Hamed; Fang, Bin; Konings, Alexandra G.
A new global estimate of surface turbulent fluxes, latent heat flux (LE) and sensible heat flux ( H), and gross primary production (GPP) is developed using a machine learning approach informed by novel remotely sensed solar-induced fluorescence (SIF) and other radiative and meteorological variables. This is the first study to jointly retrieve LE, H, and GPP using SIF observations. The approach uses an artificial neural network (ANN) with a target dataset generated from three independent data sources, weighted based on a triple collocation (TC) algorithm. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides estimatesmore » of LE, H, and GPP from 2007 to 2015 at 1° × 1° spatial resolution and at monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are evaluated using eddy covariance tower estimates from the FLUXNET network across various climates and conditions. When compared to eddy covariance estimates, WECANN typically outperforms other products, particularly for sensible and latent heat fluxes. Analyzing WECANN retrievals across three extreme drought and heat wave events demonstrates the capability of the retrievals to capture the extent of these events. Uncertainty estimates of the retrievals are analyzed and the interannual variability in average global and regional fluxes shows the impact of distinct climatic events – such as the 2015 El Niño – on surface turbulent fluxes and GPP.« less
Alemohammad, Seyed Hamed; Fang, Bin; Konings, Alexandra G.; ...
2017-09-20
A new global estimate of surface turbulent fluxes, latent heat flux (LE) and sensible heat flux ( H), and gross primary production (GPP) is developed using a machine learning approach informed by novel remotely sensed solar-induced fluorescence (SIF) and other radiative and meteorological variables. This is the first study to jointly retrieve LE, H, and GPP using SIF observations. The approach uses an artificial neural network (ANN) with a target dataset generated from three independent data sources, weighted based on a triple collocation (TC) algorithm. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides estimatesmore » of LE, H, and GPP from 2007 to 2015 at 1° × 1° spatial resolution and at monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are evaluated using eddy covariance tower estimates from the FLUXNET network across various climates and conditions. When compared to eddy covariance estimates, WECANN typically outperforms other products, particularly for sensible and latent heat fluxes. Analyzing WECANN retrievals across three extreme drought and heat wave events demonstrates the capability of the retrievals to capture the extent of these events. Uncertainty estimates of the retrievals are analyzed and the interannual variability in average global and regional fluxes shows the impact of distinct climatic events – such as the 2015 El Niño – on surface turbulent fluxes and GPP.« less
NASA Astrophysics Data System (ADS)
Hamed Alemohammad, Seyed; Fang, Bin; Konings, Alexandra G.; Aires, Filipe; Green, Julia K.; Kolassa, Jana; Miralles, Diego; Prigent, Catherine; Gentine, Pierre
2017-09-01
A new global estimate of surface turbulent fluxes, latent heat flux (LE) and sensible heat flux (H), and gross primary production (GPP) is developed using a machine learning approach informed by novel remotely sensed solar-induced fluorescence (SIF) and other radiative and meteorological variables. This is the first study to jointly retrieve LE, H, and GPP using SIF observations. The approach uses an artificial neural network (ANN) with a target dataset generated from three independent data sources, weighted based on a triple collocation (TC) algorithm. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides estimates of LE, H, and GPP from 2007 to 2015 at 1° × 1° spatial resolution and at monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are evaluated using eddy covariance tower estimates from the FLUXNET network across various climates and conditions. When compared to eddy covariance estimates, WECANN typically outperforms other products, particularly for sensible and latent heat fluxes. Analyzing WECANN retrievals across three extreme drought and heat wave events demonstrates the capability of the retrievals to capture the extent of these events. Uncertainty estimates of the retrievals are analyzed and the interannual variability in average global and regional fluxes shows the impact of distinct climatic events - such as the 2015 El Niño - on surface turbulent fluxes and GPP.
NASA Astrophysics Data System (ADS)
Migliavacca, Mirco
2017-04-01
Recent studies have shown how human induced N/P imbalances affect essential ecosystem processes, and might be particularly important in water-limited ecosystems. Hyperspectral information can be used to directly infer nutrient-induces variation in structural and functional changes of vegetation under different nutrient availability. Among those, sun-induced fluorescence in the far-red region provides a new non-invasive measurement approach that has the potential to quantify dynamic changes in light-use efficiency and photosynthetic carbon dioxide uptake (Gross Primary Production, GPP). However, the mechanistic link between GPP and sun-induced fluorescence under different environmental conditions is not completely understood. In this contribution we investigated the structural and functional factors controlling the emission of SIF at 760 nm in a Mediterranean grassland with different levels of nutrient availability (Nitrogen (N), Phosphorous (P), and Nitrogen and Phosphorous (NP)). We showed how nutrient-induced changes in canopy structure (i.e. changes in plant forms abundance that influence leaf inclination distribution function, LIDF) and functional traits (e.g. nitrogen content per dry mass of leaves, N%, Chlorophyll ab concentration - Cab, and maximum carboxylation capacity, Vcmax) affected the observed relationship between SIF and GPP. Simultaneous measurements of canopy scale GPP and SIF were conducted with transparent transient-state canopy chambers and narrow-band spectrometers, respectively. To disentangle the main drivers of the GPP-SIF relationship we performed a factorial modeling exercise with the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) model. We conclude that the addition of nutrients imposed a change in the abundance of different plant forms and biochemistry of the canopy. This lead to changes in canopy structure (leaf area index, leaf inclinaton distribution function LIDF parameters) and functional traits (N%, P%, Cab and Vcmax
NASA Astrophysics Data System (ADS)
Verma, Manish K.
Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in
Juengert, Janina R.; Borisova, Marina; Wolz, Christiane; Brigham, Christopher J.; Sinskey, Anthony J.
2017-01-01
ABSTRACT In this study, we constructed a set of Ralstonia eutropha H16 strains with single, double, or triple deletions of the (p)ppGpp synthase/hydrolase (spoT1), (p)ppGpp synthase (spoT2), and/or polyhydroxybutyrate (PHB) depolymerase (phaZa1 or phaZa3) gene, and we determined the impact on the levels of (p)ppGpp and on accumulated PHB. Mutants with deletions of both the spoT1 and spoT2 genes were unable to synthesize detectable amounts of (p)ppGpp and accumulated only minor amounts of PHB, due to PhaZa1-mediated depolymerization of PHB. In contrast, unusually high levels of PHB were found in strains in which the (p)ppGpp concentration was increased by the overexpression of (p)ppGpp synthase (SpoT2) and the absence of (p)ppGpp hydrolase. Determination of (p)ppGpp levels in wild-type R. eutropha under different growth conditions and induction of the stringent response by amino acid analogs showed that the concentrations of (p)ppGpp during the growth phase determine the amount of PHB remaining in later growth phases by influencing the efficiency of the PHB mobilization system in stationary growth. The data reported for a previously constructed ΔspoT2 strain (C. J. Brigham, D. R. Speth, C. Rha, and A. J. Sinskey, Appl Environ Microbiol 78:8033–8044, 2012, https://doi.org/10.1128/AEM.01693-12) were identified as due to an experimental error in strain construction, and our results are in contrast to the previous indication that the spoT2 gene product is essential for PHB accumulation in R. eutropha. IMPORTANCE Polyhydroxybutyrate (PHB) is an important intracellular carbon and energy storage compound in many prokaryotes and helps cells survive periods of starvation and other stress conditions. Research activities in several laboratories over the past 3 decades have shown that both PHB synthase and PHB depolymerase are constitutively expressed in most PHB-accumulating bacteria, such as Ralstonia eutropha. This implies that PHB synthase and depolymerase activities
A Model-Data Fusion Approach for Constraining Modeled GPP at Global Scales Using GOME2 SIF Data
NASA Astrophysics Data System (ADS)
MacBean, N.; Maignan, F.; Lewis, P.; Guanter, L.; Koehler, P.; Bacour, C.; Peylin, P.; Gomez-Dans, J.; Disney, M.; Chevallier, F.
2015-12-01
Predicting the fate of the ecosystem carbon, C, stocks and their sensitivity to climate change relies heavily on our ability to accurately model the gross carbon fluxes, i.e. photosynthesis and respiration. However, there are large differences in the Gross Primary Productivity (GPP) simulated by different land surface models (LSMs), not only in terms of mean value, but also in terms of phase and amplitude when compared to independent data-based estimates. This strongly limits our ability to provide accurate predictions of carbon-climate feedbacks. One possible source of this uncertainty is from inaccurate parameter values resulting from incomplete model calibration. Solar Induced Fluorescence (SIF) has been shown to have a linear relationship with GPP at the typical spatio-temporal scales used in LSMs (Guanter et al., 2011). New satellite-derived SIF datasets have the potential to constrain LSM parameters related to C uptake at global scales due to their coverage. Here we use SIF data derived from the GOME2 instrument (Köhler et al., 2014) to optimize parameters related to photosynthesis and leaf phenology of the ORCHIDEE LSM, as well as the linear relationship between SIF and GPP. We use a multi-site approach that combines many model grid cells covering a wide spatial distribution within the same optimization (e.g. Kuppel et al., 2014). The parameters are constrained per Plant Functional type as the linear relationship described above varies depending on vegetation structural properties. The relative skill of the optimization is compared to a case where only satellite-derived vegetation index data are used to constrain the model, and to a case where both data streams are used. We evaluate the results using an independent data-driven estimate derived from FLUXNET data (Jung et al., 2011) and with a new atmospheric tracer, Carbonyl sulphide (OCS) following the approach of Launois et al. (ACPD, in review). We show that the optimization reduces the strong positive
The bacterial alarmone (p)ppGpp activates the type III secretion system in Erwinia amylovora.
Ancona, Veronica; Lee, Jae Hoon; Chatnaparat, Tiyakhon; Oh, Jinrok; Hong, Jong-In; Zhao, Youfu
2015-04-01
The hypersensitive response and pathogenicity (hrp) type III secretion system (T3SS) is a key pathogenicity factor in Erwinia amylovora. Previous studies have demonstrated that the T3SS in E. amylovora is transcriptionally regulated by a sigma factor cascade. In this study, the role of the bacterial alarmone ppGpp in activating the T3SS and virulence of E. amylovora was investigated using ppGpp mutants generated by Red recombinase cloning. The virulence of a ppGpp-deficient mutant (ppGpp(0)) as well as a dksA mutant of E. amylovora was completely impaired, and bacterial growth was significantly reduced, suggesting that ppGpp is required for full virulence of E. amylovora. Expression of T3SS genes was greatly downregulated in the ppGpp(0) and dksA mutants. Western blotting showed that accumulations of the HrpA protein in the ppGpp(0) and dksA mutants were about 10 and 4%, respectively, of that in the wild-type strain. Furthermore, higher levels of ppGpp resulted in a reduced cell size of E. amylovora. Moreover, serine hydroxamate and α-methylglucoside, which induce amino acid and carbon starvation, respectively, activated hrpA and hrpL promoter activities in hrp-inducing minimal medium. These results demonstrated that ppGpp and DksA play central roles in E. amylovora virulence and indicated that E. amylovora utilizes ppGpp as an internal messenger to sense environmental/nutritional stimuli for regulation of the T3SS and virulence. The type III secretion system (T3SS) is a key pathogenicity factor in Gram-negative bacteria. Fully elucidating how the T3SS is activated is crucial for comprehensively understanding the function of the T3SS, bacterial pathogenesis, and survival under stress conditions. In this study, we present the first evidence that the bacterial alarmone ppGpp-mediated stringent response activates the T3SS through a sigma factor cascade, indicating that ppGpp acts as an internal messenger to sense environmental/nutritional stimuli for the regulation
The Bacterial Alarmone (p)ppGpp Activates the Type III Secretion System in Erwinia amylovora
Ancona, Veronica; Lee, Jae Hoon; Chatnaparat, Tiyakhon; Oh, Jinrok; Hong, Jong-In
2015-01-01
ABSTRACT The hypersensitive response and pathogenicity (hrp) type III secretion system (T3SS) is a key pathogenicity factor in Erwinia amylovora. Previous studies have demonstrated that the T3SS in E. amylovora is transcriptionally regulated by a sigma factor cascade. In this study, the role of the bacterial alarmone ppGpp in activating the T3SS and virulence of E. amylovora was investigated using ppGpp mutants generated by Red recombinase cloning. The virulence of a ppGpp-deficient mutant (ppGpp0) as well as a dksA mutant of E. amylovora was completely impaired, and bacterial growth was significantly reduced, suggesting that ppGpp is required for full virulence of E. amylovora. Expression of T3SS genes was greatly downregulated in the ppGpp0 and dksA mutants. Western blotting showed that accumulations of the HrpA protein in the ppGpp0 and dksA mutants were about 10 and 4%, respectively, of that in the wild-type strain. Furthermore, higher levels of ppGpp resulted in a reduced cell size of E. amylovora. Moreover, serine hydroxamate and α-methylglucoside, which induce amino acid and carbon starvation, respectively, activated hrpA and hrpL promoter activities in hrp-inducing minimal medium. These results demonstrated that ppGpp and DksA play central roles in E. amylovora virulence and indicated that E. amylovora utilizes ppGpp as an internal messenger to sense environmental/nutritional stimuli for regulation of the T3SS and virulence. IMPORTANCE The type III secretion system (T3SS) is a key pathogenicity factor in Gram-negative bacteria. Fully elucidating how the T3SS is activated is crucial for comprehensively understanding the function of the T3SS, bacterial pathogenesis, and survival under stress conditions. In this study, we present the first evidence that the bacterial alarmone ppGpp-mediated stringent response activates the T3SS through a sigma factor cascade, indicating that ppGpp acts as an internal messenger to sense environmental/nutritional stimuli for
Xia, Jianyang; McGuire, A. David; Lawrence, David; ...
2017-01-26
Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m -2 yr -1), most models produced higher NPP (309 ± 12 g C m -2 yr -1) over the permafrost region during 2000–2009.more » By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a twofold discrepancy among models (380 to 800 g C m -2 yr -1), which mainly resulted from differences in simulated maximum monthly GPP (GPP max). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vc max_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO 2 concentration. In conclusion, these results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPP max as well as their sensitivity to climate change.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xia, Jianyang; McGuire, A. David; Lawrence, David
Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m -2 yr -1), most models produced higher NPP (309 ± 12 g C m -2 yr -1) over the permafrost region during 2000–2009.more » By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a twofold discrepancy among models (380 to 800 g C m -2 yr -1), which mainly resulted from differences in simulated maximum monthly GPP (GPP max). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vc max_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO 2 concentration. In conclusion, these results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPP max as well as their sensitivity to climate change.« less
NASA Astrophysics Data System (ADS)
Walther, Sophia; Guanter, Luis; Voigt, Maximilian; Köhler, Philipp; Jung, Martin; Joiner, Joanna
2015-04-01
sophia.walther@gfz-potsdam.de The seasonality of photosynthesis of boreal forests is an essential driver of the terrestrial carbon, water and energy cycles. However, current carbon cycle model results only poorly represent interannual variability and predict very different magnitudes and timings of carbon fluxes between the atmosphere and the land surface (e.g. Jung et al. 2011, Richardson et al. 2012). Reflectance-based satellite measurements, which give an indication of the amount of green biomass on the Earth's surface, have so far been used as input to global carbon cycle simulations, but they have limitations as they are not directly linked to instantaneous photosynthesis. As an alternative, space-borne retrievals of sun-induced chlorophyll fluorescence (SIF) boast the potential to provide a direct indication of the seasonality of boreal forest photosynthetic activity and thus to improve carbon model performances. SIF is a small electromagnetic signal that is re-emitted from the photosystems in the chloroplasts, which results in a direct relationship to photosynthetic efficiency. In this contribution we examine the seasonality of the boreal forests with three different vegetation parameters, namely greenness, SIF and model simulations of gross primary production (gross carbon flux into the plants by photosynthesis, GPP). We use the enhanced vegetation index (EVI) to represent green biomass. EVI is calculated from NBAR MODIS reflectance measurements (0.05deg, 16 days temporal resolution) for the time from January 2007-May 2013. SIF data originate from GOME-2 measurements on board the MetOp-A satellite in a spatial resolution of 0.5deg for the time from 2007-2011 (Joiner et al. (2013), Köhler et al. (2014)). As a third data source, data-driven GPP model results are used for the time from 2006-2012 with 0.5deg spatial resolution. The method to quantify phenology developed by Gonsamo et al. (2013) is applied to infer the main phenological phases (greenup/onset of
MS_RHII-RSD, a Dual-Function RNase HII-(p)ppGpp Synthetase from Mycobacterium smegmatis
Murdeshwar, Maya S.
2012-01-01
In the noninfectious soil saprophyte Mycobacterium smegmatis, intracellular levels of the stress alarmones guanosine tetraphosphate and guanosine pentaphosphate, together termed (p)ppGpp, are regulated by the enzyme RelMsm. This enzyme consists of a single, bifunctional polypeptide chain that is capable of both synthesizing and hydrolyzing (p)ppGpp. The relMsm knockout strain of M. smegmatis (ΔrelMsm) is expected to show a (p)ppGpp null [(p)ppGpp0] phenotype. Contrary to this expectation, the strain is capable of synthesizing (p)ppGpp in vivo. In this study, we identify and functionally characterize the open reading frame (ORF), MSMEG_5849, that encodes a second functional (p)ppGpp synthetase in M. smegmatis. In addition to (p)ppGpp synthesis, the 567-amino-acid-long protein encoded by this gene is capable of hydrolyzing RNA·DNA hybrids and bears similarity to the conventional RNase HII enzymes. We have classified this protein as actRelMsm in accordance with the recent nomenclature proposed and have named it MS_RHII-RSD, indicating the two enzymatic activities present [RHII, RNase HII domain, originally identified as domain of unknown function 429 (DUF429), and RSD, RelA_SpoT nucleotidyl transferase domain, the SYNTH domain responsible for (p)ppGpp synthesis activity]. MS_RHII-RSD is expressed and is constitutively active in vivo and behaves like a monofunctional (p)ppGpp synthetase in vitro. The occurrence of the RNase HII and (p)ppGpp synthetase domains together on the same polypeptide chain is suggestive of an in vivo role for this novel protein as a link connecting the essential life processes of DNA replication, repair, and transcription to the highly conserved stress survival pathway, the stringent response. PMID:22636779
MS_RHII-RSD, a dual-function RNase HII-(p)ppGpp synthetase from Mycobacterium smegmatis.
Murdeshwar, Maya S; Chatterji, Dipankar
2012-08-01
In the noninfectious soil saprophyte Mycobacterium smegmatis, intracellular levels of the stress alarmones guanosine tetraphosphate and guanosine pentaphosphate, together termed (p)ppGpp, are regulated by the enzyme Rel(Msm). This enzyme consists of a single, bifunctional polypeptide chain that is capable of both synthesizing and hydrolyzing (p)ppGpp. The rel(Msm) knockout strain of M. smegmatis (Δrel(Msm)) is expected to show a (p)ppGpp null [(p)ppGpp(0)] phenotype. Contrary to this expectation, the strain is capable of synthesizing (p)ppGpp in vivo. In this study, we identify and functionally characterize the open reading frame (ORF), MSMEG_5849, that encodes a second functional (p)ppGpp synthetase in M. smegmatis. In addition to (p)ppGpp synthesis, the 567-amino-acid-long protein encoded by this gene is capable of hydrolyzing RNA·DNA hybrids and bears similarity to the conventional RNase HII enzymes. We have classified this protein as actRel(Msm) in accordance with the recent nomenclature proposed and have named it MS_RHII-RSD, indicating the two enzymatic activities present [RHII, RNase HII domain, originally identified as domain of unknown function 429 (DUF429), and RSD, RelA_SpoT nucleotidyl transferase domain, the SYNTH domain responsible for (p)ppGpp synthesis activity]. MS_RHII-RSD is expressed and is constitutively active in vivo and behaves like a monofunctional (p)ppGpp synthetase in vitro. The occurrence of the RNase HII and (p)ppGpp synthetase domains together on the same polypeptide chain is suggestive of an in vivo role for this novel protein as a link connecting the essential life processes of DNA replication, repair, and transcription to the highly conserved stress survival pathway, the stringent response.
NASA Astrophysics Data System (ADS)
Deb Burman, Pramit Kumar; Sarma, Dipankar; Williams, Mathew; Karipot, Anandakumar; Chakraborty, Supriyo
2017-10-01
Tropical forests act as a major sink of atmospheric carbon dioxide, and store large amounts of carbon in biomass. India is a tropical country with regions of dense vegetation and high biodiversity. However due to the paucity of observations, the carbon sequestration potential of these forests could not be assessed in detail so far. To address this gap, several flux towers were erected over different ecosystems in India by Indian Institute of Tropical Meteorology as part of the MetFlux India project funded by MoES (Ministry of Earth Sciences, Government of India). A 50 m tall tower was set up over a semi-evergreen moist deciduous forest named Kaziranga National Park in north-eastern part of India which houses a significant stretch of local forest cover. Climatically this region is identified to be humid sub-tropical. Here we report first generation of the in situ meteorological observations and leaf area index (LAI) measurements from this site. LAI obtained from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) is compared with the in situ measured LAI. We use these in situ measurements to calculate the total gross photosynthesis (or gross primary productivity, GPP) of the forest using a calibrated model. LAI and GPP show prominent seasonal variation. LAI ranges between 0.75 in winter to 3.25 in summer. Annual GPP is estimated to be 2.11 kg C m^{-2} year^{-1}.
Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks.
Lu, Zhaoming; Pan, Qi; Wang, Luhan; Wen, Xiangming
2016-01-01
Because of the limited resources on radio access channels of third generation partnership projection (3GPP) network, one of the most challenging tasks posted by 3GPP cellular-based machine type communications (MTC) is congestion due to massive requests for connection to radio access network (RAN). In this paper, an overload control algorithm in 3GPP RAN is proposed, which proactively disperses the simultaneous access attempts in evenly distributed time window. Through periodic reservation strategy, massive access requests of MTC devices are dispersed in time, which reduces the probability of confliction of signaling. By the compensation and prediction mechanism, each device can communicate with MTC server with dynamic load of air interface. Numerical results prove that proposed method makes MTC applications friendly to 3GPP cellular network.
NASA Astrophysics Data System (ADS)
Rambal, S.; Lempereur, M.; Limousin, J. M.; Martin-StPaul, N. K.; Ourcival, J. M.; Rodríguez-Calcerrada, J.
2014-06-01
The partitioning of photosynthates toward biomass compartments has a crucial role in the carbon sink function of forests. Few studies have examined how carbon is allocated toward plant compartments in drought prone forests. We analyzed the fate of GPP in relation to yearly water deficit in an old evergreen Mediterranean Quercus ilex coppice severely affected by water limitations. Gross and net carbon fluxes between the ecosystem and the atmosphere were measured with an eddy-covariance flux tower running continuously since 2001. Discrete measurements of litterfall, stem growth and fAPAR allowed us to derive annual productions of leaves, wood, flowers and acorns and an isometric relationship between stem and belowground biomass has been used to estimate perennial belowground growth. By combining eddy-covariance fluxes with annual productions we managed to close a C budget and derive values of autotrophic and heterotrophic respirations, NPP and carbon use efficiency (CUE, the ratio between NPP and GPP). Average values of yearly NEP, GPP and Reco were 282, 1259 and 977 g C m-2. The corresponding ANPP components were 142.5, 26.4 and 69.6 g C m-2 for leaves, reproductive effort (flowers and fruits) and stems. Gross and net carbon exchange between the ecosystem and the atmosphere were affected by annual water deficit. Partitioning to the different plant compartments was also impacted by drought, with a hierarchy of responses going from the most affected, the stem growth, to the least affected, the leaf production. The average CUE was 0.40, which is well in the range for Mediterranean-type forest ecosystems. CUE tended to decrease more slightly in response to drought than GPP and NPP, probably due to drought-acclimation of autotrophic respiration. Overall, our results provide a baseline for modeling the inter-annual variations of carbon fluxes and allocation in this widespread Mediterranean ecosystem and highlight the value of maintaining continuous experimental
Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks
Lu, Zhaoming; Pan, Qi; Wang, Luhan; Wen, Xiangming
2016-01-01
Because of the limited resources on radio access channels of third generation partnership projection (3GPP) network, one of the most challenging tasks posted by 3GPP cellular-based machine type communications (MTC) is congestion due to massive requests for connection to radio access network (RAN). In this paper, an overload control algorithm in 3GPP RAN is proposed, which proactively disperses the simultaneous access attempts in evenly distributed time window. Through periodic reservation strategy, massive access requests of MTC devices are dispersed in time, which reduces the probability of confliction of signaling. By the compensation and prediction mechanism, each device can communicate with MTC server with dynamic load of air interface. Numerical results prove that proposed method makes MTC applications friendly to 3GPP cellular network. PMID:27936011
NASA Astrophysics Data System (ADS)
Yebra, Marta; van Dijk, Albert
2015-04-01
Water use efficiency (WUE, the amount of transpiration or evapotranspiration per unit gross (GPP) or net CO2 uptake) is key in all areas of plant production and forest management applications. Therefore, mutually consistent estimates of GPP and transpiration are needed to analysed WUE without introducing any artefacts that might arise by combining independently derived GPP and ET estimates. GPP and transpiration are physiologically linked at ecosystem level by the canopy conductance (Gc). Estimates of Gc can be obtained by scaling stomatal conductance (Kelliher et al. 1995) or inferred from ecosystem level measurements of gas exchange (Baldocchi et al., 2008). To derive large-scale or indeed global estimates of Gc, satellite remote sensing based methods are needed. In a previous study, we used water vapour flux estimates derived from eddy covariance flux tower measurements at 16 Fluxnet sites world-wide to develop a method to estimate Gc using MODIS reflectance observations (Yebra et al. 2013). We combined those estimates with the Penman-Monteith combination equation to derive transpiration (T). The resulting T estimates compared favourably with flux tower estimates (R2=0.82, RMSE=29.8 W m-2). Moreover, the method allowed a single parameterisation for all land cover types, which avoids artefacts resulting from land cover classification. In subsequent research (Yebra et al, in preparation) we used the same satellite-derived Gc values within a process-based but simple canopy GPP model to constrain GPP predictions. The developed model uses a 'big-leaf' description of the plant canopy to estimate the mean GPP flux as the lesser of a conductance-limited and radiation-limited GPP rate. The conductance-limited rate was derived assuming that transport of CO2 from the bulk air to the intercellular leaf space is limited by molecular diffusion through the stomata. The radiation-limited rate was estimated assuming that it is proportional to the absorbed photosynthetically
NASA Astrophysics Data System (ADS)
Montero, P.; Pérez-Santos, I.; Daneri, G.; Gutiérrez, M. H.; Igor, G.; Seguel, R.; Purdie, D.; Crawford, D. W.
2017-12-01
A dense winter bloom of the dinoflagellate Heterocapsa triquetra was observed at a fixed station (44°35.3‧S; 72°43.6‧W) in the Puyuhuapi Fjord in Chilean Patagonia during July 2015. H. triquetra dominated the phytoplankton community in the surface waters between 2 and 15 m (13-58 × 109 cell m-2), with abundances some 3 to 15 times higher than the total abundance of the diatom assemblage, which was dominated by Skeletonema spp. The high abundance of dinoflagellates was reflected in high rates of gross primary production (GPP; 0.6-1.6 g C m-2 d-1) and chlorophyll-a concentration (Chl-a; 70-199.2 mg m-2) that are comparable to levels reported in spring diatom blooms in similar Patagonian fjords. We identify the main forcing factors behind a pulse of organic matter production during the non-productive winter season, and test the hypothesis that low irradiance levels are a key factor limiting phytoplankton blooms and subsequent productivity during winter. Principal Component Analysis (PCA) indicated that GPP rates were significantly correlated (r = -0.8, p < 0.05) with a decrease in salinity/temperature and the presence of the Heterocapsa bloom. The bloom occurred under low surface irradiance levels characteristic of austral winter and was accompanied by strong northern winds, associated with the passage of a low-pressure system, and a water column dominated by double diffusive layering. To our knowledge, this is the first report of a dense dinoflagellate bloom during deep austral winter in a Patagonian fjord, and our data challenge the paradigm of light limitation as a factor controlling phytoplankton blooms in this region in winter.
The linkages between photosynthesis, productivity, growth and biomass in lowland Amazonian forests.
Malhi, Yadvinder; Doughty, Christopher E; Goldsmith, Gregory R; Metcalfe, Daniel B; Girardin, Cécile A J; Marthews, Toby R; Del Aguila-Pasquel, Jhon; Aragão, Luiz E O C; Araujo-Murakami, Alejandro; Brando, Paulo; da Costa, Antonio C L; Silva-Espejo, Javier E; Farfán Amézquita, Filio; Galbraith, David R; Quesada, Carlos A; Rocha, Wanderley; Salinas-Revilla, Norma; Silvério, Divino; Meir, Patrick; Phillips, Oliver L
2015-06-01
Understanding the relationship between photosynthesis, net primary productivity and growth in forest ecosystems is key to understanding how these ecosystems will respond to global anthropogenic change, yet the linkages among these components are rarely explored in detail. We provide the first comprehensive description of the productivity, respiration and carbon allocation of contrasting lowland Amazonian forests spanning gradients in seasonal water deficit and soil fertility. Using the largest data set assembled to date, ten sites in three countries all studied with a standardized methodology, we find that (i) gross primary productivity (GPP) has a simple relationship with seasonal water deficit, but that (ii) site-to-site variations in GPP have little power in explaining site-to-site spatial variations in net primary productivity (NPP) or growth because of concomitant changes in carbon use efficiency (CUE), and conversely, the woody growth rate of a tropical forest is a very poor proxy for its productivity. Moreover, (iii) spatial patterns of biomass are much more driven by patterns of residence times (i.e. tree mortality rates) than by spatial variation in productivity or tree growth. Current theory and models of tropical forest carbon cycling under projected scenarios of global atmospheric change can benefit from advancing beyond a focus on GPP. By improving our understanding of poorly understood processes such as CUE, NPP allocation and biomass turnover times, we can provide more complete and mechanistic approaches to linking climate and tropical forest carbon cycling. © 2015 John Wiley & Sons Ltd.
Gross primary production controls the subsequent winter CO2 exchange in a boreal peatland.
Zhao, Junbin; Peichl, Matthias; Öquist, Mats; Nilsson, Mats B
2016-12-01
In high-latitude regions, carbon dioxide (CO 2 ) emissions during the winter represent an important component of the annual ecosystem carbon budget; however, the mechanisms that control the winter CO 2 emissions are currently not well understood. It has been suggested that substrate availability from soil labile carbon pools is a main driver of winter CO 2 emissions. In ecosystems that are dominated by annual herbaceous plants, much of the biomass produced during the summer is likely to contribute to the soil labile carbon pool through litter fall and root senescence in the autumn. Thus, the summer carbon uptake in the ecosystem may have a significant influence on the subsequent winter CO 2 emissions. To test this hypothesis, we conducted a plot-scale shading experiment in a boreal peatland to reduce the gross primary production (GPP) during the growing season. At the growing season peak, vascular plant biomass in the shaded plots was half that in the control plots. During the subsequent winter, the mean CO 2 emission rates were 21% lower in the shaded plots than in the control plots. In addition, long-term (2001-2012) eddy covariance data from the same site showed a strong correlation between the GPP (particularly the late summer and autumn GPP) and the subsequent winter net ecosystem CO 2 exchange (NEE). In contrast, abiotic factors during the winter could not explain the interannual variation in the cumulative winter NEE. Our study demonstrates the presence of a cross-seasonal link between the growing season biotic processes and winter CO 2 emissions, which has important implications for predicting winter CO 2 emission dynamics in response to future climate change. © 2016 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Minaya, Veronica; Corzo, Gerald; van der Kwast, Johannes; Galarraga, Remigio; Mynett, Arthur
2014-05-01
Simulations of carbon cycling are prone to uncertainties from different sources, which in general are related to input data, parameters and the model representation capacities itself. The gross carbon uptake in the cycle is represented by the gross primary production (GPP), which deals with the spatio-temporal variability of the precipitation and the soil moisture dynamics. This variability associated with uncertainty of the parameters can be modelled by multivariate probabilistic distributions. Our study presents a novel methodology that uses multivariate Copulas analysis to assess the GPP. Multi-species and elevations variables are included in a first scenario of the analysis. Hydro-meteorological conditions that might generate a change in the next 50 or more years are included in a second scenario of this analysis. The biogeochemical model BIOME-BGC was applied in the Ecuadorian Andean region in elevations greater than 4000 masl with the presence of typical vegetation of páramo. The change of GPP over time is crucial for climate scenarios of the carbon cycling in this type of ecosystem. The results help to improve our understanding of the ecosystem function and clarify the dynamics and the relationship with the change of climate variables. Keywords: multivariate analysis, Copula, BIOME-BGC, NPP, páramos
Synthetic (p)ppGpp Analogue Is an Inhibitor of Stringent Response in Mycobacteria
Syal, Kirtimaan; Flentie, Kelly; Bhardwaj, Neerupma; Maiti, Krishnagopal; Jayaraman, Narayanaswamy; Stallings, Christina L.
2017-01-01
ABSTRACT Bacteria elicit an adaptive response against hostile conditions such as starvation and other kinds of stresses. Their ability to survive such conditions depends, in part, on stringent response pathways. (p)ppGpp, considered to be the master regulator of the stringent response, is a novel target for inhibiting the survival of bacteria. In mycobacteria, the (p)ppGpp synthetase activity of bifunctional Rel is critical for stress response and persistence inside a host. Our aim was to design an inhibitor of (p)ppGpp synthesis, monitor its efficiency using enzyme kinetics, and assess its phenotypic effects in mycobacteria. As such, new sets of inhibitors targeting (p)ppGpp synthesis were synthesized and characterized by mass spectrometry and nuclear magnetic resonance spectroscopy. We observed significant inhibition of (p)ppGpp synthesis by RelMsm in the presence of designed inhibitors in a dose-dependent manner, which we further confirmed by monitoring the enzyme kinetics. The Rel enzyme inhibitor binding kinetics were investigated by isothermal titration calorimetry. Subsequently, the effects of the compounds on long-term persistence, biofilm formation, and biofilm disruption were assayed in Mycobacterium smegmatis, where inhibition in each case was observed. In vivo, (p)ppGpp levels were found to be downregulated in M. smegmatis treated with the synthetic inhibitors. The compounds reported here also inhibited biofilm formation by the pathogen Mycobacterium tuberculosis. The compounds were tested for toxicity by using an MTT assay with H460 cells and a hemolysis assay with human red blood cells, for which they were found to be nontoxic. The permeability of compounds across the cell membrane of human lung epithelial cells was also confirmed by mass spectrometry. PMID:28396544
Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther
2009-01-01
In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale. PMID:22399948
Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther
2009-01-01
In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.
Ardö, Jonas
2015-12-01
Africa is an important part of the global carbon cycle. It is also a continent facing potential problems due to increasing resource demand in combination with climate change-induced changes in resource supply. Quantifying the pools and fluxes constituting the terrestrial African carbon cycle is a challenge, because of uncertainties in meteorological driver data, lack of validation data, and potentially uncertain representation of important processes in major ecosystems. In this paper, terrestrial primary production estimates derived from remote sensing and a dynamic vegetation model are compared and quantified for major African land cover types. Continental gross primary production estimates derived from remote sensing were higher than corresponding estimates derived from a dynamic vegetation model. However, estimates of continental net primary production from remote sensing were lower than corresponding estimates from the dynamic vegetation model. Variation was found among land cover classes, and the largest differences in gross primary production were found in the evergreen broadleaf forest. Average carbon use efficiency (NPP/GPP) was 0.58 for the vegetation model and 0.46 for the remote sensing method. Validation versus in situ data of aboveground net primary production revealed significant positive relationships for both methods. A combination of the remote sensing method with the dynamic vegetation model did not strongly affect this relationship. Observed significant differences in estimated vegetation productivity may have several causes, including model design and temperature sensitivity. Differences in carbon use efficiency reflect underlying model assumptions. Integrating the realistic process representation of dynamic vegetation models with the high resolution observational strength of remote sensing may support realistic estimation of components of the carbon cycle and enhance resource monitoring, providing suitable validation data is available.
NASA Astrophysics Data System (ADS)
Liu, Yibo; Ju, Weimin; He, Honglin; Wang, Shaoqiang; Sun, Rui; Zhang, Yuandong
2013-03-01
Net primary productivity (NPP) is an important component of the terrestrial carbon cycle. Accurately mapping the spatial-temporal variations of NPP in China is crucial for global carbon cycling study. In this study the process-based Boreal Ecosystem Productivity Simulator (BEPS) was employed to study the changes of NPP in China's ecosystems for the period from 2000 to 2010. The BEPS model was first validated using gross primary productivity (GPP) measured at typical flux sites and forest NPP measured at different regions. Then it was driven with leaf area index (LAI) inversed from the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and land cover products and meteorological data interpolated from observations at 753 national basic meteorological stations to simulate NPP at daily time steps and a spatial resolution of 500 m from January 1, 2000 to December 31, 2010. Validations show that BEPS is able to capture the seasonal variations of tower-based GPP and the spatial variability of forest NPP in different regions of China. Estimated national total of annual NPP varied from 2.63 to 2.84Pg C·yr-1, averaging 2.74 Pg C·yr-1 during the study period. Simulated terrestrial NPP shows spatial patterns decreasing from the east to the west and from the south to the north, in association with land cover types and climate. South-west China makes the largest contribution to the national total of NPP while NPP in the North-west account for only 3.97% of the national total. During the recent 11 years, the temporal changes of NPP were heterogamous. NPP increased in 63.8% of China's landmass, mainly in areas north of the Yangtze River and decreased in most areas of southern China, owing to the low temperature freezing in early 2008 and the severe drought in late 2009.
Nomura, Yuhta; Izumi, Atsushi; Fukunaga, Yoshinori; Kusumi, Kensuke; Iba, Koh; Watanabe, Seiya; Nakahira, Yoichi; Weber, Andreas P. M.; Nozawa, Akira; Tozawa, Yuzuru
2014-01-01
The guanosine 3′,5′-bisdiphosphate (ppGpp) signaling system is shared by bacteria and plant chloroplasts, but its role in plants has remained unclear. Here we show that guanylate kinase (GK), a key enzyme in guanine nucleotide biosynthesis that catalyzes the conversion of GMP to GDP, is a target of regulation by ppGpp in chloroplasts of rice, pea, and Arabidopsis. Plants have two distinct types of GK that are localized to organelles (GKpm) or to the cytosol (GKc), with both enzymes being essential for growth and development. We found that the activity of rice GKpm in vitro was inhibited by ppGpp with a Ki of 2.8 μm relative to the substrate GMP, whereas the Km of this enzyme for GMP was 73 μm. The IC50 of ppGpp for GKpm was ∼10 μm. In contrast, the activity of rice GKc was insensitive to ppGpp, as was that of GK from bakers' yeast, which is also a cytosolic enzyme. These observations suggest that ppGpp plays a pivotal role in the regulation of GTP biosynthesis in chloroplasts through specific inhibition of GKpm activity, with the regulation of GTP biosynthesis in chloroplasts thus being independent of that in the cytosol. We also found that GKs of Escherichia coli and Synechococcus elongatus PCC 7942 are insensitive to ppGpp, in contrast to the ppGpp sensitivity of the Bacillus subtilis enzyme. Our biochemical characterization of GK enzymes has thus revealed a novel target of ppGpp in chloroplasts and has uncovered diversity among bacterial GKs with regard to regulation by ppGpp. PMID:24722991
Synthetic (p)ppGpp Analogue Is an Inhibitor of Stringent Response in Mycobacteria.
Syal, Kirtimaan; Flentie, Kelly; Bhardwaj, Neerupma; Maiti, Krishnagopal; Jayaraman, Narayanaswamy; Stallings, Christina L; Chatterji, Dipankar
2017-06-01
Bacteria elicit an adaptive response against hostile conditions such as starvation and other kinds of stresses. Their ability to survive such conditions depends, in part, on stringent response pathways. (p)ppGpp, considered to be the master regulator of the stringent response, is a novel target for inhibiting the survival of bacteria. In mycobacteria, the (p)ppGpp synthetase activity of bifunctional Rel is critical for stress response and persistence inside a host. Our aim was to design an inhibitor of (p)ppGpp synthesis, monitor its efficiency using enzyme kinetics, and assess its phenotypic effects in mycobacteria. As such, new sets of inhibitors targeting (p)ppGpp synthesis were synthesized and characterized by mass spectrometry and nuclear magnetic resonance spectroscopy. We observed significant inhibition of (p)ppGpp synthesis by Rel Msm in the presence of designed inhibitors in a dose-dependent manner, which we further confirmed by monitoring the enzyme kinetics. The Rel enzyme inhibitor binding kinetics were investigated by isothermal titration calorimetry. Subsequently, the effects of the compounds on long-term persistence, biofilm formation, and biofilm disruption were assayed in Mycobacterium smegmatis , where inhibition in each case was observed. In vivo , (p)ppGpp levels were found to be downregulated in M. smegmatis treated with the synthetic inhibitors. The compounds reported here also inhibited biofilm formation by the pathogen Mycobacterium tuberculosis The compounds were tested for toxicity by using an MTT assay with H460 cells and a hemolysis assay with human red blood cells, for which they were found to be nontoxic. The permeability of compounds across the cell membrane of human lung epithelial cells was also confirmed by mass spectrometry. Copyright © 2017 American Society for Microbiology.
NASA Astrophysics Data System (ADS)
Campioli, M.; Gielen, B.; Granier, A.; Verstraeten, A.; Neirynck, J.; Janssens, I. A.
2010-10-01
Carbon taken up by the forest canopy is allocated to tree organs for biomass production and respiration. Because tree organs have different life span and decomposition rate, the tree C allocation determines the residence time of C in the ecosystem and its C cycling rate. The study of the carbon-use efficiency, or ratio between net primary production (NPP) and gross primary production (GPP), represents a convenient way to analyse the C allocation at the stand level. Previous studies mostly focused on comparison of the annual NPP-GPP ratio among forests of different functional types, biomes and age. In this study, we extend the current knowledge by assessing (i) the annual NPP-GPP ratio and its interannual variability (for five years) for five tree organs (leaves, fruits, branches, stem and coarse roots), and (ii) the seasonal dynamic of NPP-GPP ratio of leaves and stems, for two stands dominated by European beech and Scots pine. The average NPP-GPP ratio for the beech stand (38%) was similar to previous estimates for temperate deciduous forests, whereas the NPP-GPP ratio for the pine stand (17%) is the lowest recorded till now in the literature. The proportion of GPP allocated to leaf NPP was similar for both species, whereas beech allocated a remarkable larger proportion of GPP to wood NPP than pine (29% vs. 6%, respectively). The interannual variability of the NPP-GPP ratio for wood was substantially larger than the interannual variability of the NPP-GPP ratio for leaves, fruits and overall stand and it is likely to be controlled by previous year air temperature (both species), previous year drought intensity (beech) and thinning (pine). Seasonal pattern of NPP-GPP ratio greatly differed between beech and pine, with beech presenting the largest ratio in early season, and pine a more uniform ratio along the season. For beech, NPP-GPP ratio of leaves and stems peaked during the same period in the early season, whereas they peaked in opposite periods of the growing
NASA Astrophysics Data System (ADS)
Viña, A.; Silva, R. F. B. D.; Yang, H.; Liu, J.
2017-12-01
The international trade of agricultural commodities, such as soybean, is driven by a series of pull and push factors linked to market demand. These in turn fluctuate based on changes in economic affluence, infrastructure development, and socioeconomic homogenization, among others, in both sending and receiving systems. While many studies have analyzed some of these push/pull factors and their environmental effects in either sending or receiving systems, few studies have assessed these effects simultaneously in both sending and receiving systems. This study evaluates the effects of the soybean trade between Brazil and China on the spatio-temporal patterns of gross primary productivity (GPP) in both sending and receiving systems. The GPP is a measure of the amount of biomass produced through photosynthesis across space and through time. This metric is directly related with the amount of carbon that is sequestered from the atmosphere, and thus is related with the impacts of land use/cover dynamics on global climate change. The spatio-temporal patterns of both GPP and land use/cover were evaluated simultaneously in two soybean-producing regions (state of Mato Grosso in Brazil, and Heilongjiang province in China) through the use of surface reflectance data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellite, combined with a production efficiency model (PEM) entirely based on remotely sensed data. Results from this analysis provide new insights on the consequences of the international trade at local/regional scales, and allow assessing how changes in market demand for agricultural commodities may generate drastic environmental effects in both sending and receiving systems, with global implications on carbon sequestration and thus on climate change.
Good Publication Practice for Communicating Company-Sponsored Medical Research: GPP3.
Battisti, Wendy P; Wager, Elizabeth; Baltzer, Lise; Bridges, Dan; Cairns, Angela; Carswell, Christopher I; Citrome, Leslie; Gurr, James A; Mooney, LaVerne A; Moore, B Jane; Peña, Teresa; Sanes-Miller, Carol H; Veitch, Keith; Woolley, Karen L; Yarker, Yvonne E
2015-09-15
This updated Good Publication Practice (GPP) guideline, known as GPP3, builds on earlier versions and provides recommendations for individuals and organizations that contribute to the publication of research results sponsored or supported by pharmaceutical, medical device, diagnostics, and biotechnology companies. The recommendations are designed to help individuals and organizations maintain ethical and transparent publication practices and comply with legal and regulatory requirements. These recommendations cover publications in peer-reviewed journals and presentations (oral or poster) at scientific congresses. The International Society for Medical Publication Professionals invited more than 3000 professionals worldwide to apply for a position on the steering committee, or as a reviewer, for this guideline. The GPP2 authors reviewed all applications (n = 241) and assembled an 18-member steering committee that represented 7 countries and a diversity of publication professions and institutions. From the 174 selected reviewers, 94 sent comments on the second draft, which steering committee members incorporated after discussion and consensus. The resulting guideline includes new sections (Principles of Good Publication Practice for Company-Sponsored Medical Research, Data Sharing, Studies That Should Be Published, and Plagiarism), expands guidance on the International Committee of Medical Journal Editors' authorship criteria and common authorship issues, improves clarity on appropriate author payment and reimbursement, and expands information on the role of medical writers. By following good publication practices (including GPP3), individuals and organizations will show integrity; accountability; and responsibility for accurate, complete, and transparent reporting in their publications and presentations.
Wu, Mingquan; Muhammad, Shakir; Chen, Fang; Niu, Zheng; Wang, Changyao
2015-04-01
Wetland ecosystems are very important for ecological diversity and have a strong ability to sequester carbon. Through comparisons with field measured eddy covariance data, we evaluated the relationships between the light use efficiency (LUE) index and the enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and land surface temperature (LST). Consequently, we have proposed a new model for the estimation of gross primary production (GPP) for wetland ecosystems using Moderate Resolution Imaging Spectroradiometer (MODIS) products, including these vegetation indices, LST and the fraction of photosynthetically active radiation (FAPAR) absorbed by the active vegetation. This model was developed and validated for a study site on Chongming Island, Shanghai, China. Our results show that photosynthetically active radiation (PAR) was highly correlated with the LST, with a coefficient of determination (R(2)) of 0.59 (p < 0.001). Vegetation indices, such as EVI, NDVI and LST, were highly correlated with LUE. We found that the product of vegetation indices (VIs) and a modified form of LST (Te) can be used to estimate LUE, with an R(2) of 0.82 (P < 0.0001) and an RMSE of 0.054 kg C per mol PAR. This new model can provide reliable estimates of GPP (R(2) of 0.87 and RMSE of 0.009 kg C m(-2) 8 d(-1) (P < 0.0001)).
NASA Astrophysics Data System (ADS)
Launois, T.; Peylin, P.; Belviso, S.; Poulter, B.
2015-08-01
Clear analogies between carbonyl sulfide (OCS) and carbon dioxide (CO2) diffusion pathways through leaves have been revealed by experimental studies, with plant uptake playing an important role for the atmospheric budget of both species. Here we use atmospheric OCS to evaluate the gross primary production (GPP) of three dynamic global vegetation models (Lund-Potsdam-Jena, LPJ; National Center for Atmospheric Research - Community Land Model 4, NCAR-CLM4; and Organising Carbon and Hydrology In Dynamic Ecosystems, ORCHIDEE). Vegetation uptake of OCS is modeled as a linear function of GPP and leaf relative uptake (LRU), the ratio of OCS to CO2 deposition velocities of plants. New parameterizations for the non-photosynthetic sinks (oxic soils, atmospheric oxidation) and biogenic sources (oceans and anoxic soils) of OCS are also provided. Despite new large oceanic emissions, global OCS budgets created with each vegetation model show exceeding sinks by several hundred Gg S yr-1. An inversion of the surface fluxes (optimization of a global scalar which accounts for flux uncertainties) led to balanced OCS global budgets, as atmospheric measurements suggest, mainly by drastic reduction (up to -50 %) in soil and vegetation uptakes. The amplitude of variations in atmospheric OCS mixing ratios is mainly dictated by the vegetation sink over the Northern Hemisphere. This allows for bias recognition in the GPP representations of the three selected models. The main bias patterns are (i) the terrestrial GPP of ORCHIDEE at high northern latitudes is currently overestimated, (ii) the seasonal variations of the GPP are out of phase in the NCAR-CLM4 model, showing a maximum carbon uptake too early in spring in the northernmost ecosystems, (iii) the overall amplitude of the seasonal variations of GPP in NCAR-CLM4 is too small, and (iv) for the LPJ model, the GPP is slightly out of phase for the northernmost ecosystems and the respiration fluxes might be too large in summer in the
Net ecosystem CO2 exchange of a primary tropical peat swamp forest in Sarawak, Malaysia
NASA Astrophysics Data System (ADS)
Tang Che Ing, A.; Stoy, P. C.; Melling, L.
2014-12-01
Tropical peat swamp forests are widely recognized as one of the world's most efficient ecosystems for the sequestration and storage of carbon through both their aboveground biomass and underlying thick deposits of peat. As the peat characteristics exhibit high spatial and temporal variability as well as the structural and functional complexity of forests, tropical peat ecosystems can act naturally as both carbon sinks and sources over their life cycles. Nonetheless, few reports of studies on the ecosystem-scale CO2 exchange of tropical peat swamp forests are available to-date and their present roles in the global carbon cycle remain uncertain. To quantify CO2 exchange and unravel the prevailing factors and potential underlying mechanism regulating net CO2 fluxes, an eddy covariance tower was erected in a tropical peat swamp forest in Sarawak, Malaysia. We observed that the diurnal and seasonal patterns of net ecosystem CO2 exchange (NEE) and its components (gross primary productivity (GPP) and ecosystem respiration (RE)) varied between seasons and years. Rates of NEE declined in the wet season relative to the dry season. Conversely, both the gross primary productivity (GPP) and ecosystem respiration (RE) were found to be higher during the wet season than the dry season, in which GPP was strongly negatively correlated with NEE. The average annual NEE was 385 ± 74 g C m-2 yr-1, indicating the primary peat swamp forest functioned as net source of CO2 to the atmosphere over the observation period.
Wright, J K; Williams, M; Starr, G; McGee, J; Mitchell, R J
2013-02-01
Environmental controls on carbon dynamics operate at a range of interacting scales from the leaf to landscape. The key questions of this study addressed the influence of water and nitrogen (N) availability on Pinus palustris (Mill.) physiology and primary productivity across leaf and canopy scales, linking the soil-plant-atmosphere (SPA) model to leaf and stand-scale flux and leaf trait/canopy data. We present previously unreported ecophysiological parameters (e.g. V(cmax) and J(max)) for P. palustris and the first modelled estimates of its annual gross primary productivity (GPP) across xeric and mesic sites and under extreme drought. Annual mesic site P. palustris GPP was ∼23% greater than at the xeric site. However, at the leaf level, xeric trees had higher net photosynthetic rates, and water and light use efficiency. At the canopy scale, GPP was limited by light interception (canopy level), but co-limited by nitrogen and water at the leaf level. Contrary to expectations, the impacts of an intense growing season drought were greater at the mesic site. Modelling indicated a 10% greater decrease in mesic GPP compared with the xeric site. Xeric P. palustris trees exhibited drought-tolerant behaviour that contrasted with mesic trees' drought-avoidance behaviour. © 2012 Blackwell Publishing Ltd.
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.
NASA Astrophysics Data System (ADS)
Lund, M.; Zona, D.; Jackowicz-Korczynski, M.; Xu, X.
2017-12-01
The eddy covariance methodology is the primary tool for studying landscape-scale land-atmosphere exchange of greenhouse gases. Since the choice of instrumental setup and processing algorithms may influence the results, efforts within the international flux community have been made towards methodological harmonization and standardization. Performing eddy covariance measurements in high-latitude, Arctic tundra sites involves several challenges, related not only to remoteness and harsh climate conditions but also to the choice of processing algorithms. Partitioning of net ecosystem exchange (NEE) of CO2 into gross primary production (GPP) and ecosystem respiration (Reco) in the FLUXNET2015 dataset is made using either Nighttime or Daytime methods. These variables, GPP and Reco, are essential for calibration and validation of Earth system models. North of the Arctic Circle, sun remains visible at local midnight for a period of time, the number of days per year with midnight sun being dependent on latitude. The absence of nighttime conditions during Arctic summers renders the Nighttime method uncertain, however, no extensive assessment on the implications for flux partitioning has yet been made. In this study, we will assess the performance and validity of both partitioning methods along a latitudinal transect of northern sites included in the FLUXNET2015 dataset. We will evaluate the partitioned flux components against model simulations using the Community Land Model (CLM). Our results will be valuable for users interested in simulating Arctic and global carbon cycling.
Remotely-sensed detection of effects of extreme droughts on gross primary production.
Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep
2016-06-15
Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space.
Remotely-sensed detection of effects of extreme droughts on gross primary production
Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep
2016-01-01
Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space. PMID:27301671
Lee, Jae-Woo; Park, Young-Ha; Seok, Yeong-Jae
2018-06-18
Bacteria respond to nutritional stresses by changing the cellular concentration of the alarmone (p)ppGpp. This control mechanism, called the stringent response, depends on two enzymes, the (p)ppGpp synthetase RelA and the bifunctional (p)ppGpp synthetase/hydrolase SpoT in Escherichia coli and related bacteria. Because SpoT is the only enzyme responsible for (p)ppGpp hydrolysis in these bacteria, SpoT activity needs to be tightly regulated to prevent the uncontrolled accumulation of (p)ppGpp, which is lethal. To date, however, no such regulation of SpoT (p)ppGpp hydrolase activity has been documented in E. coli In this study, we show that Rsd directly interacts with SpoT and stimulates its (p)ppGpp hydrolase activity. Dephosphorylated HPr, but not phosphorylated HPr, of the phosphoenolpyruvate-dependent sugar phosphotransferase system could antagonize the stimulatory effect of Rsd on SpoT (p)ppGpp hydrolase activity. Thus, we suggest that Rsd is a carbon source-dependent regulator of the stringent response in E. coli . Copyright © 2018 the Author(s). Published by PNAS.
NASA Astrophysics Data System (ADS)
Ito, Akihiko; Nishina, Kazuya; Reyer, Christopher P. O.; François, Louis; Henrot, Alexandra-Jane; Munhoven, Guy; Jacquemin, Ingrid; Tian, Hanqin; Yang, Jia; Pan, Shufen; Morfopoulos, Catherine; Betts, Richard; Hickler, Thomas; Steinkamp, Jörg; Ostberg, Sebastian; Schaphoff, Sibyll; Ciais, Philippe; Chang, Jinfeng; Rafique, Rashid; Zeng, Ning; Zhao, Fang
2017-08-01
Simulating vegetation photosynthetic productivity (or gross primary production, GPP) is a critical feature of the biome models used for impact assessments of climate change. We conducted a benchmarking of global GPP simulated by eight biome models participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a) with four meteorological forcing datasets (30 simulations), using independent GPP estimates and recent satellite data of solar-induced chlorophyll fluorescence as a proxy of GPP. The simulated global terrestrial GPP ranged from 98 to 141 Pg C yr-1 (1981-2000 mean); considerable inter-model and inter-data differences were found. Major features of spatial distribution and seasonal change of GPP were captured by each model, showing good agreement with the benchmarking data. All simulations showed incremental trends of annual GPP, seasonal-cycle amplitude, radiation-use efficiency, and water-use efficiency, mainly caused by the CO2 fertilization effect. The incremental slopes were higher than those obtained by remote sensing studies, but comparable with those by recent atmospheric observation. Apparent differences were found in the relationship between GPP and incoming solar radiation, for which forcing data differed considerably. The simulated GPP trends co-varied with a vegetation structural parameter, leaf area index, at model-dependent strengths, implying the importance of constraining canopy properties. In terms of extreme events, GPP anomalies associated with a historical El Niño event and large volcanic eruption were not consistently simulated in the model experiments due to deficiencies in both forcing data and parameterized environmental responsiveness. Although the benchmarking demonstrated the overall advancement of contemporary biome models, further refinements are required, for example, for solar radiation data and vegetation canopy schemes.
Jose Luiz Stape; Dan Binkley; Michael G. Ryan
2008-01-01
We examined resource limitations on growth and carbon allocation in a fast-growing, clonal plantation of Eucalyptus grandis urophylla in Brazil by characterizing responses to annual rainfall, and response to irrigation and fertililization for 2 years. Productivity measures included gross primary production (GPP), total belowground carbon allocation (...
Mark E. Harmon; Ken Bible; Michael G. Ryan; David C. Shaw; H. Chen; Jeffrey Klopatek; Xia Li
2004-01-01
Ground-based measurements of stores, growth, mortality, litterfall, respiration, and decomposition were conducted in an old-growth forest at Wind River Experimental Forest, Washington. These measurements were used to estimate: Gross (GPP) and Net Primary Production (NPP); autotrophic (Ra) and heterotrophic (Rh) respiration; and Net Ecosystem Production (NEP). Monte...
NASA Astrophysics Data System (ADS)
Wu, Donghai; Ciais, Philippe; Viovy, Nicolas; Knapp, Alan K.; Wilcox, Kevin; Bahn, Michael; Smith, Melinda D.; Vicca, Sara; Fatichi, Simone; Zscheischler, Jakob; He, Yue; Li, Xiangyi; Ito, Akihiko; Arneth, Almut; Harper, Anna; Ukkola, Anna; Paschalis, Athanasios; Poulter, Benjamin; Peng, Changhui; Ricciuto, Daniel; Reinthaler, David; Chen, Guangsheng; Tian, Hanqin; Genet, Hélène; Mao, Jiafu; Ingrisch, Johannes; Nabel, Julia E. S. M.; Pongratz, Julia; Boysen, Lena R.; Kautz, Markus; Schmitt, Michael; Meir, Patrick; Zhu, Qiuan; Hasibeder, Roland; Sippel, Sebastian; Dangal, Shree R. S.; Sitch, Stephen; Shi, Xiaoying; Wang, Yingping; Luo, Yiqi; Liu, Yongwen; Piao, Shilong
2018-06-01
Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon-water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results
Monitoring Crop Productivity over the U.S. Corn Belt using an Improved Light Use Efficiency Model
NASA Astrophysics Data System (ADS)
Wu, X.; Xiao, X.; Zhang, Y.; Qin, Y.; Doughty, R.
2017-12-01
Large-scale monitoring of crop yield is of great significance for forecasting food production and prices and ensuring food security. Satellite data that provide temporally and spatially continuous information that by themselves or in combination with other data or models, raises possibilities to monitor and understand agricultural productivity regionally. In this study, we first used an improved light use efficiency model-Vegetation Photosynthesis Model (VPM) to simulate the gross primary production (GPP). Model evaluation showed that the simulated GPP (GPPVPM) could well captured the spatio-temporal variation of GPP derived from FLUXNET sites. Then we applied the GPPVPM to further monitor crop productivity for corn and soybean over the U.S. Corn Belt and benchmarked with county-level crop yield statistics. We found VPM-based approach provides pretty good estimates (R2 = 0.88, slope = 1.03). We further showed the impacts of climate extremes on the crop productivity and carbon use efficiency. The study indicates the great potential of VPM in estimating crop yield and in understanding of crop yield responses to climate variability and change.
NASA Astrophysics Data System (ADS)
Gentine, P.; Alemohammad, S. H.
2018-04-01
Solar-induced fluorescence (SIF) observations from space have resulted in major advancements in estimating gross primary productivity (GPP). However, current SIF observations remain spatially coarse, infrequent, and noisy. Here we develop a machine learning approach using surface reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) channels to reproduce SIF normalized by clear sky surface irradiance from the Global Ozone Monitoring Experiment-2 (GOME-2). The resulting product is a proxy for ecosystem photosynthetically active radiation absorbed by chlorophyll (fAPARCh). Multiplying this new product with a MODIS estimate of photosynthetically active radiation provides a new MODIS-only reconstruction of SIF called Reconstructed SIF (RSIF). RSIF exhibits much higher seasonal and interannual correlation than the original SIF when compared with eddy covariance estimates of GPP and two reference global GPP products, especially in dry and cold regions. RSIF also reproduces intense productivity regions such as the U.S. Corn Belt contrary to typical vegetation indices and similarly to SIF.
NASA Astrophysics Data System (ADS)
Wu, D.; Ciais, P.; Viovy, N.; Knapp, A.; Wilcox, K.; Bahn, M.; Smith, M. D.; Ito, A.; Arneth, A.; Harper, A. B.; Ukkola, A.; Paschalis, A.; Poulter, B.; Peng, C.; Reick, C. H.; Hayes, D. J.; Ricciuto, D. M.; Reinthaler, D.; Chen, G.; Tian, H.; Helene, G.; Zscheischler, J.; Mao, J.; Ingrisch, J.; Nabel, J.; Pongratz, J.; Boysen, L.; Kautz, M.; Schmitt, M.; Krohn, M.; Zeng, N.; Meir, P.; Zhang, Q.; Zhu, Q.; Hasibeder, R.; Vicca, S.; Sippel, S.; Dangal, S. R. S.; Fatichi, S.; Sitch, S.; Shi, X.; Wang, Y.; Luo, Y.; Liu, Y.; Piao, S.
2017-12-01
Changes in precipitation variability including the occurrence of extreme events strongly influence plant growth in grasslands. Field measurements of aboveground net primary production (ANPP) in temperate grasslands suggest a positive asymmetric response with wet years resulting in ANPP gains larger than ANPP declines in dry years. Whether land surface models used for historical simulations and future projections of the coupled carbon-water system in grasslands are capable to simulate such non-symmetrical ANPP responses remains an important open research question. In this study, we evaluate the simulated responses of grassland primary productivity to altered precipitation with fourteen land surface models at the three sites of Colorado Shortgrass Steppe (SGS), Konza prairie (KNZ) and Stubai Valley meadow (STU) along a rainfall gradient from dry to wet. Our results suggest that: (i) Gross primary production (GPP), NPP, ANPP and belowground NPP (BNPP) show nonlinear response curves (concave-down) in all the models, but with different curvatures and mean values. In contrast across the sites, primary production increases and then saturates along increasing precipitation with a flattening at the wetter site. (ii) Slopes of spatial relationships between modeled primary production and precipitation are steeper than the temporal slopes (obtained from inter-annual variations). (iii) Asymmetric responses under nominal precipitation range with modeled inter-annual primary production show large uncertainties, and model-ensemble median generally suggests negative asymmetry (greater declines in dry years than increases in wet years) across the three sites. (iv) Primary production at the drier site is predicted to more sensitive to precipitation compared to wetter site, and median sensitivity consistently indicates greater negative impacts of reduced precipitation than positive effects of increased precipitation under extreme conditions. This study implies that most models
NASA Astrophysics Data System (ADS)
Ledford, S. H.; Toran, L.
2017-12-01
Impacts of wastewater treatment plant effluent on nutrient retention and stream productivity are highly varied. The working theory has been that large pulses of nutrients from plants may hinder in-stream nutrient retention. We evaluated nitrate, total dissolved phosphorus, and dissolved oxygen in Wissahickon Creek, an urban third-order stream in Montgomery and Philadelphia counties, PA, that receives effluent from four wastewater treatment plants. Wastewater treatment plant effluent had nitrate concentrations of 15-30 mg N/L and total dissolved phosphorus of 0.3 to 1.8 mg/L. Seasonal longitudinal water quality samples showed nitrate concentrations were highest in the fall, peaking at 22 mg N/L, due to low baseflow, but total dissolved phosphorous concentrations were highest in the spring, reaching 0.6 mg/L. Diurnal dissolved oxygen patterns above and below one of the treatment plants provided estimates of gross primary productivity (GPP) and ecosystem respiration (ER). A site 1 km below effluent discharge had higher GPP in April (80 g O2 m-2 d-1) than the site above the plant (28 g O2 m-2 d-1). The pulse in productivity did not continue downstream, as the site 3 km below the plant had GPP of only 12 g O2 m-2 d-1. Productivity fell in June to 1-2 g O2 m-2 d-1 and the differences in productivity above and below plants were minimal. Ecosystem respiration followed a similar pattern in April, increasing from -17 g O2 m-2 d-1 above the plant to -47 g O2 m-2 d-1 1 km below the plant, then decreasing to -8 g O2 m-2 d-1 3 km below the plant. Respiration dropped to -3 g O2 m-2 d-1 above the plant in June but only fell to -9 to -10 g O2 m-2 d-1 at the two downstream sites. These findings indicate that large nutrient pulses from wastewater treatment plants spur productivity and respiration, but that these increases may be strongly seasonally dependent. Examining in-stream productivity and respiration is critical in wastewater impacted streams to understanding the seasonal and
Estimating crop net primary production using inventory data and MODIS-derived parameters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.
2013-06-03
National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois inmore » years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.« less
NASA Astrophysics Data System (ADS)
Zanotelli, D.; Montagnani, L.; Manca, G.; Tagliavini, M.
2013-05-01
Carbon use efficiency (CUE), the ratio of net primary production (NPP) over gross primary production (GPP), is a functional parameter that could possibly link the current increasingly accurate global GPP estimates with those of net ecosystem exchange, for which global predictors are still unavailable. Nevertheless, CUE estimates are actually available for only a few ecosystem types, while information regarding agro-ecosystems is scarce, in spite of the simplified spatial structure of these ecosystems that facilitates studies on allocation patterns and temporal growth dynamics. We combined three largely deployed methods, eddy covariance, soil respiration and biometric measurements, to assess monthly values of CUE, NPP and allocation patterns in different plant organs in an apple orchard during a complete year (2010). We applied a measurement protocol optimized for quantifying monthly values of carbon fluxes in this ecosystem type, which allows for a cross check between estimates obtained from different methods. We also attributed NPP components to standing biomass increments, detritus cycle feeding and lateral exports. We found that in the apple orchard, both net ecosystem production and gross primary production on a yearly basis, 380 ± 30 g C m-2 and 1263 ± 189 g C m-2 respectively, were of a magnitude comparable to those of natural forests growing in similar climate conditions. The largest differences with respect to forests are in the allocation pattern and in the fate of produced biomass. The carbon sequestered from the atmosphere was largely allocated to production of fruit: 49% of annual NPP was taken away from the ecosystem through apple production. Organic material (leaves, fine root litter, pruned wood and early fruit falls) contributing to the detritus cycle was 46% of the NPP. Only 5% was attributable to standing biomass increment, while this NPP component is generally the largest in forests. The CUE, with an annual average of 0.71 ± 0.12, was higher
Vegetation Health and Productivity Indicators for Sustained National Climate Assessments
NASA Astrophysics Data System (ADS)
Jones, M. O.; Running, S. W.
2014-12-01
The National Climate Assessment process is developing a system of physical, ecological, and societal indicators that communicate key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness for the purpose of informing both decision makers and the public. Implementing a 14 year record of Gross and Net Primary Productivity (GPP/NPP) derived from the NASA EOS MODIS satellite sensor we demonstrate how these products can serve as Ecosystem Productivity and Vegetation Health National Climate Indicators for implementation in sustained National Climate Assessments. The NPP product combines MODIS vegetation data with daily global meteorology to calculate annual growth of all plant material at 1 sq. km resolution. NPP anomalies identify regions with above or below average plant growth that may result from climate fluctuations and can inform carbon source/sink dynamics, agricultural and forestry yield measures, and response to wildfire or drought conditions. The GPP product provides a high temporal resolution (8-day) metric of vegetation growth which can be used to monitor short-term vegetation response to extreme events and implemented to derive vegetation phenology metrics; growing season start, end, and length, which can elucidate land cover and regionally specific vegetation responses to a changing climate. The high spatial resolution GPP and NPP indicators can also inform and clarify responses seen from other proposed Pilot Indicators such as forest growth/productivity, land cover, crop production, and phenology. The GPP and NPP data are in continuous production and will be sustained into the future with the next generation satellite missions. The long-term Ecosystem Productivity and Vegetation Health Indicators are ideal for use in sustained National Climate Assessments, providing regionally specific responses to a changing climate and complete coverage at the national scale.
Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.; ...
2016-10-20
Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.
Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological
Sippel, Sebastian; Mahecha, Miguel D.; Hauhs, Michael; Bodesheim, Paul; Kaminski, Thomas; Gans, Fabian; Rosso, Osvaldo A.
2016-01-01
Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time
Leaf chlorophyll constraint on model simulated gross primary productivity in agricultural systems
NASA Astrophysics Data System (ADS)
Houborg, Rasmus; McCabe, Matthew F.; Cescatti, Alessandro; Gitelson, Anatoly A.
2015-12-01
Leaf chlorophyll content (Chll) may serve as an observational proxy for the maximum rate of carboxylation (Vmax), which describes leaf photosynthetic capacity and represents the single most important control on modeled leaf photosynthesis within most Terrestrial Biosphere Models (TBMs). The parameterization of Vmax is associated with great uncertainty as it can vary significantly between plants and in response to changes in leaf nitrogen (N) availability, plant phenology and environmental conditions. Houborg et al. (2013) outlined a semi-mechanistic relationship between Vmax25 (Vmax normalized to 25 °C) and Chll based on inter-linkages between Vmax25, Rubisco enzyme kinetics, N and Chll. Here, these relationships are parameterized for a wider range of important agricultural crops and embedded within the leaf photosynthesis-conductance scheme of the Community Land Model (CLM), bypassing the questionable use of temporally invariant and broadly defined plant functional type (PFT) specific Vmax25 values. In this study, the new Chll constrained version of CLM is refined with an updated parameterization scheme for specific application to soybean and maize. The benefit of using in-situ measured and satellite retrieved Chll for constraining model simulations of Gross Primary Productivity (GPP) is evaluated over fields in central Nebraska, U.S.A between 2001 and 2005. Landsat-based Chll time-series records derived from the Regularized Canopy Reflectance model (REGFLEC) are used as forcing to the CLM. Validation of simulated GPP against 15 site-years of flux tower observations demonstrate the utility of Chll as a model constraint, with the coefficient of efficiency increasing from 0.91 to 0.94 and from 0.87 to 0.91 for maize and soybean, respectively. Model performances particularly improve during the late reproductive and senescence stage, where the largest temporal variations in Chll (averaging 35-55 μg cm-2 for maize and 20-35 μg cm-2 for soybean) are observed. While
Bolton, Douglas K; Coops, Nicholas C; Wulder, Michael A
2013-08-01
The structure and productivity of boreal forests are key components of the global carbon cycle and impact the resources and habitats available for species. With this research, we characterized the relationship between measurements of forest structure and satellite-derived estimates of gross primary production (GPP) over the Canadian boreal. We acquired stand level indicators of canopy cover, canopy height, and structural complexity from nearly 25,000 km of small-footprint discrete return Light Detection and Ranging (Lidar) data and compared these attributes to GPP estimates derived from the MODerate resolution Imaging Spectroradiometer (MODIS). While limited in our capacity to control for stand age, we removed recently disturbed and managed forests using information on fire history, roads, and anthropogenic change. We found that MODIS GPP was strongly linked to Lidar-derived canopy cover (r = 0.74, p < 0.01), however was only weakly related to Lidar-derived canopy height and structural complexity as these attributes are largely a function of stand age. A relationship was apparent between MODIS GPP and the maximum sampled heights derived from Lidar as growth rates and resource availability likely limit tree height in the prolonged absence of disturbance. The most structurally complex stands, as measured by the coefficient of variation of Lidar return heights, occurred where MODIS GPP was highest as productive boreal stands are expected to contain a wider range of tree heights and transition to uneven-aged structures faster than less productive stands. While MODIS GPP related near-linearly to Lidar-derived canopy cover, the weaker relationships to Lidar-derived canopy height and structural complexity highlight the importance of stand age in determining the structure of boreal forests. We conclude that an improved quantification of how both productivity and disturbance shape stand structure is needed to better understand the current state of boreal forests in
Biochemical studies on Francisella tularensis RelA in (p)ppGpp biosynthesis
Wilkinson, Rachael C.; Batten, Laura E.; Wells, Neil J.; Oyston, Petra C.F.; Roach, Peter L.
2015-01-01
The bacterial stringent response is induced by nutrient deprivation and is mediated by enzymes of the RSH (RelA/SpoT homologue; RelA, (p)ppGpp synthetase I; SpoT, (p)ppGpp synthetase II) superfamily that control concentrations of the ‘alarmones’ (p)ppGpp (guanosine penta- or tetra-phosphate). This regulatory pathway is present in the vast majority of pathogens and has been proposed as a potential anti-bacterial target. Current understanding of RelA-mediated responses is based on biochemical studies using Escherichia coli as a model. In comparison, the Francisella tularensis RelA sequence contains a truncated regulatory C-terminal region and an unusual synthetase motif (EXSD). Biochemical analysis of F. tularensis RelA showed the similarities and differences of this enzyme compared with the model RelA from Escherichia coli. Purification of the enzyme yielded a stable dimer capable of reaching concentrations of 10 mg/ml. In contrast with other enzymes from the RelA/SpoT homologue superfamily, activity assays with F. tularensis RelA demonstrate a high degree of specificity for GTP as a pyrophosphate acceptor, with no measurable turnover for GDP. Steady state kinetic analysis of F. tularensis RelA gave saturation activity curves that best fitted a sigmoidal function. This kinetic profile can result from allosteric regulation and further measurements with potential allosteric regulators demonstrated activation by ppGpp (5′,3′-dibisphosphate guanosine) with an EC50 of 60±1.9 μM. Activation of F. tularensis RelA by stalled ribosomal complexes formed with ribosomes purified from E. coli MRE600 was observed, but interestingly, significantly weaker activation with ribosomes isolated from Francisella philomiragia. PMID:26450927
Syal, Kirtimaan; Bhardwaj, Neerupma; Chatterji, Dipankar
2017-01-01
Earlier, vitamin C was demonstrated to sterilize Mycobacterium tuberculosis culture via Fenton's reaction at high concentration. It alters the regulatory pathways associated with stress response and dormancy. Since (p)ppGpp is considered to be the master regulator of stress response and is responsible for bacterial survival under stress, we tested the effect of vitamin C on the formation of (p)ppGpp. In vivo estimation of (p)ppGpp showed a decrease in (p)ppGpp levels in vitamin C-treated M. smegmatis cells in comparison to the untreated cells. Furthermore, in vitro (p)ppGpp synthesis using Rel MSM enzyme was conducted in order to confirm the specificity of the inhibition in the presence of variable concentrations of vitamin C. We observed that vitamin C at high concentration can inhibit the synthesis of (p)ppGpp. We illustrated binding of vitamin C to Rel MSM by isothermal titration calorimetry. Enzyme kinetics was followed where K 0.5 was found to be increased with the concomitant reduction of V max value suggesting mixed inhibition. Both long-term survival and biofilm formation were inhibited by vitamin C. The experiments suggest that vitamin C has the potential to be developed as the inhibitor of (p)ppGpp synthesis and stress response, at least in the concentration range used here. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Developing a Data Driven Process-Based Model for Remote Sensing of Ecosystem Production
NASA Astrophysics Data System (ADS)
Elmasri, B.; Rahman, A. F.
2010-12-01
Estimating ecosystem carbon fluxes at various spatial and temporal scales is essential for quantifying the global carbon cycle. Numerous models have been developed for this purpose using several environmental variables as well as vegetation indices derived from remotely sensed data. Here we present a data driven modeling approach for gross primary production (GPP) that is based on a process based model BIOME-BGC. The proposed model was run using available remote sensing data and it does not depend on look-up tables. Furthermore, this approach combines the merits of both empirical and process models, and empirical models were used to estimate certain input variables such as light use efficiency (LUE). This was achieved by using remotely sensed data to the mathematical equations that represent biophysical photosynthesis processes in the BIOME-BGC model. Moreover, a new spectral index for estimating maximum photosynthetic activity, maximum photosynthetic rate index (MPRI), is also developed and presented here. This new index is based on the ratio between the near infrared and the green bands (ρ858.5/ρ555). The model was tested and validated against MODIS GPP product and flux measurements from two eddy covariance flux towers located at Morgan Monroe State Forest (MMSF) in Indiana and Harvard Forest in Massachusetts. Satellite data acquired by the Advanced Microwave Scanning Radiometer (AMSR-E) and MODIS were used. The data driven model showed a strong correlation between the predicted and measured GPP at the two eddy covariance flux towers sites. This methodology produced better predictions of GPP than did the MODIS GPP product. Moreover, the proportion of error in the predicted GPP for MMSF and Harvard forest was dominated by unsystematic errors suggesting that the results are unbiased. The analysis indicated that maintenance respiration is one of the main factors that dominate the overall model outcome errors and improvement in maintenance respiration estimation
NEE and GPP dynamic evolution at two biomes in the upper Spanish plateau
NASA Astrophysics Data System (ADS)
Sánchez, María Luisa; Pardo, Nuria; Pérez, Isidro Alberto; García, Maria de los Angeles
2014-05-01
In order to assess the ability of dominant biomes to act as a CO2 sink, two eddy correlation stations close to each other in central Spain have been concurrently operational since March 2008 until the present. The land use of the first station, AC, is a rapeseed rotating crop consisting of annual rotation of non-irrigated rapeseed, barley, peas, rye, and sunflower, respectively. The land use of the second, CIBA, is a mixture of open shrubs/crops, with open shrubs being markedly dominant. The period of measurements covered variable general meteorological conditions. 2009 and 2012 were dominated by drought, whereas 2010 was the rainiest year. Annual rainfall during 2008 and 2009 was close to the historical averaged annual means. This paper presents the dynamic evolution of NEE-8d and GPP-8d observed at the AC station over five years and compares the results with those concurrently observed at the CIBA station. GGP 8-d estimates at both stations were determined using a Light Use Efficiency Model, LUE. Input data for the LUE model were the FPAR 8-d products supplied by MODIS, PAR in situ measurements, and a scalar f, varying between 0 and 1, to take account of the reduction in maximum PAR conversion efficiency, ɛ0, under limiting environmental conditions. f values were assumed to be dependent on air temperature and evaporative fraction, EF, which was considered a proxy of soil moisture. ɛ0, a key parameter, which depends on land use types, was derived through the results of a linear regression fit between the GPP 8-d eddy covariance composites observed and the LUE concurrent 8-d model estimates. Over the five-year study period, both biomes behaved as CO2 sinks. However, the ratio of the NEE-8d total accumulated at AC and CIBA, respectively, was close to a factor two, revealing the effectiveness of the studied crops as CO2 sinks. On an annual basis, accumulated NEE-8d exhibited major variability in both biomes. At CIBA, the results were largely dominated by the
NASA Astrophysics Data System (ADS)
Xia, Jianyang; McGuire, A. David; Lawrence, David; Burke, Eleanor; Chen, Guangsheng; Chen, Xiaodong; Delire, Christine; Koven, Charles; MacDougall, Andrew; Peng, Shushi; Rinke, Annette; Saito, Kazuyuki; Zhang, Wenxin; Alkama, Ramdane; Bohn, Theodore J.; Ciais, Philippe; Decharme, Bertrand; Gouttevin, Isabelle; Hajima, Tomohiro; Hayes, Daniel J.; Huang, Kun; Ji, Duoying; Krinner, Gerhard; Lettenmaier, Dennis P.; Miller, Paul A.; Moore, John C.; Smith, Benjamin; Sueyoshi, Tetsuo; Shi, Zheng; Yan, Liming; Liang, Junyi; Jiang, Lifen; Zhang, Qian; Luo, Yiqi
2017-02-01
Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m-2 yr-1), most models produced higher NPP (309 ± 12 g C m-2 yr-1) over the permafrost region during 2000-2009. By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982-2009, there was a twofold discrepancy among models (380 to 800 g C m-2 yr-1), which mainly resulted from differences in simulated maximum monthly GPP (GPPmax). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vcmax_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPPmax as well as their sensitivity to climate change.
NASA Astrophysics Data System (ADS)
Yan, D.; Scott, R. L.; Moore, D. J.; Biederman, J. A.; Smith, W. K.
2017-12-01
Land surface phenology (LSP) - defined as remotely sensed seasonal variations in vegetation greenness - is intrinsically linked to seasonal carbon uptake, and is thus commonly used as a proxy for vegetation productivity (gross primary productivity; GPP). Yet, the relationship between LSP and GPP remains uncertain, particularly for understudied dryland ecosystems characterized by relatively large spatial and temporal variability. Here, we explored the relationship between LSP and the phenology of GPP for three dominant dryland ecosystem types, and we evaluated how these relationships change as a function of spatial and temporal scale. We focused on three long-term dryland eddy covariance flux tower sites: Walnut Gulch Lucky Hills Shrubland (WHS), Walnut Gulch Kendall Grassland (WKG), and Santa Rita Mesquite (SRM). We analyzed daily canopy-level, 16-day 30m, and 8-day 500m time series of greenness indices from PhenoCam, Landsat 7 ETM+/Landsat 8 OLI, and MODIS, respectively. We first quantified the impact of spatial scale by temporally resampling canopy-level PhenoCam, 30m Landsat, and 500m MODIS to 16-day intervals and then comparing against flux tower GPP estimates. We next quantified the impact of temporal scale by spatially resampling daily PhenoCam, 16-day Landsat, and 8-day MODIS to 500m time series and then comparing against flux tower GPP estimates. We find evidence of critical periods of decoupling between LSP and the phenology of GPP that vary according to the spatial and temporal scale, and as a function of ecosystem type. Our results provide key insight into dryland LSP and GPP dynamics that can be used in future efforts to improve ecosystem process models and satellite-based vegetation productivity algorithms.
GPP Webinar: The Solar Roadmap—Navigating the Evolving Solar Energy Market
GPP and State & Local Climate and Energy Branch webinar on the Solar Roadmap and the evolving solar energy market. This webinar discussed local and state government’s success stories and opportunities for progress in renewable energy goals using the Solar
Houser, J.N.; Mulholland, P.J.; Maloney, K.O.
2005-01-01
Catchment characteristics determine the inputs of sediments and nutrients to streams. As a result, natural or anthropogenic disturbance of upland soil and vegetation can affect instream processes. The Fort Benning Military Installation (near Columbus, Georgia) exhibits a wide range of upland disturbance levels because of spatial variability in the intensity of military training. This gradient of disturbance was used to investigate the effect of upland soil and vegetation disturbance on rates of stream metabolism (ecosystem respiration rate [ER] and gross primary production rate [GPP]). Stream metabolism was measured using an open-system, single-station approach. All streams were net heterotrophic during all seasons. ER was highest in winter and spring and lowest in summer and autumn. ER was negatively correlated with catchment disturbance level in winter, spring, and summer, but not in autumn. ER was positively correlated with abundance of coarse woody debris, but not significantly related to % benthic organic matter. GPP was low in all streams and generally not significantly correlated with disturbance level. Our results suggest that the generally intact riparian zones of these streams were not sufficient to protect them from the effect of upland disturbance, and they emphasize the role of the entire catchment in determining stream structure and function. ?? 2005 by The North American Benthological Society.
Baptist, Florence; Choler, Philippe
2008-01-01
Background and Aims Along snowmelt gradients, the canopies of temperate alpine meadows differ strongly in their structural and biochemical properties. Here, a study is made of the effects of these canopy dissimilarities combined with the snow-induced changes in length of growing season on seasonal gross primary production (GPP). Methods Leaf area index (LAI) and community-aggregated values of leaf angle and leaf nitrogen content were estimated for seven alpine plant canopies distributed along a marked snowmelt gradient, and these were used as input variables in a sun–shade canopy bulk-photosynthesis model. The model was validated for plant communities of early and late snowmelt sites by measuring the instantaneous CO2 fluxes with a canopy closed-chamber technique. A sensitivity analysis was conducted to estimate the relative impact of canopy properties and environmental factors on the daily and seasonal GPP. Key Results Carbon uptake was primarily related to the LAI and total canopy nitrogen content, but not to the leaf angle. For a given level of photosynthetically active radiation, CO2 assimilation was higher under overcast conditions. Sensitivity analysis revealed that increase of the length of the growing season had a higher effect on the seasonal GPP than a similar increase of any other factor. It was also found that the observed greater nitrogen content and larger LAI of canopies in late-snowmelt sites largely compensated for the negative impact of the reduced growing season. Conclusions The results emphasize the primary importance of snow-induced changes in length of growing season on carbon uptake in alpine temperate meadows. It was also demonstrated how using leaf-trait values of the dominants is a useful approach for modelling ecosystem carbon-cycle-related processes, particularly when continuous measurements of CO2 fluxes are technically difficult. The study thus represents an important step in addressing the challenge of using a plant functional
The 'overflow tap' theory: linking GPP to forest soil carbon dynamics and the mycorrhizal component
NASA Astrophysics Data System (ADS)
Heinemeyer, Andreas; Willkinson, Matthew; Subke, Jens-Arne; Casella, Eric; Vargas, Rodrigo; Morison, James; Ineson, Phil
2010-05-01
productivity. The work presented here focuses on three critical areas: (1) We present annual fluxes at hourly intervals for the three soil CO2 efflux components (R, F and H) from a 75 year-old deciduous oak forest in SE England. We investigate the individual environmental responses of the three flux components, and compare them to soil decomposition modelled by CENTURY and its latest version (i.e. DAYCENT), which separately models root-derived respiration in addition to the soil decomposition output. (2) Using estimates of gross primary productivity (GPP) based on eddy covariance measurements from the same site, we explore linkages between GPP and soil respiration component fluxes using basic regression and wavelet analyses. We show a distinctly different time lag signal between GPP and root vs. mycorrhizal fungal respiration. We then discuss how models might need to be improved to accurately predict total soil CO2 efflux, including root-derived respiration. (3) We finally discuss the ‘overflow tap' theory, that during periods of high assimilation (e.g. optimum environmental conditions or elevated CO2) surplus non-structural C is allocated belowground to the mycorrhizal network; this additional C could then be used and released by the associated fungal partners, causing soil priming through stimulating decomposition.
NASA Astrophysics Data System (ADS)
Cooper, L. A.; Ballantyne, A.; Holden, Z. A.; Landguth, E.
2015-12-01
Disturbance plays an important role in the structure, composition, and nutrient cycling of forest ecosystems. Climate change is resulting in an increase in disturbance frequency and intensity, making it critical that we quantify the physical and chemical impacts of disturbances on forests. The impacts of disturbance are thought to vary widely depending on disturbance type, location, and climate. More specifically, fires, insect infestations, and other types of disturbances differ in their timing, extent, and intensity making it difficult to assess the true impact of disturbances on local energy budgets and carbon cycling. Here, we provide a regional analysis of the impacts of fire, insect attack, and other disturbances on land surface temperature (LST), carbon stocks, and gross primary productivity (GPP). Using disturbances detected with MODIS Enhanced Vegetation Index (EVI) time series between 2002 and 2012, we find that the impacts of disturbance on LST, carbon stocks, and GPP vary widely according to local climate, vegetation, and disturbance type and intensity. Fires resulted in the most distinct impacts on all response variables. Forest responses to insect epidemics were more varied in their magnitude and timing. The results of this study provide an important estimation of the variability of climate and ecosystem responses to disturbance across a large and heterogeneous landscape. With disturbance projected to increase in both frequency and intensity around the globe in the coming years, this information is vitally important to effectively manage forests into the future.
Xia, Jianyang; McGuire, A. David; Lawrence, David; Burke, Eleanor J.; Chen, Guangsheng; Chen, Xiaodong; Delire, Christine; Koven, Charles; MacDougall, Andrew; Peng, Shushi; Rinke, Annette; Saito, Kazuyuki; Zhang, Wenxin; Alkama, Ramdane; Bohn, Theodore J.; Ciais, Philippe; Decharme, Bertrand; Gouttevin, Isabelle; Hajima, Tomohiro; Hayes, Daniel J.; Huang, Kun; Ji, Duoying; Krinner, Gerhard; Lettenmaier, Dennis P.; Miller, Paul A.; Moore, John C.; Smith, Benjamin; Sueyoshi, Tetsuo; Shi, Zheng; Yan, Liming; Liang, Junyi; Jiang, Lifen; Zhang, Qian; Luo, Yiqi
2017-01-01
Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m−2 yr−1), most models produced higher NPP (309 ± 12 g C m−2 yr−1) over the permafrost region during 2000–2009. By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a twofold discrepancy among models (380 to 800 g C m−2 yr−1), which mainly resulted from differences in simulated maximum monthly GPP (GPPmax). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vcmax_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPPmax as well as their sensitivity to climate change.
NASA Astrophysics Data System (ADS)
Liu, Z.; Ballantyne, A.; Poulter, B.; Anderegg, W.; Jacobson, A. R.; Miller, J. B.
2017-12-01
Interannual variability (IAV) of atmospheric CO2 is primarily driven by fluctuations in net carbon exchange (NEE) by terrestrial ecosystems. Recent analyses suggested that global terrestrial carbon uptake is dominated by the sensitivity of productivity to precipitation in semi-arid ecosystems, or sensitivity of respiration to temperature in tropical ecosystems. There is a need to better understand factors that control the carbon balance of land ecosystems across spatial and temporal scales. Here we used multiple observational dataset to assess: (1) What are the dominant processes controlling the IAV of NEE in terrestrial ecosystem? What are the climatic controls on the variability gross primary productivity (GPP) and total ecosystem respiration (TER) in the contiguous United States (CONUS). Our analysis revealed that there is a strong positive correlation between IAV of GPP and IAV of NEE in drier (mean annual precipitation: MAP < 750mm) western ecosystem, while there is no correlation between IAV of GPP and IAV of NEE in moist (MAP > 750mm) eastern ecosystem using observational dataset. Both βspatial and βtemporal of GPP and TER to precipitation exhibit an emergent threshold where GPP is more sensitive than TER to precipitation in semi-arid western ecosystems and TER is more sensitive than GPP to precipitation in more humid eastern ecosystems. This emergent ecosystem threshold was evident in several independent observations. However, analyses from 10 TRENDY models indicate current Dynamic Global Vegetation Models (DGVMs) tend to overestimate the sensitivity of NEE to GPP and underestimate the sensitivity of NEE to TER to precipitation across CONUS ecosystems. TER experiments showed that commonly used TER models failed to capture the IAV of TER in the moist region in CONUS. This is because heterotrophic respiration (Rh) was relatively independent of GPP in moist regions of CONUS, but was too tightly coupled to GPP in the DGVMs. The emergent thresholds at the
NASA Astrophysics Data System (ADS)
Wang, Sheng; Bandini, Filippo; Jakobsen, Jakob; Zarco-Tejada, Pablo J.; Köppl, Christian Josef; Haugård Olesen, Daniel; Ibrom, Andreas; Bauer-Gottwein, Peter; Garcia, Monica
2017-04-01
Unmanned Aerial Systems (UAS) can collect optical and thermal hyperspatial (<1m) imagery with low cost and flexible revisit times regardless of cloudy conditions. The reflectance and radiometric temperature signatures of the land surface, closely linked with the vegetation structure and functioning, are already part of models to predict Evapotranspiration (ET) and Gross Primary Productivity (GPP) from satellites. However, there remain challenges for an operational monitoring using UAS compared to satellites: the payload capacity of most commercial UAS is less than 2 kg, but miniaturized sensors have low signal to noise ratios and small field of view requires mosaicking hundreds of images and accurate orthorectification. In addition, wind gusts and lower platform stability require appropriate geometric and radiometric corrections. Finally, modeling fluxes on days without images is still an issue for both satellite and UAS applications. This study focuses on designing an operational UAS-based monitoring system including payload design, sensor calibration, based on routine collection of optical and thermal images in a Danish willow field to perform a joint monitoring of ET and GPP dynamics over continuous time at daily time steps. The payload (<2 kg) consists of a multispectral camera (Tetra Mini-MCA6), a thermal infrared camera (FLIR Tau 2), a digital camera (Sony RX-100) used to retrieve accurate digital elevation models (DEMs) for multispectral and thermal image orthorectification, and a standard GNSS single frequency receiver (UBlox) or a real time kinematic double frequency system (Novatel Inc. flexpack6+OEM628). Geometric calibration of the digital and multispectral cameras was conducted to recover intrinsic camera parameters. After geometric calibration, accurate DEMs with vertical errors about 10cm could be retrieved. Radiometric calibration for the multispectral camera was conducted with an integrating sphere (Labsphere CSTM-USS-2000C) and the laboratory
Fu, Gang; Shen, Zhen Xi
2016-01-01
Uncertainty about responses of vegetation index, aboveground biomass (AGB) and gross primary production (GPP) limits our ability to predict how climatic warming will influence plant growth in alpine regions. A field warming experiment was conducted in an alpine meadow at a low (4313 m), mid- (4513 m) and high elevation (4693 m) in the Northern Tibet since May 2010. Growing season vapor pressure deficit (VPD), soil temperature (Ts) and air temperature (Ta) decreased with increasing elevation, while growing season precipitation, soil moisture (SM), normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), AGB and GPP increased with increasing elevation. The growing season Ta, Ts and VPD in 2015 was greater than that in 2014, while the growing season precipitation, SM, NDVI, SAVI, AGB and GPP in 2015 was lower than that in 2014, respectively. Compared to the mean air temperature and precipitation during the growing season in 1963–2015, it was a warmer and wetter year in 2014 and a warmer and drier year in 2015. Experimental warming increased growing season Ts, Ta,VPD, but decreased growing season SM in 2014–2015 at all the three elevations. Experimental warming only reduced growing season NDVI, SAVI, AGB and GPP at the low elevation in 2015. Growing season NDVI, SAVI, AGB and GPP increased with increasing SM and precipitation, but decreased with increasing VPD, indicating vegetation index and biomass production increased with environmental humidity. The VPD explained more variation of growing season NDVI, SAVI, AGB and GPP compared to Ts, Ta and SM at all the three elevations. Therefore, environmental humidity regulated the effect of experimental warming on vegetation index and biomass production in alpine meadows on the Tibetan Plateau. PMID:27798690
Towards a universal trait-based model of terrestrial primary production
NASA Astrophysics Data System (ADS)
Wang, H.; Prentice, I. C.; Cornwell, W.; Keenan, T. F.; Davis, T.; Wright, I. J.; Evans, B. J.; Peng, C.
2015-12-01
Systematic variations of plant traits along environmental gradients have been observed for decades. For example, the tendencies of leaf nitrogen per unit area to increase, and of the leaf-internal to ambient CO2 concentration ratio (ci:ca) to decrease, with aridity are well established. But ecosystem models typically represent trait variation based purely on empirical relationships, or on untested conjectures, or not at all. Neglect of quantitative trait variation and its adapative significance probably contributes to the persistent large uncertainties among models in predicting the response of the carbon cycle to environmental change. However, advances in ecological theory and the accumulation of extensive data sets during recent decades suggest that theoretically based and testable predictions of trait variation could be achieved. Based on well-established ecophysiological principles and consideration of the adaptive significance of traits, we propose universal relationships between photosynthetic traits (ci:ca, carbon fixation capacity, and the ratio of electron transport capacity to carbon fixation capacity) and primary environmental variables, which capture observed trait variations both within and between plant functional types. Moreover, incorporating these traits into the standard model of C3photosynthesis allows gross primary production (GPP) of natural vegetation to be predicted by a single equation with just two free parameters, which can be estimated from independent observations. The resulting model performs as well as much more complex models. Our results provide a fresh perspective with potentially high reward: the possibility of a deeper understanding of the relationships between plant traits and environment, simpler and more robust and reliable representation of land processes in Earth system models, and thus improved predictability for biosphere-atmosphere interactions and climate feedbacks.
Below-ground carbon flux and partitioning: global patterns and response to temperature
C.M. Litton; C.P. Giardina
2008-01-01
1. The fraction of gross primary production (GPP) that is total below-ground carbon flux (TBCF) and the fraction of TBCF that is below-ground net primary production (BNPP) represent globally significant C fluxes that are fundamental in regulating ecosystem C balance. However, global estimates of the partitioning of GPP to TBCF and of TBCF to BNPP, as well as the...
Huang, Qiuling; Hu, Lili; Zhuo, Kan
2017-01-01
Plant pathogen effectors can recruit the host post-translational machinery to mediate their post-translational modification (PTM) and regulate their activity to facilitate parasitism, but few studies have focused on this phenomenon in the field of plant-parasitic nematodes. In this study, we show that the plant-parasitic nematode Meloidogyne graminicola has evolved a novel effector, MgGPP, that is exclusively expressed within the nematode subventral esophageal gland cells and up-regulated in the early parasitic stage of M. graminicola. The effector MgGPP plays a role in nematode parasitism. Transgenic rice lines expressing MgGPP become significantly more susceptible to M. graminicola infection than wild-type control plants, and conversely, in planta, the silencing of MgGPP through RNAi technology substantially increases the resistance of rice to M. graminicola. Significantly, we show that MgGPP is secreted into host plants and targeted to the ER, where the N-glycosylation and C-terminal proteolysis of MgGPP occur. C-terminal proteolysis promotes MgGPP to leave the ER, after which it is transported to the nucleus. In addition, N-glycosylation of MgGPP is required for suppressing the host response. The research data provide an intriguing example of in planta glycosylation in concert with proteolysis of a pathogen effector, which depict a novel mechanism by which parasitic nematodes could subjugate plant immunity and promote parasitism and may present a promising target for developing new strategies against nematode infections. PMID:28403192
Chen, Jiansong; Lin, Borong; Huang, Qiuling; Hu, Lili; Zhuo, Kan; Liao, Jinling
2017-04-01
Plant pathogen effectors can recruit the host post-translational machinery to mediate their post-translational modification (PTM) and regulate their activity to facilitate parasitism, but few studies have focused on this phenomenon in the field of plant-parasitic nematodes. In this study, we show that the plant-parasitic nematode Meloidogyne graminicola has evolved a novel effector, MgGPP, that is exclusively expressed within the nematode subventral esophageal gland cells and up-regulated in the early parasitic stage of M. graminicola. The effector MgGPP plays a role in nematode parasitism. Transgenic rice lines expressing MgGPP become significantly more susceptible to M. graminicola infection than wild-type control plants, and conversely, in planta, the silencing of MgGPP through RNAi technology substantially increases the resistance of rice to M. graminicola. Significantly, we show that MgGPP is secreted into host plants and targeted to the ER, where the N-glycosylation and C-terminal proteolysis of MgGPP occur. C-terminal proteolysis promotes MgGPP to leave the ER, after which it is transported to the nucleus. In addition, N-glycosylation of MgGPP is required for suppressing the host response. The research data provide an intriguing example of in planta glycosylation in concert with proteolysis of a pathogen effector, which depict a novel mechanism by which parasitic nematodes could subjugate plant immunity and promote parasitism and may present a promising target for developing new strategies against nematode infections.
Forest productivity and water stress in Amazonia: observations from GOSAT chlorophyll fluorescence.
Lee, Jung-Eun; Frankenberg, Christian; van der Tol, Christiaan; Berry, Joseph A; Guanter, Luis; Boyce, C Kevin; Fisher, Joshua B; Morrow, Eric; Worden, John R; Asefi, Salvi; Badgley, Grayson; Saatchi, Sassan
2013-06-22
It is unclear to what extent seasonal water stress impacts on plant productivity over Amazonia. Using new Greenhouse gases Observing SATellite (GOSAT) satellite measurements of sun-induced chlorophyll fluorescence, we show that midday fluorescence varies with water availability, both of which decrease in the dry season over Amazonian regions with substantial dry season length, suggesting a parallel decrease in gross primary production (GPP). Using additional SeaWinds Scatterometer onboard QuikSCAT satellite measurements of canopy water content, we found a concomitant decrease in daily storage of canopy water content within branches and leaves during the dry season, supporting our conclusion. A large part (r(2) = 0.75) of the variance in observed monthly midday fluorescence from GOSAT is explained by water stress over moderately stressed evergreen forests over Amazonia, which is reproduced by model simulations that include a full physiological representation of photosynthesis and fluorescence. The strong relationship between GOSAT and model fluorescence (r(2) = 0.79) was obtained using a fixed leaf area index, indicating that GPP changes are more related to environmental conditions than chlorophyll contents. When the dry season extended to drought in 2010 over Amazonia, midday basin-wide GPP was reduced by 15 per cent compared with 2009.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mendez-Perez, Daniel; Alonso-Gutierrez, Jorge; Hu, Qijun
Monoterpenes (C 10 isoprenoids) are the main components of essential oils and are possible precursors for many commodity chemicals and high energy density fuels. Monoterpenes are synthesized from geranyl diphosphate (GPP), which is also the precursor for the biosynthesis of farnesyl diphosphate (FPP). FPP biosynthesis diverts the carbon flux from monoterpene production to C 15 products and quinone biosynthesis. In this study, we tested a chromosomal mutation of Escherichia coli's native FPP synthase (IspA) to improve GPP availability for the production of monoterpenes using a heterologous mevalonate pathway. Monoterpene production at high levels required not only optimization of GPP productionmore » but also a basal level of FPP to maintain growth. The optimized strains produced two jet fuel precursor monoterpenoids 1,8-cineole and linalool at the titer of 653 mg/L and 505 mg/L, respectively, in batch cultures with 1% glucose. The engineered strains developed in this work provide useful resources for the production of high-value monoterpenes.« less
Mendez-Perez, Daniel; Alonso-Gutierrez, Jorge; Hu, Qijun; ...
2017-05-18
Monoterpenes (C 10 isoprenoids) are the main components of essential oils and are possible precursors for many commodity chemicals and high energy density fuels. Monoterpenes are synthesized from geranyl diphosphate (GPP), which is also the precursor for the biosynthesis of farnesyl diphosphate (FPP). FPP biosynthesis diverts the carbon flux from monoterpene production to C 15 products and quinone biosynthesis. In this study, we tested a chromosomal mutation of Escherichia coli's native FPP synthase (IspA) to improve GPP availability for the production of monoterpenes using a heterologous mevalonate pathway. Monoterpene production at high levels required not only optimization of GPP productionmore » but also a basal level of FPP to maintain growth. The optimized strains produced two jet fuel precursor monoterpenoids 1,8-cineole and linalool at the titer of 653 mg/L and 505 mg/L, respectively, in batch cultures with 1% glucose. The engineered strains developed in this work provide useful resources for the production of high-value monoterpenes.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lei, Huimin; Huang, Maoyi; Leung, Lai-Yung R.
2014-09-01
The terrestrial water and carbon cycles interact strongly at various spatio-temporal scales. To elucidate how hydrologic processes may influence carbon cycle processes, differences in terrestrial carbon cycle simulations induced by structural differences in two runoff generation schemes were investigated using the Community Land Model 4 (CLM4). Simulations were performed with runoff generation using the default TOPMODEL-based and the Variable Infiltration Capacity (VIC) model approaches under the same experimental protocol. The comparisons showed that differences in the simulated gross primary production (GPP) are mainly attributed to differences in the simulated leaf area index (LAI) rather than soil moisture availability. More specifically,more » differences in runoff simulations can influence LAI through changes in soil moisture, soil temperature, and their seasonality that affect the onset of the growing season and the subsequent dynamic feedbacks between terrestrial water, energy, and carbon cycles. As a result of a relative difference of 36% in global mean total runoff between the two models and subsequent changes in soil moisture, soil temperature, and LAI, the simulated global mean GPP differs by 20.4%. However, the relative difference in the global mean net ecosystem exchange between the two models is small (2.1%) due to competing effects on total mean ecosystem respiration and other fluxes, although large regional differences can still be found. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling.« less
NASA Astrophysics Data System (ADS)
Minunno, F.; Peltoniemi, M.; Launiainen, S.; Aurela, M.; Lindroth, A.; Lohila, A.; Mammarella, I.; Minkkinen, K.; Mäkelä, A.
2015-07-01
The problem of model complexity has been lively debated in environmental sciences as well as in the forest modelling community. Simple models are less input demanding and their calibration involves a lower number of parameters, but they might be suitable only at local scale. In this work we calibrated a simplified ecosystem process model (PRELES) to data from multiple sites and we tested if PRELES can be used at regional scale to estimate the carbon and water fluxes of Boreal conifer forests. We compared a multi-site (M-S) with site-specific (S-S) calibrations. Model calibrations and evaluations were carried out by the means of the Bayesian method; Bayesian calibration (BC) and Bayesian model comparison (BMC) were used to quantify the uncertainty in model parameters and model structure. To evaluate model performances BMC results were combined with more classical analysis of model-data mismatch (M-DM). Evapotranspiration (ET) and gross primary production (GPP) measurements collected in 10 sites of Finland and Sweden were used in the study. Calibration results showed that similar estimates were obtained for the parameters at which model outputs are most sensitive. No significant differences were encountered in the predictions of the multi-site and site-specific versions of PRELES with exception of a site with agricultural history (Alkkia). Although PRELES predicted GPP better than evapotranspiration, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests. Our analyses underlined also the importance of using long and carefully collected flux datasets in model calibration. In fact, even a single site can provide model calibrations that can be applied at a wider spatial scale, since it covers a wide range of variability in climatic conditions.
Enhancing Conservation with High Resolution Productivity Datasets for the Conterminous United States
NASA Astrophysics Data System (ADS)
Robinson, Nathaniel Paul
Human driven alteration of the earth's terrestrial surface is accelerating through land use changes, intensification of human activity, climate change, and other anthropogenic pressures. These changes occur at broad spatio-temporal scales, challenging our ability to effectively monitor and assess the impacts and subsequent conservation strategies. While satellite remote sensing (SRS) products enable monitoring of the earth's terrestrial surface continuously across space and time, the practical applications for conservation and management of these products are limited. Often the processes driving ecological change occur at fine spatial resolutions and are undetectable given the resolution of available datasets. Additionally, the links between SRS data and ecologically meaningful metrics are weak. Recent advances in cloud computing technology along with the growing record of high resolution SRS data enable the development of SRS products that quantify ecologically meaningful variables at relevant scales applicable for conservation and management. The focus of my dissertation is to improve the applicability of terrestrial gross and net primary productivity (GPP/NPP) datasets for the conterminous United States (CONUS). In chapter one, I develop a framework for creating high resolution datasets of vegetation dynamics. I use the entire archive of Landsat 5, 7, and 8 surface reflectance data and a novel gap filling approach to create spatially continuous 30 m, 16-day composites of the normalized difference vegetation index (NDVI) from 1986 to 2016. In chapter two, I integrate this with other high resolution datasets and the MOD17 algorithm to create the first high resolution GPP and NPP datasets for CONUS. I demonstrate the applicability of these products for conservation and management, showing the improvements beyond currently available products. In chapter three, I utilize this dataset to evaluate the relationships between land ownership and terrestrial production
Xu, Xia; Shi, Zheng; Chen, Xuecheng; Lin, Yang; Niu, Shuli; Jiang, Lifen; Luo, Ruiseng; Luo, Yiqi
2016-05-01
Responses of grassland carbon (C) cycling to climate change and land use remain a major uncertainty in model prediction of future climate. To explore the impacts of global change on ecosystem C fluxes and the consequent changes in C storage, we have conducted a field experiment with warming (+3 °C), altered precipitation (doubled and halved), and annual clipping at the end of growing seasons in a mixed-grass prairie in Oklahoma, USA, from 2009 to 2013. Results showed that although ecosystem respiration (ER) and gross primary production (GPP) negatively responded to warming, net ecosystem exchange of CO2 (NEE) did not significantly change under warming. Doubled precipitation stimulated and halved precipitation suppressed ER and GPP equivalently, with the net outcome being unchanged in NEE. These results indicate that warming and altered precipitation do not necessarily have profound impacts on ecosystem C storage. In addition, we found that clipping enhanced NEE due to a stronger positive response of GPP compared to ER, indicating that clipping could potentially be an effective land practice that could increase C storage. No significant interactions between warming, altered precipitation, and clipping were observed. Meanwhile, we found that belowground net primary production (BNPP) in general was sensitive to climate change and land use though no significant changes were found in NPP across treatments. Moreover, negative correlations of the ER/GPP ratio with soil temperature and moisture did not differ across treatments, highlighting the roles of abiotic factors in mediating ecosystem C fluxes in this grassland. Importantly, our results suggest that belowground C cycling (e.g., BNPP) could respond to climate change with no alterations in ecosystem C storage in the same period. © 2015 John Wiley & Sons Ltd.
Singh, Ramesh K.; Liu, Shu-Guang; Tieszen, Larry L.; Suyker, Andrew E.; Verma, Shashi B.
2012-01-01
Gross primary production (GPP) is a key indicator of ecosystem performance, and helps in many decision-making processes related to environment. We used the Eddy covariancelight use efficiency (EC-LUE) model for estimating GPP in the Great Plains, United States in order to evaluate the performance of this model. We developed a novel algorithm for computing the photosynthetically active radiation (PAR) based on net radiation. A strong correlation (R2=0.94,N=24) was found between daily PAR and Landsat-based mid-day instantaneous net radiation. Though the Moderate Resolution Spectroradiometer (MODIS) based instantaneous net radiation was in better agreement (R2=0.98,N=24) with the daily measured PAR, there was no statistical significant difference between Landsat based PAR and MODIS based PAR. The EC-LUE model validation also confirms the need to consider biological attributes (C3 versus C4 plants) for potential light use efficiency. A universal potential light use efficiency is unable to capture the spatial variation of GPP. It is necessary to use C3 versus C4 based land use/land cover map for using EC-LUE model for estimating spatiotemporal distribution of GPP.
The shifting seasonality of productivity in California during the 2015 drought
NASA Astrophysics Data System (ADS)
Yang, X.; Lee, J. E.
2016-12-01
Drought can significantly affect the ecosystem productivity through increasing surface temperature and reducing water availability. Accurately assessing how drought impacts the ecosystem productivity is critical to understand the terrestrial carbon cycle and food security; however, the assessment has been unclear partly because of lacking spatially-explicit means of measuring photosynthesis. The 2012-2015 California drought is considered to be one of the largest droughts in California during the last 1000 years. Here we used multiple satellite products including the ground meteorological and eddy covariance measurements and solar-induced chlorophyll fluorescence (SIF), a proxy for terrestrial productivity, to estimate the change in the seasonal gross primary productivity (GPP) in California during the drought years, especially in 2015 when the drought was at its fourth consecutive year. We show that with the decreasing water availability since 2012, SIF of all four vegetation types (forests, crops, savannas, and grasslands) showed significant decrease, shifting the peak-growing season about a month earlier, similar to the shift observed from the available flux-tower measurements. During 2015, vegetation productivity in forests and savannas increased in the spring (Jan-Apr) due to warm temperature and increased rainfall in the previous year, but the enhancement quickly diminished due to reduction in soil moisture. Overall, GPP decreased in more than 70% of the vegetation in California, and 50-70% of the vegetation display a negative abnormality beyond one standard deviation from the normal trend. Eddy covariance tower measurements suggested that the net carbon storage also decreased as a result of greater reduction in GPP comparing with the ecosystem respiration. We conclude that an increase in future drought events and intensity would likely shift the peak growing season earlier and shorten the growing season.
NASA Astrophysics Data System (ADS)
Bernardes, S.
2017-12-01
Outputs from coupled carbon-climate models show considerable variability in atmospheric and land fields over the 21st century, including changes in temperature and in the spatiotemporal distribution and quantity of precipitation over the planet. Reductions in water availability due to decreased precipitation and increased water demand by the atmosphere may reduce carbon uptake by critical ecosystems. Conversely, increases in atmospheric carbon dioxide have the potential to offset reductions in productivity. This work focuses on predicted responses of plants to environmental changes and on how plants will adjust their water use efficiency (WUE, plant production per water loss by evapotranspiration) in the 21st century. Predicted changes in WUE were investigated using an ensemble of Earth System Models from the Coupled Model Intercomparison Project 5 (CMIP5), flux tower data and products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Scenarios for climate futures used two representative concentration pathways, including carbon concentration peak in 2040 (RCP4.5) and rising emissions throughout the 21st century (RCP8.5). Model results included the periods 2006-2009 (predicted) and 1850-2005 (reference). IPCC SREX regions were used to compare modeled, flux and satellite data and to address the significant intermodel variability observed for the CMIP5 ensemble (larger variability for RCP8.5, higher intermodel agreement in Southeast Asia, lower intermodel agreement in arid areas). An evaluation of model skill at the regional level supported model selection and the spatiotemporal analysis of changes in WUE. Departures of projected conditions in relation to historical values are presented for both concentration pathways at global, regional levels, including latitudinal distributions. High model sensitivity to different concentration pathways and increase in GPP and WUE was observed for most of the planet (increases consistently higher for
USDA-ARS?s Scientific Manuscript database
Recent development of sun-induced chlorophyll fluorescence (SIF) technology is stimulating studies to remotely approximate canopy photosynthesis (measured as gross primary production, GPP). While multiple applications have advanced the empirical relationship between GPP and SIF, mechanistic understa...
Estimation of crop gross primary production (GPP): fAPAR_chl versus MOD15A2 FPAR
USDA-ARS?s Scientific Manuscript database
Within leaf chloroplasts chlorophylls absorb photosynthetically active radiation (PAR) for photosynthesis (PSN). The MOD15A2 FPAR (fraction of PAR absorbed by canopy, i.e., fAPARcanopy) product has been widely used to compute absorbed PAR for PSN (APARPSN). The MOD17A2 algorithm uses MOD15A2 FPAR i...
Resolving the global transpiration flux is critical to constraining global carbon cycle models because carbon uptake by photosynthesis in terrestrial plants (Gross Primary Productivity, GPP) is directly related to water lost through transpiration. Quantifying GPP globally is cha...
Riboswitches for the alarmone ppGpp expand the collection of RNA-based signaling systems
Sudarsan, Narasimhan; Breaker, Ronald R.
2018-01-01
Riboswitches are noncoding portions of certain mRNAs that bind metabolite, coenzyme, signaling molecule, or inorganic ion ligands and regulate gene expression. Most known riboswitches sense derivatives of RNA monomers. This bias in ligand chemical composition is consistent with the hypothesis that widespread riboswitch classes first emerged during the RNA World, which is proposed to have existed before proteins were present. Here we report the discovery and biochemical validation of a natural riboswitch class that selectively binds guanosine tetraphosphate (ppGpp), a widespread signaling molecule and bacterial “alarmone” derived from the ribonucleotide GTP. Riboswitches for ppGpp are predicted to regulate genes involved in branched-chain amino acid biosynthesis and transport, as well as other gene classes that previously had not been implicated to be part of its signaling network. This newfound riboswitch–alarmone partnership supports the hypothesis that prominent RNA World signaling pathways have been retained by modern cells to control key biological processes. PMID:29784782
Riboswitches for the alarmone ppGpp expand the collection of RNA-based signaling systems.
Sherlock, Madeline E; Sudarsan, Narasimhan; Breaker, Ronald R
2018-06-05
Riboswitches are noncoding portions of certain mRNAs that bind metabolite, coenzyme, signaling molecule, or inorganic ion ligands and regulate gene expression. Most known riboswitches sense derivatives of RNA monomers. This bias in ligand chemical composition is consistent with the hypothesis that widespread riboswitch classes first emerged during the RNA World, which is proposed to have existed before proteins were present. Here we report the discovery and biochemical validation of a natural riboswitch class that selectively binds guanosine tetraphosphate (ppGpp), a widespread signaling molecule and bacterial "alarmone" derived from the ribonucleotide GTP. Riboswitches for ppGpp are predicted to regulate genes involved in branched-chain amino acid biosynthesis and transport, as well as other gene classes that previously had not been implicated to be part of its signaling network. This newfound riboswitch-alarmone partnership supports the hypothesis that prominent RNA World signaling pathways have been retained by modern cells to control key biological processes. Copyright © 2018 the Author(s). Published by PNAS.
Water use efficiency in a primary subtropical evergreen forest in Southwest China.
Song, Qing-Hai; Fei, Xue-Hai; Zhang, Yi-Ping; Sha, Li-Qing; Liu, Yun-Tong; Zhou, Wen-Jun; Wu, Chuan-Sheng; Lu, Zhi-Yun; Luo, Kang; Gao, Jin-Bo; Liu, Yu-Hong
2017-02-20
We calculated water use efficiency (WUE) using measures of gross primary production (GPP) and evapotranspiration (ET) from five years of continuous eddy covariance measurements (2009-2013) obtained over a primary subtropical evergreen broadleaved forest in southwestern China. Annual mean WUE exhibited a decreasing trend from 2009 to 2013, varying from ~2.28 to 2.68 g C kg H 2 O -1 . The multiyear average WUE was 2.48 ± 0.17 (mean ± standard deviation) g C kg H 2 O -1 . WUE increased greatly in the driest year (2009), due to a larger decline in ET than in GPP. At the diurnal scale, WUE in the wet season reached 5.1 g C kg H 2 O -1 in the early morning and 4.6 g C kg H 2 O -1 in the evening. WUE in the dry season reached 3.1 g C kg H 2 O -1 in the early morning and 2.7 g C kg H 2 O -1 in the evening. During the leaf emergence stage, the variation of WUE could be suitably explained by water-related variables (relative humidity (RH), soil water content at 100 cm (SWC_100)), solar radiation and the green index (Sgreen). These results revealed large variation in WUE at different time scales, highlighting the importance of individual site characteristics.
NASA Astrophysics Data System (ADS)
Xue, Wei; Jeong, Seungtaek; Ko, Jonghan; Tenhunen, John
2017-03-01
Nitrogen and water availability alter canopy structure and physiology, and thus crop growth, yielding large impacts on ecosystem-regulating/production provisions. However, to date, explicitly quantifying such impacts remains challenging partially due to lack of adequate methodology to capture spatial dimensions of ecosystem changes associated with nitrogen and water effects. A data fitting, where close-range remote-sensing measurements of vegetation indices derived from a handheld instrument and an unmanned aerial vehicle (UAV) system are linked to in situ leaf and canopy photosynthetic traits, was applied to capture and interpret inter- and intra-field variations in gross primary productivity (GPP) in lowland rice grown under flooded conditions (paddy rice, PD) subject to three nitrogen application rates and under rainfed conditions (RF) in an East Asian monsoon region of South Korea. Spatial variations (SVs) in both GPP and light use efficiency (LUEcabs) early in the growing season were enlarged by nitrogen addition. The nutritional effects narrowed over time. A shift in planting culture from flooded to rainfed conditions strengthened SVs in GPP and LUEcabs. Intervention of prolonged drought late in the growing season dramatically intensified SVs that were supposed to seasonally decrease. Nevertheless, nitrogen addition effects on SV of LUEcabs at the early growth stage made PD fields exert greater SVs than RF fields. SVs of GPP across PD and RF rice fields were likely related to leaf area index (LAI) development less than to LUEcabs, while numerical analysis suggested that considering strength in LUEcabs and its spatial variation for the same crop type tends to be vital for better evaluation in landscape/regional patterns of ecosystem photosynthetic productivity at critical phenology stages.
NASA Technical Reports Server (NTRS)
Cook, Bruce D.; Bolstad, Paul V.; Naesset, Erik; Anderson, Ryan S.; Garrigues, Sebastian; Morisette, Jeffrey T.; Nickeson, Jaime; Davis, Kenneth J.
2009-01-01
Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the MOderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.
Skinner, R.H.; Wylie, B.K.; Gilmanov, T.G.
2011-01-01
Satellite-based normalized difference vegetation index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northeastern United States might be limited because paddock size is often smaller than the resolution limits of the satellite image. This research compared NDVI data from satellites with data obtained using a ground-based system capable of fine-scale (submeter) NDVI measurements. Gross primary productivity was measured by eddy covariance on two pastures in central Pennsylvania from 2003 to 2008. Weekly 250-m resolution satellite NDVI estimates were also obtained for each pasture from the moderate resolution imaging spectroradiometer (MODIS) sensor. Ground-based NDVI data were periodically collected in 2006, 2007, and 2008 from one of the two pastures. Multiple-regression and regression-tree estimates of GPP, based primarily on MODIS 7-d NDVI and on-site measurements of photosynthetically active radiation (PAR), were generally able to predict growing-season GPP to within an average of 3% of measured values. The exception was drought years when estimated and measured GPP differed from each other by 11 to 13%. Ground-based measurements improved the ability of vegetation indices to capture short-term grazing management effects on GPP. However, the eMODIS product appeared to be adequate for regional GPP estimates where total growing-season GPP across a wide area would be of greater interest than short-term management-induced changes in GPP at individual sites.
Cook, B.D.; Bolstad, P.V.; Naesset, E.; Anderson, R. Scott; Garrigues, S.; Morisette, J.T.; Nickeson, J.; Davis, K.J.
2009-01-01
Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30??m to 1??km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600??ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400??m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and
NASA Astrophysics Data System (ADS)
Chen, J.; Ouyang, Z.; John, R.; Henebry, G. M.; Xie, Y.; de Beurs, K.; Fan, Y.; Shao, C.; Qi, J.; Wu, J.; Liu, Y.
2015-12-01
The concept of coupled human and environmental systems (CHES) has been a dominant framework in the past decade for understanding the cohesive connections between natural and human systems. Here we focus on how socio-ecological services may be regulated by the regional and local water cycles and by ecosystem production in the drylands of Northern Asia (>40 degree N), which includes Inner Mongolia of China, Kazakhstan, Kyrgyzstan, Mongolia, Tajikistan, Turkmenistan, and Uzbekistan. Total precipitation and evapotranspiration are used as the primary drivers to explain ecosystem production (e.g., GPP) and indicators of social function and structure (e.g., GDP, population) using the data collected from 1980 through 2010 of these seven areas. We hypothesize that the changes in the regional and local water cycles in these contrasting regions and socioeconomic settings significantly affect CHES functioning. Institutional changes, including shifts in policy, can play a much stronger role than those caused by the physical changes in determining the relationships between water cycle and CHES functioning. The complex connections among the biophysical and socioeconomic variables are analyzed through structural equation modeling (SEM) at country and regional scales. The highest water use efficiency (GPP:PET=0.57) was found for Uzbekistan, which also had the highest GDP:GPP (0.66) among the seven areas. In contrast, Mongolia exhibited the lowest values during the study period despite its very high GPP:Population value (45.8). The low population in Mongolia appeared responsible for its rank within the dryland region. Regional institutional changes with global ramifications, such as the collapse of Soviet Union and China joining the World Trade Organization, appears to have affected the CHES of the study areas.
Seasonal evolution of Biomass Production Efficiency (BPE) of a French beech forest.
NASA Astrophysics Data System (ADS)
Heid, L.; Calvaruso, C.; Conil, S.; Turpault, M. P.; Longdoz, B.
2015-12-01
With the evolution of ecosystem management and the actual climate change we are facing, there is a need to improve our knowledge of carbon (C) balance and more specifically of C allocation in the plants. In our study, we quantified the seasonal variation of gross primary production (GPP, obtained through eddy covariance measurements) and biomass production (BP, the C fixed into the biomass obtained thanks to inventory campaign) for a 60-year-old even-aged beech stand located in North East of France. We also assessed the seasonal evolution of the BP efficiency (BPE=BP/GPP; Vicca et al., 2012) and its potential determining factors for our site. For 2014, we found a net ecosystem exchange (NEE) of -549 gC m-2, corresponding to a C sequestration. This value breaks down between 1089 gC m-2 for the respiration of the ecosystem and -1639 gC m-2 for the GPP. On the same year, our stand built up 461.6 gC m-2 of tree biomass (leaves, trunk, branches, fine roots), leading to an annual BPE of 0.28, which is within the range of value found on other similar sites. There was a large temporal variation of C allocation to the different parts of the tree biomass during the growth season. Our results show that the growth first happened in the trunk and branches -with a peak value of 74.5 gC m-2 month-1 in May - whereas the fine roots biomass production started later (end of July) and reached a maximum at the end of the growth season (28.49 gC m-2 month-1 for September). The BPE varied also during the year from 0.13 in April to 0.31 in August, where the BP was the same than in July but the cumulated GPP was already decreasing. The seasonal variation may be mainly explained by climatic variations, whereas the shift between woody above-ground biomass and fine roots biomass could be explained by the phenology (linked to physiological mechanisms).
Estimating carbon fluxes on small rotationally grazed pastures
USDA-ARS?s Scientific Manuscript database
Satellite-based Normalized Difference Vegetation Index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. Large-scale estimates of GPP are a necessary component of efforts to monitor the soil carbon balance of grazi...
Production of jet fuel precursor monoterpenoids from engineered Escherichia coli.
Mendez-Perez, Daniel; Alonso-Gutierrez, Jorge; Hu, Qijun; Molinas, Margaux; Baidoo, Edward E K; Wang, George; Chan, Leanne J G; Adams, Paul D; Petzold, Christopher J; Keasling, Jay D; Lee, Taek S
2017-08-01
Monoterpenes (C 10 isoprenoids) are the main components of essential oils and are possible precursors for many commodity chemicals and high energy density fuels. Monoterpenes are synthesized from geranyl diphosphate (GPP), which is also the precursor for the biosynthesis of farnesyl diphosphate (FPP). FPP biosynthesis diverts the carbon flux from monoterpene production to C 15 products and quinone biosynthesis. In this study, we tested a chromosomal mutation of Escherichia coli's native FPP synthase (IspA) to improve GPP availability for the production of monoterpenes using a heterologous mevalonate pathway. Monoterpene production at high levels required not only optimization of GPP production but also a basal level of FPP to maintain growth. The optimized strains produced two jet fuel precursor monoterpenoids 1,8-cineole and linalool at the titer of 653 mg/L and 505 mg/L, respectively, in batch cultures with 1% glucose. The engineered strains developed in this work provide useful resources for the production of high-value monoterpenes. Biotechnol. Bioeng. 2017;114: 1703-1712. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Hydrological and Climate Controls on Hyporheic Contributions to River Net Ecosystem Productivity
NASA Astrophysics Data System (ADS)
Newcomer, M. E.; Hubbard, S. S.; Fleckenstein, J. H.; Maier, U.; Schmidt, C.; Laube, G.; Chen, N.; Ulrich, C.; Dwivedi, D.; Steefel, C. I.; Rubin, Y.
2016-12-01
Hyporheic zone contributions to river net ecosystem productivity (NEP) can represent a substantial source or sink for organic and inorganic carbon (C). Hyporheic zone processes are estimated to vary with network location as a function of river-aquifer interactions as well as with climatic factors supporting riverbed gross primary productivity (GPP) and ecosystem respiration. Even though hyporheic zone NEP is hypothesized to be a significant budgetary component to river-aquifer biogeochemical cycling, models of river NEP often parameterize hyporheic zone contributions as a space-time constant input of CO2 to rivers, leading to overestimation of hyporheic zone NEP and underestimation of C storage. This assumption is problematic during the summer growing season, when GPP is largest and C is stored in surface and subsurface biomass. We investigated the dynamic role of hyporheic zone NEP using the MIN3P flow and reactive transport model with surface water GPP and ecosystem respiration simulated as a function of light, depth, temperature, pH, and atmospheric CO2. We simulated hyporheic zone NEP for low-order and high-order streams, which collectively represent a range of characteristic flow paths and subsurface residence times. Downscaled climate predictions of temperature and atmospheric CO2 representing carbon emission futures were used to force the models and to compare future and current hyporheic zone NEP. Our results show that river-aquifer flow conditions determine the relative role of the river as either a store or sink of C through direct contributions of O2 and dissolved organic content from river GPP. Modeled results show that high discharge, high order rivers are net stores of CO2 from the atmosphere; however this is dependent on perturbation events that allow stored C from summer GPP to be released (i.e. rising water tables during winter storms). Lacking a perturbation event, C remains in pore-water storage as dissolved CO2 and biomass. Conversely, low
Aboveground and belowground net primary production
Hal O. Liechty; Mark H. Eisenbies
2000-01-01
The relationship among net primary productivity (NPP), hydroperiod, and fertility in forested wetlands is poorly understood (Burke and others 1999), particularly with respect to belowground NPP (Megonigal and others 1997). Although some researchers have studied aboveground and belowground primary production in depressional, forested wetland systems, e.g., Day and...
NASA Astrophysics Data System (ADS)
Raub, H. D.; Jimenez, J. R.; Gallery, R. E.; Sutter, L., Jr.; Barron-Gafford, G.; Smith, W. K.
2017-12-01
Drylands account for 40% of the land surface and have been identified as increasingly important in driving interannual variability of the land carbon sink. Yet, understanding of dryland seasonal ecosystem productivity dynamics - termed Gross Primary Productivity (GPP) - is limited due to complex interactions between vegetation health, seasonal drought dynamics, a paucity of long-term measurements across these under-studied regions, and unanticipated disturbances from varying fire regimes. For instance, fire disturbance has been found to either greatly reduce post-fire GPP through vegetation mortality or enhance post-fire GPP though increased resource availability (e.g., water, light, nutrients, etc.). Here, we explore post-fire ecosystem recovery by evaluating seasonal GPP dynamics for two Ameriflux eddy covariance flux tower sites within the Santa Rita Experimental Range of southeastern Arizona: 1) the US-SRG savanna site dominated by a mix of grass and woody mesquite vegetation that was burned in May 2017, and 2) the US-SRM savanna site dominated by similar vegetation but unburned for the full measurement record. For each site, we collected leaf-level spectral and gas exchange measurements, as well as leaf-level chemistry and soil chemistry to characterize differences in nutrient availability and microbial activity throughout the 2017 growing season. From spectral data, we derived and evaluated multiple common vegetation metrics, including normalized difference vegetation index (NDVI), photochemical reflectivity index (PRI), near-infrared reflectance (NIRv), and MERIS terrestrial chlorophyll index (MTCI). Early results suggest rates of photosynthesis were enhanced at the burned site, with productivity increasing immediately following the onset of monsoonal precipitation; whereas initial photosynthesis at the unburned site remained relatively low following first monsoonal rains. MTCI values for burned vegetation appear to track higher levels of leaf-level nitrogen
NASA Astrophysics Data System (ADS)
Bernardes, S.
2016-12-01
Global coupled carbon-climate simulations show considerable variability in outputs for atmospheric and land fields over the 21st century. This variability includes changes in temperature and in the quantity and spatiotemporal distribution of precipitation for large regions on the planet. Studies have considered that reductions in water availability due to decreased precipitation and increased water demand by the atmosphere may negatively affect plant metabolism and reduce carbon uptake. Future increases in carbon dioxide concentrations are expected to affect those interactions and potentially offset reductions in productivity. It is uncertain how plants will adjust their water use efficiency (WUE, plant production per water loss by evapotranspiration) in response to changing environmental conditions. This work investigates predicted changes in WUE in the 21st century by analyzing an ensemble of Earth System Models from the Coupled Model Intercomparison Project 5 (CMIP5), together with flux tower data and products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Two representative concentration pathways were selected to describe possible climate futures (RCP4.5 and RCP8.5). Periods of analysis included 2006-2099 (predicted) and 1850-2005 (reference). Comparisons between modeled, flux and satellite data for IPCC SREX regions were used to address the significant intermodel variability observed for the CMIP5 ensemble (larger variability for RCP8.5, higher intermodel agreement in Southeast Asia, lower intermodel agreement in arid areas). Model skill was evaluated in support of model selection and the spatiotemporal analysis of changes in WUE. Global, regional and latitudinal distributions of departures of projected conditions in relation to historical values are presented for both concentration pathways. Results showed high model sensitivity to different concentration pathways and increase in GPP and WUE for most of the planet (increases
Global Patterns in Human Consumption of Net Primary Production
NASA Technical Reports Server (NTRS)
Imhoff, Marc L.; Bounoua, Lahouari; Ricketts, Taylor; Loucks, Colby; Harriss, Robert; Lawrence William T.
2004-01-01
The human population and its consumption profoundly affect the Earth's ecosystems. A particularly compelling measure of humanity's cumulative impact is the fraction of the planet's net primary production that we appropriate for our Net primary production-the net amount of solar energy converted to plant organic matter through photosynthesis-can be measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. Human appropriation of net primary production, apart from leaving less for other species to use, alters the composition of the atmosphere, levels of biodiversity, flows within food webs and the provision of important primary production required by humans and compare it to the total amount generated on the landscape. We then derive a spatial ba!mce sheet of net primary production supply and demand for the world. We show that human appropriation of net primary production varies spatially from almost zero to many times the local primary production. These analyses reveal the uneven footprint of human consumption and related environmental impacts, indicate the degree to which human populations depend on net primary production "imports" and suggest policy options for slowing future growth of human appropriation of net primary production.
Variability in primary productivity determines metapopulation dynamics.
Fernández, Néstor; Román, Jacinto; Delibes, Miguel
2016-04-13
Temporal variability in primary productivity can change habitat quality for consumer species by affecting the energy levels available as food resources. However, it remains unclear how habitat-quality fluctuations may determine the dynamics of spatially structured populations, where the effects of habitat size, quality and isolation have been customarily assessed assuming static habitats. We present the first empirical evaluation on the effects of stochastic fluctuations in primary productivity--a major outcome of ecosystem functions--on the metapopulation dynamics of a primary consumer. A unique 13-year dataset from an herbivore rodent was used to test the hypothesis that inter-annual variations in primary productivity determine spatiotemporal habitat occupancy patterns and colonization and extinction processes. Inter-annual variability in productivity and in the growing season phenology significantly influenced habitat colonization patterns and occupancy dynamics. These effects lead to changes in connectivity to other potentially occupied habitat patches, which then feed back into occupancy dynamics. According to the results, the dynamics of primary productivity accounted for more than 50% of the variation in occupancy probability, depending on patch size and landscape configuration. Evidence connecting primary productivity dynamics and spatiotemporal population processes has broad implications for metapopulation persistence in fluctuating and changing environments. © 2016 The Authors.
Motivating green public procurement in China: an individual level perspective.
Zhu, Qinghua; Geng, Yong; Sarkis, Joseph
2013-09-15
Green public procurement (GPP) practices have been recognized as an effective policy tool for sustainable production and consumption. However, GPP practices adoption, especially in developing countries, is still an issue. Seeking to help understand these adoption issues, we develop a conceptual model which hypothesizes moderation effects of GPP knowledge on the relationships between GPP drivers and practices. Using primary data collected from 193 Chinese government officials, we find that regulations, rewards & incentive gains, and stakeholders exert pressure to motivate adoption of GPP practices. Knowledge of GPP regulations, responsibilities and experiences in developed countries is found to be limited. The study also found that voluntary regulations may actually be demotivating GPP practices. This study contributes to further theoretical and practical understanding of GPP practices. The findings can be helpful for policy makers, especially those in developing countries, to establish promotion and diffusion mechanisms for GPP practices as an important sustainable development tool. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Koster, Randal D. (Editor); Kimball, John S.; Jones, Lucas A.; Glassy, Joseph; Stavros, E. Natasha; Madani, Nima (Editor); Reichle, Rolf H.; Jackson, Thomas; Colliander, Andreas
2015-01-01
During the post-launch Cal/Val Phase of SMAP there are two objectives for each science product team: 1) calibrate, verify, and improve the performance of the science algorithms, and 2) validate accuracies of the science data products as specified in the L1 science requirements according to the Cal/Val timeline. This report provides analysis and assessment of the SMAP Level 4 Carbon (L4_C) product specifically for the beta release. The beta-release version of the SMAP L4_C algorithms utilizes a terrestrial carbon flux model informed by SMAP soil moisture inputs along with optical remote sensing (e.g. MODIS) vegetation indices and other ancillary biophysical data to estimate global daily NEE and component carbon fluxes, particularly vegetation gross primary production (GPP) and ecosystem respiration (Reco). Other L4_C product elements include surface (<10 cm depth) soil organic carbon (SOC) stocks and associated environmental constraints to these processes, including soil moisture and landscape FT controls on GPP and Reco (Kimball et al. 2012). The L4_C product encapsulates SMAP carbon cycle science objectives by: 1) providing a direct link between terrestrial carbon fluxes and underlying freeze/thaw and soil moisture constraints to these processes, 2) documenting primary connections between terrestrial water, energy and carbon cycles, and 3) improving understanding of terrestrial carbon sink activity in northern ecosystems.
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.
Austin, Bradley J; Hardgrave, Natalia; Inlander, Ethan; Gallipeau, Cory; Entrekin, Sally; Evans-White, Michelle A
2015-10-01
Construction of unconventional natural gas (UNG) infrastructure (e.g., well pads, pipelines) is an increasingly common anthropogenic stressor that increases potential sediment erosion. Increased sediment inputs into nearby streams may decrease autotrophic processes through burial and scour, or sediment bound nutrients could have a positive effect through alleviating potential nutrient limitations. Ten streams with varying catchment UNG well densities (0-3.6 wells/km(2)) were sampled during winter and spring of 2010 and 2011 to examine relationships between landscape scale disturbances associated with UNG activity and stream periphyton [chlorophyll a (Chl a)] and gross primary production (GPP). Local scale variables including light availability and water column physicochemical variables were measured for each study site. Correlation analyses examined the relationships of autotrophic processes and local scale variables with the landscape scale variables percent pasture land use and UNG metrics (well density and well pad inverse flow path length). Both GPP and Chl a were primarily positively associated with the UNG activity metrics during most sample periods; however, neither landscape variables nor response variables correlated well with local scale factors. These positive correlations do not confirm causation, but they do suggest that it is possible that UNG development can alleviate one or more limiting factors on autotrophic production within these streams. A secondary manipulative study was used to examine the link between nutrient limitation and algal growth across a gradient of streams impacted by natural gas activity. Nitrogen limitation was common among minimally impacted stream reaches and was alleviated in streams with high UNG activity. These data provide evidence that UNG may stimulate the primary production of Fayetteville shale streams via alleviation of N-limitation. Restricting UNG activities from the riparian zone along with better enforcement of
Variability in primary productivity determines metapopulation dynamics
2016-01-01
Temporal variability in primary productivity can change habitat quality for consumer species by affecting the energy levels available as food resources. However, it remains unclear how habitat-quality fluctuations may determine the dynamics of spatially structured populations, where the effects of habitat size, quality and isolation have been customarily assessed assuming static habitats. We present the first empirical evaluation on the effects of stochastic fluctuations in primary productivity—a major outcome of ecosystem functions—on the metapopulation dynamics of a primary consumer. A unique 13-year dataset from an herbivore rodent was used to test the hypothesis that inter-annual variations in primary productivity determine spatiotemporal habitat occupancy patterns and colonization and extinction processes. Inter-annual variability in productivity and in the growing season phenology significantly influenced habitat colonization patterns and occupancy dynamics. These effects lead to changes in connectivity to other potentially occupied habitat patches, which then feed back into occupancy dynamics. According to the results, the dynamics of primary productivity accounted for more than 50% of the variation in occupancy probability, depending on patch size and landscape configuration. Evidence connecting primary productivity dynamics and spatiotemporal population processes has broad implications for metapopulation persistence in fluctuating and changing environments. PMID:27053739
MacBean, Natasha; Maignan, Fabienne; Bacour, Cédric; Lewis, Philip; Peylin, Philippe; Guanter, Luis; Köhler, Philipp; Gómez-Dans, Jose; Disney, Mathias
2018-01-31
Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary productivity - GPP) are essential for reliable future terrestrial carbon sink projections. However, uncertainties in TBM GPP estimates remain. Newly-available satellite-derived sun-induced chlorophyll fluorescence (SIF) data offer a promising direction for addressing this issue by constraining regional-to-global scale modelled GPP. Here, we use monthly 0.5° GOME-2 SIF data from 2007 to 2011 to optimise GPP parameters of the ORCHIDEE TBM. The optimisation reduces GPP magnitude across all vegetation types except C4 plants. Global mean annual GPP therefore decreases from 194 ± 57 PgCyr -1 to 166 ± 10 PgCyr -1 , bringing the model more in line with an up-scaled flux tower estimate of 133 PgCyr -1 . Strongest reductions in GPP are seen in boreal forests: the result is a shift in global GPP distribution, with a ~50% increase in the tropical to boreal productivity ratio. The optimisation resulted in a greater reduction in GPP than similar ORCHIDEE parameter optimisation studies using satellite-derived NDVI from MODIS and eddy covariance measurements of net CO 2 fluxes from the FLUXNET network. Our study shows that SIF data will be instrumental in constraining TBM GPP estimates, with a consequent improvement in global carbon cycle projections.
NASA Astrophysics Data System (ADS)
Kang, W.
2017-12-01
Ecosystem carbon-energy-water circles have significant effect on function and structure and vice verse. Based on these circles mechanism, some eco-physiological indicators, like Transpiration (T), gross primary productivity (GPP), light use efficiency (LUE) and water use efficiency (WUE), are commonly applied to assess terrestrial ecosystem function and structure dynamics. The ecosystem weakened function and simple structure in Northeast dryland regions resulted from land degradation or desertification, which could be demonstrated by above-mentioned indicators. In this study, based on MODIS atmosphere (MYD07, MYD04, MYD06 data) and land products (MYD13A2 NDVI, MYD11A1 LST, MYD15A2 LAI and land cover data), we first retrieved transpiration and LUE via Penman-Monteith Model and modified Vegetation Photosynthesis Model (VPM), respectively; and then evaluated dynamics of these eco-physiological indicators (Tair, VPD, T, LUE, GPP and WUE) and some hotspots were found for next land degradation assessment. The results showed: (1) LUE and WUE are lower in barren or sparsely vegetated area and grasslands than in forest and croplands. (2) Whereas, all indicators presented higher variability in grassland area, particularly in east Mongolia. (3) GPP and transpiration have larger variability than other indicators due to fraction of absorbed Photosynthetically active radiation (FPAR). These eco-physiological indicators are expected to continue to change under future climate change and to help to assess land degradation from ecosystem energy-water-carbon perspectives.
Metabolism of a nitrogen-enriched coastal marine lagoon during the summertime
Howarth, Robert W.; Hayn, Melanie; Marino, Roxanne M.; Ganju, Neil; Foreman, Kenneth H.; McGlathery, Karen; Giblin, Anne E.; Berg, Peter; Walker, Jeffrey D.
2014-01-01
We measured metabolism rates in a shallow, nitrogen-enriched coastal marine ecosystem on Cape Cod (MA, USA) during seven summers using an open-water diel oxygen method. We compared two basins, one directly receiving most of the nitrogen (N) load (“Snug Harbor”) and another further removed from the N load and better flushed (“Outer Harbor”). Both dissolved oxygen and pH varied greatly over the day, increasing in daylight and decreasing at night. The more N-enriched basin frequently went hypoxic during the night, and the pH in both basins was low (compared to standard seawater) when the oxygen levels were low, due to elevated carbon dioxide. Day-to-day variation in gross primary production (GPP) was high and linked in part to variation in light. Whole-ecosystem respiration tended to track this short-term variation in GPP, suggesting that respiration by the primary producers often dominated whole-system respiration. GPP was higher in the more N-loaded Snug Harbor. Seagrasses covered over 60 % of the area of the better-flushed, Outer Harbor throughout our study and were the major contributors to GPP there. Seagrasses covered 20 % of the area in Snug Harbor for the first 5 years of our study, and their contribution to GPP was relatively small. The seagrasses in Snug Harbor died off completely in the 6th year, but GPP remained high then and in the subsequent year. Overall, rates of phytoplankton GPP were relatively low, suggesting that benthic micro- and macro-algae may be the dominant primary producers in Snug Harbor in most years. Net ecosystem production in both Snug Harbor and the Outer Harbor was variable from year to year, showing net heterotrophy in some years and net autotrophy in others, with a trend towards increasing autotrophy over the 7 years reported here.
Gu, Yingxin; Wylie, Bruce K.; Bliss, Norman B.
2013-01-01
This study assessed and described a relationship between satellite-derived growing season averaged Normalized Difference Vegetation Index (NDVI) and annual productivity for grasslands within the Greater Platte River Basin (GPRB) of the United States. We compared growing season averaged NDVI (GSN) with Soil Survey Geographic (SSURGO) database rangeland productivity and flux tower Gross Primary Productivity (GPP) for grassland areas. The GSN was calculated for each of nine years (2000–2008) using the 7-day composite 250-m eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. Strong correlations exist between the nine-year mean GSN (MGSN) and SSURGO annual productivity for grasslands (R2 = 0.74 for approximately 8000 pixels randomly selected from eight homogeneous regions within the GPRB; R2 = 0.96 for the 14 cluster-averaged points). Results also reveal a strong correlation between GSN and flux tower growing season averaged GPP (R2 = 0.71). Finally, we developed an empirical equation to estimate grassland productivity based on the MGSN. Spatially explicit estimates of grassland productivity over the GPRB were generated, which improved the regional consistency of SSURGO grassland productivity data and can help scientists and land managers to better understand the actual biophysical and ecological characteristics of grassland systems in the GPRB. This final estimated grassland production map can also be used as an input for biogeochemical, ecological, and climate change models.
PRIMARY PRODUCTION ESTIMATES IN CHESAPEAKE BAY USING SEAWIFS
The temporal and spatial variability in primary production along the main stem of Chesapeake Bay was examined from 1997 through 2000. Primary production estimates were determined from the Vertically Generalized Production Model (VGPM) (Behrenfeld and Falkowski, 1997) using chloro...
Estimation of Carbon Flux of Forest Ecosystem over Qilian Mountains by BIOME-BGC Model
NASA Astrophysics Data System (ADS)
Yan, Min; Tian, Xin; Li, Zengyuan; Chen, Erxue; Li, Chunmei
2014-11-01
The gross primary production (GPP) and net ecosystem exchange (NEE) are important indicators for carbon fluxes. This study aims at evaluating the forest GPP and NEE over the Qilian Mountains using meteorological, remotely sensed and other ancillary data at large scale. To realize this, the widely used ecological-process-based model, Biome-BGC, and remote-sensing-based model, MODIS GPP algorithm, were selected for the simulation of the forest carbon fluxes. The combination of these two models was based on calibrating the Biome-BGC by the optimized MODIS GPP algorithm. The simulated GPP and NEE values were evaluated against the eddy covariance observed GPPs and NEEs, and the well agreements have been reached, with R2=0.76, 0.67 respectively.
Estimation of Carbon Flux of Forest Ecosystem over Qilian Mountains by BIOME-BGC Model
NASA Astrophysics Data System (ADS)
Yan, Min; Tian, Xin; Li, Zengyuan; Chen, Erxue; Li, Chunmei
2014-11-01
The gross primary production (GPP) and net ecosystem exchange (NEE) are important indicators for carbon fluxes. This study aims at evaluating the forest GPP and NEE over the Qilian Mountains using meteorological, remotely sensed and other ancillary data at large scale. To realize this, the widely used ecological-process- based model, Biome-BGC, and remote-sensing-based model, MODIS GPP algorithm, were selected for the simulation of the forest carbon fluxes. The combination of these two models was based on calibrating the Biome-BGC by the optimized MODIS GPP algorithm. The simulated GPP and NEE values were evaluated against the eddy covariance observed GPPs and NEEs, and the well agreements have been reached, with R2=0.76, 0.67 respectively.
NASA Technical Reports Server (NTRS)
Zhang, Qingyuan; Middleton, Elizabeth M.; Margolis, Hank A.; Drolet, Guillaume G.; Barr, Alan A.; Black, T. Andrew
2009-01-01
Gross primary production (GPP) is a key terrestrial ecophysiological process that links atmospheric composition and vegetation processes. Study of GPP is important to global carbon cycles and global warming. One of the most important of these processes, plant photosynthesis, requires solar radiation in the 0.4-0.7 micron range (also known as photosynthetically active radiation or PAR), water, carbon dioxide (CO2), and nutrients. A vegetation canopy is composed primarily of photosynthetically active vegetation (PAV) and non-photosynthetic vegetation (NPV; e.g., senescent foliage, branches and stems). A green leaf is composed of chlorophyll and various proportions of nonphotosynthetic components (e.g., other pigments in the leaf, primary/secondary/tertiary veins, and cell walls). The fraction of PAR absorbed by whole vegetation canopy (FAPAR(sub canopy)) has been widely used in satellite-based Production Efficiency Models to estimate GPP (as a product of FAPAR(sub canopy)x PAR x LUE(sub canopy), where LUE(sub canopy) is light use efficiency at canopy level). However, only the PAR absorbed by chlorophyll (a product of FAPAR(sub chl) x PAR) is used for photosynthesis. Therefore, remote sensing driven biogeochemical models that use FAPAR(sub chl) in estimating GPP (as a product of FAPAR(sub chl x PAR x LUE(sub chl) are more likely to be consistent with plant photosynthesis processes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.
Here, the maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr –1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated throughmore » to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.« less
Satellite-based terrestrial production efficiency modeling
McCallum, Ian; Wagner, Wolfgang; Schmullius, Christiane; Shvidenko, Anatoly; Obersteiner, Michael; Fritz, Steffen; Nilsson, Sten
2009-01-01
Production efficiency models (PEMs) are based on the theory of light use efficiency (LUE) which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP) monitoring. The objectives of this review are as follows: 1) to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS) identified in the literature; 2) to review each model to determine potential improvements to the general PEM methodology; 3) to review the related literature on satellite-based gross primary productivity (GPP) and NPP modeling for additional possibilities for improvement; and 4) based on this review, propose items for coordinated research. This review noted a number of possibilities for improvement to the general PEM architecture - ranging from LUE to meteorological and satellite-based inputs. Current PEMs tend to treat the globe similarly in terms of physiological and meteorological factors, often ignoring unique regional aspects. Each of the existing PEMs has developed unique methods to estimate NPP and the combination of the most successful of these could lead to improvements. It may be beneficial to develop regional PEMs that can be combined under a global framework. The results of this review suggest the creation of a hybrid PEM could bring about a significant enhancement to the PEM methodology and thus terrestrial carbon flux modeling. Key items topping the PEM research agenda identified in this review include the following: LUE should not be assumed constant, but should vary by plant functional type (PFT) or photosynthetic pathway; evidence is mounting that PEMs should consider incorporating diffuse radiation; continue to pursue relationships between satellite-derived variables and LUE, GPP and autotrophic respiration (Ra); there is an urgent need for satellite
Peak growing season gross uptake of carbon in North America is largest in the Midwest USA
NASA Astrophysics Data System (ADS)
Hilton, Timothy W.; Whelan, Mary E.; Zumkehr, Andrew; Kulkarni, Sarika; Berry, Joseph A.; Baker, Ian T.; Montzka, Stephen A.; Sweeney, Colm; Miller, Benjamin R.; Elliott Campbell, J.
2017-06-01
Gross primary production (GPP) is a first-order uncertainty in climate predictions. Large-scale CO2 observations can provide information about the carbon cycle, but are not directly useful for GPP. Recently carbonyl sulfide (COS or OCS) has been proposed as a potential tracer for regional and global GPP. Here we present the first regional assessment of GPP using COS. We focus on the North American growing season--a global hotspot for COS air-monitoring and GPP uncertainty. Regional variability in simulated vertical COS concentration gradients was driven by variation in GPP rather than other modelled COS sources and sinks. Consequently we are able to show that growing season GPP in the Midwest USA significantly exceeds that of any other region of North America. These results are inconsistent with some ecosystem models, but are supportive of new ecosystem models from CMIP6. This approach provides valuable insight into the accuracy of various ecosystem land models.
Tang, Jianwu; Luyssaert, Sebastiaan; Richardson, Andrew D; Kutsch, Werner; Janssens, Ivan A
2014-06-17
The traditional view of forest dynamics originated by Kira and Shidei [Kira T, Shidei T (1967) Jap J Ecol 17:70-87] and Odum [Odum EP (1969) Science 164(3877):262-270] suggests a decline in net primary productivity (NPP) in aging forests due to stabilized gross primary productivity (GPP) and continuously increased autotrophic respiration (Ra). The validity of these trends in GPP and Ra is, however, very difficult to test because of the lack of long-term ecosystem-scale field observations of both GPP and Ra. Ryan and colleagues [Ryan MG, Binkley D, Fownes JH (1997) Ad Ecol Res 27:213-262] have proposed an alternative hypothesis drawn from site-specific results that aboveground respiration and belowground allocation decreased in aging forests. Here, we analyzed data from a recently assembled global database of carbon fluxes and show that the classical view of the mechanisms underlying the age-driven decline in forest NPP is incorrect and thus support Ryan's alternative hypothesis. Our results substantiate the age-driven decline in NPP, but in contrast to the traditional view, both GPP and Ra decline in aging boreal and temperate forests. We find that the decline in NPP in aging forests is primarily driven by GPP, which decreases more rapidly with increasing age than Ra does, but the ratio of NPP/GPP remains approximately constant within a biome. Our analytical models describing forest succession suggest that dynamic forest ecosystem models that follow the traditional paradigm need to be revisited.
NASA Technical Reports Server (NTRS)
Nemani, Ramakrishna R.
2016-01-01
Photosynthesis and light use efficiency (LUE) are major factors in the evolution of the continental carbon cycle due to their contribution to gross primary production (GPP). However, while the drivers of photosynthesis and LUE on a plant or canopy scale can often be identified, significant uncertainties exist when modeling these on a global scale. This is due to sparse observations in regions such as the tropics and the lack of a direct global observation dataset. Although others have attempted to address this issue using correlations (Beer, 2010) or calculating GPP from vegetation indices (Running, 2004), in this study we take a new approach. We combine the statistical method of Granger frequency causality and partial Granger frequency causality with remote sensing data products (including sun-induced fluorescence used as a proxy for GPP) to determine the main environmental drivers of GPP across the globe.
Do Offshore Wind Farms Influence Marine Primary Production?
NASA Astrophysics Data System (ADS)
Tweddle, J. F.; Murray, R. B. O.; Gubbins, M.; Scott, B. E.
2016-02-01
Primary producers (phytoplankton) form the basis of marine food-webs, supporting production of higher trophic levels, and act as a sink of CO2. We considered the impact of proposed large scale offshore wind farms in moderately deep waters (> 45 m) off the east coast of Scotland on rates of primary production. A 2 stage modelling process was used, employing state-of-the-art 3-D hydrographic models with the ability to capture flow at the spatial resolution of 10 m combined with 1-D vertical modelling using 7 years of local forcing data. Through influencing the strength of stratification via changes in current flow, large (100 m) modelled wind turbine foundations had a significant effect on primary producers, consistently reducing total annual primary production, although within the range of natural interannual variability. The percentage reduction was largest over submarine banks less than 54 m in depth, and was outside the range of natural interannual variability. Smaller (10 m) turbine foundations had no discernible effect on total annual primary production. The results indicate that smaller foundations should be favored as a mitigation measure, in terms of effects on primary production, and this type of analysis should be considered within sectoral planning and licensing processes for future renewable energy developments.
Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate.
Beer, Christian; Reichstein, Markus; Tomelleri, Enrico; Ciais, Philippe; Jung, Martin; Carvalhais, Nuno; Rödenbeck, Christian; Arain, M Altaf; Baldocchi, Dennis; Bonan, Gordon B; Bondeau, Alberte; Cescatti, Alessandro; Lasslop, Gitta; Lindroth, Anders; Lomas, Mark; Luyssaert, Sebastiaan; Margolis, Hank; Oleson, Keith W; Roupsard, Olivier; Veenendaal, Elmar; Viovy, Nicolas; Williams, Christopher; Woodward, F Ian; Papale, Dario
2010-08-13
Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.
OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence
NASA Astrophysics Data System (ADS)
Sun, Y.; Frankenberg, C.; Wood, J. D.; Schimel, D.; Jung, M.; Guanter, L.; Drewry, D.; Verma, M.; Porcar-Castell, A.; Griffis, T. J.; Gu, L.; Magney, T.; Köhler, P.; Evans, B. J.; Yuen, K.
2017-12-01
Quantifying gross primary production (GPP) remains a grand challenge in global carbon cycle research. Space-borne monitoring of solar-induced chlorophyll fluorescence (SIF), an integrative photosynthetic signal of molecular origin, can assist in terrestrial GPP monitoring. However, the extent to which SIF tracks spatiotemporal variations in GPP remains unresolved. OCO-2 SIF's data acquisition and fine spatial resolution permit the first direct validation against ground/airborne observations. Empirical orthogonal function analysis shows consistent spatiotemporal correspondence between OCO-2 SIF and GPP globally. A linear SIF-GPP relationship is also obtained at eddy-flux sites covering diverse biomes, setting the stage for future investigations of the robustness of such relationship across more biomes. Our findings support the central importance of high-quality satellite SIF for studying terrestrial carbon cycle dynamics.
The relative influence of nutrients and habitat on stream metabolism in agricultural streams
Frankforter, J.D.; Weyers, H.S.; Bales, J.D.; Moran, P.W.; Calhoun, D.L.
2010-01-01
Stream metabolism was measured in 33 streams across a gradient of nutrient concentrations in four agricultural areas of the USA to determine the relative influence of nutrient concentrations and habitat on primary production (GPP) and respiration (CR-24). In conjunction with the stream metabolism estimates, water quality and algal biomass samples were collected, as was an assessment of habitat in the sampling reach. When data for all study areas were combined, there were no statistically significant relations between gross primary production or community respiration and any of the independent variables. However, significant regression models were developed for three study areas for GPP (r 2 = 0.79-0.91) and CR-24 (r 2 = 0.76-0.77). Various forms of nutrients (total phosphorus and area-weighted total nitrogen loading) were significant for predicting GPP in two study areas, with habitat variables important in seven significant models. Important physical variables included light availability, precipitation, basin area, and in-stream habitat cover. Both benthic and seston chlorophyll were not found to be important explanatory variables in any of the models; however, benthic ash-free dry weight was important in two models for GPP. ?? 2009 The Author(s).
NASA Astrophysics Data System (ADS)
Butterfield, Z.; Keppel-Aleks, G.
2015-12-01
The seasonality of carbon dioxide (CO2) concentrations in the northern hemisphere (NH) has increased by up to 50% over the previous five decades. A significant portion of this increase may be explained by enhanced agricultural productivity. The impact that increased crop production has on CO2 seasonality is dependent on the fraction of the crop Gross Primary Product (GPP) that occurs during the natural carbon uptake period (CUP). Solar Induced Fluorescence (SIF), an artifact of photosynthesis, can be used to assess GPP directly via remote sensing. New methods for measuring SIF from space provide tools for obtaining GPP data at regional and global levels. We use SIF data from the GOSAT and OCO-2 satellites to obtain observational estimates of the fraction of GPP occurring within the CUP in NH agricultural regions. We compare these fractions with estimates made using crop calendars and inventories and, where available, with CO2 flux data from eddy covariance towers. Our results offer insight into the impact that increased agricultural productivity has on the seasonal amplitude of NH CO2 concentrations.
Iyer, Sukanya; Le, Dai; Park, Bo Ryoung; Kim, Minsu
2018-05-14
Bacteria adapt to environmental stress by producing proteins that provide stress protection. However, stress can severely perturb the kinetics of gene expression, disrupting protein production. Here, we characterized how Escherichia coli mitigates such perturbations under nutrient stress through the kinetic coordination of transcription and translation. We observed that, when translation became limiting under nitrogen starvation, transcription elongation slowed accordingly. This slowdown was mediated by (p)ppGpp, the alarmone whose primary role is thought to be promoter regulation. This kinetic coordination by (p)ppGpp was critical for the robust synthesis of gene products. Surprisingly, under carbon starvation, (p)ppGpp was dispensable for robust synthesis. Characterization of the underlying kinetics revealed that under carbon starvation, transcription became limiting, and translation aided transcription elongation. This mechanism naturally coordinated transcription with translation, alleviating the need for (p)ppGpp as a mediator. These contrasting mechanisms for coordination resulted in the condition-dependent effects of (p)ppGpp on global protein synthesis and starvation survival. Our findings reveal a kinetic aspect of gene expression plasticity, establishing (p)ppGpp as a condition-dependent global effector of gene expression.
Interannual Variation in Phytoplankton Primary Production at a Global Scale
NASA Technical Reports Server (NTRS)
Rousseaux, Cecile Severine; Gregg, Watson W.
2013-01-01
We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of four phytoplankton groups to the total primary production. First, we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms contributed the most to the total phytoplankton production ((is)approximately 50%, the equivalent of 20 PgC·y1). Coccolithophores and chlorophytes each contributed approximately 20% ((is) approximately 7 PgC·y1) of the total primary production and cyanobacteria represented about 10% ((is) approximately 4 PgC·y1) of the total primary production. Primary production by diatoms was highest in the high latitudes ((is) greater than 40 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4% (1-2 PgC·y1). We assessed the effects of climate variability on group-specific primary production using global (i.e., Multivariate El Niño Index, MEI) and "regional" climate indices (e.g., Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p (is) less than 0.05) between the MEI and the group-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatoms/cyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect
Primary forest products industry and industrial roundwood production, Michigan, 1969.
James E. Blyth; Allen H. Boelter
1971-01-01
Michigan loggers cut 173.8 million cubic feet of industrial roundwood products in 1969. Ninety percent was pulpwood and saw logs. Production is shifting from softwoods to hardwoods. The number of active primary wood-using mills declined rapidly from 1954 to 1969, but production per mill has expanded.
NASA Astrophysics Data System (ADS)
Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.
2012-12-01
Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis
Zhao, Jing-Jing; Liu, Liang-Yun
2013-02-01
Flux tower method can effectively monitor the vegetation seasonal and phenological variation processes. At present, the differences in the detection and quantitative evaluation of various phenology extraction methods were not well validated and quantified. Based on the gross primary productivity (GPP) and net ecosystem productivity (NEP) data of temperate forests from 9 forest FLUXNET sites in North America, and by using the start dates (SOS) and end dates (EOS) of the temperate forest growth seasons extracted by different phenology threshold extraction methods, in combining with the forest ecosystem carbon source/sink functions, this paper analyzed the effects of different threshold standards on the extraction results of the vegetations phenology. The results showed that the effects of different threshold standards on the stability of the extracted results of deciduous broadleaved forest (DBF) phenology were smaller than those on the stability of the extracted results of evergreen needleleaved forest (ENF) phenology. Among the extracted absolute and relative thresholds of the forests GPP, the extracted threshold of the DBF daily GPP= 2 g C.m-2.d-1 had the best agreement with the DBF daily GPP = 20% maximum GPP (GPPmax) , the phenological metrics with a threshold of daily GPP = 4 g C.m-2.d-1 was close to that between daily GPP = 20% GPPmax and daily GPP = 50% GPPmax, and the start date of ecosystem carbon sink function was close to the SOS metrics between daily GPP = 4 g C.m-2.d-1 and daily GPP= 20% GPPmax. For ENF, the phenological metrics with a threshold of daily GPP = 2 g C.m-2.d-1 and daily GPP = 4 g C.m-2.d-1 had the best agreement with the daily GPP = 20% GPPmax and daily GPP = 50% GPPmax, respectively, and the start date of the ecosystem carbon sink function was close to the SOS metrics between daily GPP = 2 g C.m-2.d-1 and daily GPP= 10% GPPmax.
NASA Astrophysics Data System (ADS)
Dechant, B.; Ryu, Y.; Jiang, C.; Yang, K.
2017-12-01
Solar-induced chlorophyll fluorescence (SIF) is rapidly becoming an important tool to remotely estimate terrestrial gross primary productivity (GPP) at large spatial scales. Many findings, however, are based on empirical relationships between SIF and GPP that have been found to be dependent on plant functional types. Therefore, combining model-based analysis with observations is crucial to improve our understanding of SIF-GPP relationships. So far, most model-based results were based on SCOPE, a complex ecophysiological model with explicit description of canopy layers and a large number of parameters that may not be easily obtained reliably on large scales. Here, we report on our efforts to incorporate SIF into a two-big leaf (sun and shade) process-based model that is suitable for obtaining its inputs entirely from satellite products. We examine if the SIF-GPP relationships are consistent with the findings from SCOPE simulations and investigate if incorporation of the SIF signal into BESS can help improve GPP estimation. A case study in a rice paddy is presented.
Patterns of Ecosystem Metabolism in the Tonle Sap Lake, Cambodia with Links to Capture Fisheries
Holtgrieve, Gordon W.; Arias, Mauricio E.; Irvine, Kim N.; Lamberts, Dirk; Ward, Eric J.; Kummu, Matti; Koponen, Jorma; Sarkkula, Juha; Richey, Jeffrey E.
2013-01-01
The Tonle Sap Lake in Cambodia is a dynamic flood-pulsed ecosystem that annually increases its surface area from roughly 2,500 km2 to over 12,500 km2 driven by seasonal flooding from the Mekong River. This flooding is thought to structure many of the critical ecological processes, including aquatic primary and secondary productivity. The lake also has a large fishery that supports the livelihoods of nearly 2 million people. We used a state-space oxygen mass balance model and continuous dissolved oxygen measurements from four locations to provide the first estimates of gross primary productivity (GPP) and ecosystem respiration (ER) for the Tonle Sap. GPP averaged 4.1±2.3 g O2 m−3 d−1 with minimal differences among sites. There was a negative correlation between monthly GPP and lake level (r = 0.45) and positive correlation with turbidity (r = 0.65). ER averaged 24.9±20.0 g O2 m−3 d−1 but had greater than six-fold variation among sites and minimal seasonal change. Repeated hypoxia was observed at most sampling sites along with persistent net heterotrophy (GPP
Patterns of ecosystem metabolism in the Tonle Sap Lake, Cambodia with links to capture fisheries.
Holtgrieve, Gordon W; Arias, Mauricio E; Irvine, Kim N; Lamberts, Dirk; Ward, Eric J; Kummu, Matti; Koponen, Jorma; Sarkkula, Juha; Richey, Jeffrey E
2013-01-01
The Tonle Sap Lake in Cambodia is a dynamic flood-pulsed ecosystem that annually increases its surface area from roughly 2,500 km(2) to over 12,500 km(2) driven by seasonal flooding from the Mekong River. This flooding is thought to structure many of the critical ecological processes, including aquatic primary and secondary productivity. The lake also has a large fishery that supports the livelihoods of nearly 2 million people. We used a state-space oxygen mass balance model and continuous dissolved oxygen measurements from four locations to provide the first estimates of gross primary productivity (GPP) and ecosystem respiration (ER) for the Tonle Sap. GPP averaged 4.1±2.3 g O2 m(-3) d(-1) with minimal differences among sites. There was a negative correlation between monthly GPP and lake level (r = 0.45) and positive correlation with turbidity (r = 0.65). ER averaged 24.9±20.0 g O2 m(-3) d(-1) but had greater than six-fold variation among sites and minimal seasonal change. Repeated hypoxia was observed at most sampling sites along with persistent net heterotrophy (GPP
Oh, Young Taek; Park, Yongjin; Yoon, Mi Young; Bari, Wasimul; Go, Junhyeok; Min, Kyung Bae; Raskin, David M.; Lee, Kang-Mu; Yoon, Sang Sun
2014-01-01
As a facultative anaerobe, Vibrio cholerae can grow by anaerobic respiration. Production of cholera toxin (CT), a major virulence factor of V. cholerae, is highly promoted during anaerobic growth using trimethylamine N-oxide (TMAO) as an alternative electron acceptor. Here, we investigated the molecular mechanisms of TMAO-stimulated CT production and uncovered the crucial involvement of stringent response in this process. V. cholerae 7th pandemic strain N16961 produced a significantly elevated level of ppGpp, the bacterial stringent response alarmone, during anaerobic TMAO respiration. Bacterial viability was impaired, and DNA replication was also affected under the same growth condition, further suggesting that stringent response is induced. A ΔrelA ΔspoT ppGpp overproducer strain produced an enhanced level of CT, whereas anaerobic growth via TMAO respiration was severely inhibited. In contrast, a ppGpp-null strain (ΔrelA ΔspoT ΔrelV) grew substantially better, but produced no CT, suggesting that CT production and bacterial growth are inversely regulated in response to ppGpp accumulation. Bacterial capability to produce CT was completely lost when the dksA gene, which encodes a protein that works cooperatively with ppGpp, was deleted. In the ΔdksA mutant, stringent response growth inhibition was alleviated, further supporting the inverse regulation of CT production and anaerobic growth. In vivo virulence of ΔrelA ΔspoT ΔrelV or ΔdksA mutants was significantly attenuated. The ΔrelA ΔspoT mutant maintained virulence when infected with exogenous TMAO despite its defective growth. Together, our results reveal that stringent response is activated under TMAO-stimulated anaerobic growth, and it regulates CT production in a growth-dependent manner in V. cholerae. PMID:24648517
Decadal Changes in Global Ocean Annual Primary Production
NASA Technical Reports Server (NTRS)
Gregg, Watson; Conkright, Margarita E.; Behrenfeld, Michael J.; Ginoux, Paul; Casey, Nancy W.; Koblinsky, Chester J. (Technical Monitor)
2002-01-01
The Sea-viewing Wide Field-of-View Sensor (SeaWiFS) has produced the first multi-year time series of global ocean chlorophyll observations since the demise of the Coastal Zone Color Scanner (CZCS) in 1986. Global observations from 1997-present from SeaWiFS combined with observations from 1979-1986 from the CZCS should in principle provide an opportunity to observe decadal changes in global ocean annual primary production, since chlorophyll is the primary driver for estimates of primary production. However, incompatibilities between algorithms have so far precluded quantitative analysis. We have developed and applied compatible processing methods for the CZCS, using modern advances in atmospheric correction and consistent bio-optical algorithms to advance the CZCS archive to comparable quality with SeaWiFS. We applied blending methodologies, where in situ data observations are incorporated into the CZCS and SeaWiFS data records, to provide improvement of the residuals. These re-analyzed, blended data records provide maximum compatibility and permit, for the first time, a quantitative analysis of the changes in global ocean primary production in the early-to-mid 1980's and the present, using synoptic satellite observations. An intercomparison of the global and regional primary production from these blended satellite observations is important to understand global climate change and the effects on ocean biota. Photosynthesis by chlorophyll-containing phytoplankton is responsible for biotic uptake of carbon in the oceans and potentially ultimately from the atmosphere. Global ocean annual primary decreased from the CZCS record to SeaWiFS, by nearly 6% from the early 1980s to the present. Annual primary production in the high latitudes was responsible for most of the decadal change. Conversely, primary production in the low latitudes generally increased, with the exception of the tropical Pacific. The differences and similarities of the two data records provide evidence
24 CFR 3282.362 - Production Inspection Primary Inspection Agencies (IPIAs).
Code of Federal Regulations, 2010 CFR
2010-04-01
... in production which fails to conform to the design or where the design is not specific, to the... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Production Inspection Primary... REGULATIONS Primary Inspection Agencies § 3282.362 Production Inspection Primary Inspection Agencies (IPIAs...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sun, Ying; Frankenberg, C.; Wood, Jeff D.
Quantifying gross primary production (GPP) remains a major challenge in global carbon cycle research. Spaceborne monitoring of solar-induced chlorophyll fluorescence (SIF), an integrative photosynthetic signal of molecular origin, can assist in terrestrial GPP monitoring. However, the extent to which SIF tracks spatiotemporal variations in GPP remains unresolved. Orbiting Carbon Observatory-2 (OCO-2)’s SIF data acquisition and fine spatial resolution permit direct validation against ground and airborne observations. Empirical orthogonal function analysis shows consistent spatiotemporal correspondence between OCO-2 SIF and GPP globally. A linear SIF-GPP relationship is also obtained at eddy-flux sites covering diverse biomes, setting the stage for future investigations ofmore » the robustness of such a relationship across more biomes. In conclusion, our findings support the central importance of high-quality satellite SIF for studying terrestrial carbon cycle dynamics.« less
OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence
Sun, Ying; Frankenberg, C.; Wood, Jeff D.; ...
2017-10-12
Quantifying gross primary production (GPP) remains a major challenge in global carbon cycle research. Spaceborne monitoring of solar-induced chlorophyll fluorescence (SIF), an integrative photosynthetic signal of molecular origin, can assist in terrestrial GPP monitoring. However, the extent to which SIF tracks spatiotemporal variations in GPP remains unresolved. Orbiting Carbon Observatory-2 (OCO-2)’s SIF data acquisition and fine spatial resolution permit direct validation against ground and airborne observations. Empirical orthogonal function analysis shows consistent spatiotemporal correspondence between OCO-2 SIF and GPP globally. A linear SIF-GPP relationship is also obtained at eddy-flux sites covering diverse biomes, setting the stage for future investigations ofmore » the robustness of such a relationship across more biomes. In conclusion, our findings support the central importance of high-quality satellite SIF for studying terrestrial carbon cycle dynamics.« less
Cosmogenic-nuclide production by primary cosmic-ray protons
NASA Technical Reports Server (NTRS)
Reedy, R. C.
1985-01-01
The production rates of cosmogenic nuclides were calculated for the primary protons in the galactic and solar cosmic rays. At 1 AU, the long-term average fluxes of solar protons usually produce many more atoms of cosmogenic nuclide than the primary protons in the galactic cosmic rays (GCR). Because the particle fluxes inside meteorites and other large objects in space include many secondary neutrons, the production rates and ratios inside large objects are often very different from those by just the primary GCR protons. It is possible to determine if a small object, was small in space or broken from a meteorite. Because heliospherical modulation and other interactions change the GCR particle spectrum, the production of cosmogenic nuclides by the GCR particles outside the heliosphere will be different from that by modulated GCR primaries.
Patterns of NPP, GPP, Respiration and NEP During Boreal Forest Succession
DOE Office of Scientific and Technical Information (OSTI.GOV)
Goulden, Michael L.; McMillan, Andrew; Winston, Greg
2010-12-15
We deployed a mesonet of year-round eddy covariance towers in boreal forest stands that last burned in ~1850, ~1930, 1964, 1981, 1989, 1998, and 2003 to understand how CO2 exchange changes during secondary succession.The strategy of using multiple methods, including biometry and micrometeorology, worked well. In particular, the three independent measures of NEP during succession gave similar results. A stratified and tiered approach to deploying eddy covariance systems that combines many lightweight and portable towers with a few permanent ones is likely to maximize the science return for a fixed investment. The existing conceptual models did a good job ofmore » capturing the dominant patterns of NPP, GPP, Respiration and NEP during succession. The initial loss of carbon following disturbance was neither as protracted nor large as predicted. This muted response reflects both the rapid regrowth of vegetation following fire and the prevalence of standing coarse woody debris following the fire, which is thought to decay slowly. In general, the patterns of forest recovery from disturbance should be expected to vary as a function of climate, ecosystem type and disturbance type. The NPP decline at the older stands appears related to increased Rauto rather than decreased GPP. The increase in Rauto in the older stands does not appear to be caused by accelerated maintenance respiration with increased biomass, and more likely involves increased allocation to fine root turnover, root metabolism, alternative forms of respiration, mycorrhizal relationships, or root exudates, possibly associated with progressive nutrient limitation. Several studies have now described a similar pattern of NEP following boreal fire, with 10-to-15 years of modest carbon loss followed by 50-to-100 years of modest carbon gain. This trend has been sufficiently replicated and evaluated using independent techniques that it can be used to quantify the likely effects of changes in boreal fire frequency
Zhang, Tao; Zhang, Yangjian; Xu, Mingjie; Zhu, Juntao; Wimberly, Michael C; Yu, Guirui; Niu, Shuli; Xi, Yi; Zhang, Xianzhou; Wang, Jingsheng
2015-10-30
To explore grazing effects on carbon fluxes in alpine meadow ecosystems, we used a paired eddy-covariance (EC) system to measure carbon fluxes in adjacent fenced (FM) and grazed (GM) meadows on the Tibetan plateau. Gross primary productivity (GPP) and ecosystem respiration (Re) were greater at GM than FM for the first two years of fencing. In the third year, the productivity at FM increased to a level similar to the GM site. The higher productivity at GM was mainly caused by its higher photosynthetic capacity. Grazing exclusion did not increase carbon sequestration capacity for this alpine grassland system. The higher optimal photosynthetic temperature and the weakened ecosystem response to climatic factors at GM may help to facilitate the adaption of alpine meadow ecosystems to changing climate.
Khalifa, Muhammad; Elagib, Nadir Ahmed; Ribbe, Lars; Schneider, Karl
2018-05-15
The impact of climate variability on the Net Primary Productivity (NPP) of different land cover types and the reaction of NPP to drought conditions are still unclear, especially in Sub-Saharan Africa. This research utilizes public-domain data for the period 2000 through 2013 to analyze these aspects for several land cover types in Sudan and Ethiopia, as examples of data-scarce countries. Spatio-temporal variation in NPP, water use efficiency (WUE) and carbon use efficiency (CUE) for several land covers were correlated with variations in precipitation, temperature and drought at different time scales, i.e. 1, 3, 6 and 12months using Standardized Precipitation Evapotranspiration Index (SPEI) datasets. WUE and CUE were estimated as the ratios of NPP to actual evapotranspiration and NPP to Gross Primary Productivity (GPP), respectively. Results of this study revealed that NPP, WUE and CUE of the different land cover types in Ethiopia have higher magnitudes than their counterparts in Sudan. Moreover, they exhibit higher sensitivity to drought and variation in precipitation. Whereas savannah represents the most sensitive land cover to drought, croplands and permanent wetlands are the least sensitive ones. The inter-annual variation in NPP, WUE and CUE in Ethiopia is likely to be driven by a drought of time scale of three months. No statistically significant correlation was found for Sudan between the inter-annual variations in these indicators with drought at any of the time scales considered in the study. Our findings are useful from the view point of both food security for a growing population and mitigation to climate change as discussed in the present study. Copyright © 2017 Elsevier B.V. All rights reserved.
Canopy near-infrared reflectance and terrestrial photosynthesis.
Badgley, Grayson; Field, Christopher B; Berry, Joseph A
2017-03-01
Global estimates of terrestrial gross primary production (GPP) remain highly uncertain, despite decades of satellite measurements and intensive in situ monitoring. We report a new approach for quantifying the near-infrared reflectance of terrestrial vegetation (NIR V ). NIR V provides a foundation for a new approach to estimate GPP that consistently untangles the confounding effects of background brightness, leaf area, and the distribution of photosynthetic capacity with depth in canopies using existing moderate spatial and spectral resolution satellite sensors. NIR V is strongly correlated with solar-induced chlorophyll fluorescence, a direct index of photons intercepted by chlorophyll, and with site-level and globally gridded estimates of GPP. NIR V makes it possible to use existing and future reflectance data as a starting point for accurately estimating GPP.
Canopy near-infrared reflectance and terrestrial photosynthesis
Badgley, Grayson; Field, Christopher B.; Berry, Joseph A.
2017-01-01
Global estimates of terrestrial gross primary production (GPP) remain highly uncertain, despite decades of satellite measurements and intensive in situ monitoring. We report a new approach for quantifying the near-infrared reflectance of terrestrial vegetation (NIRV). NIRV provides a foundation for a new approach to estimate GPP that consistently untangles the confounding effects of background brightness, leaf area, and the distribution of photosynthetic capacity with depth in canopies using existing moderate spatial and spectral resolution satellite sensors. NIRV is strongly correlated with solar-induced chlorophyll fluorescence, a direct index of photons intercepted by chlorophyll, and with site-level and globally gridded estimates of GPP. NIRV makes it possible to use existing and future reflectance data as a starting point for accurately estimating GPP. PMID:28345046
2007-09-01
CONCEPTS, REAL-TIME IMPLEMENTATION AND MEASUREMENTS TOWARDS 3GPP-LTE T. Haustein , J. Eichinger, W. Zirwas, E. Schulz Nokia Siemens...BER (bottom) in an office scenario while the UE is moved from one room to another. REFERENCES [1] V. Jungnickel, A. Forck, T. Haustein , C. Juchems...2.12.2006 [3] T. Haustein , A. Forck, H. Gäbler, V. Jungnickel and S. Schif- fermüller, „Real-Time Experiments on Channel Adaptive Transmis- sion in
NASA Technical Reports Server (NTRS)
Chang, Jinfeng; Ciais, Philippe; Herrero, Mario; Havlik, Petr; Campioli, Matteo; Zhang, Xianzhou; Bai, Yongfei; Viovy, Nicolas; Joiner, Joanna; Wang, Xuhui;
2016-01-01
Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5deg by 0.5deg. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 19012012. The grass-biomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, risingCO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6.1 x 10(exp 6) km(exp 2) in 1901 to 12.3 x 10(exp 6) kmI(exp 2) in 2000, although the expansion pathway varies between different regions. ORCHIDEE-GM also simulated augmentation in global mean productivity and herbage-use efficiency over managed grassland during the 20th century, indicating a general intensification of grassland management at global scale but with regional differences. The gridded grassland management intensity maps are model dependent because they depend on modelled productivity. Thus specific attention was given to the evaluation of modelled productivity against a series of observations from site-level net primary productivity (NPP) measurements to two global satellite products of gross primary productivity (GPP) (MODIS-GPP and SIF data). Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle, and inter-annual variability of grassland productivity at global
Comprehensive description of the carbon cycle of an ancient temperate broadleaved woodland
NASA Astrophysics Data System (ADS)
Fenn, K.; Malhi, Y.; Morecroft, M.; Lloyd, C.; Thomas, M.
2010-05-01
There exist very few comprehensive descriptions of the productivity and carbon cycling of forest ecosystems. Here we present a description of the components of annual Net Primary Productivity (NPP), Gross Primary Productivity (GPP), autotrophic and heterotrophic respiration, and ecosystem respiration (RECO) for a temperate mixed deciduous woodland at Wytham Woods in southern Britain, calculated using "bottom-up" biometric and chamber measurements (leaf and wood production and soil and stem respiration). These are compared with estimates of these parameters from eddy-covariance measurements made at the same site. NPP was estimated as 7.0±0.8 Mg C ha-1 yr-1, and GPP as 20.3+1.0 Mg C ha-1 yr-1, a value which closely matched to eddy covariance-derived GPP value of 21.1 Mg C ha-1 yr-1. Annual RECO was calculated as 18.9±1.7 Mg C ha-1 yr-1, close to the eddy covariance value of 19.8 Mg C ha-1 yr-1; the seasonal cycle of biometric and eddy covariance RECO estimates also closely matched. The consistency between eddy covariance and biometric measurements substantially strengthens the confidence we attach to each as alternative indicators of site carbon dynamics, and permits an integrated perspective of the ecosystem carbon cycle. 37% of NPP was allocated below ground, and the ecosystem carbon use efficiency (CUE, = NPP/GPP) calculated to be 0.35±0.05, lower than reported for many temperate broadleaved sites.
Cavaleri, Molly A; Coble, Adam P; Ryan, Michael G; Bauerle, William L; Loescher, Henry W; Oberbauer, Steven F
2017-10-01
Changes in tropical forest carbon sink strength during El Niño Southern Oscillation (ENSO) events can indicate future behavior under climate change. Previous studies revealed ˜6 Mg C ha -1 yr -1 lower net ecosystem production (NEP) during ENSO year 1998 compared with non-ENSO year 2000 in a Costa Rican tropical rainforest. We explored environmental drivers of this change and examined the contributions of ecosystem respiration (RE) and gross primary production (GPP) to this weakened carbon sink. For 1998-2000, we estimated RE using chamber-based respiration measurements, and we estimated GPP in two ways: using (1) the canopy process model MAESTRA, and (2) combined eddy covariance and chamber respiration data. MAESTRA-estimated GPP did not statistically differ from GPP estimated using approach 2, but was ˜ 28% greater than published GPP estimates for the same site and years using eddy covariance data only. A 7% increase in RE (primarily increased soil respiration) and a 10% reduction in GPP contributed equally to the difference in NEP between ENSO year 1998 and non-ENSO year 2000. A warming and drying climate for tropical forests may yield a weakened carbon sink from both decreased GPP and increased RE. Understanding physiological acclimation will be critical for the large carbon stores in these ecosystems. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
NASA Astrophysics Data System (ADS)
Deppeler, Stacy; Petrou, Katherina; Schulz, Kai G.; Westwood, Karen; Pearce, Imojen; McKinlay, John; Davidson, Andrew
2018-01-01
High-latitude oceans are anticipated to be some of the first regions affected by ocean acidification. Despite this, the effect of ocean acidification on natural communities of Antarctic marine microbes is still not well understood. In this study we exposed an early spring, coastal marine microbial community in Prydz Bay to CO2 levels ranging from ambient (343 µatm) to 1641 µatm in six 650 L minicosms. Productivity assays were performed to identify whether a CO2 threshold existed that led to a change in primary productivity, bacterial productivity, and the accumulation of chlorophyll a (Chl a) and particulate organic matter (POM) in the minicosms. In addition, photophysiological measurements were performed to identify possible mechanisms driving changes in the phytoplankton community. A critical threshold for tolerance to ocean acidification was identified in the phytoplankton community between 953 and 1140 µatm. CO2 levels ≥ 1140 µatm negatively affected photosynthetic performance and Chl a-normalised primary productivity (csGPP14C), causing significant reductions in gross primary production (GPP14C), Chl a accumulation, nutrient uptake, and POM production. However, there was no effect of CO2 on C : N ratios. Over time, the phytoplankton community acclimated to high CO2 conditions, showing a down-regulation of carbon concentrating mechanisms (CCMs) and likely adjusting other intracellular processes. Bacterial abundance initially increased in CO2 treatments ≥ 953 µatm (days 3-5), yet gross bacterial production (GBP14C) remained unchanged and cell-specific bacterial productivity (csBP14C) was reduced. Towards the end of the experiment, GBP14C and csBP14C markedly increased across all treatments regardless of CO2 availability. This coincided with increased organic matter availability (POC and PON) combined with improved efficiency of carbon uptake. Changes in phytoplankton community production could have negative effects on the Antarctic food web and the
Modeling Surface Climate in US Cities Using Simple Biosphere Model Sib2
NASA Technical Reports Server (NTRS)
Zhang, Ping; Bounoua, Lahouari; Thome, Kurtis; Wolfe, Robert; Imhoff, Marc
2015-01-01
We combine Landsat- and the Moderate Resolution Imaging Spectroradiometer (MODIS)-based products in the Simple Biosphere model (SiB2) to assess the effects of urbanized land on the continental US (CONUS) surface climate. Using National Land Cover Database (NLCD) Impervious Surface Area (ISA), we define more than 300 urban settlements and their surrounding suburban and rural areas over the CONUS. The SiB2 modeled Gross Primary Production (GPP) over the CONUS of 7.10 PgC (1 PgC= 10(exp 15) grams of Carbon) is comparable to the MODIS improved GPP of 6.29 PgC. At state level, SiB2 GPP is highly correlated with MODIS GPP with a correlation coefficient of 0.94. An increasing horizontal GPP gradient is shown from the urban out to the rural area, with, on average, rural areas fixing 30% more GPP than urbans. Cities built in forested biomes have stronger UHI magnitude than those built in short vegetation with low biomass. Mediterranean climate cities have a stronger UHI in wet season than dry season. Our results also show that for urban areas built within forests, 39% of the precipitation is discharged as surface runoff during summer versus 23% in rural areas.
Duchi, Diego; Mazumder, Abhishek; Malinen, Anssi M; Ebright, Richard H; Kapanidis, Achillefs N
2018-06-06
RNA polymerase (RNAP) contains a mobile structural module, the 'clamp,' that forms one wall of the RNAP active-center cleft and that has been linked to crucial aspects of the transcription cycle, including promoter melting, transcription elongation complex stability, transcription pausing, and transcription termination. Using single-molecule FRET on surface-immobilized RNAP molecules, we show that the clamp in RNAP holoenzyme populates three distinct conformational states and interconvert between these states on the 0.1-1 s time-scale. Similar studies confirm that the RNAP clamp is closed in open complex (RPO) and in initial transcribing complexes (RPITC), including paused initial transcribing complexes, and show that, in these complexes, the clamp does not exhibit dynamic behaviour. We also show that, the stringent-response alarmone ppGpp, which reprograms transcription during amino acid starvation stress, selectively stabilizes the partly-closed-clamp state and prevents clamp opening; these results raise the possibility that ppGpp controls promoter opening by modulating clamp dynamics.
NASA Astrophysics Data System (ADS)
Li, Wei; Ciais, Philippe; Wang, Yilong; Yin, Yi; Peng, Shushi; Zhu, Zaichun; Bastos, Ana; Yue, Chao; Ballantyne, Ashley P.; Broquet, Grégoire; Canadell, Josep G.; Cescatti, Alessandro; Chen, Chi; Cooper, Leila; Friedlingstein, Pierre; Le Quéré, Corinne; Myneni, Ranga B.; Piao, Shilong
2018-01-01
To assess global carbon cycle variability, we decompose the net land carbon sink into the sum of gross primary productivity (GPP), terrestrial ecosystem respiration (TER), and fire emissions and apply a Bayesian framework to constrain these fluxes between 1980 and 2014. The constrained GPP and TER fluxes show an increasing trend of only half of the prior trend simulated by models. From the optimization, we infer that TER increased in parallel with GPP from 1980 to 1990, but then stalled during the cooler periods, in 1990-1994 coincident with the Pinatubo eruption, and during the recent warming hiatus period. After each of these TER stalling periods, TER is found to increase faster than GPP, explaining a relative reduction of the net land sink. These results shed light on decadal variations of GPP and TER and suggest that they exhibit different responses to temperature anomalies over the last 35 years.
Emergent Hydrological Regimes in Amazonia Determine Vegetation Productivity and Structure.
NASA Astrophysics Data System (ADS)
Ahlström, A.; Canadell, J.; Schurgers, G.; Berry, J. A.; Guan, K.; Jackson, R. B.
2016-12-01
The Amazon rain forest has a disproportionate significance for global CO2 storage and biodiversity. Earth system models (ESMs) that estimate future climate and vegetation show little agreement in simulations in Amazonia. Here we show that evapotranspiration (ET), gross primary productivity (GPP) and above ground biomass in both models and empirical data align on an emergent hydrologically determined relationship that describes a functional relationship with annual precipitation (P). The physical relationship describes the potential for plant productivity and has a breakpoint at 2000 mm annual precipitation, where the system transitions between water and radiation limitation of annual ET. While ESM GPP is generally underestimated due to a low-bias in their internally generated P, their response to annual precipitation generally matches empirical data. It is different for biomass: ESMs show some ability in capturing biomass levels in the energy-limited wet hydrological regime above 2000 mm annual precipitation but they do not fully capture the biomass structure tipping point found in empirical data at the hydrological regime breakpoint that coincide with the forest-savanna transition. This discrepancy is likely due to the relatively simple representation of disturbances, primarily fires, and vegetation dynamics found in ESMs, and implies that ESMs likely overestimate the resilience to a potential future drying of the Amazon. Future elevated CO2 may increase plant water use efficiency and shift GPP upwards, but it will not affect the breakpoint between the regimes or the susceptibility of the forest which are both determined by precipitation and its role in determining the hydrological regime. This analysis reconciles and explains the findings of many studies on the Amazon. Our results suggests that future Amazonian biomass is governed by changes in precipitation, vegetation dynamics and disturbances, none of which are well predicted and represented by ESMs
Human Appropriation of Net Primary Production - Can Earth Keep Up?
NASA Technical Reports Server (NTRS)
Imhoff, Marc L.
2006-01-01
The amount of Earth's vegetation or net primary production required to support human activities is powerful measure of aggregate human impacts on the biosphere. Biophysical models applied to consumption statistics were used to estimate the annual amount of net primary production in the form of elemental carbon required for food, fibre, and fuel-wood by the global population. The calculations were then compared to satellite-based estimates of Earth's average net primary production to produce a geographically explicit balance sheet of net primary production "supply" and "demand". Humans consume 20% of Earth's net primary production (11.5 petagrams carbon) annually and this percentage varies regionally from 6% (South America) to over 70% (Europe and Asia), and locally from near 0% (central Australia) to over 30,000% (New York City, USA). The uneven footprint of human consumption and related environmental impacts, indicate the degree to which human populations are vulnerable to climate change and suggest policy options for slowing future growth of NPP demand.
Effects of oligotrophication on primary production in peri-alpine lakes
NASA Astrophysics Data System (ADS)
Finger, David; Wüest, Alfred; Bossard, Peter
2013-08-01
During the second half of the 20th century untreated sewage released from housing and industry into natural waters led to a degradation of many freshwater lakes and reservoirs worldwide. In order to mitigate eutrophication, wastewater treatment plants, including Fe-induced phosphorus precipitation, were implemented throughout the industrialized world, leading to reoligotrophication in many freshwater lakes. To understand and assess the effects of reoligotrophication on primary productivity, we analyzed 28 years of 14C assimilation rates, as well as other biotic and abiotic parameters, such as global radiation, nutrient concentrations and plankton densities in peri-alpine Lake Lucerne, Switzerland. Using a simple productivity-light relationship, we estimated continuous primary production and discussed the relation between productivity and observed limnological parameters. Furthermore, we assessed the uncertainty of our modeling approach based on monthly 14C assimilation measurements using Monte Carlo simulations. Results confirm that monthly sampling of productivity is sufficient for identifying long-term trends in productivity and that conservation management has successfully improved water quality during the past three decades via reducing nutrients and primary production in the lake. However, even though nutrient concentrations have remained constant in recent years, annual primary production varies significantly from year to year. Despite the fact that nutrient concentrations have decreased by more than an order of magnitude, primary production has decreased only slightly. These results suggest that primary production correlates well to nutrients availability but meteorological conditions lead to interannual variability regardless of the trophic status of the lake. Accordingly, in oligotrophic freshwaters meteorological forcing may reduce productivity impacting on the entire food chain of the ecosystem.
Gilmanov, Tagir G.; Johnson, Douglas A.; Saliendra, Nicanor Z.; Akshalov, Kanat; Wylie, Bruce K.
2004-01-01
Compared to other characteristics of CO2 exchange, gross primary productivity (P g ) is most directly related to photosynthetic activity. Until recently, it was considered difficult to obtain measurement-based P g . The objective of our study was to evaluate if P g can be estimated from continuous CO2 flux measurements using nonlinear identification of the nonrectangular hyperbolic model of ecosystem-scale, light-response curves. Estimates of P g and ecosystem respiration (R e ) were obtained using Bowen ratio– energy-balance measurements of CO2 exchange in a true-steppe ecosystem in northern Kazakhstan during four growing seasons (1998–2001). The maximum mean weekly apparent quantum yield (αmax) was 0.0388 mol CO2 mol photons and the maximum mean weekly P g was 28 g CO2/m2/day in July 2000. The highest mean weekly R e max (20 g CO2m2/day) was observed in July of both 1999 and 2000. Nighttime respiration calculated from daily respiration corrected for length of the dark period and temperature (using Q 10 = 2) was closely associated with measured nighttime respiration (R 2 = 0.67 to 0.93). The 4-year average annual gross primary production (GPP) was 1617 g CO2/m2/ year (range = 1308–1957). Ten-day normalized difference vegetation index corrected for the start of the season (NDVIsos) was closely associated with 10-day average P g (R 2 = 0.66 to 0.83), which was higher than R 2 values for regressions of mean 10-day net daytime fluxes on NDVIsos (0.55–0.72). This demonstrates the advantage of usingP g in scaling up flux-tower measurements compared to other characteristics (net daytime flux or net 24-h flux).
De Colibus, Luigi; Wang, Xiangxi; Tijsma, Aloys; Neyts, Johan; Spyrou, John A B; Ren, Jingshan; Grimes, Jonathan M; Puerstinger, Gerhard; Leyssen, Pieter; Fry, Elizabeth E; Rao, Zihe; Stuart, David I
2015-10-01
The replication of enterovirus 71 (EV71) and coxsackievirus A16 (CVA16), which are the major cause of hand, foot and mouth disease (HFMD) in children, can be inhibited by the capsid binder GPP3. Here, we present the crystal structure of CVA16 in complex with GPP3, which clarifies the role of the key residues involved in interactions with the inhibitor. Based on this model, in silico docking was performed to investigate the interactions with the two next-generation capsid binders NLD and ALD, which we show to be potent inhibitors of a panel of enteroviruses with potentially interesting pharmacological properties. A meta-analysis was performed using the available structural information to obtain a deeper insight into those structural features required for capsid binders to interact effectively and also those that confer broad-spectrum anti-enterovirus activity.
Zhang, Tao; Zhang, Yangjian; Xu, Mingjie; Zhu, Juntao; Wimberly, Michael C.; Yu, Guirui; Niu, Shuli; Xi, Yi; Zhang, Xianzhou; Wang, Jingsheng
2015-01-01
To explore grazing effects on carbon fluxes in alpine meadow ecosystems, we used a paired eddy-covariance (EC) system to measure carbon fluxes in adjacent fenced (FM) and grazed (GM) meadows on the Tibetan plateau. Gross primary productivity (GPP) and ecosystem respiration (Re) were greater at GM than FM for the first two years of fencing. In the third year, the productivity at FM increased to a level similar to the GM site. The higher productivity at GM was mainly caused by its higher photosynthetic capacity. Grazing exclusion did not increase carbon sequestration capacity for this alpine grassland system. The higher optimal photosynthetic temperature and the weakened ecosystem response to climatic factors at GM may help to facilitate the adaption of alpine meadow ecosystems to changing climate. PMID:26515954
Amazon Deforestation Fires Increase Plant Productivity through Changes in Diffuse Radiation
NASA Astrophysics Data System (ADS)
Rap, A.; Reddington, C.; Spracklen, D. V.; Mercado, L.; Haywood, J. M.; Bonal, D.; Butt, N.; Phillips, O.
2013-12-01
model to show that this increase in diffuse radiation is responsible for a substantial growth in gross primary productivity (GPP), enhancing Amazon-wide dry-season GPP by 5% with local increases of up to 15%. Most of this GPP response results in an increase in NPP, estimated in the dry season at 10% across the Amazon with local increases as large as 30%. This substantial NPP enhancement spatially matches observed increases in forest biomass storage across the Amazon. We thus suggest that deforestation fires have an important impact on the Amazon carbon budget and attempt to estimate the fraction of the observed forest carbon sink that can be attributed to this mechanism. Change [%] in diffuse radiation due to deforestation
Groundwater productivity potential mapping using evidential belief function.
Park, Inhye; Kim, Yongsung; Lee, Saro
2014-09-01
The evidential belief function (EBF) model was applied and validated for analysis of groundwater-productivity potential (GPP) in Boryeong and Pohang cities, agriculture region in Korea using geographic information systems (GIS). Data about related factors, including topography, lineament, geology, forest, soil, and groundwater data were collected and input into a spatial database. Additionally, in the Boryeong area, specific capacity (SPC) data not lower than 4.55 m3 /d/m were collected, corresponding to 300 m3 /d yield from 72 well locations. In the Pohang area, SPC data of ≥ 6.25 m3 /d/m were collected, corresponding to a yield of 500 m3 /d from 44 well locations. By using the constructed spatial database, 19 factors related to groundwater productivity were extracted. The relationships between the well locations and the factors were identified and quantified by using the EBF model. Four relationships were calculated: belief (Bel), disbelief (Dis), uncertainty (Unc), and plausibility (Pls). The relationships were used as factor ratings in the overlay analysis to create GPP indices and maps. The resulting GPP maps showed 83.41% and 77.53% accuracy in Boryeong and Pohang areas, respectively. The EBF model was found to be more effective in terms of prediction accuracy. © 2014, National Ground Water Association.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Campbell, J. E.; Berry, J. A.; Seibt, U.
Growth in terrestrial gross primary production (GPP) may provide a feedback for climate change, but there is still strong disagreement on the extent to which biogeochemical processes may suppress this GPP growth at the ecosystem to continental scales. The consequent uncertainty in modeling of future carbon storage by the terrestrial biosphere constitutes one of the largest unknowns in global climate projections for the next century. Here we provide a global, measurement-based estimate of historical GPP growth using long-term atmospheric carbonyl sulfide (COS) records derived from ice core, firn, and ambient air samples. We interpret these records using a model thatmore » relates changes in the COS concentration to changes in its sources and sinks, the largest of which is proportional to GPP. The COS history was most consistent with simulations that assume a large historical GPP growth. Carbon-climate models that assume little to no GPP growth predicted trajectories of COS concentration over the anthropogenic era that differ from those observed. Continued COS monitoring may be useful for detecting ongoing changes in GPP while extending the ice core record to glacial cycles could provide further opportunities to evaluate earth system models.« less
Interannual Variation in Phytoplankton Class-Specific Primary Production at a Global Scale
NASA Technical Reports Server (NTRS)
Rousseaux, Cecile Severine; Gregg, Watson W.
2014-01-01
We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. First we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms were the group that contributed the most to the total phytoplankton production (50, the equivalent of 20 PgC y-1. Coccolithophores and chlorophytes each contributed to 20 (7 PgC y-1 of the total primary production and cyanobacteria represented about 10 (4 PgC y(sub-1) of the total primary production. Primary production by diatoms was highest in high latitude (45) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4 (1-2 PgC y-1. We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nio Index, MEI) and regional climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p 0.05) between the MEI and the class-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatomscyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on the class-specific primary production in the Southern Ocean. These results provide a modeling and
Soil Moisture Active Passive Mission L4_C Data Product Assessment (Version 2 Validated Release)
NASA Technical Reports Server (NTRS)
Kimball, John S.; Jones, Lucas A.; Glassy, Joseph; Stavros, E. Natasha; Madani, Nima; Reichle, Rolf H.; Jackson, Thomas; Colliander, Andreas
2016-01-01
The SMAP satellite was successfully launched January 31st 2015, and began acquiring Earth observation data following in-orbit sensor calibration. Global data products derived from the SMAP L-band microwave measurements include Level 1 calibrated and geolocated radiometric brightness temperatures, Level 23 surface soil moisture and freezethaw geophysical retrievals mapped to a fixed Earth grid, and model enhanced Level 4 data products for surface to root zone soil moisture and terrestrial carbon (CO2) fluxes. The post-launch SMAP mission CalVal Phase had two primary objectives for each science product team: 1) calibrate, verify, and improve the performance of the science algorithms, and 2) validate accuracies of the science data products as specified in the L1 science requirements. This report provides analysis and assessment of the SMAP Level 4 Carbon (L4_C) product pertaining to the validated release. The L4_C validated product release effectively replaces an earlier L4_C beta-product release (Kimball et al. 2015). The validated release described in this report incorporates a longer data record and benefits from algorithm and CalVal refinements acquired during the SMAP post-launch CalVal intensive period. The SMAP L4_C algorithms utilize a terrestrial carbon flux model informed by SMAP soil moisture inputs along with optical remote sensing (e.g. MODIS) vegetation indices and other ancillary biophysical data to estimate global daily net ecosystem CO2 exchange (NEE) and component carbon fluxes for vegetation gross primary production (GPP) and ecosystem respiration (Reco). Other L4_C product elements include surface (10 cm depth) soil organic carbon (SOC) stocks and associated environmental constraints to these processes, including soil moisture and landscape freeze/thaw (FT) controls on GPP and respiration (Kimball et al. 2012). The L4_C product encapsulates SMAP carbon cycle science objectives by: 1) providing a direct link between terrestrial carbon fluxes and
Global climate change and terrestrial net primary production
NASA Technical Reports Server (NTRS)
Melillo, Jerry M.; Mcguire, A. D.; Kicklighter, David W.; Moore, Berrien, III; Vorosmarty, Charles J.; Schloss, Annette L.
1993-01-01
A process-based model was used to estimate global patterns of net primary production and soil nitrogen cycling for contemporary climate conditions and current atmospheric CO2 concentration. Over half of the global annual net primary production was estimated to occur in the tropics, with most of the production attributable to tropical evergreen forest. The effects of CO2 doubling and associated climate changes were also explored. The responses in tropical and dry temperate ecosystems were dominated by CO2, but those in northern and moist temperate ecosystems reflected the effects of temperature on nitrogen availability.
NASA Astrophysics Data System (ADS)
Green, J.; Lee, J. E.; Gentine, P.; Berry, J. A.; Konings, A. G.
2015-12-01
hotosynthesis and light use efficiency (LUE) are major factors in the evolution of the continental carbon cycle due to their contribution to gross primary production (GPP). However, while the drivers of photosynthesis and LUE on a plant or canopy scale can often be identified, significant uncertainties exist when modeling these on a global scale. This is due to sparse observations in regions such as the tropics and the lack of a direct global observation dataset. Although others have attempted to address this issue using correlations (Beer, 2010) or calculating GPP from vegetation indices (Running, 2004), in this study we take a new approach. We combine the statistical method of Granger frequency causality and partial Granger frequency causality with remote sensing data products (including sun-induced fluorescence used as a proxy for GPP) to determine the main environmental drivers of GPP across the globe. References:Beer, C., M. Reichstein, E. Tomelleri, P. Ciais, M. Jung, N. Carvalhais, C. Ro¨denbeck, M. Altaf Arain, D. Baldocchi, G. B. Bonan, A. Bondeau, A. Cescatti, G. Lasslop, A. Lindroth, M. Lomas, S. Luyssaert, H. Margolis, K. W. Oleson, O. Roupsard, E. Veenendaal, N. Viovy, C. Williams, I. Woodward, and D. Papale, 2010: Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate. doi: 10.1126/science.1184984. Running, S.W., Nemani, R. R., Heinsch, F. A., Zhao, M., Reeves, M., Hashimoto, H., 2004. A Continuous Satellite Derived Measure of Global Terrestrial Primary Production. BioScience 54(6), 547-560.
NASA Astrophysics Data System (ADS)
González, Humberto E.; Daneri, Giovanni; Iriarte, José L.; Yannicelli, Beatriz; Menschel, Eduardo; Barría, Claudio; Pantoja, Silvio; Lizárraga, Lorena
2009-12-01
The information from 54 drifting sediment traps deployed between 1997 and 2006 along the Humboldt Current System off Chile (from 19.9°S to 42.2°S) was analyzed to contribute to unveiling the recurrent global-ocean issue of the lack of relationship between gross primary production (GPP) and particulate organic carbon (POC) export below 50 m depth. When the proportion of carbon that effectively sinks is relatively low compared to the carbon being fixed through GPP, a significant amount (average of 32%) of the sinking organic matter is composed of diatoms, regardless of GPP rates. Such a fraction seems to be affected by the physiological state of phytoplankton. In contrast, when the fraction of carbon sinking is high relative to GPP, most of sinking organic matter is composed of euphausid faecal strings. Such a situation occurs at relatively low values of GPP and chlorophyll-a. Most of these high sinking rates of pellets and low phytoplankton biomass occur during summer, when physical conditions favour the presence of phytoplankton blooms, and when the GPP/Biomass ratio indicates healthy phytoplankton physiological conditions. All this evidence supports the assessment of the relevance of euphausiids as key species in the Humboldt Current System pointing to (i) the top-down control that euphausiids are capable of exerting over primary producer biomass, and (ii) euphausiids‘ paramount role on total organic carbon flux over the Concepción continental shelf, regarding both POC export to the sediments and possibly the channelling of GPP directly to higher trophic levels.
NASA Astrophysics Data System (ADS)
Donohue, Randall; Yang, Yuting; McVicar, Tim; Roderick, Michael
2016-04-01
A fundamental question in climate and ecosystem science is "how does climate regulate the land surface carbon budget?" To better answer that question, here we develop an analytical model for estimating mean annual terrestrial gross primary productivity (GPP), which is the largest carbon flux over land, based on a rate-limitation framework. Actual GPP (climatological mean from 1982 to 2010) is calculated as a function of the balance between two GPP potentials defined by the climate (i.e., precipitation and solar radiation) and a third parameter that encodes other environmental variables and modifies the GPP-climate relationship. The developed model was tested at three spatial scales using different GPP sources, i.e., (1) observed GPP from 94 flux-sites, (2) modelled GPP (using the model-tree-ensemble approach) at 48654 (0.5 degree) grid-cells and (3) at 32 large catchments across the globe. Results show that the proposed model could account for the spatial GPP patterns, with a root-mean-square error of 0.70, 0.65 and 0.3 g C m-2 d-1 and R2 of 0.79, 0.92 and 0.97 for the flux-site, grid-cell and catchment scales, respectively. This analytical GPP model shares a similar form with the Budyko hydroclimatological model, which opens the possibility of a general analytical framework to analyze the linked carbon-water-energy cycles.
Drake, John E; Tjoelker, Mark G; Aspinwall, Michael J; Reich, Peter B; Barton, Craig V M; Medlyn, Belinda E; Duursma, Remko A
2016-08-01
Given the contrasting short-term temperature dependences of gross primary production (GPP) and autotrophic respiration, the fraction of GPP respired by trees is predicted to increase with warming, providing a positive feedback to climate change. However, physiological acclimation may dampen or eliminate this response. We measured the fluxes of aboveground respiration (Ra ), GPP and their ratio (Ra /GPP) in large, field-grown Eucalyptus tereticornis trees exposed to ambient or warmed air temperatures (+3°C). We report continuous measurements of whole-canopy CO2 exchange, direct temperature response curves of leaf and canopy respiration, leaf and branch wood respiration, and diurnal photosynthetic measurements. Warming reduced photosynthesis, whereas physiological acclimation prevented a coincident increase in Ra . Ambient and warmed trees had a common nonlinear relationship between the fraction of GPP that was respired above ground (Ra /GPP) and the mean daily temperature. Thus, warming significantly increased Ra /GPP by moving plants to higher positions on the shared Ra /GPP vs daily temperature relationship, but this effect was modest and only notable during hot conditions. Despite the physiological acclimation of autotrophic respiration to warming, increases in temperature and the frequency of heat waves may modestly increase tree Ra /GPP, contributing to a positive feedback between climate warming and atmospheric CO2 accumulation. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
Wortmann, Hannah; Dickschat, Jeroen S.; Schrader, Jens
2018-01-01
The structural diversity of terpenoids is limited by the isoprene rule which states that all primary terpene synthase products derive from methyl-branched building blocks with five carbon atoms. With this study we discover a broad spectrum of novel terpenoids with eleven carbon atoms as byproducts of bacterial 2-methylisoborneol or 2-methylenebornane synthases. Both enzymes use 2-methyl-GPP as substrate, which is synthesized from GPP by the action of a methyltransferase. We used E. coli strains that heterologously produce different C11-terpene synthases together with the GPP methyltransferase and the mevalonate pathway enzymes. With this de novo approach, 35 different C11-terpenes could be produced. In addition to eleven known compounds, it was possible to detect 24 novel C11-terpenes which have not yet been described as terpene synthase products. Four of them, 3,4-dimethylcumene, 2-methylborneol and the two diastereomers of 2-methylcitronellol could be identified. Furthermore, we showed that an E. coli strain expressing the GPP-methyltransferase can produce the C16-terpene 6-methylfarnesol which indicates the condensation of 2-methyl-GPP and IPP to 6-methyl-FPP by the E. coli FPP-synthase. Our study demonstrates the broad range of unusual terpenes accessible by expression of GPP-methyltransferases and C11-terpene synthases in E. coli and provides an extended mechanism for C11-terpene synthases. PMID:29672609
Methylmercury bioaccumulation in stream food webs declines with increasing primary production
Walters, David; D.F. Raikow,; C.R. Hammerschmidt,; M.G. Mehling,; A. Kovach,; J.T. Oris,
2015-01-01
Opposing hypotheses posit that increasing primary productivity should result in either greater or lesser contaminant accumulation in stream food webs. We conducted an experiment to evaluate primary productivity effects on MeHg accumulation in stream consumers. We varied light for 16 artificial streams creating a productivity gradient (oxygen production =0.048–0.71 mg O2 L–1 d–1) among streams. Two-level food webs were established consisting of phytoplankton/filter feeding clam, periphyton/grazing snail, and leaves/shredding amphipod (Hyalella azteca). Phytoplankton and periphyton biomass, along with MeHg removal from the water column, increased significantly with productivity, but MeHg concentrations in these primary producers declined. Methylmercury concentrations in clams and snails also declined with productivity, and consumer concentrations were strongly correlated with MeHg concentrations in primary producers. Heterotroph biomass on leaves, MeHg in leaves, and MeHg in Hyalella were unrelated to stream productivity. Our results support the hypothesis that contaminant bioaccumulation declines with stream primary production via the mechanism of bloom dilution (MeHg burden per cell decreases in algal blooms), extending patterns of contaminant accumulation documented in lakes to lotic systems.
Primary production in the Delta: Then and now
Cloern, James E.; Robinson, April; Richey, Amy; Grenier, Letitia; Grossinger, Robin; Boyer, Katharyn E.; Burau, Jon; Canuel, Elizabeth A.; DeGeorge, John F.; Drexler, Judith Z.; Enright, Chris; Howe, Emily R.; Kneib, Ronald; Mueller-Solger, Anke; Naiman, Robert J.; Pinckney, James L.; Safran, Samuel M.; Schoellhamer, David H.; Simenstad, Charles A.
2016-01-01
To evaluate the role of restoration in the recovery of the Delta ecosystem, we need to have clear targets and performance measures that directly assess ecosystem function. Primary production is a crucial ecosystem process, which directly limits the quality and quantity of food available for secondary consumers such as invertebrates and fish. The Delta has a low rate of primary production, but it is unclear whether this was always the case. Recent analyses from the Historical Ecology Team and Delta Landscapes Project provide quantitative comparisons of the areal extent of 14 habitat types in the modern Delta versus the historical Delta (pre-1850). Here we describe an approach for using these metrics of land use change to: (1) produce the first quantitative estimates of how Delta primary production and the relative contributions from five different producer groups have been altered by large-scale drainage and conversion to agriculture; (2) convert these production estimates into a common currency so the contributions of each producer group reflect their food quality and efficiency of transfer to consumers; and (3) use simple models to discover how tidal exchange between marshes and open water influences primary production and its consumption. Application of this approach could inform Delta management in two ways. First, it would provide a quantitative estimate of how large-scale conversion to agriculture has altered the Delta's capacity to produce food for native biota. Second, it would provide restoration practitioners with a new approach—based on ecosystem function—to evaluate the success of restoration projects and gauge the trajectory of ecological recovery in the Delta region.
Modelling size-fractionated primary production in the Atlantic Ocean from remote sensing
NASA Astrophysics Data System (ADS)
Brewin, Robert J. W.; Tilstone, Gavin H.; Jackson, Thomas; Cain, Terry; Miller, Peter I.; Lange, Priscila K.; Misra, Ankita; Airs, Ruth L.
2017-11-01
Marine primary production influences the transfer of carbon dioxide between the ocean and atmosphere, and the availability of energy for the pelagic food web. Both the rate and the fate of organic carbon from primary production are dependent on phytoplankton size. A key aim of the Atlantic Meridional Transect (AMT) programme has been to quantify biological carbon cycling in the Atlantic Ocean and measurements of total primary production have been routinely made on AMT cruises, as well as additional measurements of size-fractionated primary production on some cruises. Measurements of total primary production collected on the AMT have been used to evaluate remote-sensing techniques capable of producing basin-scale estimates of primary production. Though models exist to estimate size-fractionated primary production from satellite data, these have not been well validated in the Atlantic Ocean, and have been parameterised using measurements of phytoplankton pigments rather than direct measurements of phytoplankton size structure. Here, we re-tune a remote-sensing primary production model to estimate production in three size fractions of phytoplankton (<2 μm, 2-10 μm and >10 μm) in the Atlantic Ocean, using measurements of size-fractionated chlorophyll and size-fractionated photosynthesis-irradiance experiments conducted on AMT 22 and 23 using sequential filtration-based methods. The performance of the remote-sensing technique was evaluated using: (i) independent estimates of size-fractionated primary production collected on a number of AMT cruises using 14C on-deck incubation experiments and (ii) Monte Carlo simulations. Considering uncertainty in the satellite inputs and model parameters, we estimate an average model error of between 0.27 and 0.63 for log10-transformed size-fractionated production, with lower errors for the small size class (<2 μm), higher errors for the larger size classes (2-10 μm and >10 μm), and errors generally higher in oligotrophic waters
40 CFR 63.11166 - What General Provisions apply to primary beryllium production facilities?
Code of Federal Regulations, 2010 CFR
2010-07-01
... Primary Nonferrous Metals Area Sources-Zinc, Cadmium, and Beryllium Primary Beryllium Production Facilities § 63.11166 What General Provisions apply to primary beryllium production facilities? (a) You must... primary beryllium production facilities? 63.11166 Section 63.11166 Protection of Environment ENVIRONMENTAL...
MODIS-derived terrestrial primary production [chapter 28
Maosheng Zhao; Steven Running; Faith Ann Heinsch; Ramakrishna Nemani
2011-01-01
Temporal and spatial changes in terrestrial biological productivity have a large impact on humankind because terrestrial ecosystems not only create environments suitable for human habitation, but also provide materials essential for survival, such as food, fiber and fuel. A recent study estimated that consumption of terrestrial net primary production (NPP; a list of...
40 CFR 63.11164 - What General Provisions apply to primary zinc production facilities?
Code of Federal Regulations, 2011 CFR
2011-07-01
... primary zinc production facilities? 63.11164 Section 63.11164 Protection of Environment ENVIRONMENTAL... Primary Nonferrous Metals Area Sources-Zinc, Cadmium, and Beryllium Primary Zinc Production Facilities § 63.11164 What General Provisions apply to primary zinc production facilities? (a) If you own or...
40 CFR 63.11164 - What General Provisions apply to primary zinc production facilities?
Code of Federal Regulations, 2010 CFR
2010-07-01
... primary zinc production facilities? 63.11164 Section 63.11164 Protection of Environment ENVIRONMENTAL... Primary Nonferrous Metals Area Sources-Zinc, Cadmium, and Beryllium Primary Zinc Production Facilities § 63.11164 What General Provisions apply to primary zinc production facilities? (a) If you own or...
NASA Astrophysics Data System (ADS)
Washington-Allen, R. A.; Therrell, M. D.; Emanuel, R. E.
2007-12-01
Herbivory, fire, and climatic events such as El Niño-Southern Oscillation (ENSO) and La Niña have been shown to have proximal and evolutionary effects on the dynamics of Dryland fauna, flora, and soils. However, spatially-explicit historical impacts of these climatic events on Dryland ecosystems is not known. Consequently, this paper has the purpose of presenting the theory and practical application for estimating the historical spatial impacts of these climatic events. We hypothesize that if remotely-sensed vegetation indices (VI) are correlated to historical tree ring data and also to functional ecosystem processes, specifically gross primary productivity (GPP) and net ecosystem production (NEP) as measured by eddy covariance flux towers, then VIs can be used to spatially and temporally distribute GPP and NEP within the species- or community-specific land cover extent over the length of the tree ring record of selected Dryland ecosystems. Secondly, the Shuttle Radar Topography Mission (SRTM) digital terrain model (DTM) data has been used to estimate tree height and in conjuction with plant allometric equations: biomass and standing carbon in various forest ecosystems. Tree height data in relation to tree ring age data and fire history can be used to reconstruct the spatial distribution of savanna demographic age structure, predict standing carbon and thus provide a complementary and independent dataset for comparison to DTMs from Multiangle Imaging Spectroradiometer (MISR), Interferometric Synthetic Aperture Radar (IFSAR), and Moderate Resolution Imaging Spectroradiometer (MODIS) derived GPP spatial maps. We developed a database consisting of a dendrochronology record, SRTM data, globa fre history data, Long term Data Record Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (LTDR AVHRR NDVI, 1981 - 2003), contemporary gridded climate data, National Land Cover Data (NLCD), and short term eddy covariance flux tower data for the
[Review of estimation on oceanic primary productivity by using remote sensing methods.
Xu, Hong Yun; Zhou, Wei Feng; Ji, Shi Jian
2016-09-01
Accuracy estimation of oceanic primary productivity is of great significance in the assessment and management of fisheries resources, marine ecology systems, global change and other fields. The traditional measurement and estimation of oceanic primary productivity has to rely on in situ sample data by vessels. Satellite remote sensing has advantages of providing dynamic and eco-environmental parameters of ocean surface at large scale in real time. Thus, satellite remote sensing has increasingly become an important means for oceanic primary productivity estimation on large spatio-temporal scale. Combining with the development of ocean color sensors, the models to estimate the oceanic primary productivity by satellite remote sensing have been developed that could be mainly summarized as chlorophyll-based, carbon-based and phytoplankton absorption-based approach. The flexibility and complexity of the three kinds of models were presented in the paper. On this basis, the current research status for global estimation of oceanic primary productivity was analyzed and evaluated. In view of these, four research fields needed to be strengthened in further stu-dy: 1) Global oceanic primary productivity estimation should be segmented and studied, 2) to dee-pen the research on absorption coefficient of phytoplankton, 3) to enhance the technology of ocea-nic remote sensing, 4) to improve the in situ measurement of primary productivity.
NASA Astrophysics Data System (ADS)
Asrar, G.; Wolf, J.; Rafique, R.; West, T. O.; Ogle, S. M.
2016-12-01
Rangelands play an important role in providing ecosystem services such as food, forage, and fuels in many parts of the world. The net primary productivity (NPP), a difference between CO2 fixed by plants and CO2 lost to autotrophic respiration, is a good indicator of the productivity of rangeland ecosystems, and their contribution to the cycling of carbon in the Earth system. In this study, we estimated the NPP of global rangelands, the consumption thereof by grazing livestock, and associated uncertainties, to better understand and quantify the contribution of rangelands to land-based carbon storage. We estimated rangeland NPP using mean annual precipitation data from Climate Research Unit (CRU), and a regression model based on global observations (Del Grosso et al., 2008). Spatial distributions of annual livestock consumption of rangeland NPP (Wolf et al., 2015) were combined with gridded annual rangeland NPP for the years 2000 - 2011. The uncertainty analysis of these estimates was conducted using a Monte Carlo approach. The rangeland NPP estimates with associated uncertainties were also compared with the total modeled GPP estimates obtained from vegetation dynamic model simulations. Our results showed that mean above-ground NPP of rangelands is 1017.5 MgC/km2, while mean below-ground NPP is 847.6 MgC/km2. The total rangeland NPP represents a significant portion of the total NPP of the terrestrial ecosystem. The livestock area requirements used to geographically distribute livestock spatially are based on optimal pasturage and are low relative to area requirements on less productive land. Even so, ca. 90% of annual livestock consumption of rangeland NPP were met with no adjustment of livestock distributions. Moreover, the results of this study allowed us to explicitly quantify the temporal and spatial variations of rangeland NPP under different climatic conditions. Uncertainty analysis was helpful in identifying the strength and weakness of the methods used to
Musavi, Talie; Migliavacca, Mirco; Reichstein, Markus; Kattge, Jens; Wirth, Christian; Black, T Andrew; Janssens, Ivan; Knohl, Alexander; Loustau, Denis; Roupsard, Olivier; Varlagin, Andrej; Rambal, Serge; Cescatti, Alessandro; Gianelle, Damiano; Kondo, Hiroaki; Tamrakar, Rijan; Mahecha, Miguel D
2017-01-23
The total uptake of carbon dioxide by ecosystems via photosynthesis (gross primary productivity, GPP) is the largest flux in the global carbon cycle. A key ecosystem functional property determining GPP is the photosynthetic capacity at light saturation (GPP sat ), and its interannual variability (IAV) is propagated to the net land-atmosphere exchange of CO 2 . Given the importance of understanding the IAV in CO 2 fluxes for improving the predictability of the global carbon cycle, we have tested a range of alternative hypotheses to identify potential drivers of the magnitude of IAV in GPP sat in forest ecosystems. Our results show that while the IAV in GPP sat within sites is closely related to air temperature and soil water availability fluctuations, the magnitude of IAV in GPP sat is related to stand age and biodiversity (R 2 = 0.55, P < 0.0001). We find that the IAV of GPP sat is greatly reduced in older and more diverse forests, and is higher in younger forests with few dominant species. Older and more diverse forests seem to dampen the effect of climate variability on the carbon cycle irrespective of forest type. Preserving old forests and their diversity would therefore be beneficial in reducing the effect of climate variability on Earth's forest ecosystems.
The effects of light, primary production, and temperature on bacterial production at Station ALOHA
NASA Astrophysics Data System (ADS)
Viviani, D. A.; Church, M. J.
2016-02-01
In the open oceans, bacterial metabolism is responsible for a large fraction of the movement of reduced carbon through these ecosystems. While broad meta-analyses suggest that factors such as temperature or primary production control rates of bacterial production over large geographic scales, to date little is known about how these factors influence variability in bacterial production in the open sea. Here we present two years of measurements of 3H-leucine incorporation, a proxy for bacterial production, at the open ocean field site of the Hawaii Ocean Time-series, Station ALOHA (22° 45'N, 158° 00'W). By examining 3H-leucine incorporation over monthly, daily, and hourly scales, this work provides insight into processes controlling bacterial growth in this persistently oligotrophic habitat. Rates of 3H-leucine incorporation were consistently 60% greater when measured in the light than in the dark, highlighting the importance of sunlight in fueling bacterial metabolism in this ecosystem. Over diel time scales, rates of 3H-leucine incorporation were quasi-sinusoidal, with rates in the light higher near midday, while rates in the dark were greatest after sunset. Depth-integrated (0 -125 m) rates of 3H-leucine incorporation in both light and dark were more variable ( 5- and 4-fold, respectively) than coincident measurements of primary production ( 2-fold). On average, rates of bacterial production averaged 2 and 4% of primary production (in the dark and light, respectively). At near-monthly time scales, rates of 3H-leucine incorporation in both light and dark were significantly related to temperature. Our results suggest that in the subtropical oligotrophic Pacific, bacterial production appears decoupled from primary production as a result of seasonal-scale variations in temperature and light.
Clinical productivity of primary care nurse practitioners in ambulatory settings.
Xue, Ying; Tuttle, Jane
Nurse practitioners are increasingly being integrated into primary care delivery to help meet the growing demand for primary care. It is therefore important to understand nurse practitioners' productivity in primary care practice. We examined nurse practitioners' clinical productivity in regard to number of patients seen per week, whether they had a patient panel, and patient panel size. We further investigated practice characteristics associated with their clinical productivity. We conducted cross-sectional analysis of the 2012 National Sample Survey of Nurse Practitioners. The sample included full-time primary care nurse practitioners in ambulatory settings. Multivariable survey regression analyses were performed to examine the relationship between practice characteristics and nurse practitioners' clinical productivity. Primary care nurse practitioners in ambulatory settings saw an average of 80 patients per week (95% confidence interval [CI]: 79-82), and 64% of them had their own patient panel. The average patient panel size was 567 (95% CI: 522-612). Nurse practitioners who had their own patient panel spent a similar percent of time on patient care and documentation as those who did not. However, those with a patient panel were more likely to provide a range of clinical services to most patients. Nurse practitioners' clinical productivity was associated with several modifiable practice characteristics such as practice autonomy and billing and payment policies. The estimated number of patients seen in a typical week by nurse practitioners is comparable to that by primary care physicians reported in the literature. However, they had a significantly smaller patient panel. Nurse practitioners' clinical productivity can be further improved. Copyright © 2016 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
He, L.; Frankenberg, C.; Wood, J. D.; Sun, Y.
2017-12-01
Accurate estimate of the photosynthetic uptake of CO2, denoted gross primary productivity (GPP), is important to understand and quantify the carbon cycles at regional to global scales, and has implications in crop and forest management. Solar-induced chlorophyll fluorescence (SIF) retrieved from space was found to be strongly correlated with GPP and is now being used as a potential new technique to estimate photosynthetic rates at large scale. We selected the Missouri Ozark Site as a test bed, a well-characterized Eddy Covariance site in deciduous broadleaf forests, to explore the relationships of vegetation indices (VIs) and SIF with GPP and their response to environmental conditions. We find that both GPP fluxes and OCO-2 SIF decreased in late summer at the Ozark Site, directly related to water stress, evidenced by a progressive decrease in soil moisture and concomitant changer in leaf water potential. However, VIs (both NDVI and EVI) stayed stable during the same period. With a focus on this wet-dry transition period, we analyze driving factors of changes in GPP and SIF, which appear to be linearly related even in this period with little reflectance changes. We also used the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model to compare observations of SIF and GPP against measurement. The primary motivation is not only to quantify the expected correlations between the GPP and SIF but also to validate performance of SCOPE in reproducing such correlations, which have not been tested against independent observations. This study clearly underlines the potential of SIF measurements to study moderate water stress and its impact on photosynthesis.
Pathways between primary production and fisheries yields of large marine ecosystems.
Friedland, Kevin D; Stock, Charles; Drinkwater, Kenneth F; Link, Jason S; Leaf, Robert T; Shank, Burton V; Rose, Julie M; Pilskaln, Cynthia H; Fogarty, Michael J
2012-01-01
The shift in marine resource management from a compartmentalized approach of dealing with resources on a species basis to an approach based on management of spatially defined ecosystems requires an accurate accounting of energy flow. The flow of energy from primary production through the food web will ultimately limit upper trophic-level fishery yields. In this work, we examine the relationship between yield and several metrics including net primary production, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production. We also evaluate the relationship between yield and two additional rate measures that describe the export of energy from the pelagic food web, particle export flux and mesozooplankton productivity. We found primary production is a poor predictor of global fishery yields for a sample of 52 large marine ecosystems. However, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production were positively associated with yields. The latter two measures provide greater mechanistic insight into factors controlling fishery production than chlorophyll concentration alone. Particle export flux and mesozooplankton productivity were also significantly related to yield on a global basis. Collectively, our analyses suggest that factors related to the export of energy from pelagic food webs are critical to defining patterns of fishery yields. Such trophic patterns are associated with temperature and latitude and hence greater yields are associated with colder, high latitude ecosystems.
Pathways between Primary Production and Fisheries Yields of Large Marine Ecosystems
Friedland, Kevin D.; Stock, Charles; Drinkwater, Kenneth F.; Link, Jason S.; Leaf, Robert T.; Shank, Burton V.; Rose, Julie M.; Pilskaln, Cynthia H.; Fogarty, Michael J.
2012-01-01
The shift in marine resource management from a compartmentalized approach of dealing with resources on a species basis to an approach based on management of spatially defined ecosystems requires an accurate accounting of energy flow. The flow of energy from primary production through the food web will ultimately limit upper trophic-level fishery yields. In this work, we examine the relationship between yield and several metrics including net primary production, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production. We also evaluate the relationship between yield and two additional rate measures that describe the export of energy from the pelagic food web, particle export flux and mesozooplankton productivity. We found primary production is a poor predictor of global fishery yields for a sample of 52 large marine ecosystems. However, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production were positively associated with yields. The latter two measures provide greater mechanistic insight into factors controlling fishery production than chlorophyll concentration alone. Particle export flux and mesozooplankton productivity were also significantly related to yield on a global basis. Collectively, our analyses suggest that factors related to the export of energy from pelagic food webs are critical to defining patterns of fishery yields. Such trophic patterns are associated with temperature and latitude and hence greater yields are associated with colder, high latitude ecosystems. PMID:22276100
NASA Astrophysics Data System (ADS)
Weston, Keith; Jickells, Timothy D.; Carson, Damien S.; Clarke, Andrew; Meredith, Michael P.; Brandon, Mark A.; Wallace, Margaret I.; Ussher, Simon J.; Hendry, Katharine R.
2013-05-01
A study was carried out to assess primary production and associated export flux in the coastal waters of the western Antarctic Peninsula at an oceanographic time-series site. New, i.e., exportable, primary production in the upper water-column was estimated in two ways; by nutrient deficit measurements, and by primary production rate measurements using separate 14C-labelled radioisotope and 15N-labelled stable isotope uptake incubations. The resulting average annual exportable primary production estimates at the time-series site from nutrient deficit and primary production rates were 13 and 16 mol C m-2, respectively. Regenerated primary production was measured using 15N-labelled ammonium and urea uptake, and was low throughout the sampling period. The exportable primary production measurements were compared with sediment trap flux measurements from 2 locations; the time-series site and at a site 40 km away in deeper water. Results showed ˜1% of the upper mixed layer exportable primary production was exported to traps at 200 m depth at the time-series site (total water column depth 520 m). The maximum particle flux rate to sediment traps at the deeper offshore site (total water column depth 820 m) was lower than the flux at the coastal time-series site. Flux of particulate organic carbon was similar throughout the spring-summer high flux period for both sites. Remineralisation of particulate organic matter predominantly occurred in the upper water-column (<200 m depth), with minimal remineralisation below 200 m, at both sites. This highly productive region on the Western Antarctic Peninsula is therefore best characterised as 'high recycling, low export'.
NASA Astrophysics Data System (ADS)
Canion, Andy; MacIntyre, Hugh L.; Phipps, Scott
2013-10-01
The inputs of primary productivity models may be highly variable on short timescales (hourly to daily) in turbid estuaries, but modeling of productivity in these environments is often implemented with data collected over longer timescales. Daily, seasonal, and spatial variability in primary productivity model parameters: chlorophyll a concentration (Chla), the downwelling light attenuation coefficient (kd), and photosynthesis-irradiance response parameters (Pmchl, αChl) were characterized in Weeks Bay, a nitrogen-impacted shallow estuary in the northern Gulf of Mexico. Variability in primary productivity model parameters in response to environmental forcing, nutrients, and microalgal taxonomic marker pigments were analysed in monthly and short-term datasets. Microalgal biomass (as Chla) was strongly related to total phosphorus concentration on seasonal scales. Hourly data support wind-driven resuspension as a major source of short-term variability in Chla and light attenuation (kd). The empirical relationship between areal primary productivity and a combined variable of biomass and light attenuation showed that variability in the photosynthesis-irradiance response contributed little to the overall variability in primary productivity, and Chla alone could account for 53-86% of the variability in primary productivity. Efforts to model productivity in similar shallow systems with highly variable microalgal biomass may benefit the most by investing resources in improving spatial and temporal resolution of chlorophyll a measurements before increasing the complexity of models used in productivity modeling.
NASA Astrophysics Data System (ADS)
El Masri, Bassil
2011-12-01
Modeling terrestrial ecosystem functions and structure has been a subject of increasing interest because of the importance of the terrestrial carbon cycle in global carbon budget and climate change. In this study, satellite data were used to estimate gross primary production (GPP), evapotranspiration (ET) for two deciduous forests: Morgan Monroe State forest (MMSF) in Indiana and Harvard forest in Massachusetts. Also, above-ground biomass (AGB) was estimated for the MMSF and the Howland forest (mixed forest) in Maine. Surface reflectance and temperature, vegetation indices, soil moisture, tree height and canopy area derived from the Moderate Resolution Imagining Spectroradiometer (MODIS), the Advanced Microwave Scanning Radiometer (AMRS-E), LIDAR, and aerial imagery respectively, were used for this purpose. These variables along with others derived from remotely sensed data were used as inputs variables to process-based models which estimated GPP and ET and to a regression model which estimated AGB. The process-based models were BIOME-BGC and the Penman-Monteith equation. Measured values for the carbon and water fluxes obtained from the Eddy covariance flux tower were compared to the modeled GPP and ET. The data driven methods produced good estimation of GPP and ET with an average root mean square error (RMSE) of 0.17 molC/m2 and 0.40 mm/day, respectively for the MMSF and the Harvard forest. In addition, allometric data for the MMSF were used to develop the regression model relating AGB with stem volume. The performance of the AGB regression model was compared to site measurements using remotely sensed data for the MMSF and the Howland forest where the model AGB RMSE ranged between 2.92--3.30 Kg C/m2. Sensitivity analysis revealed that improvement in maintenance respiration estimation and remotely sensed maximum photosynthetic activity as well as accurate estimate of canopy resistance will result in improved GPP and ET predictions. Moreover, AGB estimates were
Primary forest products industry and timber use, Kansas, 1980.
James E. Blyth; Leonard K. Gould; W. Brad Smith
1984-01-01
Highlights recent Kansas forest industry trends, production and receipts of saw logs in 1980, and production of other timber products in 1980. Reports on wood and bark residue generated at primary mills and the disposition of this residue.
Primary forest products industry and timber use, Nebraska, 1980.
James E. Blyth; Tom D. Wardle; W. Brad Smith
1984-01-01
Highlights recent Nebraska forest industry trends, production and receipts of saw logs in 1980, and production of other timber products in 1980. Reports on wood and bark residue generated at primary mills and the disposition of this residue.
Yuan, Wenping; Liu, Shuguang; Dong, Wenjie; Liang, Shunlin; Zhao, Shuqing; Chen, Jingming; Xu, Wenfang; Li, Xianglan; Barr, Alan; Andrew Black, T; Yan, Wende; Goulden, Mike L; Kulmala, Liisa; Lindroth, Anders; Margolis, Hank A; Matsuura, Yojiro; Moors, Eddy; van der Molen, Michiel; Ohta, Takeshi; Pilegaard, Kim; Varlagin, Andrej; Vesala, Timo
2014-06-26
The satellite-derived normalized difference vegetation index (NDVI), which is used for estimating gross primary production (GPP), often includes contributions from both mosses and vascular plants in boreal ecosystems. For the same NDVI, moss can generate only about one-third of the GPP that vascular plants can because of its much lower photosynthetic capacity. Here, based on eddy covariance measurements, we show that the difference in photosynthetic capacity between these two plant functional types has never been explicitly included when estimating regional GPP in the boreal region, resulting in a substantial overestimation. The magnitude of this overestimation could have important implications regarding a change from a current carbon sink to a carbon source in the boreal region. Moss abundance, associated with ecosystem disturbances, needs to be mapped and incorporated into GPP estimates in order to adequately assess the role of the boreal region in the global carbon cycle.
Tropical rainforest response to marine sky brightening climate engineering
NASA Astrophysics Data System (ADS)
Muri, Helene; Niemeier, Ulrike; Kristjánsson, Jón Egill
2015-04-01
Tropical forests represent a major atmospheric carbon dioxide sink. Here the gross primary productivity (GPP) response of tropical rainforests to climate engineering via marine sky brightening under a future scenario is investigated in three Earth system models. The model response is diverse, and in two of the three models, the tropical GPP shows a decrease from the marine sky brightening climate engineering. Partial correlation analysis indicates precipitation to be important in one of those models, while precipitation and temperature are limiting factors in the other. One model experiences a reversal of its Amazon dieback under marine sky brightening. There, the strongest partial correlation of GPP is to temperature and incoming solar radiation at the surface. Carbon fertilization provides a higher future tropical rainforest GPP overall, both with and without climate engineering. Salt damage to plants and soils could be an important aspect of marine sky brightening.
Differentiating moss from higher plants is critical in studying the carbon cycle of the boreal biome
Yuan, Wenping; Liu, Shuguang; Dong, Wenjie; Liang, Shunlin; Zhao, Shuqing; Chen, Jingming; Xu, Wenfang; Li, Xianglan; Barr, Alan; Black, T. Andrew; Yan, Wende; Goulden, Michael; Kulmala, Liisa; Lindroth, Anders; Margolis, Hank A.; Matsuura, Yojiro; Moors, Eddy; van der Molen, Michiel; Ohta, Takeshi; Pilegaard, Kim; Varlagin, Andrej; Vesala, Timo
2014-01-01
The satellite-derived normalized difference vegetation index (NDVI), which is used for estimating gross primary production (GPP), often includes contributions from both mosses and vascular plants in boreal ecosystems. For the same NDVI, moss can generate only about one-third of the GPP that vascular plants can because of its much lower photosynthetic capacity. Here, based on eddy covariance measurements, we show that the difference in photosynthetic capacity between these two plant functional types has never been explicitly included when estimating regional GPP in the boreal region, resulting in a substantial overestimation. The magnitude of this overestimation could have important implications regarding a change from a current carbon sink to a carbon source in the boreal region. Moss abundance, associated with ecosystem disturbances, needs to be mapped and incorporated into GPP estimates in order to adequately assess the role of the boreal region in the global carbon cycle.
A review of ocean chlorophyll algorithms and primary production models
NASA Astrophysics Data System (ADS)
Li, Jingwen; Zhou, Song; Lv, Nan
2015-12-01
This paper mainly introduces the five ocean chlorophyll concentration inversion algorithm and 3 main models for computing ocean primary production based on ocean chlorophyll concentration. Through the comparison of five ocean chlorophyll inversion algorithm, sums up the advantages and disadvantages of these algorithm,and briefly analyzes the trend of ocean primary production model.
Biogeochemistry from Gliders at the Hawaii Ocean Times-Series
NASA Astrophysics Data System (ADS)
Nicholson, D. P.; Barone, B.; Karl, D. M.
2016-02-01
At the Hawaii Ocean Time-series (HOT) autonomous, underwater gliders equipped with biogeochemical sensors observe the oceans for months at a time, sampling spatiotemporal scales missed by the ship-based programs. Over the last decade, glider data augmented by a foundation of time-series observations have shed light on biogeochemical dynamics occuring spatially at meso- and submesoscales and temporally on scales from diel to annual. We present insights gained from the synergy between glider observations, time-series measurements and remote sensing in the subtropical North Pacific. We focus on diel variability observed in dissolved oxygen and bio-optics and approaches to autonomously quantify net community production and gross primary production (GPP) as developed during the 2012 Hawaii Ocean Experiment - DYnamics of Light And Nutrients (HOE-DYLAN). Glider-based GPP measurements were extended to explore the relationship between GPP and mesoscale context over multiple years of Seaglider deployments.
Primary forest products industry and timber use, Iowa, 1972.
James E. Blyth; William A. Farris
1975-01-01
Discusses recent Iowa forest industry trends, and production of saw logs, veneer logs, pulpwood, and other roundwood products. Comments on outlook for Iowa forest industry and production and use of roundwood and primary wood-using plant wood and bark residue.
Continuous monitoring reveals multiple controls on ecosystem metabolism in a suburban stream.
Ecosystem metabolism is an important mechanism for nutrient retention in streams, yet few high studies have investigated temporal patterns in gross primary production (GPP) and ecosystem respiration (ER) using high frequency measurements. This is a potentially important oversig...
Interannual Variation in Phytoplankton Class-specific Primary Production at a Global Scale
NASA Technical Reports Server (NTRS)
Rousseaux, Cecile; Gregg, Watson
2014-01-01
Phytoplankton is responsible for over half of the net primary production on earth. The knowledge on the contribution of various phytoplankton groups to the total primary production is still poorly understood. Data from satellite observations suggest that for upwelling regions, photosynthetic rates by microplankton is higher than that of nanoplankton but that when the spatial extent is considered, the production by nanoplankton is comparable or even larger than microplankton. Here, we used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. Globally, diatoms were the group that contributed the most to the total phytoplankton production (approx. 50%) followed by coccolithophores and chlorophytes. Primary production by diatoms was highest in high latitude (>45 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nino Index, MEI) and 'regional' climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.
Energy release properties of amorphous boron and boron-based propellant primary combustion products
NASA Astrophysics Data System (ADS)
Liang, Daolun; Liu, Jianzhong; Xiao, Jinwu; Xi, Jianfei; Wang, Yang; Zhang, Yanwei; Zhou, Junhu
2015-07-01
The microstructure of amorphous boron and the primary combustion products of boron-based fuel-rich propellant (hereafter referred to as primary combustion products) was analyzed by scanning electron microscope. Composition analysis of the primary combustion products was carried out by X-ray diffraction and X-ray photoelectron spectroscopy. The energy release properties of amorphous boron and the primary combustion products were comparatively studied by laser ignition experimental system and thermogravimetry-differential scanning calorimetry. The primary combustion products contain B, C, Mg, Al, B4C, B13C2, BN, B2O3, NH4Cl, H2O, and so on. The energy release properties of primary combustion products are different from amorphous boron, significantly. The full-time spectral intensity of primary combustion products at a wavelength of 580 nm is ~2% lower than that of amorphous boron. The maximum spectral intensity of the former at full wave is ~5% higher than that of the latter. The ignition delay time of primary combustion products is ~150 ms shorter than that of amorphous boron, and the self-sustaining combustion time of the former is ~200 ms longer than that of the latter. The thermal oxidation process of amorphous boron involves water evaporation (weight loss) and boron oxidation (weight gain). The thermal oxidation process of primary combustion products involves two additional steps: NH4Cl decomposition (weight loss) and carbon oxidation (weight loss). CL-20 shows better combustion-supporting effect than KClO4 in both the laser ignition experiments and the thermal oxidation experiments.
Twenty-million-year relationship between mammalian diversity and primary productivity
NASA Astrophysics Data System (ADS)
Fritz, Susanne A.; Eronen, Jussi T.; Schnitzler, Jan; Hof, Christian; Janis, Christine M.; Mulch, Andreas; Böhning-Gaese, Katrin; Graham, Catherine H.
2016-09-01
At global and regional scales, primary productivity strongly correlates with richness patterns of extant animals across space, suggesting that resource availability and climatic conditions drive patterns of diversity. However, the existence and consistency of such diversity-productivity relationships through geological history is unclear. Here we provide a comprehensive quantitative test of the diversity-productivity relationship for terrestrial large mammals through time across broad temporal and spatial scales. We combine >14,000 occurrences for 690 fossil genera through the Neogene (23-1.8 Mya) with regional estimates of primary productivity from fossil plant communities in North America and Europe. We show a significant positive diversity-productivity relationship through the 20-million-year record, providing evidence on unprecedented spatial and temporal scales that this relationship is a general pattern in the ecology and paleo-ecology of our planet. Further, we discover that genus richness today does not match the fossil relationship, suggesting that a combination of human impacts and Pleistocene climate variability has modified the 20-million-year ecological relationship by strongly reducing primary productivity and driving many mammalian species into decline or to extinction.
Estimating carbon and showing impacts of drought using satellite data in regression-tree models
Boyte, Stephen; Wylie, Bruce K.; Howard, Danny; Dahal, Devendra; Gilmanov, Tagir G.
2018-01-01
Integrating spatially explicit biogeophysical and remotely sensed data into regression-tree models enables the spatial extrapolation of training data over large geographic spaces, allowing a better understanding of broad-scale ecosystem processes. The current study presents annual gross primary production (GPP) and annual ecosystem respiration (RE) for 2000–2013 in several short-statured vegetation types using carbon flux data from towers that are located strategically across the conterminous United States (CONUS). We calculate carbon fluxes (annual net ecosystem production [NEP]) for each year in our study period, which includes 2012 when drought and higher-than-normal temperatures influence vegetation productivity in large parts of the study area. We present and analyse carbon flux dynamics in the CONUS to better understand how drought affects GPP, RE, and NEP. Model accuracy metrics show strong correlation coefficients (r) (r ≥ 94%) between training and estimated data for both GPP and RE. Overall, average annual GPP, RE, and NEP are relatively constant throughout the study period except during 2012 when almost 60% less carbon is sequestered than normal. These results allow us to conclude that this modelling method effectively estimates carbon dynamics through time and allows the exploration of impacts of meteorological anomalies and vegetation types on carbon dynamics.
Primary forest products industry and timber use, Minnesota, 1973.
James E. Blyth; Steven Wilhelm; Jerold T. Hahn
1979-01-01
Discusses recent Minnesota forest industry trends; timber removals for industrial roundwood in 1973; production and receipts in 1973 of pulpwood, saw logs, and other industrial roundwood products. Shows trends in pulpwood and veneer log production and compares saw log production in 1960 and 1973. Discusses primary wood-using mill residue and its disposition.
9 CFR 113.51 - Requirements for primary cells used for production of biologics.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Requirements for primary cells used... VECTORS STANDARD REQUIREMENTS Ingredient Requirements § 113.51 Requirements for primary cells used for production of biologics. Primary cells used to prepare biological products shall be derived from normal...
9 CFR 113.51 - Requirements for primary cells used for production of biologics.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Requirements for primary cells used... VECTORS STANDARD REQUIREMENTS Ingredient Requirements § 113.51 Requirements for primary cells used for production of biologics. Primary cells used to prepare biological products shall be derived from normal...
9 CFR 113.51 - Requirements for primary cells used for production of biologics.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 9 Animals and Animal Products 1 2014-01-01 2014-01-01 false Requirements for primary cells used... VECTORS STANDARD REQUIREMENTS Ingredient Requirements § 113.51 Requirements for primary cells used for production of biologics. Primary cells used to prepare biological products shall be derived from normal...
9 CFR 113.51 - Requirements for primary cells used for production of biologics.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Requirements for primary cells used... VECTORS STANDARD REQUIREMENTS Ingredient Requirements § 113.51 Requirements for primary cells used for production of biologics. Primary cells used to prepare biological products shall be derived from normal...
9 CFR 113.51 - Requirements for primary cells used for production of biologics.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Requirements for primary cells used... VECTORS STANDARD REQUIREMENTS Ingredient Requirements § 113.51 Requirements for primary cells used for production of biologics. Primary cells used to prepare biological products shall be derived from normal...
Costa, Cristina S; Pizarro, Ramón A; Antón, Dora N
2009-11-01
A transcriptional fusion (opgG1::MudJ) to the opgGH operon of Salmonella enterica serovar Typhimurium (S. Typhimurium) LT2, isolated by resistance to mecillinam, was used to study the influence of global regulators RpoS, ppGpp, and cAMP/cAMP-receptor protein (CRP) on expression of the opgGH operon and osmoregulated periplasmic glucan (OPG) content. Neither high growth medium osmolarity nor absence of ppGpp or CRP had important effects on opgG1::MudJ expression in exponential cultures. However, under the same conditions, OPG content was strongly decreased by high osmolarity or cAMP/CRP defectiveness, and reduced to a half by lack of ppGpp. In stationary cultures, high osmolarity as well as CRP loss caused significant descents in opgG1::MudJ expression that were compensated by inactivation of RpoS sigma factor. No effect of RpoS inactivation on OPG content was observed. It is concluded that opgGH expression in S. Typhimurium is only slightly affected by high osmolarity, but is inversely modulated by RpoS level. On the other hand, osmolarity and the cAMP/CRP global regulatory system appear to control OPG content, either directly or indirectly, mainly at the post-transcriptional level.
Chlorophyll Fluorescence Is a Better Proxy for Sunlit Leaf Than Total Canopy Photosynthesis
NASA Astrophysics Data System (ADS)
Chen, J. M.; Wang, Z.; Zhang, F.; Mo, G.
2015-12-01
Chlorophyll fluorescence (CF) results from non-photochemical quenching during plant photosynthesis under excessive radiation. We explore the relationship between gross primary productivity (GPP) and CF using a process ecosystem model, which separates a vegetation canopy into sunlit and shaded leaf groups and simulates the total canopy GPP as the sum of sunlit and shaded leaf GPP. Using GOME-2 and GOSAT data acquired in 2010 over the global land surface, we found that measured CF signals gridded in 1 degree resolution are well correlated with simulated total GPP and its sunlit and shaded components, but the correlation coefficients (R) are largest for the sunlit GPP and smallest for shaded GPP. The seasonal R2 values vary from 0.57 to 0.74, 0.58 to 0.71, and 0.48 to 0.56 for sunlit, total and shaded GPP, respectively. The significance levels for these correlations are all greater than p<0.01. Averaged over the globe, the total simulated shaded GPP is 39% of the total GPP. Theoretically, CF from vegetation comes mostly from sunlit leaves. The significant correlation between measured canopy-level CF and the shaded GPP is likely due to the correlation between shaded and sunlit GPP as both increase with leaf area index. Our simulation confirms the validity of using canopy-level CF measurements to assess the total GPP as the first approximation, although these measurements are a consistently better indicator of sunlit GPP than total GPP. In previous studies, the R2 values for the correlation between CF and total GPP were found to range from 0.76 to 0.88, 0.56 to 0.78, and 0.57 to 0.77 for MPI-BGC, MODIS and CASA model results, respectively. These values are similar or larger than those for sunlit GPP simulated in our study, but are considerably larger than those for total GPP in our study because the correlation for total GPP is contaminated by the inclusion of shaded GPP. All these three models use canopy total light use efficiency without considering the differences
Primary forest products industry and timber use, Wisconsin, 1973.
James E. Blyth; Eugene F. Landt; James W. Whipple; Jerold T. Hahn
1976-01-01
Discusses recent Wisconsin forest industry trends; timber removals for industrial roundwood in 1973; production and receipts in 1973 of pulpwood, saw logs, veneer logs, and other industrial roundwood products. Shows trends in pulpwood and veneer log production and compares saw log production in 1967 and 1973. Discusses primary wood-using plant residue and its...
Primary forest products industry and timber use, Michigan, 1972.
James E. Blyth; Allan H. Boelter; Carl W. Danielson
1975-01-01
Discusses recent Michigan forest industry trends; timber removals for industrial roundwood in 1972; production and receipts in 1972 of pulpwood, saw logs, veneer logs ,and other roundwood products. Shows trends in pulpwood and veneer-log production, and compares saw log production in 1969 and 1972. Discusses primary wood-using plant residue and its disposition.
NASA Astrophysics Data System (ADS)
Bunk, Rüdiger; Behrendt, Thomas; Yi, Zhigang; Kesselmeier, Jürgen
2016-04-01
Carbonyl sulfide is discussed to be used as a proxy for gross primary productivity (GPP) of forest ecosystems. However, soils may interfere. Soils play an important role in budgeting global and local carbonyl sulfide (OCS) fluxes, yet the available data on the uptake and emission behavior of soils in conjunction with environmental factors is limited. The work of many authors has shown that the OCS exchange of soils depends on various factors, such as soil type, atmospheric OCS concentrations, temperature or soil water content (Kesselmeier et al., J. Geophys. Res., 104, No. D9, 11577-11584, 1999; Van Diest & Kesselmeier, Biogeosciences, 5, 475-483, 2008; Masyek et al., PNAS, 111, No 25, 9064-9069, doi: 10.1073/pnas.1319132111, 2014; Whelan and Rhew, J. Geophys. Res. Biogeosciences., 120, 54-62, doi: 10.1002/2014JG002661, 2015) and the light dependent and obviously abiotic OCS production as reported by Whelan and Rhew (2015). To get a better constraint on the impact of some environmental factors on the OCS exchange of soils we used a new laser based integrated cavity output spectroscopy instrument (LGR COS/CO Analyzer Model 907-0028, Los Gatos, Mountain View, California, USA) in conjunction with an automated soil chamber system (as described in Behrendt et al, Biogeosciences, 11, 5463-5492, doi: 10.5194/bg-11-5463-2014, 2014). The OCS exchange of various soils under the full range of possible soil humidity and various CO2 mixing ratios was examined. Additionally OCS exchange of chloroform sterilized subsamples was compared to their live counterparts to illuminate the influence of microorganisms. Results were quite heterogeneous between different soils. With few exceptions, all examined soils show dependence between OCS exchange and soil humidity, usually with strongest uptake at a certain humidity range and less uptake or even emission at higher and lower humidity. Differences in CO2 mixing ratio also clearly impacts on OCS exchange, but trends for different soils
Matsuzaki, Shin-Ichiro S; Suzuki, Kenta; Kadoya, Taku; Nakagawa, Megumi; Takamura, Noriko
2018-06-09
Nutrient supply is a key bottom-up control of phytoplankton primary production in lake ecosystems. Top-down control via grazing pressure by zooplankton also constrains primary production, and primary production may simultaneously affect zooplankton. Few studies have addressed these bidirectional interactions. We used convergent cross-mapping (CCM), a numerical test of causal associations, to quantify the presence and direction of the causal relationships among environmental variables (light availability, surface water temperature, NO 3 -N, and PO 4 -P), phytoplankton community composition, primary production, and the abundances of five functional zooplankton groups (large-cladocerans, small-cladocerans, rotifers, calanoids, and cyclopoids) in Lake Kasumigaura, a shallow, hypereutrophic lake in Japan. CCM suggested that primary production was causally influenced by NO 3 -N and phytoplankton community composition; there was no detectable evidence of a causal effect of zooplankton on primary production. Our results also suggest that rotifers and cyclopoids were forced by primary production, and cyclopoids were further influenced by rotifers. However, our CCM suggested that primary production was weakly influenced by rotifers (i.e., bidirectional interaction). These findings may suggest complex linkages between nutrients, primary production, and rotifers and cyclopoids, a pattern that has not been previously detected or has been neglected. We used linear regression analysis to examine the relationships between the zooplankton community and pond smelt (Hypomesus nipponensis), the most abundant planktivore and the most important commercial fish species in Lake Kasumigaura. The relative abundance of pond smelt was significantly and positively correlated with the abundances of rotifers and cyclopoids, which were causally influenced by primary production. This finding suggests that bottom-up linkages between nutrient, primary production, and zooplankton abundance might be a
Primary forest products industry and timber use, Iowa, 1980.
James E. Blyth; John Tibben; W. Brad Smith
1984-01-01
Discusses recent Iowa forest industry trends, timber removals for industrial roundwood in 1980, production and receipts of saw logs in 1980, and production of other industrial roundwood products in 1980. Reports on wood and bark residue generated at primary mills and the disposition of this residue.
Xu, Wenting; Zhou, Guoyi; Bai, Yongfei; Li, Jiaxiang; Tang, Xuli; Liu, Qing; Ma, Wenhong; Xiong, Gaoming; He, Honglin; Guo, Yanpei; Guo, Qiang; Zhu, Jiangling; Han, Wenxuan; Hu, Huifeng; Fang, Jingyun; Xie, Zongqiang
2018-01-01
Plant nitrogen (N) and phosphorus (P) content regulate productivity and carbon (C) sequestration in terrestrial ecosystems. Estimates of the allocation of N and P content in plant tissues and the relationship between nutrient content and photosynthetic capacity are critical to predicting future ecosystem C sequestration under global change. In this study, by investigating the nutrient concentrations of plant leaves, stems, and roots across China’s terrestrial biomes, we document large-scale patterns of community-level concentrations of C, N, and P. We also examine the possible correlation between nutrient content and plant production as indicated by vegetation gross primary productivity (GPP). The nationally averaged community concentrations of C, N, and P were 436.8, 14.14, and 1.11 mg·g−1 for leaves; 448.3, 3.04 and 0.31 mg·g−1 for stems; and 418.2, 4.85, and 0.47 mg·g−1 for roots, respectively. The nationally averaged leaf N and P productivity was 249.5 g C GPP·g-1 N·y−1 and 3,157.9 g C GPP·g–1 P·y−1, respectively. The N and P concentrations in stems and roots were generally more sensitive to the abiotic environment than those in leaves. There were strong power-law relationships between N (or P) content in different tissues for all biomes, which were closely coupled with vegetation GPP. These findings not only provide key parameters to develop empirical models to scale the responses of plants to global change from a single tissue to the whole community but also offer large-scale evidence of biome-dependent regulation of C sequestration by nutrients. PMID:29666316
Agricultural land use alters the seasonality and magnitude of stream metabolism
Streams are active processors of organic carbon; however, spatial and temporal variation in the rates and controls on metabolism are not well quantified in streams draining intensively-farmed landscapes. We present a comprehensive dataset of gross primary production (GPP) and ec...
Using NDVI to estimate carbon fluxes from small rotationally grazed pastures
USDA-ARS?s Scientific Manuscript database
Satellite-based Normalized Difference Vegetation Index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northea...
Holtgrieve, Gordon W; Schindler, Daniel E
2011-02-01
In coastal areas of the North Pacific Ocean, annual returns of spawning salmon provide a substantial influx of nutrients and organic matter to streams and are generally believed to enhance the productivity of recipient ecosystems. Loss of this subsidy from areas with diminished salmon runs has been hypothesized to limit ecosystem productivity in juvenile salmon rearing habitats (lakes and streams), thereby reinforcing population declines. Using five to seven years of data from an Alaskan stream supporting moderate salmon densities, we show that salmon predictably increased stream water nutrient concentrations, which were on average 190% (nitrogen) and 390% (phosphorus) pre-salmon values, and that primary producers incorporated some of these nutrients into tissues. However, benthic algal biomass declined by an order of magnitude despite increased nutrients. We also measured changes in stream ecosystem metabolic properties, including gross primary productivity (GPP) and ecosystem respiration (ER), from three salmon streams by analyzing diel measurements of oxygen concentrations and stable isotopic ratios (delta O-O2) within a Bayesian statistical model of oxygen dynamics. Our results do not support a shift toward higher primary productivity with the return of salmon, as is expected from a nutrient fertilization mechanism. Rather, net ecosystem metabolism switched from approximately net autotrophic (GPP > or = ER) to a strongly net heterotrophic state (GPP < ER) in response to bioturbation of benthic habitats by salmon. Following the seasonal arrival of salmon, GPP declined to <12% of pre-salmon rates, while ER increased by over threefold. Metabolism by live salmon could not account for the observed increase in ER early in the salmon run, suggesting salmon nutrients and disturbance enhanced in situ heterotrophic respiration. Salmon also changed the physical properties of the stream, increasing air-water gas exchange by nearly 10-fold during peak spawning. We suggest
Seasonal variation of carbon dioxide fluxes over irrigated soybean ( Glycine max L.)
NASA Astrophysics Data System (ADS)
Şaylan, Levent; Kimura, Reiji; Munkhtsetseg, Erdenebayar; Kamichika, Makio
2011-08-01
In this study, variations in carbon dioxide (CO2) fluxes resulting from gross primary production (GPP), net ecosystem exchange (NEE), and respiration ( R e) of soybean ( Glycine max L.) were investigated by the Eddy Covariance method during the growing period from June to November 2005 on an irrigated sand field at the Arid Land Research Center, Tottori University in Tottori, Japan. Although climatic conditions were humid and temperate, the soybeans required frequent irrigation because of the low water holding capacity of the sandy soil at the field site. Finally, it has been found that the accumulated NEE, GPP, and R e fluxes of soybean over 126 days amount to -93, 319, and 226 gC m-2, respectively. Furthermore, the average ratio of GPP to R e was 1.4 and the average ratio of NEE to GPP was about -0.29 for the growth period of soybean. Daily maximum NEE of -3.8 gC m-2 occurred when LAI was 1.1.
Twenty-million-year relationship between mammalian diversity and primary productivity
Fritz, Susanne A.; Eronen, Jussi T.; Schnitzler, Jan; Hof, Christian; Janis, Christine M.; Mulch, Andreas; Böhning-Gaese, Katrin; Graham, Catherine H.
2016-01-01
At global and regional scales, primary productivity strongly correlates with richness patterns of extant animals across space, suggesting that resource availability and climatic conditions drive patterns of diversity. However, the existence and consistency of such diversity–productivity relationships through geological history is unclear. Here we provide a comprehensive quantitative test of the diversity–productivity relationship for terrestrial large mammals through time across broad temporal and spatial scales. We combine >14,000 occurrences for 690 fossil genera through the Neogene (23–1.8 Mya) with regional estimates of primary productivity from fossil plant communities in North America and Europe. We show a significant positive diversity–productivity relationship through the 20-million-year record, providing evidence on unprecedented spatial and temporal scales that this relationship is a general pattern in the ecology and paleo-ecology of our planet. Further, we discover that genus richness today does not match the fossil relationship, suggesting that a combination of human impacts and Pleistocene climate variability has modified the 20-million-year ecological relationship by strongly reducing primary productivity and driving many mammalian species into decline or to extinction. PMID:27621451
Development and status of Arkansas' primary forest products industry
Dennis M. May
1990-01-01
The development of Arkansas' primary forest products industry is presented by following the changes in numbers and types of mills operating through time as well as the State's production of roundwood to supply the changing industry.
Analysis of Water Use Efficiency derived from MODIS satellite image in Northeast Asia
NASA Astrophysics Data System (ADS)
Park, J.; Jang, K.; Kang, S.
2014-12-01
Water Use Efficiency (WUE) is defined as ratio of evapotranspriation (ET) to gross primary productivity (GPP). It can detect the changes of ecosystem properties due to the variability of enviromental condition, and provide a chance to understand the linkage between carbon and water processes in terrestrial ecosystem. In a changing climate, the understanding of ecosystem functional responses to climate variability is crucial for evaluating effect. However, continental or sub-continental scale WUE analysis is were rare. In this study, WUE was estimated in the Northeast Asia using satellite data from 2003 to 2010. ET and GPP were estimated using various MODIS products. The estimated ET and GPP showed favorable agreements with flux tower observations. WUE in the study domain showed considerable variations according to the plant functional types and climatic and elevational gradients. The results produced in this study indicate that satellite remote sensing provides a useful tool for monitoring variability of terrestrial ecosystem functions.
NASA Astrophysics Data System (ADS)
He, Liming; Chen, Jing M.; Gonsamo, Alemu; Luo, Xiangzhong; Wang, Rong; Liu, Yang; Liu, Ronggao
2018-05-01
Globally shaded leaves contribute to more than a half of the total increase in gross primary production (GPP; 7.6 Pg C) for 1982-2016. During 1982-2016, the fraction of shaded GPP increases by 1.1% (p < 0.01) in tropical forests and decreases by 1.4% (p < 0.01) and 1.8% (p < 0.01) in evergreen needleleaf and deciduous needleleaf boreal forests, respectively, suggesting an ecological niche of certain canopy structure for ecosystems to achieve maximum GPP. Unlike transpiration from sunlit leaves that has a turning point in the trend in 2003, global transpiration from shaded leaves steadily increased at the rate of 34 km3/year (p < 0.0001) during 1982-2016. Our study therefore suggests that shaded leaves have an increasing role in buffering the adverse impact of climate change and extremes. Further studies are still needed to reduce the uncertainties in reported trends arisen from climate forcing data, leaf area index, and land cover and land change products.
Three years of results from a mooring over a Posidonia Oceanica seagrass meadow (Corsica, France)
NASA Astrophysics Data System (ADS)
Champenois, Willy; Delille, Bruno; Lepoint, Gilles; Beckers, Jean-Marie; Grégoire, Marilaure; Borges Alberto, V.
2010-05-01
We report the first three years of results from a 10m deep mooring over a Posidonia Oceanica seagrass meadow (Corsica, France) where we deployed from August 2006 to November 2009 an array of 3 optodes. The oxygen data are used to compute by mass balance ecosystem metabolic performance rates (gross primary production (GPP), community respiration (CR), net community production (NCP)), allowing a detailed analysis of seasonal and year-to-year variability of GPP, CR and NCP. The comparison of GPP and CR values derived from the O2 mass balance with rates derived from discrete benthic incubations (every 2 months in 2006-2007, every 4 months in 2008-2009) is very satisfactory. An application of such a mooring is to detect changes in the productivity of the Posidonia meadow that can be used as indicators of overall ecosystem "health" or degradation by human activities. Such a mooring can be used as an affordable and simple tool for management and sustainable development of coastal areas in the Mediterranean.
Li, Xing; Xiao, Jingfeng; He, Binbin; Arain, M Altaf; Beringer, Jason; Desai, Ankur R; Emmel, Carmen; Hollinger, David Y; Krasnova, Alisa; Mammarella, Ivan; Noe, Steffen M; Serrano Ortiz, Penélope; Rey-Sanchez, Camilo; Rocha, Adrian V; Varlagin, Andrej
2018-05-07
Solar-induced chlorophyll fluorescence (SIF) has been increasingly used as a proxy for terrestrial gross primary productivity (GPP). Previous work mainly evaluated the relationship between satellite-observed SIF and gridded GPP products both based on coarse spatial resolutions. Finer-resolution SIF (1.3 km × 2.25 km) measured from the Orbiting Carbon Observatory-2 (OCO-2) provides the first opportunity to examine the SIF-GPP relationship at the ecosystem scale using flux tower GPP data. However, it remains unclear how strong the relationship is for each biome and whether a robust, universal relationship exists across a variety of biomes. Here we conducted the first global analysis of the relationship between OCO-2 SIF and tower GPP for a total of 64 flux sites across the globe encompassing eight major biomes. OCO-2 SIF showed strong correlations with tower GPP at both mid-day and daily timescales, with the strongest relationship observed for daily SIF at the 757 nm (R 2 =0.72, p<0.0001). Strong linear relationships between SIF and GPP were consistently found for all biomes (R 2 =0.57-0.79, p<0.0001) except for evergreen broadleaf forests (R 2 =0.16, p<0.05) at the daily timescale. A higher slope was found for C 4 grasslands and croplands than for C 3 ecosystems. The generally consistent slope of the relationship among biomes suggests a nearly universal rather than biome-specific SIF-GPP relationship, and this finding is an important distinction and simplification compared to previous results. OCO-2 SIF generally had a better performance for predicting GPP than satellite-derived vegetation indices and a light use efficiency model. The universal SIF-GPP relationship can potentially lead to more accurate GPP estimates regionally or globally. Our findings revealed the remarkable ability of finer-resolution SIF observations from OCO-2 and other new or future missions (e.g., TROPOMI, FLEX) for estimating terrestrial photosynthesis across a wide variety of biomes and
VandenBerg, Kelsey E; Ahn, Sarah; Visick, Jonathan E
2016-09-01
The l-isoaspartyl protein carboxyl methyltransferase (PCM) repairs protein damage resulting from spontaneous conversion of aspartyl or asparaginyl residues to isoaspartate and increases long-term stationary-phase survival of Escherichia coli under stress. In the course of studies intended to examine PCM function in metabolically inactive cells, we identified pcm as a gene whose mutation influences the formation of ofloxacin-tolerant persisters. Specifically, a Δpcm mutant produced persisters for an extended period in stationary phase, and a ΔglpD mutation drastically increased persisters in a Δpcm background, reaching 23% of viable cells. The high-persister double mutant showed much higher competitive fitness than the pcm mutant in competition with wild type during long-term stationary phase, suggesting a link between persistence and the mitigation of unrepaired protein damage. We hypothesized that reduced metabolism in the high-persister strain might retard protein damage but observed no gross differences in metabolism relative to wild-type or single-mutant strains. However, methylglyoxal, which accumulates in glpD mutants, also increased fitness, suggesting a possible mechanism. High-level persister formation in the Δpcm ΔglpD mutant was dependent on guanosine pentaphosphate [(p)ppGpp] and polyphosphate. In contrast, persister formation in the Δpcm mutant was (p)ppGpp independent and thus may occur by a distinct pathway. We also observed an increase in conformationally unstable proteins in the high-persister strain and discuss this as a possible trigger for persistence as a response to unrepaired protein damage. Protein damage is an important factor in the survival and function of cells and organisms. One specific form of protein damage, the formation of the abnormal amino acid isoaspartate, can be repaired by a nearly universally conserved enzyme, PCM. PCM-directed repair is associated with stress survival and longevity in bacteria, insects, worms, plants
NASA Technical Reports Server (NTRS)
Schwarz, P. A.; Law, B. E.; Williams, M.; Irvine, J.; Kurpius, M.; Moore, D.
2005-01-01
We investigated the relative importance of climatic versus biotic controls on gross primary production (GPP) and water vapor fluxes in seasonally drought-affected ponderosa pine forests. The study was conducted in young (YS), mature (MS), and old stands (OS) over 4 years at the AmeriFlux Metolius sites. Model simulations showed that interannual variation of GPP did not follow the same trends as precipitation, and effects of climatic variation were smallest at the OS (
Zhao, Jianzhi; Bao, Xiaoming; Li, Chen; Shen, Yu; Hou, Jin
2016-05-01
Monoterpenes have wide applications in the food, cosmetics, and medicine industries and have recently received increased attention as advanced biofuels. However, compared with sesquiterpenes, monoterpene production is still lagging in Saccharomyces cerevisiae. In this study, geraniol, a valuable acyclic monoterpene alcohol, was synthesized in S. cerevisiae. We evaluated three geraniol synthases in S. cerevisiae, and the geraniol synthase Valeriana officinalis (tVoGES), which lacked a plastid-targeting peptide, yielded the highest geraniol production. To improve geraniol production, synthesis of the precursor geranyl diphosphate (GPP) was regulated by comparing three specific GPP synthase genes derived from different plants and the endogenous farnesyl diphosphate synthase gene variants ERG20 (G) (ERG20 (K197G) ) and ERG20 (WW) (ERG20 (F96W-N127W) ), and controlling endogenous ERG20 expression, coupled with increasing the expression of the mevalonate pathway by co-overexpressing IDI1, tHMG1, and UPC2-1. The results showed that overexpressing ERG20 (WW) and strengthening the mevalonate pathway significantly improved geraniol production, while expressing heterologous GPP synthase genes or down-regulating endogenous ERG20 expression did not show positive effect. In addition, we constructed an Erg20p(F96W-N127W)-tVoGES fusion protein, and geraniol production reached 66.2 mg/L after optimizing the amino acid linker and the order of the proteins. The best strain yielded 293 mg/L geraniol in a fed-batch cultivation, a sevenfold improvement over the highest titer previously reported in an engineered S. cerevisiae strain. Finally, we showed that the toxicity of geraniol limited its production. The platform developed here can be readily used to synthesize other monoterpenes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kumar, Jitendra; Hoffman, Forrest M.; Hargrove, William W.
This data set contain global gridded surfaces of Gross Primary Productivity (GPP) at 2 arc minute (approximately 4 km) spatial resolution monthly for the period of 2000-2014 derived from FLUXNET2015 (released July 12, 2016) observations using a representativeness based upscaling approach.
Estimating autotrophic respiration in streams using daily metabolism data
Knowing the fraction of gross primary production (GPP) that is immediately respired by autotrophs and their closely associated heterotrophs (ARf) is necessary to understand the trophic base and carbon spiraling in streams. We show a means to estimate ARf from daily metabolism da...
Primary forest products industry and timber use, Michigan, 1977.
James E. Blyth; Jack Zollner; W. Brad Smith
1981-01-01
Discusses recent Michigan forest industry trends, timber removals for industrial roundwood in 1977, and production and receipts of pulpwood, saw logs, and other industrial roundwood products. Reports on associated logging and primary mill residues and the disposition of mill residue.
Microphytobenthos primary production estimated by hyperspectral reflectance
Jesus, Bruno; Barnett, Alexandre; Barillé, Laurent; Lavaud, Johann
2018-01-01
The use of remote sensing techniques allows monitoring of photosynthesis at the ecosystem level and improves our knowledge of plant primary productivity. The main objective of the current study was to develop a remote sensing based method to measure microphytobenthos (MPB) primary production from intertidal mudflats. This was achieved by coupling hyperspectral radiometry (reflectance, ρ and second derivative, δδ) and PAM-fluorometry (non-sequential light curves, NSLC) measurements. The latter allowed the estimation of primary production using a light use efficiency parameter (LUE) and electron transport rates (ETR) whereas ρ allowed to estimate pigment composition and optical absorption cross-section (a*). Five MPB species representative of the main growth forms: epipelic (benthic motile), epipsammic (benthic motile and non motile) and tychoplanktonic (temporarily resuspended in the water column) were submitted to increasing light intensities from dark to 1950 μmol photons.m-2.s-1. Different fluorescence patterns were observed for the three growth-forms and were linked to their xanthophyll cycle (de-epoxydation state). After spectral reflectance measurements, a* was retrieved using a radiative transfer model and several radiometric indices were tested for their capacity to predict LUE and ETR measured by PAM-fluorometry. Only one radiometric index was not species or growth-form specific, i.e. δδ496/508. This index was named MPBLUE and could be used to predict LUE and ETR. The applicability of this index was tested with simulated bands of a wide variety of hyperspectral sensors at spectral resolutions between 3 and 15 nm of Full Width at Half Maximum (FWHM). PMID:29758047
Bacterial and primary production in the Greenland Sea
NASA Astrophysics Data System (ADS)
Børsheim, Knut Yngve
2017-12-01
Bacterial production rates were measured in water profiles collected in the Greenland Sea and adjacent areas. Hydrography and nutrients throughout the water column were measured along 75°N from 12°W to 10°E at 20 km distance intervals. Net primary production rates from satellite sensed data were compared with literature values from 14C incubations and used for regional and seasonal comparisons. Maximum bacterial production rates were associated with the region close to the edge of the East Greenland current, and the rates decreased gradually towards the center of the Greenland Sea central gyre. Integrated over the upper 20 m the maximum bacterial production rate was 17.9 mmol C m- 2 day- 1, and east of the center of the gyre the average integrated rate was 4.6 mmol C m- 2 day- 1. It is hypothesized that high bacterial production rates in the western Greenland Sea were sustained by organic material carried from the Arctic Ocean by the East Greenland Current. The depth profiles of nitrate and phosphate were very similar both sides of the Arctic front, with 2% higher values between 500 m and 2000 m in the Arctic domain, and a N/P ratio of 13.6. The N/Si ratio varied by depth and region, with increasing silicate depletion from 1500 m depth to the surface. The rate of depletion from 1500 m depth to surface in the Atlantic domain was twice as high as in the Arctic domain. Net primary production rates in the area between the edge of the East Greenland current and the center of the Greenland Sea gyre was 96 mmol C m- 2 day- 1 at the time of the expedition in 2006, and 78 mmol C m- 2 day- 1 east of the center including the Atlantic domain. Annual net primary production estimated from satellite data in the Greenland Sea increased substantially in the period between 2003 and 2016, and the rate of increase was lowest close to the East Greenland Current.
NASA Technical Reports Server (NTRS)
Ganguly, Sangram
2015-01-01
Plant phenology and maximum photosynthetic state determine spatiotemporal variability of gross primary productivity (GPP) of vegetation. Recent warming induced impacts accelerate shifts of phenology and physiological status over Northern vegetated land. Thus, understanding and quantifying these changes are very important. Here, we investigate 1) how vegetation phenology and physiological status (maximum photosynthesis) are evolved over last three decades and 2) how such components (phenology and physiological status) contribute on inter-annual variation of the GPP during the last three decades. We utilized both long-term remotely sensed (GIMMS (Global Inventory Modeling and Mapping Studies), NDVI3g (Normalized Difference Vegetation Index 3rd generation) and MODIS (Moderate Resolution Imaging Spectroradiometer)) to extract larger scale phenology metrics (growing season start, end and duration); and productivity (i.e., growing season integrated vegetation index, GSIVI) to answer these questions. For evaluation purpose, we also introduced field-measured phenology and productivity datasets (e.g., FLUXNET) and possible remotely-sensed and modeled metrics at continental and regional scales. From this investigation, we found that onset of the growing season has advanced by 1.61 days per decade and the growing season end has delayed by 0.67 days per decade over the circumpolar region. This asymmetric extension of growing season results in a longer growing-season trend (2.96 days per decade) and widespread increasing vegetation-productivity trend (2.96 GSIVI per decade) over Northern land. However, the regionally-diverged phenology shift and maximum photosynthetic state contribute differently characterized productivity, inter-annual variability and trend. We quantified that about 50 percent, 13 percent and 6.5 percent of Northern land's inter-annual variability are dominantly controlled by the onset of the growing season, the end of the growing season and the maximum
Primary production of the cryptoendolithic microbiota from the Antarctic Desert
NASA Technical Reports Server (NTRS)
Vestal, J. R.; Friedmann, E. I. (Principal Investigator)
1988-01-01
Primary production in the Antarctic cryptoendolithic microbiota can be determined from biomass and photosynthetic 14CO2 incorporation measurements. Even though good nanoclimate data are available, it is difficult to determine the amount of time when abiotic conditions permit metabolism. Making appropriate assumptions concerning the metabolism of the cryptoendolithic microbiota during periods of warmth, light and moisture, the primary production of the biota was calculated to be on the order of 0.108 to 4.41 mgC/m2/yr, with a carbon turnover time from 576 to 23,520 years. These production values are the lowest found on planet Earth.
On Tour... Primary Hardwood Processing, Products and Recycling Unit
Philip A. Araman; Daniel L. Schmoldt
1995-01-01
Housed within the Department of Wood Science and Forest Products at Virginia Polytechnic Institute is a three-person USDA Forest Service research work unit (with one vacancy) devoted to hardwood processing and recycling research. Phil Araman is the project leader of this truly unique and productive unit, titled ãPrimary Hardwood Processing, Products and Recycling.ä The...
Primary forest products industry and timber use, Indiana, 1980.
James E. Blyth; Donald H. McGuire; W. Brad Smith
1982-01-01
Discusses recent Indiana forest industry trends; timber removals for industrial roundwood in 1980; and production and receipts of saw logs, pulpwood, veneer logs, and other industrial roundwood products. Reports on associated primary mill wood and bark residue and the disposition of mill residue.
Evaluation of Organic Proxies for Quantifying Past Primary Productivity
NASA Astrophysics Data System (ADS)
Raja, M.; Rosell-Melé, A.; Galbraith, E.
2017-12-01
Ocean primary productivity is a key element of the marine carbon cycle. However, its quantitative reconstruction in the past relies on the use of biogeochemical models as the available proxy approaches are qualitative at best. Here, we present an approach that evaluates the use of phytoplanktonic biomarkers (i.e. chlorins and alkenones) as quantitative proxies to reconstruct past changes in marine productivity. We compare biomarkers contents in a global suite of core-top sediments to sea-surface chlorophyll-a abundance estimated by satellites over the last 20 years, and the results are compared to total organic carbon (TOC). We also assess satellite data and detect satellite limitations and biases due to the complexity of optical properties and the actual defined algorithms. Our findings show that sedimentary chlorins can be used to track total sea-surface chlorophyll-a abundance as an indicator for past primary productivity. However, degradation processes restrict the application of this proxy to concentrations below a threshold value (1µg/g). Below this threshold, chlorins are a useful tool to identify reducing conditions when used as part of a multiproxy approach to assess redox sedimentary conditions (e.g. using Re, U). This is based on the link between anoxic/disoxic conditions and the flux of organic matter from the sea-surface to the sediments. We also show that TOC is less accurate than chlorins for estimating sea-surface chlorophyll-a due to the contribution of terrigenous organic matter, and the different degradation pathways of all organic compounds that TOC includes. Alkenones concentration also relates to primary productivity, but they are constrained by different processes in different regions. In conclusion, as lons as specific constraints are taken into account, our study evaluates the use of chlorins and alkenones as quantitative proxies of past primary productivity, with more accuracy than by using TOC.
Factors affecting the estimate of primary production from space
NASA Technical Reports Server (NTRS)
Balch, W. M.; Byrne, C. F.
1994-01-01
Remote sensing of primary production in the euphotic zone has been based mostly on visible-band and water-leaving radiance measured with the coastal zone color scanner. There are some robust, simple relationships for calculating integral production based on surface measurements, but they also require knowledge for photoadaptive parameters such as maximum photosynthesis which currently cannot be obtained from spave. A 17,000-station data set is used to show that space-based estimates of maximum photosynthesis could improve predictions of psi, the water column light utiliztion index, which is an important term in many primary productivity models. Temperature is also examined as a factor for predicting hydrographic structure and primary production. A simple model is used to relate temperature and maximum photosynthesis; the model incorporates (1) the positive relationship between maximum photosynthesis and temperature and (2) the strongly negative relationship between temperature and nitrate in the ocean (which directly affects maximum growth rates via nitrogen limitation). Since these two factors relate to carbon and nitrogen, 'balanced carbon/nitrogen assimilation' was calculated using the Redfield ratio, It is expected that the relationship between maximum balanced carbon assimilation versus temperature is concave-down, with the peak dependent on nitrate uptake kinetics, temperature-nitrate relationships,a nd the carbon chlorophyll ration. These predictions were compared with the sea truth data. The minimum turnover time for nitrate was also calculated using this approach. Lastly, sea surface temperature gradients were used to predict the slope of isotherms (a proxy for the slope of isopycnals in many waters). Sea truth data show that at size scales of several hundred kilometers, surface temperature gradients can provide information on the slope of isotherms in the top 200 m of the water column. This is directly relevant to the supply of nutrients into the surface
NASA Astrophysics Data System (ADS)
Sandoval-Soto, L.; Stanimirov, M.; von Hobe, M.; Schmitt, V.; Valdes, J.; Wild, A.; Kesselmeier, J.
2005-06-01
COS uptake by trees, as observed under dark/light changes and under application of the plant hormone abscisic acid, exhibited a strong correlation with the CO2 assimilation rate and the stomatal conductance. As the uptake of COS occurred exclusively through the stomata we compared experimentally derived and re-evaluated deposition velocities (Vd; related to stomatal conductance) for COS and CO2. We show that Vd of COS is generally significantly larger than that of CO2. We therefore introduced this attribute into a new global estimate of COS fluxes into vegetation. The new global estimate of the COS uptake based on available net primary productivity data (NPP) ranges between 0.69-1.40 Tga-1. However, as a COS molecule is irreversibly split in contrast to CO2 which is released again by respiration processes, we took into account the Gross Primary Productivity (GPP) representing the true CO2 leaf flux the COS uptake has to be related to. Such a GPP based deposition estimate ranged between 1.4--2.8 Tga-1 (0.73-1.50 TgSa-1). We believe that in order to obtain accurate global COS sink estimates such a GPP-based estimate corrected by the different deposition velocities of COS and CO2 must be taken into account.
Mass extinctions: Ecological selectivity and primary production
NASA Astrophysics Data System (ADS)
Rhodes, Melissa Clark; Thayer, Charles W.
1991-09-01
If mass extinctions were caused by reduced primary productivity, then extinctions should be concentrated among animals with starvation-susceptible feeding modes, active lifestyles, and high-energy budgets. The stratigraphic ranges (by stage) of 424 genera of bivalves and 309 genera of articulate brachiopods suggest that there was an unusual reduction of primary productivity at the Cretaceous/Tertiary (K/T) boundary extinction. For bivalves at the K/T, there were (1) selective extinction of suspension feeders and other susceptible trophic categories relative to deposit feeders and other resistant categories, and (2) among suspension feed-ers, selective extinction of bivalves with active locomotion. During the Permian-Triassic (P/Tr) extinction and Jurassic background time, extinction rates among suspension feeders were greater for articulate brachiopods than for bivalves. But during the K/T event, extinction rates of articulates and suspension-feeding bivalves equalized, possibly because the low-energy budgets of articulates gave them an advantage when food was scarce.
Primary forest products industry and timber use, Missouri, 1980.
James E. Blyth; Shelby Jones; W. Brad Smith
1983-01-01
Discusses recent Missouri forest industry trends; timber removals for industrial roundwood in 1980; and production and receipts of saw logs, pulpwood, cooperage logs, charcoal wood, and other industrial roundwood products. Reports on associated primary mill wood and bark residue and the disposition of mill residue.
Watershed Land Use and Seasonal Variation Constrain the ...
While watershed and local scale controls on stream metabolism have been independently investigated, little is known about how controls exerted at these different scales interact to determine stream metabolic rates, or how these interactions vary across seasons. To address this knowledge gap, we measured ecosystem metabolism in four urban and four reference streams in northern Kentucky, USA, with paired closed and open riparian canopies, during each of the four seasons of the year. Gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) were all best predicted by models with season as a main effect, but interactions between season, canopy and watershed varied for each response. Urban streams exhibited higher GPP during most seasons, likely due to elevated nutrient loads. Open canopy reaches in both urban and forested streams supported higher rates of GPP than the closed canopy reaches during the summer and fall when the overhead vegetation shaded the closed reaches. Surprisingly, the effect of canopy cover on GPP was similar among urban and forested streams. The combination of watershed and local-scale controls resulted in urban streams that alternated between net heterotrophy (NEP 0) between seasons with and without dense canopy cover. This finding has management relevance because net production can lead to accumulation of algal biomass and associated issues like dissolved oxygen sags at night. Our study reinforces
Malhi, Yadvinder; Girardin, Cécile A J; Goldsmith, Gregory R; Doughty, Christopher E; Salinas, Norma; Metcalfe, Daniel B; Huaraca Huasco, Walter; Silva-Espejo, Javier E; Del Aguilla-Pasquell, Jhon; Farfán Amézquita, Filio; Aragão, Luiz E O C; Guerrieri, Rossella; Ishida, Françoise Yoko; Bahar, Nur H A; Farfan-Rios, William; Phillips, Oliver L; Meir, Patrick; Silman, Miles
2017-05-01
Why do forest productivity and biomass decline with elevation? To address this question, research to date generally has focused on correlative approaches describing changes in woody growth and biomass with elevation. We present a novel, mechanistic approach to this question by quantifying the autotrophic carbon budget in 16 forest plots along a 3300 m elevation transect in Peru. Low growth rates at high elevations appear primarily driven by low gross primary productivity (GPP), with little shift in either carbon use efficiency (CUE) or allocation of net primary productivity (NPP) between wood, fine roots and canopy. The lack of trend in CUE implies that the proportion of photosynthate allocated to autotrophic respiration is not sensitive to temperature. Rather than a gradual linear decline in productivity, there is some limited but nonconclusive evidence of a sharp transition in NPP between submontane and montane forests, which may be caused by cloud immersion effects within the cloud forest zone. Leaf-level photosynthetic parameters do not decline with elevation, implying that nutrient limitation does not restrict photosynthesis at high elevations. Our data demonstrate the potential of whole carbon budget perspectives to provide a deeper understanding of controls on ecosystem functioning and carbon cycling. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
Photoperiodic controls on ecosystem-level photosynthetic capacity
NASA Astrophysics Data System (ADS)
Stoy, P. C.; Trowbridge, A. M.; Bauerle, W.
2012-12-01
Most models of photosynthesis at the leaf or canopy level assume that temperature is the dominant control on the variability of photosynthetic parameters. Recent studies, however, have found that photoperiod is a better descriptor of the seasonal variability of photosynthetic function at the leaf and plant scale, and that spectral indices of leaf functionality are poor descriptors of this seasonality. We explored the variability of photosynthesic parameters at the ecosystem scale using over 100 site-years of air temperature and gross primary productivity (GPP) data from non-tropical forested sites in the Free/Fair Use LaThuille FLUXNET database (www.fluxdata.org), excluding sites that were classified as dry and/or with savanna vegetation, where we expected GPP to be driven by moisture availability. Both GPP and GPP normalized by daily photosynthetic photon flux density (GPPn) were considered, and photoperiod was calculated from eddy covariance tower coordinates. We performed a Granger causality analysis, a method based on the understanding that causes precede effects, on both the GPP and GPPn. Photoperiod Granger-caused GPP (GPPn) in 95% (87%) of all site-years. While temperature Granger-caused GPP in a mere 23% of site years, it Granger-caused GPPn 73% of the time. Both temperature values are significantly less than the percent of cases in which day length Granger-caused GPP (p<0.05, Student's t-test). An inverse analysis was performed for completeness, and it was found that GPP Granger-caused photoperiod (temperature) in 39% (78%) of all site years. Results demonstrate that incorporating simple photoperiod controls may be a logical step in improving ecosystem and global model output.
QUANTIFYING UNCERTAINTY IN NET PRIMARY PRODUCTION MEASUREMENTS
Net primary production (NPP, e.g., g m-2 yr-1), a key ecosystem attribute, is estimated from a combination of other variables, e.g. standing crop biomass at several points in time, each of which is subject to errors in their measurement. These errors propagate as the variables a...
Järveoja, Järvi; Nilsson, Mats B; Gažovič, Michal; Crill, Patrick M; Peichl, Matthias
2018-04-30
The net ecosystem CO 2 exchange (NEE) drives the carbon (C) sink-source strength of northern peatlands. Since NEE represents a balance between various production and respiration fluxes, accurate predictions of its response to global changes require an in depth understanding of these underlying processes. Currently, however, detailed information of the temporal dynamics as well as the separate biotic and abiotic controls of the NEE component fluxes is lacking in peatland ecosystems. In this study, we address this knowledge gap by using an automated chamber system established across natural and trenching-/vegetation removal plots to partition NEE into its production (i.e. gross and net primary production; GPP and NPP) and respiration (i.e. ecosystem, heterotrophic and autotrophic respiration; ER, Rh and Ra) fluxes in a boreal peatland in northern Sweden. Our results showed that daily NEE patterns were driven by GPP while variations in ER were governed by Ra rather than Rh. Moreover, we observed pronounced seasonal shifts in the Ra/Rh and above-/belowground NPP ratios throughout the main phenological phases. Generalized linear model analysis revealed that the greenness index derived from digital images (as a proxy for plant phenology) was the strongest control of NEE, GPP and NPP while explaining considerable fractions also in the variations of ER and Ra. In addition, our data exposed greater temperature sensitivity of NPP compared to Rh resulting in enhanced C sequestration with increasing temperature. Overall, our study suggests that the temporal patterns in NEE and its component fluxes are tightly coupled to vegetation dynamics in boreal peatlands and thus challenges previous studies that commonly identify abiotic factors as key drivers. These findings further emphasize the need for integrating detailed information on plant phenology into process-based models to improve predictions of global change impacts on the peatland C cycle. This article is protected by
NASA Astrophysics Data System (ADS)
Zhang, Y.; Guanter, L.; Van der Tol, C.; Joiner, J.; Berry, J. A.
2015-12-01
Global sun-induced chlorophyll fluorescence (SIF) retrievals are currently available from several satellites. SIF is intrinsically linked to photosynthesis, so the new data sets allow to link remotely-sensed vegetation parameters and the actual photosynthetic activity of plants. In this study, we used space measurements of SIF together with the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model in order to simulate regional photosynthetic uptake of croplands in the US corn belt. SCOPE couples fluorescence and photosynthesis at leaf and canopy levels. To do this, we first retrieved a key parameter of photosynthesis model, the maximum rate of carboxylation (Vcmax), from field measurements of CO2 and water flux during 2007-2012 at some crop eddy covariance flux sites in the Midwestern US. Then we empirically calibrated Vcmax with apparent fluorescence yield which is SIF divided by PAR. SIF retrievals are from the European GOME-2 instrument onboard the MetOp-A platform. The resulting apparent fluorescence yield shows a stronger relationship with Vcmax during the growing season than widely-used vegetation index, EVI and NDVI. New seasonal and regional Vcmax maps were derived based on the calibration model for the cropland of the corn belt. The uncertainties of Vcmax were also estimated through Gaussian error propagation. With the newly derived Vcmax maps, we modeled regional cropland GPP during the growing season for the Midwestern USA, with meteorological data from MERRA reanalysis data and LAI from MODIS product (MCD15A2). The results show the improvement in the seasonal and spatial patterns of cropland productivity in comparisons with both flux tower and agricultural inventory data.
Primary production in the tropical continental shelf seas bordering northern Australia
NASA Astrophysics Data System (ADS)
Furnas, Miles J.; Carpenter, Edward J.
2016-10-01
Pelagic primary production (14C uptake) was measured 81 times between 1990 and 2013 at sites spanning the broad, shallow Northern Australian Shelf (NAS; 120-145°E) which borders the Australian continent. The mean of all areal production measurements was 1048±109 mg C m-2 d-1 (mean±95% CI). Estimates of areal primary production were correlated with integral upper-euphotic zone chlorophyll stocks (above the 50% and 20% light penetration depths) accessible to ocean color remote sensing and total water column chlorophyll standing crop, but not surface (0-2 m) chlorophyll concentrations. While the NAS is subject to a well characterized monsoonal climate regime (austral summer-NW monsoon -wet: austral winter- SE monsoon -dry), most seasonal differences in means of regional-scale chlorophyll standing crop (11-33 mg Chl m-2 for 12 of 15 season-region combinations) and areal primary production (700-1850 mg C m- day-1 for 12 of 15 season-region combinations) fell within a 3-fold range. Apart from the shallow waters of the Torres Strait and northern Great Barrier Reef, picoplankton (<2 μm size fraction) dominated chlorophyll standing crop and primary production with regional means of picoplankton contributions ranging from 45 to >80%. While the range of our post-1990 areal production estimates overlaps the range of production estimates made in NAS waters during 1960-62, the mean of post-1990 estimates is over 2-fold greater. We regard the difference to be due to improvements in production measurement techniques, particularly regarding the reduction of potential metal toxicity and incubations in more realistic light regimes.
Defoliation effects on pasture photosynthesis and respiration
USDA-ARS?s Scientific Manuscript database
Ecosystem C gain or loss from managed grasslands can depend on the type and intensity of management practices that are employed. However, limited information is available at the field scale on how the type of defoliation, specifically grazing vs. cutting, affects gross primary productivity (GPP) an...
Basin-scale estimates of oceanic primary production by remote sensing - The North Atlantic
NASA Technical Reports Server (NTRS)
Platt, Trevor; Caverhill, Carla; Sathyendranath, Shubha
1991-01-01
The monthly averaged CZCS data for 1979 are used to estimate annual primary production at ocean basin scales in the North Atlantic. The principal supplementary data used were 873 vertical profiles of chlorophyll and 248 sets of parameters derived from photosynthesis-light experiments. Four different procedures were tested for calculation of primary production. The spectral model with nonuniform biomass was considered as the benchmark for comparison against the other three models. The less complete models gave results that differed by as much as 50 percent from the benchmark. Vertically uniform models tended to underestimate primary production by about 20 percent compared to the nonuniform models. At horizontal scale, the differences between spectral and nonspectral models were negligible. The linear correlation between biomass and estimated production was poor outside the tropics, suggesting caution against the indiscriminate use of biomass as a proxy variable for primary production.
Role of eddy pumping in enhancing primary production in the ocean
NASA Technical Reports Server (NTRS)
Falkowski, Paul G.; Kolber, Zbigniew; Ziemann, David; Bienfang, Paul K.
1991-01-01
Eddy pumping is considered to explain the disparity between geochemical estimates and biological measurements of exported production. Episodic nutrient injections from the ocean into the photic zone can be generated by eddy pumping, which biological measurements cannot sample accurately. The enhancement of production is studied with respect to a cyclonic eddy in the subtropical Pacific. A pump-and-probe fluorimeter generates continuous vertical profiles of primary productivity from which the contributions of photochemical and nonphotochemical processes to fluorescence are derived. A significant correlation is observed between the fluorescence measurements and radiocarbon measurements. The results indicate that eddy pumping has an important effect on phytoplankton production and that this production is near the maximum relative specific growth rates. Based on the production enhancement observed in this case, eddy pumping increases total primary production by only 20 percent and does not account for all enhancement.
Observations of Ocean Primary Productivity Using MODIS
NASA Technical Reports Server (NTRS)
Esaias, Wayne E.; Abbott, Mark R.; Koblinsky, Chester J. (Technical Monitor)
2001-01-01
Measuring the magnitude and variability of oceanic net primary productivity (NPP) represents a key advancement toward our understanding of the dynamics of marine ecosystems and the role of the ocean in the global carbon cycle. MODIS observations make two new contributions in addition to continuing the bio-optical time series begun with Orbview-2's SeaWiFS sensor. First, MODIS provides weekly estimates of global ocean net primary productivity on weekly and annual time periods, and annual empirical estimates of carbon export production. Second, MODIS provides additional insight into the spatial and temporal variations in photosynthetic efficiency through the direct measurements of solar-stimulated chlorophyll fluorescence. The two different weekly productivity indexes (first developed by Behrenfeld & Falkowski and by Yoder, Ryan and Howard) are used to derive daily productivity as a function of chlorophyll biomass, incident daily surface irradiance, temperature, euphotic depth, and mixed layer depth. Comparisons between these two estimates using both SeaWiFS and MODIS data show significant model differences in spatial distribution after allowance for the different integration depths. Both estimates are strongly dependence on the accuracy of the chlorophyll determination. In addition, an empirical approach is taken on annual scales to estimate global NPP and export production. Estimates of solar stimulated fluorescence efficiency from chlorophyll have been shown to be inversely related to photosynthetic efficiency by Abbott and co-workers. MODIS provides the first global estimates of oceanic chlorophyll fluorescence, providing an important proof of concept. MODIS observations are revealing spatial patterns of fluorescence efficiency which show expected variations with phytoplankton photo-physiological parameters as measured during in-situ surveys. This has opened the way for research into utilizing this information to improve our understanding of oceanic NPP
Comparison of Community Metabolism in two Streams With Different Landuse
NASA Astrophysics Data System (ADS)
Jin, H.; Kipphut, G. W.
2005-05-01
Gross primary production (GPP) and community respiration (CR) were measured in a forested (Panther Creek) and an agricultural stream (Ledbetter Creek) using the single-station, open-system method. Reaeration coefficients were estimated using the energy-dissipation model. Both GPP and CR were consistently higher in the forested stream than the agricultural stream. P/R ratio ranged from 0.09 to 0.23 showing the heterotrophic nature in both streams. In Panther Creek, mean daily GPP (1.58 gO2/m2) and CR (15.82 gO2/m2) were significantly higher during fall than summer (GPP=1.17 gO2, CR=5.02 gO2/m2). However, the seasonal differences in daily GPP (0.45 gO2 in summer and 0.33 gO2/m2 in fall) and CR (2.39 gO2 in summer and 3.53 gO2/m2 in fall) were not significant in Ledbetter Creek. Higher GPP and CR in the forested stream can be attributed to more stable hydrology and sediment composition compare to the agricultural stream that is subject to frequent spates and sediment movements. The higher metabolic activities observed in Panther Creek during fall compare to summer is a result of combined effect of higher light intensity reaching to benthic community and increased organic matter post litterfall.
Food waste quantification in primary production - The Nordic countries as a case study.
Hartikainen, Hanna; Mogensen, Lisbeth; Svanes, Erik; Franke, Ulrika
2018-01-01
Our understanding of food waste in the food supply chain has increased, but very few studies have been published on food waste in primary production. The overall aims of this study were to quantify the total amount of food waste in primary production in Finland, Sweden, Norway and Denmark, and to create a framework for how to define and quantify food waste in primary production. The quantification of food waste was based on case studies conducted in the present study and estimates published in scientific literature. The chosen scope of the study was to quantify the amount of edible food (excluding inedible parts like peels and bones) produced for human consumption that did not end up as food. As a result, the quantification was different from the existing guidelines. One of the main differences is that food that ends up as animal feed is included in the present study, whereas this is not the case for the recently launched food waste definition of the FUSIONS project. To distinguish the 'food waste' definition of the present study from the existing definitions and to avoid confusion with established usage of the term, a new term 'side flow' (SF) was introduced as a synonym for food waste in primary production. A rough estimate of the total amount of food waste in primary production in Finland, Sweden, Norway and Denmark was made using SF and 'FUSIONS Food Waste' (FFW) definitions. The SFs in primary production in the four Nordic countries were an estimated 800,000 tonnes per year with an additional 100,000 tonnes per year from the rearing phase of animals. The 900,000 tonnes per year of SF corresponds to 3.7% of the total production of 24,000,000 tonnes per year of edible primary products. When using the FFW definition proposed by the FUSIONS project, the FFW amount was estimated at 330,000 tonnes per year, or 1% of the total production. Copyright © 2017 Elsevier Ltd. All rights reserved.
Assessment of model estimates of land-atmosphere CO2 exchange across northern Eurasia
Rawlins, M.A.; McGuire, A.D.; Kimball, J.S.; Dass, P.; Lawrence, D.; Burke, E.; Chen, X.; Delire, C.; Koven, C.; MacDougall, A.; Peng, S.; Rinke, A.; Saito, K.; Zhang, W.; Alkama, R.; Bohn, T. J.; Ciais, P.; Decharme, B.; Gouttevin, I.; Hajima, T.; Ji, D.; Krinner, G.; Lettenmaier, D.P.; Miller, P.; Moore, J.C.; Smith, B.; Sueyoshi, T.
2015-01-01
A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m−2 yr−2, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model
Assessment of model estimates of land-atmosphere CO 2 exchange across Northern Eurasia
Rawlins, M. A.; McGuire, A. D.; Kimball, J. S.; ...
2015-07-28
A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO 2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climatemore » model simulations. Model performance benchmarks were drawn from comparisons against both observed CO 2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m⁻² yr⁻², equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO 2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO 2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements
Solar-Induced Fluorescence of Maize Across A Water Stress Gradient in the Midwestern USA
NASA Astrophysics Data System (ADS)
Miao, G.; Guan, K.; Suyker, A.; Yang, X.; Benarcchi, C. J.; Gamon, J. A.; Berry, J. A.; DeLucia, E.; Franz, T.; Arkebauer, T. J.; Zygielbaum, A. I.; Walter-Shea, E. A.; Moore, C.; Zhang, Y.; Kim, H.; Hmimina, G.
2017-12-01
In the coming decades, agricultural ecosystems will be challenged by rising temperatures, changing rainfall patterns, and increasing extreme weather. Understanding how crops respond to weather variability and how humans manage agriculture to mitigate and adapt to climate change is critical for improving agricultural sustainability and supporting increasing global food demands. Accurately estimating gross primary productivity (GPP) of crops is of importance to evaluate their sustainability and capability but remains a challenge. The recent development of solar-induced fluorescence (SIF) technology is stimulating studies to use SIF to approximate GPP. It has been observed that agricultural lands have remarkably high SIF and the SIF signal could be used as an indicator of vegetation stress, which is particularly valuable for improved monitoring of crop productivity and stress. To investigate the applicability of SIF for detecting maize stress and estimating GPP, we deployed three FluoSpec2 systems in 2017 at three long-term eddy covariance flux sites across the US Corn Belt, a rain-fed maize field (AmeriFlux sites US-NE3) and an irrigated maize field (US-NE2) at Mead, Nebraska and a rain-fed maize field at Urbana, Illinois. Together these form a water stress gradient. Variations in GPP, SIF, photosynthetic efficiency (LUE), SIF yield (SIFy), and relationships between GPP and SIF, LUE and SIFy will be compared as indications of the difference in maize growth across the water stress gradient. More importantly, differences in GPP and SIF signals will be examined over multiple growth stages to assess the potential of SIF in identifying the growth stages that are mostly affected by water stress and the ones that play the most important roles on the crop yield.
NASA Astrophysics Data System (ADS)
Strada, Susanna; Unger, Nadine
2016-04-01
A global Earth system model is applied to quantify the impacts of direct anthropogenic aerosol effective radiative forcing on gross primary productivity (GPP) and isoprene emission. The impacts of different pollution aerosol sources (anthropogenic, biomass burning, and non-biomass burning) are investigated by performing sensitivity experiments. The model framework includes all known light and meteorological responses of photosynthesis, but uses fixed canopy structures and phenology. On a global scale, our results show that global land carbon fluxes (GPP and isoprene emission) are not sensitive to pollution aerosols, even under a global decline in surface solar radiation (direct + diffuse) by ˜ 9 %. At a regional scale, GPP and isoprene emission show a robust but opposite sensitivity to pollution aerosols in regions where forested canopies dominate. In eastern North America and Eurasia, anthropogenic pollution aerosols (mainly from non-biomass burning sources) enhance GPP by +5-8 % on an annual average. In the northwestern Amazon Basin and central Africa, biomass burning aerosols increase GPP by +2-5 % on an annual average, with a peak in the northwestern Amazon Basin during the dry-fire season (+5-8 %). The prevailing mechanism varies across regions: light scattering dominates in eastern North America, while a reduction in direct radiation dominates in Europe and China. Aerosol-induced GPP productivity increases in the Amazon and central Africa include an additional positive feedback from reduced canopy temperatures in response to increases in canopy conductance. In Eurasia and northeastern China, anthropogenic pollution aerosols drive a decrease in isoprene emission of -2 to -12 % on an annual average. Future research needs to incorporate the indirect effects of aerosols and possible feedbacks from dynamic carbon allocation and phenology.
Anthropogenic climate change has altered primary productivity in Lake Superior
O'Beirne, M. D.; Werne, J. P.; Hecky, R. E.; Johnson, T. C.; Katsev, S.; Reavie, E. D.
2017-01-01
Anthropogenic climate change has the potential to alter many facets of Earth's freshwater resources, especially lacustrine ecosystems. The effects of anthropogenic changes in Lake Superior, which is Earth's largest freshwater lake by area, are not well documented (spatially or temporally) and predicted future states in response to climate change vary. Here we show that Lake Superior experienced a slow, steady increase in production throughout the Holocene using (paleo)productivity proxies in lacustrine sediments to reconstruct past changes in primary production. Furthermore, data from the last century indicate a rapid increase in primary production, which we attribute to increasing surface water temperatures and longer seasonal stratification related to longer ice-free periods in Lake Superior due to anthropogenic climate warming. These observations demonstrate that anthropogenic effects have become a prominent influence on one of Earth's largest, most pristine lacustrine ecosystems. PMID:28598413
Anthropogenic climate change has altered primary productivity in Lake Superior.
O'Beirne, M D; Werne, J P; Hecky, R E; Johnson, T C; Katsev, S; Reavie, E D
2017-06-09
Anthropogenic climate change has the potential to alter many facets of Earth's freshwater resources, especially lacustrine ecosystems. The effects of anthropogenic changes in Lake Superior, which is Earth's largest freshwater lake by area, are not well documented (spatially or temporally) and predicted future states in response to climate change vary. Here we show that Lake Superior experienced a slow, steady increase in production throughout the Holocene using (paleo)productivity proxies in lacustrine sediments to reconstruct past changes in primary production. Furthermore, data from the last century indicate a rapid increase in primary production, which we attribute to increasing surface water temperatures and longer seasonal stratification related to longer ice-free periods in Lake Superior due to anthropogenic climate warming. These observations demonstrate that anthropogenic effects have become a prominent influence on one of Earth's largest, most pristine lacustrine ecosystems.
Hot-spots of primary productivity: An Alternative interpretation to Conventional upwelling models
NASA Astrophysics Data System (ADS)
van Ruth, Paul D.; Ganf, George G.; Ward, Tim M.
2010-12-01
The eastern Great Australian Bight (EGAB) forms part of the Southern and Indian Oceans and is an area of high ecological and economic importance. Although it supports a commercial fishery, quantitative estimates of the primary productivity underlying this industry are open to debate. Estimates range from <100 mg C m -2 day -1 to > 500 mg C m -2 day -1. Part of this variation may be due to the unique upwelling circulation of shelf waters in summer/autumn (November-April), which shares some similarities with highly productive eastern boundary current upwelling systems, but differs due to the influence of a northern boundary current, the Flinders current, and a wide continental shelf. This study examines spatial variations in primary productivity in the EGAB during the upwelling seasons of 2005 and 2006. Daily integral productivity calculated using the vertically generalised production model (VGPM) showed a high degree of spatial variation. Productivity was low (<800 mg C m -2 day -1) in offshore central and western regions of the EGAB. High productivities (1600-3900 mg C m -2 day -1) were restricted to hotspots in the east that were influenced by the upwelled water mass. There was a strong correlation between the depth of the euphotic zone and the depth of the mixed layer that suggested that ˜50% of the euphotic zone lay below the mixed layer depth. As a result, high rates of primary productivity did not require upwelled water to reach the surface. A significant proportion of total productivity in the euphotic zone (57% in 2005 and 65% in 2006) occurred in the upwelled water mass below the surface mixed layer. This result has implications for daily integral productivities modelled with the VGPM, which uses surface measures of phytoplankton biomass to calculate productivity. Macro-nutrient concentrations could not be used to explain the difference in the low and high productivities (silica > 1 μmol L -1, nitrate/nitrite > 0.4 μmol L -1, phosphate > 0.1 μmol L -1
Atkinson, Gemma C.; Tenson, Tanel; Hauryliuk, Vasili
2011-01-01
RelA/SpoT Homologue (RSH) proteins, named for their sequence similarity to the RelA and SpoT enzymes of Escherichia coli, comprise a superfamily of enzymes that synthesize and/or hydrolyze the alarmone ppGpp, activator of the “stringent” response and regulator of cellular metabolism. The classical “long” RSHs Rel, RelA and SpoT with the ppGpp hydrolase, synthetase, TGS and ACT domain architecture have been found across diverse bacteria and plant chloroplasts, while dedicated single domain ppGpp-synthesizing and -hydrolyzing RSHs have also been discovered in disparate bacteria and animals respectively. However, there is considerable confusion in terms of nomenclature and no comprehensive phylogenetic and sequence analyses have previously been carried out to classify RSHs on a genomic scale. We have performed high-throughput sensitive sequence searching of over 1000 genomes from across the tree of life, in combination with phylogenetic analyses to consolidate previous ad hoc identification of diverse RSHs in different organisms and provide a much-needed unifying terminology for the field. We classify RSHs into 30 subgroups comprising three groups: long RSHs, small alarmone synthetases (SASs), and small alarmone hydrolases (SAHs). Members of nineteen previously unidentified RSH subgroups can now be studied experimentally, including previously unknown RSHs in archaea, expanding the “stringent response” to this domain of life. We have analyzed possible combinations of RSH proteins and their domains in bacterial genomes and compared RSH content with available RSH knock-out data for various organisms to determine the rules of combining RSHs. Through comparative sequence analysis of long and small RSHs, we find exposed sites limited in conservation to the long RSHs that we propose are involved in transmitting regulatory signals. Such signals may be transmitted via NTD to CTD intra-molecular interactions, or inter-molecular interactions either among individual
Yang, Xi; Tang, Jianwu; Mustard, John F.; ...
2015-03-24
Previous studies have suggested that solar-induced chlorophyll fluorescence (SIF) is correlated with Gross Primary Production (GPP). However, it remains unclear to what extent this relationship is due to absorbed photosynthetically active radiation (APAR) and/or light use efficiency (LUE). Here in this work, we present the first time series of near-surface measurement of canopy-scale SIF at 760 nm in temperate deciduous forests. SIF correlated with GPP estimated with eddy covariance at diurnal and seasonal scales (r 2 = 0.82 and 0.73, respectively), as well as with APAR diurnally and seasonally (r 2 = 0.90 and 0.80, respectively). SIF/APAR is significantly positivelymore » correlated with LUE and is higher during cloudy days than sunny days. Weekly tower-based SIF agreed with SIF from the Global Ozone Monitoring Experiment-2 (r 2 = 0.82). Finally, our results provide ground-based evidence that SIF is directly related to both APAR and LUE and thus GPP, and confirm that satellite SIF can be used as a proxy for GPP.« less
Global and Time-Resolved Monitoring of Crop Photosynthesis with Chlorophyll Fluorescence
NASA Technical Reports Server (NTRS)
Guanter, Luis; Zhang, Yongguang; Jung, Martin; Joiner, Joanna; Voigt, Maximilian; Berry, Joseph A.; Frankenberg, Christian; Huete, Alfredo R.; Zarco-Tejada, Pablo; Lee, Jung-Eun;
2014-01-01
Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50-75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.
Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence
Guanter, Luis; Zhang, Yongguang; Jung, Martin; Joiner, Joanna; Voigt, Maximilian; Berry, Joseph A.; Frankenberg, Christian; Huete, Alfredo R.; Zarco-Tejada, Pablo; Lee, Jung-Eun; Moran, M. Susan; Ponce-Campos, Guillermo; Beer, Christian; Camps-Valls, Gustavo; Buchmann, Nina; Gianelle, Damiano; Klumpp, Katja; Cescatti, Alessandro; Baker, John M.; Griffis, Timothy J.
2014-01-01
Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50–75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle. PMID:24706867
NASA Astrophysics Data System (ADS)
Forest, Alexandre; Tremblay, Jean-Éric; Gratton, Yves; Martin, Johannie; Gagnon, Jonathan; Darnis, Gérald; Sampei, Makoto; Fortier, Louis; Ardyna, Mathieu; Gosselin, Michel; Hattori, Hiroshi; Nguyen, Dan; Maranger, Roxane; Vaqué, Dolors; Marrasé, Cèlia; Pedrós-Alió, Carlos; Sallon, Amélie; Michel, Christine; Kellogg, Colleen; Deming, Jody; Shadwick, Elizabeth; Thomas, Helmuth; Link, Heike; Archambault, Philippe; Piepenburg, Dieter
2011-12-01
Major pathways of biogenic carbon (C) flow are resolved for the planktonic food web of the flaw lead polynya system of the Amundsen Gulf (southeast Beaufort Sea, Arctic Ocean) in spring-summer 2008. This period was relevant to study the effect of climate change on Arctic marine ecosystems as it was characterized by unusually low ice cover and warm sea surface temperature. Our synthesis relied on a mass balance estimate of gross primary production (GPP) of 52.5 ± 12.5 g C m -2 calculated using the drawdown of nitrate and dissolved inorganic C, and a seasonal f-ratio of 0.64. Based on chlorophyll a biomass, we estimated that GPP was dominated by phytoplankton (93.6%) over ice algae (6.4%) and by large cells (>5 μm, 67.6%) over small cells (<5 μm, 32.4%). Ancillary in situ data on bacterial production, zooplankton biomass and respiration, herbivory, bacterivory, vertical particle fluxes, pools of particulate and dissolved organic carbon (POC, DOC), net community production (NCP), as well as selected variables from the literature were used to evaluate the fate of size-fractionated GPP in the ecosystem. The structure and functioning of the planktonic food web was elucidated through inverse analysis using the mean GPP and the 95% confidence limits of every other field measurement as lower and upper constraints. The model computed a net primary production of 49.2 g C m -2, which was directly channeled toward dominant calanoid copepods (i.e. Calanus hyperboreus 20%, Calanus glacialis 10%, and Metridia longa 10%), other mesozooplankton (12%), microzooplankton (14%), detrital POC (18%), and DOC (16%). Bacteria required 29.9 g C m -2, a demand met entirely by the DOC derived from local biological activities. The ultimate C outflow comprised respiration fluxes (82% of the initial GPP), a small sedimentation (3%), and a modest residual C flow (15%) resulting from NCP, dilution and accumulation. The sinking C flux at the model limit depth (395 m) supplied 60% of the estimated
NASA Astrophysics Data System (ADS)
Sun, S.; Sun, G.; Cohen, E.; McNulty, S. G.; Caldwell, P.; Duan, K.; Zhang, Y.
2015-12-01
Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) dynamically downscaled climate projections of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12 digit Hydrologic Unit Code level) in the conterminous US (CONUS), and evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or 2-digit HUCs. Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8 °C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 g C m-2 yr-1 (9 %) increase in GPP. Response to climate change was highly variable across the 82, 773 watersheds, but in general, the majority would see consistent increases in all variables evaluated. Over half of the 82 773 watersheds, mostly found in the northeast and the southern part of the southwest would have an increase in annual Q (>100 mm yr-1 or 20 %). This study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results will be useful for policy-makers and land managers in formulating appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.
Benjamin N. Sulman; Daniel Tyler Roman; Todd M. Scanlon; Lixin Wang; Kimberly A. Novick
2016-01-01
The eddy covariance (EC) method is routinely used to measure net ecosystem fluxes of carbon dioxide (CO2) and evapotranspiration (ET) in terrestrial ecosystems. It is often desirable to partition CO2 flux into gross primary production (GPP) and ecosystem respiration (RE), and to partition ET into evaporation and...
Short-term carbon partitioning fertilizer responses vary among two full-sib loblolly pine clones
Jeremy P. Stovall; John R. Seiler; Thomas R. Fox
2012-01-01
We investigated the effects of fertilizer application on the partitioning of gross primary productivity (GPP) between contrasting full-sib clones of Pinus taeda (L.). Our objective was to determine if fertilizer growth responses resulted from similar short-term changes to partitioning. A modeling approach incorporating respiratory carbon (C) fluxes,...
Satellites for the study of ocean primary productivity
NASA Technical Reports Server (NTRS)
Smith, R. C.; Baker, K. S.
1983-01-01
The use of remote sensing techniques for obtaining estimates of global marine primary productivity is examined. It is shown that remote sensing and multiplatform (ship, aircraft, and satellite) sampling strategies can be used to significantly lower the variance in estimates of phytoplankton abundance and of population growth rates from the values obtained using the C-14 method. It is noted that multiplatform sampling strategies are essential to assess the mean and variance of phytoplankton biomass on a regional or on a global basis. The relative errors associated with shipboard and satellite estimates of phytoplankton biomass and primary productivity, as well as the increased statistical accuracy possible from the utilization of contemporaneous data from both sampling platforms, are examined. It is shown to be possible to follow changes in biomass and the distribution patterns of biomass as a function of time with the use of satellite imagery.
Primary production control of methane emission from wetlands
NASA Technical Reports Server (NTRS)
Whiting, G. J.; Chanton, J. P.
1993-01-01
Based on simultaneous measurements of CO2 and CH4 exchange in wetlands extending from subarctic peatlands to subtropical marshes, a positive correlation between CH4 emission and net ecosystem production is reported. It is suggested that net ecosystem production is a master variable integrating many factors which control CH4 emission in vegetated wetlands. It is found that about 3 percent of the daily net ecosystem production is emitted back to the atmosphere as CH4. With projected stimulation of primary production and soil microbial activity in wetlands associated with elevated atmospheric CO2 concentration, the potential for increasing CH4 emission from inundated wetlands, further enhancing the greenhouse effect, is examined.
Primary Productivity Regime and Nutrient Removal in the Danube Estuary
NASA Astrophysics Data System (ADS)
Humborg, C.
1997-11-01
The primary productivity regime, as well as the distribution of dissolved inorganic nutrients and particulate organic matter in the Danube estuary, were investigated during several cruises at different discharge regimes of the Danube River. The shallowness of the upper surface layer due to insignificant tidal mixing and strong stratification of the Danube estuary, as well as the high nutrient concentrations, are favourable for elevated primary production. The incident light levels at the bottom of the upper surface layer of the water column (0·5-3·0 m) were generally higher than 20% of the surface irradiance. Elevated chlorophyll (Chl) aconcentrations with maxima at mid salinities were found during each survey. Within the upper mixed layer estimated primary production of 0·2-4·4 g m-2day-1is very high compared with estuaries of other major world rivers. Mixing diagrams of dissolved inorganic nutrients reveal removal of significant quantities of nutrients during estuarine mixing. These observations were consistent with the distribution of particular organic matter, which was negatively correlated to the nutrient distribution during each survey. C:Chl aratios, as well as the elevated estimated production, indicate that biological transformation processes govern the nutrient distribution in this estuary.
NASA Astrophysics Data System (ADS)
Washington-Allen, R. A.; Mitchell, J. E.; Oslen, H. E.
2008-12-01
The "State of Nation's Ecosystems" by the Heinz Institute and the recent "Millennium Ecosystem Assessment of Drylands" concluded that the amount of desertification and the extent to which human management actions contribute to this process is unknown at national to global spatial scales. This is primarily due to lack of studies at these large spatial scales and the temporal scales (> a 15-year time series of data) necessary to separate the effects of anthropogenic practices from climate change on Drylands. Consequently, this research seeks to develop procedures for determining 1) the area of Drylands within the United States where commercial grazing livestock occur or the livestock ecological footprint and 2) the impact of the footprint on the US's productive capacity. Our approach has been to develop a pilot geodatabase of year 2002 data that includes administrative boundaries, the Moderate Resolution Infrared Spectroradiometer's (MODIS) measures of gross and net primary productivity (GPP and NPP, respectively), US Department of Agriculture's National Agricultural Statistics Service's (USDA-NASS) county-level data on cattle, sheep, and goat inventories, transportation and power consumption networks, dryland extent, and land cover/land use. Secondly, the ratio of 1-km2 gridded mean annual potential evapotranspiration (MAPET) to mean annual precipitation (MAP) data were used to define the 50-year mean dryland extent in accordance with the United Nations Convention to Combat Desertification's definition of Drylands, the aridity index (AI) ≤ 0.65. Urban features, including transportation, power consumption, and land use/land cover, were subtracted from this dryland map to further refine it. The NASS tabular data was then related to the counties boundary map thus producing a county-level livestock number map that was then intersected with the dryland extent map to yield the US livestock ecological footprint. Lastly, this footprint map was then converted to a
NASA Astrophysics Data System (ADS)
Norton, Alexander J.; Rayner, Peter J.; Koffi, Ernest N.; Scholze, Marko
2018-04-01
The synthesis of model and observational information using data assimilation can improve our understanding of the terrestrial carbon cycle, a key component of the Earth's climate-carbon system. Here we provide a data assimilation framework for combining observations of solar-induced chlorophyll fluorescence (SIF) and a process-based model to improve estimates of terrestrial carbon uptake or gross primary production (GPP). We then quantify and assess the constraint SIF provides on the uncertainty in global GPP through model process parameters in an error propagation study. By incorporating 1 year of SIF observations from the GOSAT satellite, we find that the parametric uncertainty in global annual GPP is reduced by 73 % from ±19.0 to ±5.2 Pg C yr-1. This improvement is achieved through strong constraint of leaf growth processes and weak to moderate constraint of physiological parameters. We also find that the inclusion of uncertainty in shortwave down-radiation forcing has a net-zero effect on uncertainty in GPP when incorporated into the SIF assimilation framework. This study demonstrates the powerful capacity of SIF to reduce uncertainties in process-based model estimates of GPP and the potential for improving our predictive capability of this uncertain carbon flux.
Coherence between woody carbon uptake and net ecosystem productivity at five eddy-covariance sites
NASA Astrophysics Data System (ADS)
Babst, F.; Bouriaud, O.; Papale, D.; Gielen, B.; Janssens, I.; Nikinmaa, E.; Ibrom, A.; Wu, J.; Bernhofer, C.; Koestner, B.; Gruenwald, T.; Seufert, G.; Ciais, P.; Frank, D. C.
2013-12-01
Forest growth ranks amongst the most important processes that determine the carbon balance of terrestrial ecosystems. Quantifications of forest carbon cycling can be made e.g. using biometric and eddy-covariance (EC) techniques. Both offer different perspectives on carbon uptake and attempts to combine them have been inconsistent and variably successful in the past. This contributes to persistent uncertainties regarding carbon allocation in forest ecosystems and complicates precise vegetation model parameterization. Aiming to reconcile assessments of carbon cycling from biometric and EC techniques, we measured radial tree growth and wood density at five long-term EC stations across Europe. The resulting records were used to calculate annual carbon uptake during above-ground wood formation and compared to monthly and seasonal CO2-flux measurements. Efforts were made to identify i) the time periods when EC and tree-ring data correspond best in different parts of Europe and ii) the fraction of eddy-fluxes which is associated with changes in above-ground woody carbon stocks. Biometric measurements and net ecosystem productivity (NEP) proved largely compatible at seasonal time scales while relationships with gross primary productivity (GPP) were often weaker. Results suggest a partitioning of sequestered carbon mainly used for volume increase (January-June) and a combination of cell-wall thickening and storage (July-September). The inter-annual variability in above-ground woody carbon uptake was significantly linked with absolute productivity ranging between 69-366 g C m-2 y-1 at boreal and temperate sites, thereby accounting for 10-25% of GPP, 15-32% of TER, and 25-80% of NEP. These findings from sites representing the major European climate zones and tree species contribute to improved quantification of above-ground carbon allocation in forests. Furthermore, they refine knowledge on processes driving ecosystem productivity important for e.g. vegetation models and
NASA Astrophysics Data System (ADS)
Zhang, Leiming; Cao, Peiyu; Li, Shenggong; Yu, Guirui; Zhang, Junhui; Li, Yingnian
2016-04-01
To accurately assess the change of phenology and its relationship with ecosystem gross primary productivity (GPP) is one of the key issues in context of global change study. In this study, an alpine shrubland meadow in Haibei (HBS) of Qinghai-Tibetan plateau and a broad-leaved Korean pine forest in Changbai Mountain (CBM) of Northeastern China were selected. Based on the long-term GPP from eddy flux measurements and the Normalized Difference Vegetation Index (NDVI) from remote sensed vegetation index, phenological indicators including the start of growing season (SOS), the end of growing season (EOS), and the growing season length (GSL) since 2003 were derived via multiple methods, and then the influences of phenology variation on GPP were explored. Compared with ground phenology observations of dominant plant species, both GPP- and NDVI-derived SOS and EOS exhibited a similar interannual trend. GPP-derived SOS was quite close to NDVI-derived SOS, but GPP-derived EOS differed significantly from NDVI-derived EOS, and thus leading to a significant difference between GPP- and NDVI-derived GSL. Relative to SOS, EOS presented larger differences between the extraction methods, indicating large uncertainties to accurately define EOS. In general, among the methods used, the threshold methods produced more satisfactory assessment on phenology change. This study highlights that how to harmonize with the flux measurements, remote sensing and ground monitoring are a big challenge that needs further consideration in phenology study, especially the accurate extraction of EOS. Key words: phenological variation, carbon flux, vegetation index, vegetation grwoth, interannual varibility
Increasing the Confidence of African Carbon Cycle Assessments
NASA Astrophysics Data System (ADS)
Ardö, Jonas
2016-04-01
Scarcity of in situ measurements of greenhouse gas (GHG) fluxes hamper calibration and validation of assessments of carbon budgets in Africa. It limits essential studies of ecosystem function and ecosystem processes. The wide range reported net primary production (NPP) and gross primary production (GPP) for continental African is partly a function of the uncertainty originating from this data scarcity. GPP estimates, based on vegetation models and remote sensing based models, range from ~17 to ~40 Pg C yr-1 and NPP estimates roughly range from ~7 to ~20 Pg C yr-1 for continental Africa. According to the MOD17 product does Africa contribute about 23 % of the global GPP and about 25 % of the global NPP. These percentages have recently increased slightly. Differences in modeled carbon use efficiency (i.e. the NPP/GPP ratio) further enhance the uncertainty caused by low spatial resolution driver data sets when deriving NPP from GPP. Current substantial uncertainty in vegetation productivity estimates for Africa (both magnitudes and carbon use efficiency) may be reduced by increased abundance and availability of in situ collected field data including meteorology, radiation, spectral properties, GHG fluxes as well as long term ecological field experiments. Current measurements of GHGs fluxes in Africa are sparse and lacking impressive coordination. The European Fluxes Database Cluster includes ~24 African sites with carbon flux data, most of them with a small amount of data in short time series. Large and diverse biomes such as the evergreen broad leafed forest are under-represented whereas savannas are slightly better represented. USA for example, with 171 flux site listed in FLUXNET has a flux site density of 17 sites per million km2, whereas Africa has density of 0.8 sites per million km2. Increased and coordinated collection of data on fluxes of GHGs, ecosystem properties and processes, both through advanced micro meteorological measurements and through cost
A long-term simulation of forest carbon fluxes over the Qilian Mountains
NASA Astrophysics Data System (ADS)
Yan, Min; Tian, Xin; Li, Zengyuan; Chen, Erxue; Li, Chunmei; Fan, Wenwu
2016-10-01
In this work, we integrated a remote-sensing-based (the MODIS MOD_17 Gross Primary Productivity (GPP) model (MOD_17)) and a process-based (the Biome-BioGeochemical Cycles (Biome-BGC) model) ecological model in order to estimate long-term (from 2000 to 2012) forest carbon fluxes over the Qilian Mountains in northwest China, a cold and arid forest ecosystem. Our goal was to obtain an accurate and quantitative simulation of spatial GPP patterns using the MOD_17 model and a temporal description of forest processes using the Biome-BGC model. The original MOD_17 model was first optimized using a biome-specific parameter, observed meteorological data, and reproduced fPAR at the eddy covariance site. The optimized MOD_17 model performed much better (R2 = 0.91, RMSE = 5.19 gC/m2/8d) than the original model (R2 = 0.47, RMSE = 20.27 gC/m2/8d). The Biome-BGC model was then calibrated using GPP for 30 representative forest plots selected from the optimized MOD_17 model. The calibrated Biome-BGC model was then driven in order to estimate forest GPP, net primary productivity (NPP), and net ecosystem exchange (NEE). GPP and NEE were validated against two-year (2010 and 2011) EC measurements (R2 = 0.79, RMSE = 1.15 gC/m2/d for GPP; and R2 = 0.69, RMSE = 1.087 gC/m2/d for NEE). NPP estimates from 2000 to 2012 were then compared to dendrochronological measurements (R2 = 0.73, RMSE = 24.46 gC/m2/yr). Our results indicated that integration of the two models can be used for estimating carbon fluxes with good accuracy and a high temporal and spatial resolution. Overall, NPP displayed a downward trend, with an average rate of 0.39 gC/m2/yr, from 2000 and 2012 over the Qilian Mountains. Simulated average annual NPP yielded higher values for the southeast as compared to the northwest. The most positive correlative climatic factor to average annual NPP was downward shortwave radiation. The vapor pressure deficit, and mean temperature and precipitation yielded negative correlations to average
Satellite remote sensing of primary production
NASA Technical Reports Server (NTRS)
Tucker, C. J.; Sellers, P. J.
1986-01-01
Leaf structure and function are shown to result in distinctive variations in the absorption and reflection of solar radiation from plant canopies. The leaf properties that determine the radiation-interception characteristics of plant canopies are directly linked to photosynthesis, stomatal resistance and evapotranspiration and can be inferred from measurements of reflected solar energy. The effects of off-nadir viewing and atmospheric constituents, coupled with the need to measure changing surface conditions, emphasize the need for multitemporal measurements of reflected radiation if primary production is to be estimated.
Ma, Xiaohui; Guo, Juan; Ma, Ying; Jin, Baolong; Zhan, Zhilai; Yuan, Yuan; Huang, Luqi
2016-07-01
To identify a terpene synthase that catalyzes the conversion of geranyl pyrophosphate (GPP) to α-pinene and is involved in the biosynthesis of paeoniflorin. Two new terpene synthase genes were isolated from the transcriptome data of Peaonia lactiflora. Phylogenetic analysis and sequence characterization revealed that one gene, named PlPIN, encoded a monoterpene synthase that might be involved in the biosynthesis of paeoniflorin. In vitro enzyme assay showed that, in contrast to most monoterpene synthases, PlPIN encoded an α-pinene synthase which converted GPP into α-pinene as a single product. This newly identified α-pinene synthase could be used for improving paeoniflorin accumulation by metabolic engineering or for producing α-pinene via synthetic biology.
NASA Astrophysics Data System (ADS)
Sun, Shanlei; Sun, Ge; Cohen, Erika; McNulty, Steven G.; Caldwell, Peter V.; Duan, Kai; Zhang, Yang
2016-03-01
Quantifying the potential impacts of climate change on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, and ecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled climate data of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12-digit Hydrologic Unit Code level) in the coterminous US (CONUS). Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8° C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 gC m-2 yr-1 (9 %) increase in GPP. We found a large spatial variability in response to climate change across the CONUS 12-digit HUC watersheds, but in general, the majority would see consistent increases all variables evaluated. Over half of the watersheds, mostly found in the northeast and the southern part of the southwest, would see an increase in annual Q (> 100 mm yr-1 or 20 %). In addition, we also evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or two-digit HUCs. The study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results may be useful for policy-makers and land managers to formulate appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.
Evaluation of bio-optical algorithms to remotely sense marine primary production from space
NASA Technical Reports Server (NTRS)
Berthelot, Beatrice; Deschamps, Pierre-Yves
1994-01-01
In situ bio-optical measurements from several oceanographic campaigns were analyzed to derive a direct relationship between water column primary production P (sub t) ocean color as expressed by the ratio of reflectances R (sub 1) at 440 nm and R (sub 3) at 550 nm and photosynthetically available radiation (PAR). The study is restricted to the Morel case I waters for which the following algorithm is proposed: log (P(sub f)) = -4.286 - 1.390 log (R(sub 1)/R(sub3)) + 0.621 log (PAR), with P(sub t) in g C m(exp -2)/d and PAR in J m(exp -2)/d. Using this algorithm the rms accuracy of primary production estimate is 0.17 on a logarithmic scale, i.e., a factor of 1.5. Using spectral reflectance measurements in the entire visible spectral range, the central wavelength, spectral bandwidth, and radiometric noise level requirements are investigated for the channels to be used by an ocean color space mission dedicated to estimating global marine primary production and the associated carbon fluxes. Nearly all the useful information is provided by two channels centered at 440 nm and 550 nm, but the accuracy of primary production estimate appears weakly sensitive to spectral bandwidth, which, consequently, may be enlarged by several tens of nanometers. The sensitivity to radiometric noise, on the contrary, is strong, and a noise equivalent reflectance of 0.005 degraded the accuracy on the primary production estimate by a factor 2 (0.14-0.25 on a logarithmic scale). The results should be applicable to evaluating the primary production of oligotrophic and mesotrophic waters, which constitute most of the open ocean.
NASA Astrophysics Data System (ADS)
Calleja, María Ll.; Duarte, Carlos M.; Navarro, Nuria; Agustí, Susana
2005-04-01
The air-sea CO2 gradient at the subtropical NE Atlantic was strongly dependent on the metabolism of the planktonic community within the top cms, but independent of that of the communities deeper in the water column. Gross primary production (GPP) and community respiration (R) of the planktonic community within the top cms exceeded those of the communities deeper in the water column by >10-fold and >7 fold, respectively. Net autotrophic metabolism (GPP > R) at the top cms of the water column in some stations drove CO2 uptake by creating a CO2 deficit at the ocean surface, while net heterotrophic metabolism (GPP < R) at the top cms of the water column in other stations resulted in strong CO2 supersaturation, driving CO2 emissions. These results suggest a strong control of the air-sea pCO2 anomaly by intense biological processes.
Climate change decouples oceanic primary and export productivity and organic carbon burial
Lopes, Cristina; Kucera, Michal; Mix, Alan C.
2015-01-01
Understanding responses of oceanic primary productivity, carbon export, and burial to climate change is essential for model-based projection of biological feedbacks in a high-CO2 world. Here we compare estimates of productivity based on the composition of fossil diatom floras with organic carbon burial off Oregon in the Northeast Pacific across a large climatic transition at the last glacial termination. Although estimated primary productivity was highest during the Last Glacial Maximum, carbon burial was lowest, reflecting reduced preservation linked to low sedimentation rates. A diatom size index further points to a glacial decrease (and deglacial increase) in the fraction of fixed carbon that was exported, inferred to reflect expansion, and contraction, of subpolar ecosystems that today favor smaller plankton. Thus, in contrast to models that link remineralization of carbon to temperature, in the Northeast Pacific, we find dominant ecosystem and sea floor control such that intervals of warming climate had more efficient carbon export and higher carbon burial despite falling primary productivity. PMID:25453073
NASA Astrophysics Data System (ADS)
Winkler, A. J.; Brovkin, V.; Myneni, R.; Alexandrov, G.
2017-12-01
Plant growth in the northern high latitudes benefits from increasing temperature (radiative effect) and CO2 fertilization as a consequence of rising atmospheric CO2 concentration. This enhanced gross primary production (GPP) is evident in large scale increase in summer time greening over the 36-year record of satellite observations. In this time period also various global ecosystem models simulate a greening trend in terms of increasing leaf area index (LAI). We also found a persistent greening trend analyzing historical simulations of Earth system models (ESM) participating in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). However, these models span a large range in strength of the LAI trend, expressed as sensitivity to both key environmental factors, temperature and CO2 concentration. There is also a wide spread in magnitude of the associated increase of terrestrial GPP among the ESMs, which contributes to pronounced uncertainties in projections of future climate change. Here we demonstrate that there is a linear relationship across the CMIP5 model ensemble between projected GPP changes and historical LAI sensitivity, which allows using the observed LAI sensitivity as an "emerging constraint" on GPP estimation at future CO2 concentration. This constrained estimate of future GPP is substantially higher than the traditional multi-model mean suggesting that the majority of current ESMs may be significantly underestimating carbon fixation by vegetation in NHL. We provide three independent lines of evidence in analyzing observed and simulated CO2 amplitude as well as atmospheric CO2 inversion products to arrive at the same conclusion.
NASA Technical Reports Server (NTRS)
Jeong, Su-Jong; Schimel, David; Frankenberg, Christian; Drewry, Darren T.; Fisher, Joshua B.; Verma, Manish; Berry, Joseph A.; Lee, Jung-Eun; Joiner, Joanna
2016-01-01
This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40 deg - 55 deg N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and observation-based estimate of gross primary productivity (GPP) from 2009 to 2011. Based on GPP phenology estimation in GPP, the growing season determined by SIF time-series is shorter in length than the growing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (+/-11 days), indicating a large-scale seasonal decoupling of physiological activity and changes in greenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout the growing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF and GPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF and GPP in response to temperature changes across boreal ecosystems throughout their growing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall. Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure and greenness and physiology at large-scales across the critical boreal regions.
Net ecosystem production in a Little Ice Age moraine: the role of plant functional traits
NASA Astrophysics Data System (ADS)
Varolo, E.; Zanotelli, D.; Tagliavini, M.; Zerbe, S.; Montagnani, L.
2015-07-01
Current glacier retreat allows vast mountain ranges available for vegetation establishment and growth. Little is known about the effective carbon (C) budget of these new ecosystems and how the presence of different vegetation communities, characterized by their specific physiology and life forms influences C fluxes. In this study, using a comparative analysis of the C fluxes of two contrasting vegetation types, we intend to evaluate if the different physiologies of the main species have an effect on Ecosystem Respiration (Reco), Gross Primary Production (GPP), annual cumulated Net Ecosystem Exchange (NEE), and long-term carbon accumulation in soil. The NEE of two plant communities present on a Little Ice Age moraine in the Matsch glacier forefield (Alps, Italy) was measured over two growing seasons. They are a typical C3 grassland, dominated by Festuca halleri All. and a community dominated by CAM rosettes Sempervivum montanum L. on rocky soils. Using transparent and opaque chambers, we extrapolated the ecophysiological responses to the main environmental drivers and performed the partition of NEE into Reco and GPP. Soil samples were collected from the same site to measure long-term C accumulation in the ecosystem. The two communities showed contrasting GPP but similar Reco patterns and as a result significantly different in NEE. The grassland acted mainly as a carbon sink with a total cumulated value of -46.4 ± 35.5 g C m-2 NEE while the plots dominated by the CAM rosettes acted as a source with 31.9 ± 22.4 g C m-2. In spite of the NEE being different in the two plant communities, soil analysis did not reveal significant differences in carbon accumulation. Grasslands showed 1.76 ± 0.12 kg C m-2, while CAM rosettes showed 2.06 ± 0.23 kg C m-2. This study demonstrates that carbon dynamics of two vegetation communities can be distinct even though the growing environment is similar. The physiological traits of the dominant species determine large differences in
Past climates primary productivity changes in the Indian Ocean
NASA Astrophysics Data System (ADS)
Le Mézo, P. K.; Kageyama, M.; Bopp, L.; Beaufort, L.; Braconnot, P.; Bassinot, F. C.
2016-02-01
Organic climate recorders, e.g., coccolithophorids and foraminifera, are widely used to reconstruct past climate conditions, such as the Indian monsoon intensity and variability, since they are sensitive to climate-induced fluctuations of their environment. In the Indian Ocean, it is commonly accepted that a stronger summer monsoon will enhance productivity in the Arabian Sea and therefore the amount of organisms in a sediment core should reflect monsoon intensity. In this study, we use the coupled Earth System Model IPSLCM5A, which has a biogeochemical component PISCES that simulates primary production. We use 8 climate simulations of the IPSL-CM5A model, from -72kyr BP climate conditions to a preindustrial state. Our simulations have different orbital forcing (precession, obliquity and eccentricity), greenhouse gas concentrations as well as different ice sheet covers. The objective of this work is to characterize the mechanisms behind the changes in primary productivity between the different time periods. Our model shows that in climates where monsoon is enhanced (due to changes in precession) we do not necessarily see an increase in summer productivity in the Arabian Sea, and inversely. It seems that the glacial-interglacial state of the simulation is important in driving productivity changes in this region of the world. We try to explain the changes in productivity in the Arabian Sea with the local climate and then to link the changes in local climate to large scale atmospheric forcing and commonly used Indian monsoon definitions.