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1,141 results for “primary_productivity”
Data from: Geographical variation in ant foraging activity and resource use is driven by climate and net primary productivity
<p><b>Aim: </b>Foraging activity is critical for animal survival. Comprehending how ecological drivers influence foraging behavior would benefit our understanding of the link between animals and ecological processes. Here, we evaluated the influence of ecological drivers on ant foraging activity and relative resource use.</p> <p><b>Location: </b>Six Brazilian biomes: Amazon, Atlantic rainforest, Caatinga, Cerrado, Pampa and Pantanal.</p> <p><b>Taxon: </b>Formicidae.</p> <p><b>Methods: </b>We assessed ant foraging activity and resource use by sampling across 60 sites. We placed baited tubes that contained one of five liquid resources (sugar, lipids, amino acid, sodium and distilled water). We used model selection to assess the influence of ecological drivers (temperature, precipitation, temperature seasonality and net primary productivity) on ant foraging activity and relative resource use.</p> <p><b>Results: </b>Foraging activity was higher in wetter, more productive and less thermally seasonal environments. The relative use of amino acids increased at higher temperatures while the relative use of lipids decreased. The relative use of sugar increased in drier and less productive environments with high temperature seasonality while the relative use of amino acid and sodium decreased in those environments. The relative use of lipids was complex: increasing with increasing temperature seasonality and decreasing with increasing precipitation. Further, the relative use of sodium was greater where the foraging activity was high.</p> <p><b>Main Conclusions: </b>We demonstrate how ecological drivers are correlated to ant foraging activity and resource use in the field across large spatial scales. The search for resources encompasses different interactions involving ants with abiotic and biotic components in the ecosystem. Thus, we suggest that changes in climate and NPP, which influence the intensity and the way that ants search for resources, will result in changes in ant-mediated ecological processes.</p>
Model simulations for " Potential impacts of LUCC and climate change on evapotranspiration and gross primary productivity in the Haihe River Basin, China"
<p>Experiment_1.rar, Experiment_2.rar, and Experiment_3.rar are the model simulations from experiment 1, experiment 2, and experiment 3, respectively. All the simulations are original from the CLM5 model in netcdf format.</p> <p>More details on these data can be found in the paper "Potential impacts of LUCC and climate change on evapotranspiration and gross primary productivity in the Haihe River Basin, China". </p>
Above- and below-ground net primary productivity: a field-based global database of grasslands
<p>Net primary productivity (NPP) over global grasslands is crucial for understanding the terrestrial carbon cycling and for the assessments of wild herbivores food security. During the past few decades, numerous field investigations have been conducted to estimate grassland NPP since the measuring criterion released by the International Biological Program. However, a comprehensive NPP database, particularly for belowground NPP (BNPP), in global grasslands is rare to date. Here, field NPP measurements from 438 publications (1957–2018) in global grasslands were collected, critically filtered, and incorporated in a comprehensive global database with observations for aboveground NPP (ANPP), BNPP, total NPP (TNPP), and BNPP fraction (fBNPP). Associated information on geographical locations, climatic records, grassland types, land use patterns, manipulations subjected to manipulative experiments, sampling year of study sites as well as NPP measurement methods are also documented. This database included 2985 entries from 1785 study sites. Among them, 806 entries contained paired data of ANPP and BNPP, resulting in the 806 fBNPP data. The study sites encompassed global grasslands with latitudinal range of 54.5° S~78.9° N, longitudinal range of 157.4° W~175.8° E, and altitudes from 0 to 5168 m above sea level, covering broad climatic gradients (-17.6 to 28.8 °C in mean annual temperature and 63 to 2052 mm in mean annual precipitation). This global database is the world's largest paired data of ANPP and BNPP field measurements in grasslands. It can be used to study the spatio-temporal patterns of NPP and its allocation, evaluate the responses of above- and below-ground carbon components to future global changes, and validate the NPP estimation by empirical or process-based models in global grasslands. The database can be freely used for non-commercial applications. We kindly request users cite this data paper when using the database, respecting all the hard work during data compilation.</p>
Evapotranspiration components, soil water content and net primary productivity in a black locust plantation
<p>ET components, i.e. transpiration (T), soil evaporation(E) and canopy interception (I), soil water and net primary productivity (NPP), water use efficiency (WUE) were estimated in a black locust plantation during a drier (2015) and a wetter (2016) growing season (i.e., June to September).</p>
Zonal mean of primary production and carbon export in the Southern Ocean (Huang and Fassbender, 2023, Geophysical Research Letters)
<p>This dataset contains zonal means of primary production, export potential of distinct biogenic carbon pools, particle sinking flux, and particle export efficiency in the Southern Ocean. See more details in the relevant publication of Huang and Fassbender (2023, Geophysical Research Letters).</p> <p> </p>
Augmented Net Primary Production in Arctic Ocean Sustained by Increased Subarctic Inflow Water
<p>Developing an optical classification-based chlorophyll (Chla) retrieval algorithm for the Arctic Ocean by matching in situ and remote sensing data. The statistical relationship between mixed layer depth integrated primary productivity (NPP) and sea surface Chla was also regressed from a large field measurement data set. Through principal component analysis and correlation analysis, NPP environmental driving factors were analyzed. Data sets include remote sensing reflectance data used to invert NPP and environmental drivers of NPP changes.</p>
Comparison of primary production between different models and measurements in the Indian Ocean
<p>This data set contains the various cruises data of Chlorophyll, Primary Production, photic zone integrated chlorophyll and normalized chlorophyll in the Indian Ocean.</p> <p> </p>
Global Gross Primary Productivity (GPP) Dataset 2020 (GeoTIFF) - ZIP file
<p>Product: Gross Primary Productivity (GPP)</p> <p>Year: 2020</p> <p>Region: Global (in MODIS tile grid)</p> <p>Temporal Scale: 8 Days</p> <p>Spatial Resolution: 500 meters</p> <p>Method: Light-use-efficiency (LUE) approach.</p> <p>Referred Publications: https://www.sciencedirect.com/science/article/pii/S0048969718307149</p> <p>https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261</p> <p>This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. </p> <p><strong>NOTE:</strong> This dataset has been produced in the MODIS tile format, to allow comparison to existing products. </p>
MUSES 500m Global Annual Gross and Net Primary Productivity Dataset
<p>The MUltiscale Satellite remotE Sensing (MUSES) 500m global annual vegetation productivity dataset includes gross primary productivity (GPP) and net primary productivity (NPP) data from 2001 to 2019. GPP and NPP were estimated with a light use efficiency (LUE) model and GLASS leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR) products.</p> <p>The MUSES product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/).</p> <p>The detail information of the MUSES 500m global annual GPP and NPP dataset is as below:</p> <p>Name: MUSES 500m global annual GPP and NPP dataset</p> <p>Period: 2001-2019</p> <p>Projection: Sinusoidal projection;</p> <p>Spatial resolution: 463.3127165 m;</p> <p>Temporal resolution: annual;</p> <p>Data format: zipped GeoTiff file;</p> <p>Data type: unsigned short integer (16bit);</p> <p>Image size: 86400 columns, 36000 rows</p> <p>Upper left coordinates: ULX = -20015109.354 m, ULY = 10007554.677 m;</p> <p>Scale factor: 10. NPP = DN / scale factor; GPP = DN / scale factor;</p> <p>Unit: gC/m<sup>2</sup>/yr.</p> <p> </p> <p>Citation (Please cite these papers when these data are used)</p> <p>1. Wang, J.M., Sun, R., Zhang, H.L., Xiao, Z.Q., Zhu A.R., Wang, M.J., Yu, T., Xiang, K.L., New global MuSyQ GPP/NPP remote sensing products from 1981 to 2018. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14, 5596-5612.</p> <p>2. Wang, M.J.; Sun, R.; Zhu, A.R.; Xiao, Z. Q. Evaluation and Comparison of Light Use Efficiency and Gross Primary Productivity Using Three Different Approaches. Remote Sensing. 2020, 12, 1003.</p> <p>3. Yu, T.; Sun, R.; Xiao, Z.Q. ;Zhang , Q.; Liu, G.; Cui, T.X.; Wang, J.M. Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data. Remote sensing. 2018, 10, 327.</p>
A global 0.05° gross primary productivity of sunlit and shaded leaves dataset via combining two-leaf light use efficiency model with random forest over 2002~2020
<p>The TL-CRF model generated a global 0.05´0.05° product for eight-day gross primary productivity (GPP) of sunlit and shaded canopies from 2002 to 2020 by embedding the random forest (RF) submodule into the two-leaf light use efficiency (TL-LUE) model while considering the seasonal differences in the clumping index. The RF technique was used to integrate various environmental stress factors including meteorological, hydrological, soil properties, and elevation, thereby improving the overall scale of the complex environmental conditions to the maximum LUE. This novel GPP product could support further research on spatial and temporal patterns of the carbon cycle and its association with climate change.</p> <p> </p> <p> </p> <p>Variable: GPP, GPP<sub>sh</sub>, and GPP<sub>su</sub></p> <p>Spatial coverage: global</p> <p>Temporal coverage: 2002 to 2020</p> <p>Spatial resolution: 0.05×0.05°</p> <p>Temporal resolution: eight-day</p> <p>Unite: g C m<sup>−2</sup> d<sup>−1</sup></p> <p>Data format: raster (.tif)</p>
A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production: Dataset 3
<p>This dataset is part of the LUIcube, a global dataset on land-use at 30 arcsecond spatial resolution. The LUIcube includes information on area, the change in NPP due to land conversions (HANPP<sub>luc</sub>), the harvested NPP (including losses, HANPP<sub>harv</sub>), and the NPP remaining in ecosystems after harvest (NPP<sub>eco</sub>) for 32 land-use classes in annual time-steps from 1992 to 2020. A detailed description of the LUIcube is available in the accompanying publication.</p> <p>The layers of land-use areas are provided in square kilometers (km²) per grid cell. All NPP flows are provided in tC/yr per grid cell. Adding HANPP<sub>harv</sub> to NPP<sub>eco</sub> results in the actual NPP available before harvest (NPP<sub>act</sub>=NPP<sub>eco</sub>+HANPP<sub>harv</sub>), and adding HANPP<sub>luc</sub> to NPP<sub>act</sub> results in the potential NPP available in the hypothetical absence of land use (NPP<sub>pot</sub>=NPP<sub>act</sub>+HANPP<sub>luc</sub>) for the given land-use class. Area-intensive values (in gC/m²/yr) can be calculated by dividing the NPP flows by the area of the respective land-use class per grid cell. HANPP in % of NPP<sub>pot</sub> can be calculated by summing up HANPP<sub>harv</sub> and HANPP<sub>luc</sub> and dividing it by NPP<sub>pot</sub>. Areas and NPP flows of land-use classes can be aggregated to calculate their overall HANPP.</p> <p>This Zenodo repository provides data on following land-use classes: grazing land with (almost) no trees (GL-notrees); cropland used for production of other fibres (CL-OFIB); fallow cropland areas (CL-FALL)</p>
Data from: Primary production calculations for sea ice from bio-optical observations in the Baltic Sea
Bio-optics is a powerful approach for estimating photosynthesis rates, but has seldom been applied to sea ice, where measuring photosynthesis is a challenge. We measured absorption coefficients of chromophoric dissolved organic matter (CDOM), algae, and non-algal particles along with solar radiation, albedo and transmittance at four sea-ice stations in the Gulf of Finland, Baltic Sea. This unique compilation of optical and biological data for Baltic Sea ice was used to build a radiative transfer model describing the light field and the light absorption by algae in 1-cm increments. The maximum quantum yields and photoadaptation of photosynthesis were determined from 14C-incorporation in photosynthetic-irradiance experiments using melted ice. The quantum yields were applied to the radiative transfer model estimating the rate of photosynthesis based on incident solar irradiance measured at 1-min intervals. The calculated depth-integrated mean primary production was 5 mg C m–2 d–1 for the surface layer (0–20 cm ice depth) at Station 3 (fast ice) and 0.5 mg C m–2 d–1 for the bottom layer (20–57 cm ice depth). Additional calculations were performed for typical sea ice in the area in March using all ice types and a typical light spectrum, resulting in depth-integrated mean primary production rates of 34 and 5.6 mg C m–2 d–1 in surface ice and bottom ice, respectively. These calculated rates were compared to rates determined from 14C incorporation experiments with melted ice incubated in situ. The rate of the calculated photosynthesis and the rates measured in situ at Station 3 were lower than those calculated by the bio-optical algorithm for typical conditions in March in the Gulf of Finland by the bio-optical algorithm. Nevertheless, our study shows the applicability of bio-optics for estimating the photosynthesis of sea-ice algae.
Data from: Primary productivity explains size variation across the Pallid bat's (Antrozous pallidus) western geographic range
1. Body size is associated with many aspects of the life history, ecology, and physiology of animals. Within a species, body size can vary substantially across space and time, and the mechanisms generating these patterns have been the focus of evolutionary and ecology research. 2. Bergmann's Rule predicts a negative relationship between body size and temperature across the geographic range of endothermic animals; larger animals have a lower surface to volume ratio, which would allow for greater heat conservation. Despite the broad support for this pattern, its underlying mechanisms are heavily debated. Numerous alternative explanations have been proposed to explain why larger animals are found in colder climates, and vice versa, including heat dissipation, environmental seasonality, and resource availability. 3. We used the Pallid bat, Antrozous pallidus, as a model to evaluate Bergmannian size patterns and the relative support for major explanatory hypotheses of geographic body size variation. We tested the hypothesis that geographic size variation is predicted by productivity, as opposed to seasonality, heat conservation or dissipation, or some combination of these processes. Additionally, we investigated the potential ecomorphological consequences of size variation in Pallid bats by determining if skull shape (an indicator of bite performance) varies with size. 4. Whereas we did find that Pallid bat populations in northern latitudes are composed of larger individuals, our results suggest that net primary productivity and, to a lesser extent heat conservation, best explains size variation throughout the western range of this species. We also found that skull shape in Pallid bats changes in tandem with skull size, with larger bats having cranial traits associated with greater bite force production. 5. The results of our study indicate that variation in resource availability may be a key factor underlying spatial patterns in size, morphology and, possibly, feeding performance within wide-ranging bat species.
Data from: Response of net primary production to land use and climate changes in the middle-reaches of the Heihe River basin
Net primary production (NPP) supplies matter, energy, and services to facilitate the sustainable development of human society and ecosystem. The response mechanism of NPP to land use and climate changes is essential for food security and biodiversity conservation but lacks a comprehensive understanding, especially in arid and semi-arid regions. To this end, taking the middle-reaches of the Heihe River basin (MHRB) as an example, we uncovered the NPP responses to land use and climate changes by integrating multi-source data (e.g., MOD17A3 NPP, land use, temperature, and precipitation) and multiple methods. The results showed that: (1) land use intensity (LUI) increasing, and climate warming and wetting promoted NPP. From 2000 to 2014, the LUI, temperature and precipitation of MHRB increased by 1.46, 0.58 °C and 15.76 mm, respectively, resulting in an increase of 14.62 gC/m2 in annual average NPP. (2) The conversion of low-yield cropland to forest and grassland increased NPP. Although the widespread conversion of unused land and grassland to cropland boosted both LUI and NPP, it was not conducive to ecosystem sustainability and stability due to huge water consumption and human-appropriated NPP. Urban sprawl occupied cropland, forest and grassland, and reduced NPP. (3) Increase in temperature and precipitation generally improved NPP. The temperature decreasing less than 1.2 °C also promoted the NPP of hardy vegetation due to the simultaneous precipitation increasing. However, warming-induced water stress compromised the NPP in arid sparse grassland and deserts. Cropland had greater NPP and NPP increase than natural vegetation due to the irrigation, fertilizers and other artificial inputs it received. Decrease in both temperature and precipitation generally reduced NPP, but the NPP in the well-protection or less-disturbance areas still increased slightly.
C:N:P stoichiometric indicator of net primary production of Cynodon dactylon (Linn.) Pers. in the riparian zone of a Three Gorges tributary
<p>Net primary production (NPP) was strongly influenced by the flooding stress, which is closely related to carbon (C), nitrogen (N) and phosphorus (P) allocation in plant aboveground (leaf-stem) and belowground (root) biomass. However, the relationship of NPP with the C:N:P stoichiometric ratio in plant tissues remains unknown, especially in the riparian zone of the Three Gorges Reservoir (TGR). In this study, the leaf-stem and root C, N, P content and biomass of <i>Cynodon dactylon (Linn.) Pers. </i>(<i>C. dactylon</i>) were investigated at the 145-155m, 155-165m and 165-175m altitudes of the riparian zone in TGR tributary-Pengxi River. The results showed that the biomass and NPP of <i>C. dactylon</i> had a similar trend along the riparian zone altitudes. The root showed much lower N and P content, but much higher N and P use efficiency with higher C:N and C:P ratio than that of leaf-stem under N limitation condition. Hydrological and C:N:P stoichiometric variables could predict 68% of the NPP variance. NPP was positively directly correlated to C:N in the stem-leaf to root ratio (C:N<sub>stem-leaf/root</sub>) and C:P ratio in the root<sub> </sub>(C:P<sub>root </sub>ratio ), thus could be regarded as the indicators of NPP in the riparian zone of the TGR.</p>
Potential increasing marine primary production in stratified shelf seas under climate warming
<p>Chronological framework and biogenic silicon (BSi) content of sediment core NYS05 (122.67°E, 37.83°N; 545 cm in length) collected from the North Yellow Sea. The chronological framework was based on AMS <sup>14</sup>C analysis of foraminifera and shell and calibrated by Marine13 curve. BSi content was determined by silicon molybdenum blue method.</p>
Three datasets of global monthly gross primary productivity (GPP) during 2003-2018 derived from SIF, NIRv and LAI and their best-matching environmental factors
<p>As the largest source of uncertainty in carbon cycle studies, accurate quantification of gross primary productivity (GPP) is critical for the global carbon budget in the context of global climate change. Numerous remote sensing vegetation indices (VIs) have participated in the estimation of global GPP. However, the relative performance of various VIs in estimating GPP and what additional factors should be combined with them to reveal the photosynthetic capacity of vegetation mechanistically better are still poorly understood.</p> <p>We used the Random Forest (RF) algorithm to identify the factors with the most powerful explanation of GPP and to explore the importance of these predictors. We trained six RF models to select features, i.e., two types of models (Plant Functional Type [PFT]-specific and universal) for each vegetation index (SIF, NIRv, and LAI). Each model comprised 100 decision trees, was sampled without replacement, and was trained using 70% of the data. Model performance was evaluated using out-of-bag (OOB) R-squared (R<sup>2</sup>) and root mean square error (RMSE) values. The predictor with the lowest importance score in the iteration was removed and the whole procedure was then repeated until only the vegetation index, CO<sub>2</sub>, and PFTs were left. The predictors used to estimate GPP were identified based on the performance curve of OOB R<sup>2</sup> and RMSE. The determination of the model is based on the principle that further reductions in the number of predictors would considerably reduce model performance, while increasing the number of predictors would not significantly improve model performance.</p> <p>Here we provide a set of high-spatial resolution (1/12°) global gridded products of monthly GPP for 2003-2018 generated for each vegetation index based on a generic model with an optimal configuration, i.e., an optimal combination of VI and other relevant variables using the RF algorithm. R<sup>2</sup> of three optimal VI-based GPP estimation models ranges from 0.84 to 0.85, and RMSE ranges from 1.51g C·m<sup>−2</sup>·d<sup>−1</sup> to 1.54g C·m<sup>−2</sup>·d<sup>−1</sup>. More information about the datasets can be found in Zhao and Zhu (2022) <strong><em>Remote Sensing</em></strong>.</p> <p><em>Zhao W, Zhu Z. Exploring the Best-Matching Plant Traits and Environmental Factors for Vegetation Indices in Estimates of Global Gross Primary Productivity[J]. Remote Sensing, 2022, 14(24): 6316.</em></p>
《Effects of Typhoons on primary production and dissolved oxygen in the East China Sea》dataset
<p>Data used in the article《Effects of Typhoons on primary production and dissolved oxygen in the East China Sea》</p>
The linkage between methane fluxes and gross primary productivity at diurnal and seasonal scales on a rice paddy field in Eastern China
<p>The data includes the hourly and seasonal data (eddy flux and meteorological data)</p>
Simulations from four process-based ecosystem models describing primary productivity in a tallgrass prairie long-term irrigation experiment
<p class="MsoNormal"><span>To demonstrate current capabilities in modeling herbaceous ecosystems, we selected four different process-based models that vary in their representation of community change from no community representation to vegetation demographic models. These models were used to simulate a long-term irrigation experiment at a US tallgrass prairie (Konza Prairie Biological Station) following a standardized simulation protocol. Specifically, we were interested in how model output under a monotonic increase in water availability matched up to experimental findings of (1) herbaceous plant community change and (2) aboveground net primary productivity before and after the plant community change. The results of this simulation are included here.</span></p>
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