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54 results for “environmental productivity”
Datasets for "The direct and indirect effects of the environmental factors on global terrestrial gross primary productivity over the past four decades"
<p>The environmental changes can affect gross primary productivity (GPP) by altering not only the biogeochemical characteristics of the photosynthesis system (direct effects) but also the structure of the vegetation canopy (indirect effects). However, comprehensively quantifying the multi-pathway effects of environmental change on GPP is currently challenging. We proposed a framework to analyse the changes in global GPP by combining a nested machine-learning model and a theoretical photosynthesis model. We quantified direct and indirect effects of changes in key environmental factors (atmospheric CO2 concentration, temperature, solar radiation, vapor pressure deficit (VPD), and soil moisture) on global GPP from 1982 to 2020. The three datasets(RF_LAI, RF_GPP, and RF_GPPlai) are derived from LAI random forest model, GPP random forest model and hierarchical nested model respectively.</p>
Global meta-analysis of individual and combined nitrogen inhibitors: Enhancing plant productivity and reducing environmental losses
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Code and Data for: Importance of environmental productivity and diet quality in intraguild predation
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Data from: High environmental stress and productivity increase functional diversity along a deep-sea hydrothermal vent gradient
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Seed Production Survey, 1988-2009, Adirondack Long-Term Ecological Monitoring Program Project No. 26 by Adirondack Ecological Center of the State University of New York College of Environmental Science and Forestry, Newcomb, New York, USA
The purpose of this project is to 1) estimate number of seeds per unit area in a mature northern hardwood/mixed conifer forest stand and 2) document changes over time in selected tree and shrub seed production. Permanent seed traps were established in 1988 in two forest types. Seed traps (13.9 L [5 gal] capacity buckets) are installed 0.5 m off the ground on two metal stakes in the center of each forested plot. Buckets are open to the tree canopy and have small (< 2cm) holes near the bottom edges for drainage. Fifty collection buckets are placed approximately 30 m (100 feet) apart and distributed along painted grid lines in the Huntington Wildlife Forest Natural Area. Twenty-five plots are northern hardwood upland forest (dominated by sugar maple, American beech and yellow birch with some conifers) and 25 plots are in the mixed hardwood/conifer lakeshore forest type (dominated by red maple, yellow birch, red spruce and eastern hemlock). Tree and shrub seeds are collected annually during two periods: July to November (Fall) and November to July (Spring). The spring and autumn collections are based on tree species’ seed phenology. If a bucket was tipped over due to disturbance by a bear or some other factor, it was censored from the survey for that year. Mice or other seed predators that were physically found/present in buckets also resulted in sample censoring. Animal scat or partly-consumed seeds are not censored, as these may have fallen from the tree canopy during seed predators’ normal activities.
Milk production and environmental conditions of mountain-pastured Braunvieh cows between 2000 and 2015
<p>This dataset is a subset of the dataset used in the associated article, linking environmental data to milk records of mountain-pastured cows between 2000 and 2015.</p> <p>In particular it contains information on the cow and lactation cycle (lactation number, date of calving, date of first record in the alp, average quantity of milk over 3 milk records taken in the alp) and environmental condition (temperature humidity index, cold stress index, averaged over 3 and 30 days before the milk records and precipitation during spring).</p> <p>This dataset does not allow the reproducibility of the associated article but enables the analysis of conjoint milk data and associated environmental conditions. It should be noted that the publication of the full dataset was not possible.</p>
Data from: Plant functional diversity modulates global environmental change effects on grassland productivity
1. Although much research has explored changes in ecosystem functions associated with global environmental changes, the mechanistic pathways behind the observed changes remain poorly understood. 2. Using an 11-year experiment that increased growing season precipitation and nitrogen deposition in a temperate steppe, we explored the relative importance of direct and indirect environmental change effects on plant primary productivity. 3. We show that increases in water and nitrogen availability influenced plant productivity via both direct and indirect pathways. While both treatments stimulated plant productivity, changes in plant productivity cannot be explained by observed changes in species or phylogenetic diversity. Instead, the indirect effects of water and nitrogen addition were through their positive effects on plant functional diversity. Importantly, while the increase in one component of functional diversity (community-level weighted mean of plant stature) resulted in increased productivity, the increase in another component of functional diversity (functional dispersion) resulted in decreased productivity. 4. Synthesis. Our study provides the first evidence for the opposite effects of community weighted means and functional dispersion of plant functional traits on grassland productivity, and highlights the importance of both traits of dominant species and trait distribution among species in modulating the effects of global changes on ecosystem functions.
Data from: Analysing biodiversity and conservation knowledge products to support regional environmental assessments
Two processes for regional environmental assessment are currently underway: the Global Environment Outlook (GEO) and Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES). Both face constraints of data, time, capacity, and resources. To support these assessments, we disaggregate three global knowledge products according to their regions and subregions. These products are: The IUCN Red List of Threatened Species, Key Biodiversity Areas (specifically Important Bird & Biodiversity Areas [IBAs], and Alliance for Zero Extinction [AZE] sites), and Protected Planet. We present fourteen Data citations: numbers of species occurring and percentages threatened; numbers of endemics and percentages threatened; downscaled Red List Indices for mammals, birds, and amphibians; numbers, mean sizes, and percentage coverages of IBAs and AZE sites; percentage coverage of land and sea by protected areas; and trends in percentages of IBAs and AZE sites wholly covered by protected areas. These data will inform the regional/subregional assessment chapters on the status of biodiversity, drivers of its decline, and institutional responses, and greatly facilitate comparability and consistency between the different regional/subregional assessments.
Data from: ECOALIM: a dataset of environmental impacts of feed ingredients used in French animal production
Feeds contribute highly to environmental impacts of livestock products. Therefore, formulating low-impact feeds requires data on environmental impacts of feed ingredients with consistent perimeters and methodology for life cycle assessment (LCA). We created the ECOALIM dataset of life cycle inventories (LCIs) and associated impacts of feed ingredients used in animal production in France. It provides several perimeters for LCIs (field gate, storage agency gate, plant gate and harbour gate) with homogeneously collected data from French R&D institutes covering the 2005–2012 period. The dataset of environmental impacts is available as a Microsoft® Excel spreadsheet on the ECOALIM website and provides climate change, acidification, eutrophication, non-renewable and total cumulative energy demand, phosphorus demand, and land occupation. LCIs in the ECOALIM dataset are available in the AGRIBALYSE® database in SimaPro® software. The typology performed on the dataset classified the 149 average feed ingredients into categories of low impact (co-products of plant origin and minerals), high impact (feed-use amino acids, fats and vitamins) and intermediate impact (cereals, oilseeds, oil meals and protein crops). Therefore, the ECOALIM dataset can be used by feed manufacturers and LCA practitioners to investigate formulation of low-impact feeds. It also provides data for environmental evaluation of feeds and animal production systems. Included in AGRIBALYSE® database and SimaPro®, the ECOALIM dataset will benefit from their procedures for maintenance and regular updating. Future use can also include environmental labelling of commercial products from livestock production.
Primary production and environmental variables from 1971 to 2021 in the North Basin of Lake Biwa
<p><strong>Abstract: </strong>Global climate change and anthropogenic oligotrophication are expected to reshape the dynamics of primary production (PP) in aquatic ecosystems however, few studies have explored their long-term effects. In theory, the PP of phytoplankton in Lake Biwa may decline over decades due to warming, heightened stratification, and anthropogenic oligotrophication. Furthermore, the PP of large phytoplankton, which are inedible to zooplankton, along with biomass-specific productivity (PBc), could decrease. In this study, data from 1976–2021 and active fluorometry measurements taken in 2020 and 2021 were evaluated. Quantitatively, the temporal dynamics of mean seasonal PP during 1971–2021 were assessed according to the carbon fixation rate to investigate relationships among environmental factors. Qualitatively, phytoplankton biomass, PP, and PBc were measured in two size fractions [edible (S) or inedible (L) for zooplankton] in 2020 and 2021, and the L:S balance for these three measures was compared between 1992 (low-temperature/high-nutrient conditions) and 2020–2021 (high-temperature/low-nutrient conditions) to assess seasonal dynamics. The results indicated that climate change and anthropogenic oligotrophication over the past 50 years have diminished Lake Biwa's PP since the 1990s, impacting the phenology of PP dynamics. However, the L:S balance in PP and PBc has exhibited minimal change since 1992. These findings suggest that, although climate change and oligotrophication may reduce overall PP, they do not markedly alter the inedible/edible phytoplankton balance in terms of PP and PBc. Instead, as total PP declines, the production of small edible phytoplankton decreases proportionally, potentially affecting trophic transfer efficiency and material cycling in Lake Biwa.</p>
Supporting Information: Environmental benefits of large-scale second-generation bioethanol production in the EU: An integrated supply chain network optimization and Life Cycle Assessment approache
<p>This supporting information provides all input data of the model, the assumptions made and the literature and database references for the publication<em> Environmental benefits of large-scale second-generation bioethanol production in the EU: An integrated supply chain network optimization and Life Cycle Assessment approache</em>. The environmental data is based on life cycle assessments, with full information on the life cycle inventory and the results of the life cycle impact assessment based on the ReCiPe method. It also includes detailed results for all objective functions in all scenarios (optimization of 18 midpoints, 3 endpoints, and economic optimization in 5 tax scenarios and 2 feedstock scenarios), and detailed results of the sensitivity analysis and Pareto optimization.</p>
Data for: Modular environmental and economic assessment applied to the production of Hermetia illucens
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China's Greener Production Reduces East-to-West Pollution Transfers and Alleviates Environmental-Economic Inequalities
<p>The data contains 1. Pro-andCon-base_APE_Value added (the production- and consumption-based APE and value added in 2007, 2012, 2017, and the change); 2. f_d (the production- and consumption-based emission intensity (<em>f</em>) and value added intensity (<em>d</em>) in 2007, 2012, 2017); 3. REI_REIC (the REI index in 2007 and 2017, and REIC index); 4. ape_flow2007 (the APE flows in 2007); 5. ape_flow2012 (the APE flows in 2012); 6. ape_flow2017 (the APE flows in 2017); 7. ape_flowchange (the change of the APE flows from 2007 to 2017); 8. va_flow2007 (the value added flows in 2007); 9. va_flow2012 (the value added flows in 2012); 10. va_flow2017 (the value added flows in 2017); 11. va_flowchange (the change of the value added flows from 2007 to 2017);</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>
Raw data for Mangan et al,. Loss and replacement of macroalgal standing stock and productivity after a major environmental disturbance
<p>Raw data for the journal article: Mangan et al., (2023). Loss and replacement of macroalgal standing stock and productivity after a major environmental disturbance. Ecosphere.</p>
Data from: ECOALIM: a dataset of environmental impacts of feed ingredients used in French animal production
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Data from: Genetic and environmental determinants of unreduced gamete production in Brassica napus, Sinapis arvensis and their hybrids
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Data from: Plant functional diversity modulates global environmental change effects on grassland productivity
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Data from: Analysing biodiversity and conservation knowledge products to support regional environmental assessments
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Data from: Genome analysis reveals genetic admixture and signature of selection for productivity and environmental traits in Iraqi cattle
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.