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7 results for “gross ecosystem production”
Dataset for "Gross primary productivity of four European ecosystems constrained by joint CO2 and COS flux measurements"
<p>Data of measurements and model output of the publication "Gross primary productivity of four European ecosystems constrained by joint CO<sub>2</sub> and COS flux measurements".</p> <p>Data consists of micrometeorological data, COS and CO<sub>2</sub> flux measurements for 4 sites including filters for the fluxes.</p> <p>The sites include: a managed temperate mountain grassland in Austria (18.06.-21.08.2015), a Mediterranean savanna ecosystem in Spain(29.04.-24.05.2016)), a Temperate beach forest in Denmark(07.06.-03.07.2016) and an agricultural soy bean field in Italy(03.07.-01.08.2017).</p> <p>Version 2: param2950** are now correct (were filled with the same values for all field sites) </p> <p>For additional information please contact: <a href="mailto:Georg.Wohlfahrt@uibk.ac.at">Georg.Wohlfahrt@uibk.ac.at</a></p>
Standardized Dataset of the Ecosystem's Water Use Efficiency, Gross Primary Productivity and the Evapotranspiration Deficit Index for 1982–2017 over the Middle East
<p>This data aimed to investigate the spatial-temporal variability of Standardized Actual Evapotranspiration (sAET), Gross Primary Productivity (sGPP) and Water Use Efficiency (WUE) anomalies series, and the Standardized Evapotranspiration Deficit Index (SEDI). The Middle East (ME), was selected as a case study to monitoring drought events as one of the major natural disasters for the ecosystem. To this end, the yearly gross primary production of GLASS, GIMMS, FloxCom, and VPM datasets for the study area spanning 1982–2017 was used to develop the sGPPR data. On the other hand, the Global Land Evaporation Amsterdam Model (GLEAM-version (v3.3a)), which estimated the several components of terrestrial evaporation (annual actual and potential evaporation (AET, PET)) was used for the same period this aimed to detect the variability of the SEDI.<br> This version of the yearly GLASS-sGPPR dataset (1982–2017) is available for the ME at 0.05° spatial resolution, as the original data of the GPP-GLASS products, While, sGPPR dataset of GIMMS, FloxCom, and VPM are also at annual temporal resolution, and at 0.5 degree spatial resolution spanning 1982–2016 for GIMMS, FloxCom, and 2000-2016 for VPM (Excel wrokbook .xlsx). The SEDI data are also available at 0.25 degree spatial resolution for 1980–2018 ( Raster files (TIFF)). For more details about Standardization of the GPP and evapotranspiration deficit data see: <strong>Alsafadi, K., Al-Ansari, N., Mokhtar, A., Mohammed, S., Elbeltagi, A., Sammen, S. S., & Bi, S. (2021). An evapotranspiration deficit-based drought index to detect variability of terrestrial carbon productivity in the Middle East. <em>Environmental Research Letters</em>. <a href="http://dx.doi.org/10.1088/1748-9326/ac4765">10.1088/1748-9326/ac4765</a></strong></p>
Gross primary production responses to warming, elevated CO2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland
<p>Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO<sub>2</sub> (eCO<sub>2</sub>) 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<sub>2</sub> 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 (<i>A</i><sub>max</sub>) and light‐use efficiency (<i>Q</i>) 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 (<i>R</i><sup>2</sup> = 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%, <i>P</i> = 0.02) and eCO<sub>2</sub> (26%, <i>P</i> = 0.07) was primarily driven by enhanced C uptake during spring (129%, <i>P</i> = 0.001) and fall (124%, <i>P</i> = 0.001), respectively, which was consistent across years. Antecedent air temperature (Tair<sub>ant</sub>) and vapor pressure deficit (VPD<sub>ant</sub>) effects on <i>A</i><sub>max</sub> (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<sub>ant</sub> 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<sub>2</sub> 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‐independent data streams for validating TBMs.</p>
eLUE-GPP (MODIS): A global gross primary productivity product based on ecosystem light-use-efficiency model and MODIS EVI
<p>Gross Primary Productivity (GPP) represents the cumulative amount of carbon dioxide (CO<sub>2</sub>) assimilated by green plants through photosynthesis at specific time intervals and spatial scales. It is the main component of the carbon exchange between the terrestrial biosphere and the atmosphere, and has a major influence on global climate and terrestrial ecosystem functioning. Over the last two decades, the continuous and reliable collection of global land surface variables by EOS-MODIS, and the parallel development of the eddy-covariance flux tower network (FLUXNET) have enabled the integration of MODIS observations with tower measurements for the calibration and validation of remote sensing models to obtain global GPP estimates. Despite the significant progress and success to date, current remote sensing GPP models based on the light use efficiency (LUE) concept share several limitations, including the difficulty in accurately predicting LUE variability and the associated use of land cover maps and look-up tables for biome specific maximum LUE, further down-regulated by coarse resolution interpolated meteorological data, which introduce significant uncertainties in the predicted GPP. To address the above limitations, here we applied a simple yet ecologically sound remote sensing GPP model based on the ecosystem light use efficiency (eLUE) concept, using the more than two decades of global MODIS Enhanced Vegetation Index (EVI) product and the publicly available FLUXDATA2015 dataset, to generate a global 5 km, 16-d GPP product (eLUE-GPP) from February 2000 to March 2024. Cross-validation with 202 flux tower sites (1494 site/year) showed favorable accuracy of eLUE-GPP (hereafter GPP<sub>eLUE</sub>) (<em>R</em><sup>2</sup> = 0.71, RMSE = 2.11 g C m<sup>-2</sup> d<sup>-1</sup>). The uncertainty associated with GPP<sub>eLUE</sub> is comparatively lower than that of the other global GPP datasets (MOD17, FluxSat, VPM, among others). We have also calculated the uncertainty analytically for each GPP estimate based on the law of error propagation, which allows quantification of the error budget in applications such as Earth system model benchmarking and atmospheric inversion. Our estimate of global total annual GPP, averaged over the period 2001-2023, was 138.46±13.92 Pg C yr<sup>-1</sup>. Furthermore, we found a significant increasing trend in global total annual GPP at a rate of 0.28±0.05 Pg C yr<sup>-1</sup> (<em>p</em> < 0.001) from 2001 to 2023, particularly in eastern Asia, northern India, Europe, eastern North America, and central South America. We expect that the eLUE-GPP product will enable a more accurate diagnostic analysis of the global carbon budget and thus contribute to climate change research.</p>
eLUE-GPP (MODIS): A global gross primary productivity product based on ecosystem light-use-efficiency model and MODIS EVI
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Gross primary production responses to warming, elevated CO2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland
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Gross primary production and ecosystem respiration measurments based on the Terrestrial Ecosystem Model (TEM)
Gross primary production and ecosystem respiration measurments based on the Terrestrial Ecosystem Model (TEM).
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