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2,837 results for “Climate Data”
Data from: A camera trap based assessment of climate-driven phenotypic plasticity of seasonal moulting in an endangered carnivore
<p>For many species, the ability to rapidly adapt to changes in seasonality is essential for long-term survival. In the Arctic, seasonal moulting is a key life history event that provides year-round camouflage and thermal protection. However, increased seasonal variability can lead to phenological mismatch. In this study, we investigated whether winter-white (white morph) and winter-brown (blue morph) Arctic foxes (<em>Vulpes lagopus</em>) could adjust their winter-to-summer moult to match local environmental conditions. We used camera trap images spanning an eight-year period to quantify the timing and rate of fur change in a polymorphic subpopulation in south-central Norway. Seasonal snow cover duration and temperature governed the phenology of the spring moult. We observed a later onset and longer moulting duration with decreasing temperature and longer snow season. Additionally, white foxes moulted earlier than blue in years with shorter periods of snow cover and warmer temperatures. These results suggest that phenotypic plasticity allows Arctic foxes to modulate the timing and rate of their spring moult as snow conditions and temperatures fluctuate. With the Arctic warming at an unprecedented rate, understanding the capacity of polar species to physiologically adapt to a changing environment is urgently needed in order to develop adaptive conservation efforts. Moreover, we provide the first evidence for variations in the moulting phenology of blue and white Arctic foxes. Our study underlines the different intraspecific selective pressures that can exist in populations where several morphs co-occur, and illustrates the importance of integrating morph-based differences in future management strategies of such polymorphic species.</p>
DATA FOR: Contemporary tree growth shows altered climate memory
<p><strong>All data (1-4) is publicly available either through the ITRDB, PRISM, or the WestWideDroughtTracker.</strong></p> <p>1. ITRDB sites used in the ITRDB network analysis.</p> <p>2. PRISM (PPT, TEMP) and WWDT (scPDSI) data used in the ITRDB network analysis.</p> <p>2. ITRDB sites used in the Ecologically sampled network analysis.</p> <p>4. PRISM (PPT, TEMP) and WWDT (scPDSI) data used in the Ecologically sampled network analysis.</p> <p>5. An organized data object to run the ITRDB network rjags model; this is an R "list" object readable into R with the "load()" function.</p> <p>6. Additional code for the analysis presented in Fig. 6 in the main text, including monitoring of the "short" antecedent covariate within the model.</p>
Data from: What drives diversification? Range expansion tops climate, life history, habitat, and size in lizards and snakes
<p><strong>Aim: </strong>A major challenge in ecology and evolutionary biology is to explain the dramatic differences in species richness among clades. Much variation in richness is explained by differences in diversification rates among clades, and variation in diversification rates is often linked to various traits. But what types of traits are most important for explaining diversification? Here, we compared the impacts of different types of traits on diversification rates among lizard and snake families, and tested predictions about the relative importance of ecology vs. morphology, static vs. dynamic traits, and alpha vs. beta niche traits.</p> <p><strong>Location: </strong>Global.</p> <p><strong>Time period:</strong> Recent to ~200 million years ago.</p> <p><strong>Major taxa studied:</strong> Squamata.</p> <p><strong>Methods: </strong>We compared the relative impacts of traits related to biogeography (range size, range expansion), climate, life history (viviparity), microhabitat, and morphology (body-size) on diversification rates among all 72 family-level clades of squamates. We compiled data on traits, and tested for relationships between traits and diversification rates using phylogenetic multiple regression models.</p> <p><strong>Results: </strong>The best-fitting model explained ~60% of the variation in diversification rates across squamate families. This model included only microhabitat (proportion of arboreal species) and a novel, dynamic, ecological/biogeographic beta-niche trait (rate of range expansion), which explained most variance. Other variables had more variable or non-significant contributions, including rates of climatic-niche change. Rates of range expansion were related to species richness, larger body size, and faster rates of climatic-niche change.</p> <p><strong>Main conclusions:</strong> Overall, we provide possibly the most comprehensive comparison of the types of traits that can drive diversification. We also help explain diversity patterns in one of the largest vertebrate clades. We show that the rate of range expansion is the most important variable for explaining diversification rates and richness patterns in squamates. We also identify traits that help explain variation in rates of range expansion among clades.</p>
Data and software in support of article submitted to Journal Geophy. Res. Atmos., titled "Self lofting increases altitude of black carbon in a climate model""
<p>The collection provides data and software to support a journal article submission to the Journal of Geophysical Research Atmospheres. The contents will allow potential future investigators to explore the simulation data and reproduce the analyses in the submitted article.</p> <p>This dataset includes 7 tarred files that when expanded will contain a set of netcdf data files and a collection of python programs to read and analyze the data. The data provided in the netcdfs are model outputs from the UK Earth System Model (UKESM1) from a pair of simulations that explored the impact of black carbon aerosol on atmospheric motion.</p> <p> </p>
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The code, scripts, and data used in the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>All Figures&Table and their corresponding NCL scripts are under the directory of Figs&Table. </li> <li>The modified model code, corresponding original model code, and model run scripts are under the directory of Mods_Scripts.</li> <li>The postprocessing NCL scripts, which select useful variables from simulation results, are under the directory of PostProcessing.</li> <li>The zonal mean data from model results used for making figures and corresponding data processing scripts are under the directory of Model_Results.</li> <li>The FORTRAN code used for offline tests is under the directory of Offline_Code.</li> <li>The code, data, and NCL scripts used for the figures and table in the Appendix are under the directory of Appendix.</li> </ul>
Data for: Projecting changes in the frequency and magnitude of ozone pollution events under uncertain climate sensitivity
<p>Climate change is projected to worsen ozone pollution over many populated regions, with larger impacts at higher concentrations. More intense and frequent ozone episodes risk setbacks to human health and environmental policy achievements. However, assessing these changes is complicated by uncertain climate sensitivity, closely related to climate model response, and internal variability in simulations projecting climate's influence on air quality. Here, leveraging a global modeling framework that one-way couples a human activity model, an Earth system model of intermediate complexity, and an atmospheric chemistry model, we investigate the role of climate sensitivity in climate-induced changes to high ozone pollution episodes in the United States using multiple greenhouse gas emissions scenarios, representations of climate sensitivity, and initial condition members. We bias correct and evaluate historical model simulations, identifying modeled and observed O<sub>3</sub> episodes using extreme value theory, and extend the approach to projections of mid- and end-century climate impacts. Results show that the influence of climate sensitivity can be as significant as that of greenhouse gas emissions scenario absent precursor emissions changes. Climate change is projected to increase the magnitude of the highest annually occurring O<sub>3</sub> concentrations by over 2.3 ppb on average across the U.S. at mid-century under a high climate sensitivity and moderate emissions scenario, but the increase is limited to less than 0.3 ppb under lower climate sensitivity. Further, we show that areas in the U.S. currently meeting air quality standards risk being pushed into non-compliance due to a climate-induced increase in frequency of high ozone days.</p>
Replication data for Chen and Khanna. (Global Environmental Change Advances, 2024), "Heterogeneous and Long-Term Effects of a Changing Climate on Bird Biodiversity"
<p>This dataset contains code and data to replicate the results for "Heterogeneous and Long-Term Effects of a Changing Climate on Bird Biodiversity" by Luoye Chen and Madhu Khanna.</p>
Data from: Unveiling the landscape predictors of resilient vegetation in coastal wetlands to inform conservation in the face of climate extremes
<div> <p>Unveiling spatial variation in vegetation resilience to climate extremes can inform effective conservation planning under climate change. Although many conservation efforts are implemented on landscape scales, they often remain blind to landscape variation in vegetation resilience. We explored the distribution of drought-resilient vegetation (i.e., vegetation that could withstand and quickly recover from drought) and its predictors across a heterogeneous coastal landscape under long-term wetland conversion, through a series of high-resolution satellite image interpretations, spatial analyses, and nonlinear modelling. We found that vegetation varied greatly in drought resilience across the coastal wetland landscape and that drought-resilient vegetation could be predicted with distances to coastline and tidal channel. Specifically, drought-resilient vegetation exhibited a nearly bimodal distribution and had a seaward optimum at ~2 km from coastline (corresponding to an inundation frequency of ~30%), a pattern particularly pronounced in areas further away from tidal channels. Furthermore, we found that areas with drought-resilient vegetation were more likely to be eliminated by wetland conversion. Even in protected areas where wetland conversion was slowed, drought-resilient vegetation was increasingly lost to wetland conversion at its landward optimum in combination with rapid plant invasions at its seaward optimum. Our study highlights that the distribution of drought-resilient vegetation can be predicted using landscape features but without incorporating this predictive understanding, conservation efforts may risk failing in the face of climate extremes.</p> <p> </p> <p>This ZIP file contains the following datasets and code for the above paper:</p> <p>1. data_cheng_et_al_GCB_2024.zip This file contain a total of three files.</p> <p>(1) analys_grid_50_m.shp This file is a shapefile for the 50-by-50 m grid cells analyzed in the focal study area and their IDs.</p> <p>(2) veg_change.shp This file contains the spatial distribution of vegetation before and after the 2011 drought. </p> <p> Variable list:</p> <p> change: Changes of vegetation after the 2011 drought.</p> <p> vegBefore: Distribution of vegetation before the drought.</p> <p> vegAfter: Distribution of vegetation after the drought.</p> <p>(3) tidalchannel.shp This file contains manually digitized tidal channels (and water surfaces).</p> <p>2. gridfeatures.xlsx This file contains data on the landscape features of each analysis grid.</p> <p>3. analyses.R This file contains the R code used for data analysis.</p> </div>
Data for global agricultural water scarcity assessment incorporating blue and green water availability under future climate change
<p>This dataset is for the publication Global agricultural water scarcity assessment incorporating blue and green water availability under future climate change by Liu et al., 2022 (Earth's Future, doi: <a href="http://doi.org/10.1029/2021EF002567">10.1029/2021EF002567</a>).</p> <p>Three observation-based global meteorological datasets, namely PGMFD v.2, GSWP3, and WFDEI, were used to calculate ETc over the baseline period. The bias-corrected climate projections of four GCMs (namely GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5) provided by the ISIMIP phase 2b (ISIMIP2b) were used to calculate the ETc over the future period.</p> <p> </p> <p>Liu, X., Liu, W., Tang, Q., Liu, B., Wada, Y., & Yang, H. (2022). Global agricultural water scarcity assessment incorporating blue and green water availability under future climate change. Earth's Future, 10, e2021EF002567. <a href="https://doi.org/10.1029/2021EF002567">https://doi.org/10.1029/2021EF002567</a></p>
Supplementary data to research paper "Linking local climate scenarios to global warming levels: Applicability, prospects and uncertainties"
<p>This file contains supplementary data for the research paper "<span>Linking local climate scenarios to global warming levels: Applicability, prospects and uncertainties"", submitted to IOP Publishing Environmental Research: Climate. The DOI and link to the paper will be added once it is published.</span></p> <p><span>Each file lists the annual mean temperature anomalies relative to the period 1991-2020 for a model of the Austrian climate scenarios OEKS15 (Leuprecht, 2018). The full dataset is available here: https://data.hub.geosphere.at/dataset/oks15_bias_corrected<br></span></p> <p> </p> <div> <div>Leuprecht, A. (2018). <em>ÖKS15 Bias Corrected EURO-CORDEX Model Precipitaion, Radiation, Temperature</em> [dataset]. <a href="https://doi.org/10.60669/B37Q-JD39">https://doi.org/10.60669/B37Q-JD39</a></div> </div>
Data and code for reproduction of: "Climate change to exacerbate the burden of water collection on women's welfare globally"
<p>This repository contains the data and code necessary to reproduce the analysis of the paper:</p> <p> </p> <p>"<span>Climate change to exacerbate the burden of water </span><span>collection on women’s welfare globally"</span></p> <p><span>by Robert Carr, Maximilian Kotz, Peter-Paul Pichler, Helga Weisz, and Leonie Wenz.</span></p> <p> </p> <p><span>Please see the README.txt file for detailed description and instructions on use, and contact maxkotz@pik-potsdam.de for further questions.</span></p>
Data from Climate adaptability in hydrological models: variable storage capacity to improve performance under contrasting climates.
Open the record for dataset details and reuse information.
Data for "Impacts of an active Pacific Meridional Overturning Circulation on the Pliocene climate and hydrological cycle"
<p>Post-Processing Scripts and Data for the Paper<br>Title: Impacts of an Active Pacific Meridional Overturning Circulation on the Pliocene Climate and Hydrological Cycle<br>Authors: Minmin Fu, Alexey Fedorov<br>Publication Year: 2024<br>Contact: minmin.fu@yale.edu</p> <p>Overview<br>This repository contains the post-processing scripts and data used in the paper. It includes Jupyter notebooks for data analysis and plot generation, as well as the GCM output and utilities for adding land-sea masks and proxy sites.</p> <p>Repository Structure<br>notebooks/: Jupyter notebooks for analyzing data and creating plots.<br>data/: GCM output files for reproducing all figures in the paper.<br>utilities/: Functions for adding the land-sea mask and proxy sites.<br>PlioMIP2/: PlioMIP2 boundary conditions.</p> <p>Data<br>The data directory contains the GCM output files necessary for reproducing all figures. Ensure you have the necessary storage space as these files may be large.</p> <p>Utilities<br>The utilities directory contains utility functions, including:</p> <p>Land-Sea Mask Functions: Scripts to apply land-sea masks to the data.<br>Proxy Site Functions: Scripts to integrate proxy site data into the analysis.<br>The PlioMIP2 directory contains the boundary condition files used for the PlioMIP2 experiments.</p>
Data from: Climate interacts with the functional trait structure of tree communities to influence forest productivity
<p>Tree functional diversity can increase forest productivity by enhancing species interactions and providing greater growth stability. However, very few studies have examined the influence of tree community trait structure on survivor growth, recruitment, and mortality simultaneously, which are the main drivers of forest population dynamics. Here we explore the interactions among functional diversity, productivity, and climate to investigate the role of the trait structure of communities on forest productivity and to determine under what circumstances functional diversity should be promoted to ensure forest adaptive capacity under future climate. Using random-forest modeling and a network of permanent sample plots covering a broad gradient of climatic conditions, we isolated the effects of functional diversity—described as the distribution of trait values in a community—and climate variables on net forest productivity (NFP), survivor growth, recruitment, and mortality. Based on our findings, community-level trait structure affects forest productivity in different ways. NFP was influenced by three traits from three different plant strategy dimensions, whereas survivor growth and recruitment were strongly correlated with leaf and resource acquisition traits, and tree mortality with a mix of traits reflecting various plant strategies. We also observed climate interactions with the functional trait structure of tree communities. For instance, we observed an interaction between drought tolerance and mean annual temperature: at low temperatures, NFP biomass accumulation increased with the value of the drought tolerance trait; however, at higher temperatures, the opposite pattern was observed. However, we found contrasting patterns of population response to climate variability, depending on their functional diversity. Greater functional diversity does not necessarily increase biomass accumulation under different climatic conditions.</p> <p><em>Synthesis</em>. As all components of forest productivity contribute to NFP, studies on forest productivity should not only consider survivor growth but also recruitment and mortality. Each component responds differently in terms of biomass changes to climatic variation, according to the trait structure of tree communities. This study provides a framework to identify the trait structure that should be targeted under different climate scenarios to anticipate change and help strengthen forest response capacity to climate change.</p>
Supporting data for "Assessing GFDL-ESM4.1 Climate Responses to a Stratospheric Aerosol Injection Strategy Intented to Avoid Overshoot 2.0°C Warming"
<p>Supporting data for our work on GRL. You will find:</p> <p> - Post-processed data from GFDL-ESM4.1 ssp534os and ssp534os-sai experiments,</p> <p> - python codes for generating the plots in the manuscript.</p>
Data for: Unraveling the influence of essential climatic factors on the number of tones through an extensive database of languages in China
Open the record for dataset details and reuse information.
Data associated with "The importance of terrain and climate for predicting soil organic carbon is highly variable across local to continental scales"
<p>The zipped folder contains the processed soil datasets including covariates, soil depths, and SOC concentrations for training the deep learning models described in the paper "The importance of terrain and climate for predicting soil organic carbon is highly variable across local to continental scales". </p> <p>"soil_profile/" contains a table including the geolocations of all the soil profiles in this study. "patch_data/" and "point_data/" contain the covariates to feed the models with patch input and point input respectively. "depth/" contains the upper and lower depths of the soil samples. "y/" contains the target variable - SOC concentration of the soil samples. The data files with suffix "_1" is a small subset of their counterparts without "_1" (10 % in sample size) used for model hyperparameters tuning.</p>
Data supporting 'Assessing the Spurious Impacts of Ice-Constraining Methods on the Climate Response to Sea-Ice Loss using an Idealized Aquaplanet GCM' by Neil T Lewis et al.
<p>Data supporting Lewis et al., 2024. Assessing the Spurious Impacts of Ice-Constraining Methods on the Climate Response to Sea-Ice Loss using an Idealised Aquaplanet GCM. Submitted to Journal of Climate. </p> <p>All data is in NetCDF format. </p> <p>Output from each experiment is contained in its own folder (e.g., 'ALB.1'). For a description of each experiment, see the accompanying paper. </p> <p>Data files contain the following outputs: </p> <p>dyn_vars_daily_clim.nc contains day of year- and zonally-averaged atmospheric fields (u, v, T, etc). </p> <p>eddy_products.nc constains day of year- and zonally-averaged products of atmospheric fields (e.g., u'v'). </p> <p>ice_temp_daily.nc contains daily-averaged surface temperature and sea-ice thickness. </p> <p>toa_fluxes_clim.nc contains day of year-averaged top of atmosphere radiative fluxes (e.g., OLR). </p> <p>For the experiments NDG1.05, NDG1.1, and NDG1.2, nudge_daily_clim.nc is also included, and contains the day of year-averaged nudging heat flux applied to melt the ice. </p>
Goldenberg, J., Bisschop, K., Bruni, G., Di Nicola, M. R., Banfi, F., Faraone, F. P. "Replication Data for: Melanin-based color variation in response to changing climates in snakes"
<p>This repository contains the data used to produce the manuscrpit "Melanin-based color variation in response to changing climates in snakes" by Goldenberg, J., Bisschop, K., Bruni, G., Di Nicola, M. R., Banfi, F., Faraone, F. P.</p> <p>Article DOI: 10.1002/ece3.11627</p> <p>Journal: Ecology and Evolution</p>
Supplementary geochronological data for "A revised chronostratigraphy of the Triassic-Jurassic Moenave Formation, USA: Implications for timing of continental climate change"
<p>Geochronological data (supplemental tables and figure) related to the article "A revised chronostratigraphy of the Triassic-Jurassic Moenave Formation, USA: Implications for timing of continental climate change", submitted to the Geological Society of America Bulletin.</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.