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382 results for “Climate impacts”
Data from: Herbivory and climate as drivers of woody plant growth: Do deer decrease the impacts of warming?
<p>Vegetation at ecotone transitions between open and forested areas is often heavily affected by two key processes: climate change and management of large herbivore densities. These both drive woody plant state-shifts, determining the location and the nature of the limit between open and tree or shrub-dominated landscapes. In order to adapt management to prevailing and future climate, we need to understand how browsing and climatic factors together affect the growth of plants at biome borders. To disentangle herbivory and climate effects, we combined long-term tree growth monitoring and dendroecology to investigate woody plant growth under different temperatures and red deer (<i>Cervus elaphus</i>) herbivory pressures at forest-moorland ecotones in the Scottish highlands. Reforestation and deer densities are core and conflicting management concerns in the area, and there is an urgent need for additional knowledge. We found that deer herbivory and climate had significant and interactive effects on tree growth: in the presence of red deer, pine (<i>Pinus sylvestris</i>) growth responded more strongly to annual temperature than in the absence of deer, possibly reflecting differing plant-plant competition and facilitation conditions. As expected, pine growth was negatively related to deer density and positively to temperature. However, at the tree population level, warming decreased growth when more than 60% of shoots were browsed. Heather (<i>Calluna vulgaris</i>) growth was negatively related to temperature and the direction of the response to deer switched from negative to positive when mean annual temperatures fell below 6.0°C. In addition, our models allow estimates to be made of how woody plant growth responds under specific combinations of temperature and herbivory, and show how deer management can be adapted to predicted climatic changes in order to more effectively achieve reforestation goals. Our results support the hypothesis that temperature and herbivory have interactive effects on woody plant growth, and thus accounting for just one of these two factors is insufficient for understanding plant growth mechanics at biome transitions. Furthermore, we show that climate-driven woody plant growth increases can be negated by herbivory.</p>
Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models
<p>This contains the data and plot scripts to reproduce the figures of the manuscript: <em>Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models</em>.</p> <p><strong>Authors:</strong></p> <p>Eduardo Moreno-Chamarro<sup>1*</sup>, Louis-Philippe Caron<sup>1,2</sup>, Saskia Loosveldt Tomas<sup>1</sup>, Oliver Gutjahr<sup>3,4</sup> , Marie-Pierre Moine<sup>5</sup>, Dian Putrasahan<sup>3</sup> , Christopher D. Roberts<sup>6</sup>, Malcolm J. Roberts<sup>7</sup>, Retish Senan<sup>6</sup>, Laurent Terray<sup>5</sup>, Etienne Tourigny<sup>1</sup>, Pier Luigi Vidale<sup>8</sup></p> <p><br> <sup>1 Barcelona Supercomputing Center (BSC), Barcelona, Spain.</sup></p> <p><sup>2 Ouranos, Montreal, H3A 1B9, Canada.</sup></p> <p><sup>3 Max Planck Institute for Meteorology. Hamburg, Germany.</sup></p> <p><sup>4 Now at Institut für Meereskunde, Universität Hamburg, Hamburg, Germany.</sup></p> <p><sup>5 CECI, Université de Toulouse, CERFACS/CNRS, Toulouse, France.</sup></p> <p><sup>6 ECMWF European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom.</sup></p> <p><sup>7 Met Office, Exeter EX1 3PB, United Kingdom.</sup></p> <p><sup>8 NCAS-Climate, Department of Meteorology, University of Reading, Reading, United Kingdom.</sup></p> <p><sup>Correspondence to: Eduardo Moreno-Chamarro (eduardo.moreno@bsc.es)</sup></p> <p><strong>Abstract. </strong>We examine the impacts of increased resolution on four long-standing biases using five different climate models developed within the PRIMAVERA project. Atmospheric resolution is increased from ~100–200 km to ~25–50 km, and ocean resolution is increased from ~1° (i.e., eddy-parametrized) to ~0.25° (i.e., eddy-present). For one model, ocean resolution is also increased to 1/12° (i.e., eddy-rich). Fully-coupled general circulation models and their atmosphere-only versions are compared with observations and reanalysis of near-surface temperature, precipitation, cloud cover, net cloud radiative effect, and zonal wind over the period 1980–2014. Both the ensemble mean and the individual models are analyzed. Increased resolution especially in the atmosphere helps reduce the surface warm bias over the tropical upwelling regions in the coupled models, with further improvements in the cloud cover and precipitation biases over the tropical Atlantic particularly. Related to this and to the improvement in the precipitation distribution over the western tropical Pacific, the double ITCZ bias also weakens with resolution. Overall, increased ocean resolution from 1° to 0.25° offers limited improvements or even bias degradation in some models, although an eddy-rich ocean resolution seems beneficial to reduce the North Atlantic cold bias and the Gulf Stream path. Despite the improvements, however, large biases in precipitation and cloud cover persist over the whole tropics as well as in the upper-troposphere zonal winds at mid-latitudes in both coupled and atmosphere-only models at higher resolutions. The SO warm bias also worsens or persists in some coupled models. And a new warm bias emerges in the Labrador Sea in all the high-resolution coupled models. The analysis of the PRIMAVERA models therefore suggests that, to reduce biases, i) increased atmosphere resolution up to ~25–50 km alone might not be sufficient and ii) an eddy-rich ocean resolution might be needed. The study thus adds to evidence that further improved model physics and tuning might be necessary in addition to increased resolution to mitigate biases.</p>
Data from: Impacts of rainfall extremes predicted by climate-change models on major trophic groups in the leaf-litter arthropod community
1. Arthropods in the leaf-litter layer of forest soils influence ecosystem processes such as decomposition. Climate-change models predict both increases and decreases in average rainfall. Increased drought may have greater impacts on the litter arthropod community. In addition to affecting survival or behavior of desiccation-sensitive species, lower rainfall may indirectly lower abundances of consumers that graze drought-stressed fungi, with repercussions for higher trophic levels. 2. We tested the hypothesis that trophic structure will differ between the two rainfall scenarios. In particular, we hypothesized that densities of several broadly defined trophic groupings of arthropods would be lower under reduced rainfall. 3. To test this hypothesis we used sprinklers to impose two rainfall treatments during three growing seasons in roofed, fenced 14-m2 plots; and documented changes in abundance from initial, pre-treatment densities of 39 arthropod taxa. Experimental plots were subjected to either LOW (fortnightly) or HIGH (weekly) average rainfall based upon climate models and the previous 100 years of regional weekly averages. Unroofed open plots, our reference treatment (REF), experienced higher-than-average rainfall during the experiment. 4. The two rainfall extremes produced clear negative effects of lowered rainfall on major trophic groups. Broad categories of fungivores, detritivores and predators were more abundant in HIGH than LOW plots by the final year. Springtails (Collembola), which graze fungal hyphae, were 3x more abundant in the HIGH-rainfall treatment. Taxa of larger-bodied fungivores and detritivores, spiders (Araneae), and non-spider predators were 2x more abundant under HIGH rainfall. Densities of mites (Acari), which include fungivores, detritivores and predators, were 1.5x greater in HIGH rainfall plots. Abundances and community structure of arthropods were similar in REF and experimental plots, showing that effects of rainfall uncovered in the experiment are applicable to nature. 5. This pattern suggests that changes in rainfall will alter bottom-up control processes in a critical detritus-based food web of deciduous forests. Our results, in conjunction with other findings on the impact of desiccation on arthropods and fungal growth, suggest that drier conditions will depress densities of fungal consumers, causing declines in higher trophic levels, with possible impacts on soil processes and the larger forest food web.
Metabolic impacts of climate change on marine fish communities and fisheries - Dataset and figure plot script
<p>Here we provide the MATLAB functions, model forcing data (net primary production and temperature), and model output required to generate the figures and perform calculations from the manuscript "Metabolic impacts of climate change on marine fish communities and fisheries", which is currently in submission as a research article. The figures plot script (plot_figures_climate_fish_deconstruction.m) is written in MATLAB version R2012a.</p>
Integrative assessment of climate change-related impacts and risks on urban land
<p>Shapefile data set estimating trends of mean annual terrestrial surface air temperature (°C) and mean annual total precipitation (mm) and several heat indicators for urban land, characterised by clusters of local spatial autocorrelation in regard to the age of urban area and the coefficient of variation of urban area extent over time.</p>
Data for "Impact of Precipitation Mass Sinks on Midlatitude Storms in Idealized GCM Simulations over a Wide Range of Climates"
<p>Code, simulation input files, and postprocessed simulation output data supporting "Impact of Precipitation Mass Sinks on Midlatitude Storms in Idealized GCM Simulations over a Wide Range of Climates", submitted to Weather and Climate Dynamics. Enclosed README file provides detailed descriptions of the archive contents.</p>
Dataset for "Impacts and state-dependence of AMOC weakening in a warming climate" by Bellomo & Mehling
<p>This dataset allows the user to reproduce figures from the journal article "Impacts and state-dependence of AMOC weakening in a warming climate" by Bellomo & Mehling.</p>
Identifying climate impacts from different stratospheric aerosol injection strategies in UKESM1
<p>Data to plot figures in Identifying climate impacts from different stratospheric aerosol injection strategies in UKESM1 - Wells et al., 2023</p>
Season-specific impacts of climate change on canopy-forming seaweed communities
<p><span>Understory assemblages associated with canopy-forming species such as trees, kelps, and rockweeds should respond strongly to climate stressors due to strong interaction strengths. Climate change can directly and indirectly modify these assemblages, particularly during more stressful seasons and climate scenarios. </span><span>However, fully understanding the seasonal impacts of different climate conditions on canopy-reliant assemblages is difficult due to a continued emphasis on studying single species responses to a single future climate scenario during a single season. To examine these more complex interactions, we used mesocosm experiments to expose intertidal assemblages associated with the canopy-forming golden rockweed, <em>Silvetia compressa</em>, to elevated temperature and pCO<sub>2 </sub>conditions reflecting two projected greenhouse emission scenarios [RCP 2.6 (low) & RCP 4.5 (moderate)]. Assemblages were grown in the presence and absence of <em>Silvetia</em>, and in two seasons. Relative to ambient conditions, predicted climate scenarios generally suppressed <em>Silvetia</em> biomass and photosynthetic efficiency. However, these effects varied seasonally - both future scenarios reduced <em>Silvetia</em> biomass in summer, but only the moderate scenario did so in winter. These reductions shifted the assemblage, with more extreme shifts occurring in summer. Contrarily, future scenarios did not shift assemblages within <em>Silvetia </em>Absent treatments, suggesting that climate primarily affected assemblages indirectly through changes in <em>Silvetia</em>. Mesocosm experiments were coupled with a field <em>Silvetia</em>-removal experiment to simulate the effects of climate-mediated <em>Silvetia</em> loss on natural assemblages. Consistent with the mesocosm experiment, <em>Silvetia</em> loss resulted in season-specific assemblage shifts, with weaker effects observed in winter. Together,</span><span> our study supports the hypotheses that climate-mediated changes to canopy-forming species can indirectly affect the associated assemblage, and that these effects vary seasonally. Such seasonality is important to consider as it may provide periods of recovery when conditions are less stressful, especially if we can reduce the severity of future climate scenarios. </span></p>
Impact of climate on a host-hyperparasite interaction on Arabica coffee in its native range
<p>Natural enemies of plant pathogens might play an important role in controlling plant disease levels in natural and agricultural systems. Yet, plant pathogen-natural enemy interactions might be sensitive to climatic changes. Understanding the relationship between climate, plant pathogens, and their natural enemies is thus important for developing climate-resilient, sustainable agriculture.</p> <p>To this aim, we recorded shade cover, daily minimum and maximum temperature, relative humidity, coffee leaf rust, and its hyperparasite at 58 sites in southwestern Ethiopia during the dry and wet season for two years. </p> <p>Coffee leaf rust severity was positively related to the maximum temperature. Hyperparasite severity was higher when the minimum temperature was low (i.e. in places with cold night temperatures). While canopy cover did not have a direct effect on rust severity, it reduced rust severity indirectly by lowering the maximum temperature. Canopy cover had a direct positive effect on the hyperparasite severity during one surveying period. </p> <p><em><strong>Synthesis and applications.</strong></em> Our findings highlight that coffee leaf rust and its hyperparasite are both affected by shade cover and temperature, but in different ways. On the one hand, these niche differences lead to the worrying prediction that levels of coffee leaf rust will increase, and its hyperparasite will decrease, with climate change. On the other hand, these niche differences between coffee leaf rust and its hyperparasite provide opportunities to develop strategies to manage the environment (such as shade cover and microclimate) in such a way that the rust is disfavored and the hyperparasite is favored.</p>
Supplementary Tables for Can leafhoppers help us trace the impact of climate change on agriculture?
<p>Supplementary Tables for the Preprint entitled: Can leafhoppers help us trace the impact of climate change on agriculture? to be posted in bioRxiv. </p> <p><strong>Table S1. </strong>Detailed information on the strawberry fields included in this study.</p> <p><strong>Table S2</strong>. Detailed information on the weather stations used to retrieve temperature and precipitation data used in this study </p> <p><strong>Table S3. </strong>Strawberry samples analyzed in this study with symptoms resembling strawberry green petal phytoplasma disease during both growing seasons studied here.</p> <p><strong>Table S4.</strong> The geographic location of all the strawberry green petal phytoplasma disease cases reported to the provincial laboratory in expertise in diagnostic and phytopathology in the last decade.</p> <p><strong>Table S5.</strong> Leafhopper species and the number of specimens per species analyzed by phytoplasma-specific PCR to detect the presence of the pathogen.</p> <p><strong>Table S6.</strong> Detailed information on the leafhoppers incubated with strawberry plants during the phytoplasma transmission assays.</p> <p><strong>Table S7.</strong> Detailed information on <em>Macosteles quadrilineatus</em> used to study the leafhopper microbiome.</p> <p><strong>Table S8. </strong>Detailed information on the insecticides used by strawberry growers during both grow seasons included in the study and those treatments selected for further statistic analyses.</p> <p><strong>Table S9. </strong>Identification and number of leafhopper species captured in strawberry fields in each geographic region screened in this study.</p> <p><strong>Table S10. </strong>Detailed information of diversity indexes Shannon and Simpson calculated using the data collected in this study.</p> <p><strong>Table S11.</strong> Fixed days and temperature values used during leafhopper populations modelling.</p> <p><strong>Table S12.</strong> Detailed information on the taxonomy of the phytoplasma strain SbGPQ affecting strawberry plants in eastern Canada by hybridization and illumine sequencing and by PCR amplification, cloning and Sanger sequencing.</p> <p><strong>Table S13.</strong> Detailed information on <em>Macosteles quadrilineatus</em> microbiome including OTUs, reads, and metadata information.</p> <p><strong>Table S14.</strong> Detailed information on the core microbiome for <em>Macosteles quadrilineatus</em> captured during each growing season and in common for all the leafhoppers analyzed during this study.</p> <p><strong>Table S15. </strong><span>BIC values for models selection. </span></p>
Converging findings of climate models and satellite observations on the positive impact of European forests on cloud cover
<p>Overview:<br>This repository hosts a comprehensive dataset resulting from a Space for Time (S4T) analysis (<em>Duveiller et al. 2018</em>). The dataset spans monthly data from 2004 to 2014, providing detailed insights into cloud cover dynamics and land cover characteristics. Leveraging observations from the Cloud CCI MODIS-Aqua dataset (<em>Stengel et al. 2017</em>) and RegCM5 (<em>Giorgi et al. 2023</em>) model outputs at 0.05 degrees resolution, it offers valuable resources for researchers studying atmospheric and terrestrial interactions.</p> <p>Contents:</p> <p>s4t_ESACCI.zip:<br>Output of the space-for-time algorithm applied to the Global MODIS-Aqua cloud cover data for low, medium, and high clouds.<br>s4t_RegCM5.zip:<br>Output of the space for time algorithm applied to the European RegCM5 cloud data for low, medium, and high clouds.<br>Variables:</p> <p>Cloud Area Fractions:<br>Includes low (cll), medium (clm), and high (clh) cloud area fractions, expressed as percentages.<br>Cloud layers are categorized based on cloud top pressure (CTP), following the convention of the International Satellite Cloud Climatology Project.</p>
Data to the Supporting Information to "Radiative Heating of High-Level Clouds and its Impacts on Climate"
<p><strong>Author:</strong> Kerstin Haslehner kerstin.haslehner@univie.ac.at</p> <p>This archive includes the ICON-ESM output files used to study the radiative heating of high-level clouds.</p> <p>This dataset is related to the manuscript "Radiative Heating of High-Level Clouds and its Impacts on Climate" by Kerstin Haslehner, Blaž Gasparini and Aiko Voigt, which will be submitted to the Journal of Geophysical Research: Atmospheres.</p> <p>The output data was originally created as part of a Master's thesis by Kerstin Haslehner at the Department of Meteorology and Geophysics at University Vienna. This thesis is available here: https://utheses.univie.ac.at/detail/67015/#</p> <p> </p> <p>Descriptions of names:</p> <p>"clouds off": radiative heating of all clouds turned off</p> <p>"ice-off": radiative heating of when clouds at temperatures colder than -35°C are turned off</p> <p>"ice-off-warmbase": radiative heating of high-level clouds turned off</p> <p>"ice-on": radiative heating of all clouds active, reference run</p> <p>"diagice-cirrus": contains output variables that diagnose the radiative heating of clouds at temperatures colder than -35°C</p> <p>"hl": height levels</p>
Data to "Radiative Heating of High-Level Clouds and its Impacts on Climate"
<p><strong>Author:</strong> Kerstin Haslehner kerstin.haslehner@univie.ac.at</p> <p>This archive includes the ICON-ESM output files used to study the radiative heating of high-level clouds.</p> <p>This dataset is related to the manuscript "Radiative Heating of High-Level Clouds and its Impacts on Climate" by Kerstin Haslehner, Blaž Gasparini and Aiko Voigt, which will be submitted to the Journal of Geophysical Research: Atmospheres.</p> <p>The output data was originally created as part of a Master's thesis by Kerstin Haslehner at the Department of Meteorology and Geophysics at University Vienna. This thesis is available here: https://utheses.univie.ac.at/detail/67015/#</p> <p> </p> <p>Descriptions of names:</p> <p>"clouds off": radiative heating of all clouds turned off</p> <p>"ice-off-warmbase": radiative heating of high-level clouds turned off</p> <p>"ice-on": radiative heating of all clouds active, reference run</p> <p>"diagice-warmbase": contains output variables that diagnose the radiative heating of high-level clouds</p> <p>"diagice-cirrus": contains output variables that diagnose the radiative heating of clouds at temperatures colder than -35°C</p> <p>"ua700": zonal wind at 700hPa</p> <p>"mastrfu": mass stream function, calculated with CDO</p> <p>"hl": height levels</p> <p>"wap500hPa": omega at 500hPa</p>
Data from: Evaluating the impact of historical climate and early human groups in the Araucaria Forest of Eastern South America
<p>It has been hypothesized that the Araucaria Forest in Southern Brazil underwent expansions in the past, driven either by human groups or by climate fluctuations of the Holocene and Pleistocene. Fossil pollen records of the Paraná Pine (<em>Araucaria angustifolia</em>), a dominant tree in that forest, provide some insights into when those may have occurred. Still, the timing of those expansions has never been estimated. To infer past range shifts and shed light on their main drivers, we employed next-generation DNA sequencing (ddRADseq), machine learning, and a comprehensive database of fossil pollen records in a study of historical demographic inference and paleo-distribution modeling of the Paraná Pine. We found that <em>A. angustifolia</em> comprises two populations expanding at different times: one in the Mantiqueira mountain chain, and the other in the southern Brazilian plateau. The Southern population began to expand during the Last Glacial Period ~70kya, long before human arrival in South America. Still, genetic analyses support that humans later impacted this population, resulting in lower genetic diversity, higher inbreeding, and high levels of gene flow over large distances with a weak pattern of isolation by distance. It is possible this resulted from human influence on seed dispersal and germination on the Southern Brazilian plateau. The Mantiqueira population, in contrast, expanded only recently (~3kya). This timing coincides with Holocene climatic changes and human settlements established further south, although, to date, there is little archeological evidence of human impact in the Mantiqueira. In addition, multitemporal species distribution models built from a combination of present-day and pollen records infer range expansion of the Araucaria Forest during glacial times until the cold humid HS1 event (~16kya), when the forest was most widespread, with no evidence of glacial refugia. The combination of genomic and spatial analyses suggests that both human and climatic controls played a role in the dynamics of the Araucaria Forest.</p>
Data for: A protocol for model intercomparison of impacts of Marine Cloud Brightening Climate Intervention
<p>Replication data for "A protocol for model intercomparison of impacts of Marine Cloud Brightening Climate Intervention" submitted to Geophysical Model Development.</p>
Data from: Climate change is predicted to impact the global distribution and richness of pines (genus Pinus) by 2070
<p>Aim: Climate change is altering habitat suitability for many organisms and modifying species ranges at a global scale. Here we explored the impact of climate change on 112 pine species (<em>Pinus</em>), fundamental elements of Northern terrestrial ecosystems.</p> <p>Location: Global.</p> <p>Methods: We applied a novel methodology for species distribution modelling that considers uncertainty in climatic projections and taxon sampling, and incorporates elements of species' recent evolutionary history. We based our niche calculations on climate and soil data and computed projections across multiple algorithms and IPCC scenarios, which were ensembled into one single suitability map. We then used phylogenetic methods to account for recent evolution in climatic requirements by estimating the evolution of climatic niche. Edaphoclimatic and evolutionary analyses were then combined to calibrate the projections in areas showing high uncertainty. We validated our models using naturalized occurrences of invasive pine species.</p> <p>Results: Our models predicted that by 2070 most pine species (58%) might face important reductions of habitat suitability, potentially leading to range losses and a decrease in species richness, particularly in some regions such as the Mediterranean Basin and South North America, albeit migration might mitigate these shifts in some cases. In contrast, our projections showed increased habitat suitability for approx. 20% of species, which may undergo range expansions under climate change. Moreover, the consideration of recent evolutionary trends modified projected scenarios, decreasing range loss and increasing range expansion for some species. The independent validation endorsed our models for many species and the influence of recent evolution in some cases.</p> <p>Conclusions: We predict that climate change will impose drastic changes in pine distribution and diversity across biogeographical regions, but the magnitude and direction of change will vary significantly across regions and taxa. Species-level responses are likely to be influenced by regional conditions and the recent evolutionary history of each taxon.</p>
Modelling 21st-century refugia and the impact of climate change on Amazonia's largest primates
<p>Edaphic and vegetation conditions can render climatically suitable sites inadequate for a species to persist, constraining the amount of suitable habitat and the possibilities of tracking preferred climatic conditions as they shift in response to climate change. We combined climatic and remotely sensed data to model current and future distributions of nine extant taxa of ateline primates across the Amazon basin. We used the models to identify and quantify potential range changes and refugia of suitable habitats from the present to the latter half of the 21st century.<strong> </strong>We applied an ensemble forecasting approach for species distribution models using 596 spatially rarefied occurrences. We parameterised these models by combining reflectance data from a basin‐wide Landsat TM/ETM+ image composite, three sets of bioclimatic layers containing data for the current period, and two different (moderate and worst-case) climate change scenarios for 2041-2070. Eight out of nine taxa are likely to experience pronounced range losses, with seven of them predicted to lose over 50% of their currently suitable habitats irrespective of climate change scenarios. Modelled ateline richness exhibited a broad decrease in high-richness areas and a possible redistribution along the northernmost parts of western Amazonia. Refugia from 21st-century climate change for the whole complex was mostly concentrated in western Amazonia, especially in its southern part. We identified hotspots of vulnerability to climate change and 21st-century refugia for all Amazonian atelines while accounting for habitat characteristics that are important to guarantee the continued existence of suitable habitats for these strictly arboreal taxa. Increasing the understanding of climate change impacts on Amazonia's largest primates can help to inform spatial conservation planning decisions and management to sustain forest-dwelling biodiversity over large areas such as Amazonia.</p>
Spatiotemporal dynamics of grassland aboveground biomass in northern China and the alpine region: Impacts of climate change and human activities
<p>We employed CASA model to estimate grassland Net Primary Productivity and aboveground biomass A(AGB) from meteorological and GIMMS Normalized Difference Vegetation Index (NDVI) remote sensing data in northern China. We analyzed the dynamics of grassland AGB and impacts climate change and human activites.</p>
Spatiotemporal dynamics of grassland aboveground biomass in northern China and the alpine region: Impacts of climate change and human activities
<p>We employed CASA model to estimate grassland Net Primary Productivity and aboveground biomass A(AGB) from meteorological and GIMMS Normalized Difference Vegetation Index (NDVI) remote sensing data in northern China. We analyzed the dynamics of grassland AGB and impacts climate change and human activites.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.