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608 results for “Heat stress”
Supplementary material 2 from: Brzoska P, Fügener T, Moderow U, Ziemann A, Schünemann C, Westermann J, Grunewald K, Maul L (2022) Towards a web tool for assessing the impact of climate change adaptation measures on heat stress at urban site level. One Ecosystem 7: e85559. https://doi.org/10.3897/oneeco.7.e85559
Table of data inputs/outputs
Supplementary material 1 from: Brzoska P, Fügener T, Moderow U, Ziemann A, Schünemann C, Westermann J, Grunewald K, Maul L (2022) Towards a web tool for assessing the impact of climate change adaptation measures on heat stress at urban site level. One Ecosystem 7: e85559. https://doi.org/10.3897/oneeco.7.e85559
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Supplementary material 1 from: Sprondel N, Donner J, Mahlkow N, Köppel J (2016) Urban climate and heat stress: how likely is the implementation of adaptation measures in mid-latitude cities? The case of façade greening analyzed with Bayesian networks. One Ecosystem 1: e9280. https://doi.org/10.3897/oneeco.1.e9280
Questionnaire for Bayesian network analysis
Fig. 2 in Oxidative stress parameters in juvenile Brazilian flounder Paralichthys orbignyanus (Valenciennes, 1839) (Pleuronectiformes: Paralichthyidae) exposed to cold and heat shocks
Fig. 2. (TBARS), (GST) and (CAT) activity in the gills of Paralichthys orbignyanus juveniles exposed to different temperatures (17.1, 23.0 and 28.8ºC) as a function of time exposition (72 h). Values are expressed as means ± SEM, N=5. aLower case letters indicate significantly different at the different temperatures and same time (P <0.05), determined by two-way ANOVA and by Dunnet test. ACapital letters indicate significantly different at the same temperatures and different times (P <0.05), determined by two-way ANOVA and by Dunnet test.
A global high-resolution and bias-corrected dataset of CMIP6 projected heat stress metrics
<p><strong>Motivation</strong></p> <p>Increasing heat stress due to climate change poses significant risks to human health and can lead to widespread social and economic consequences. Evaluating these impacts requires reliable datasets of heat stress projections. </p> <p><strong>Data Record</strong></p> <p><strong>CMIP6</strong></p> <p>We present a global dataset projecting future dry-bulb, wet-bulb, and wet-bulb globe temperatures under 1-4°C global warming scenarios (at 0.5°C intervals) relative to the preindustrial era, using outputs from 16 CMIP6 global climate models (GCMs) (Table 1). All variables were retrieved from the historical and SSP585 scenarios which were selected to maximize the warming signal.</p> <p>Wet-bulb and wet-bulb globe temperature are calculated using the Davies-Jones[1] and Liljegren[2] approach respectively.</p> <p>The dataset was bias-corrected against ERA5 reanalysis by incorporating the GCM-simulated climate change signal onto the ERA5 baseline (1950-1976) at a 3-hourly frequency. It therefore includes a 27-year sample for each GCM under each warming target.</p> <p>The data is provided at a fine spatial resolution of 0.25° x 0.25° and a temporal resolution of 3 hours, and is stored in a self-describing NetCDF format. Filenames follow the pattern "VAR_bias_corrected_3hr_GCM_XC_yyyy.nc", where:</p> <ul> <li> <p>"VAR" represents the variable (Ta, Tw, WBGT for dry-bulb, wet-bulb, and wet-bulb globe temperature, respectively),</p> </li> <li> <p>"GCM" denotes the CMIP6 GCM name,</p> </li> <li> <p>"X" indicates the warming target compared to the preindustrial period,</p> </li> <li> <p>"yyyy" represents the year index (0001-0027) of the 27-year sample</p> </li> </ul> <p><strong>Table 1 </strong>CMIP6 GCMs used for generating the dataset for Ta, Tw and WBGT.</p> <div> <table> <tbody> <tr> <td> <p>GCM</p> </td> <td> <p>Realization</p> </td> <td> <p>GCM grid spacing</p> </td> <td> <p>Ta</p> </td> <td> <p>Tw</p> </td> <td> <p>WBGT</p> </td> </tr> <tr> <td> <p>ACCESS-CM2</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.25ox1.875o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>BCC-CSM2-MR</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.1ox1.125o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>CanESM5</p> </td> <td> <p>r1i1p2f1</p> </td> <td> <p>2.8ox2.8o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>CMCC-CM2-SR5</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>0.94ox1.25o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>CMCC-ESM2</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>0.94ox1.25o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>CNRM-CM6-1</p> </td> <td> <p>r1i1p1f2</p> </td> <td> <p>1.4ox1.4o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> </td> </tr> <tr> <td> <p>EC-Earth3</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>0.7ox0.7o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>GFDL-ESM4</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.0ox1.25o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>HadGEM3-GC31-LL</p> </td> <td> <p>r1i1p1f3</p> </td> <td> <p>1.25ox1.875o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>HadGEM3-GC31-MM</p> </td> <td> <p>r1i1p1f3</p> </td> <td> <p>0.55ox0.83o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>KACE-1-0-G</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.25ox1.875o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>KIOST-ESM</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.9ox1.9o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>MIROC-ES2L</p> </td> <td> <p>r1i1p1f2</p> </td> <td> <p>2.8ox2.8o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>MIROC6</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.4ox1.4o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>MPI-ESM1-2-HR</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>0.93ox0.93o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> <tr> <td> <p>MPI-ESM1-2-LR</p> </td> <td> <p>r1i1p1f1</p> </td> <td> <p>1.85ox1.875o</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> <td> <p>✓</p> </td> </tr> </tbody> </table> </div> <p><strong>ERA5</strong></p> <p>We also provide hourly Tw and WBGT derived from ERA5 reanalysis during 1950-2023 to enable analyses of heat stress changes from historical period to a warmer climate.</p> <p><strong> </strong></p> <p><strong>Data Access</strong></p> <p>An inventory of the dataset is available in this repository. The complete dataset, approximately 57 TB in size, is freely accessible via Purdue Fortress' long-term archive through Globus. The bias-corrected CMIP6 dataset is available at <a href="https://transfer.rcac.purdue.edu/file-manager?origin_id=6538f53a-1ea7-4c13-a0cf-10478190b901&origin_path=%2F">Globus Link1</a>, and the ERA5 dataset is available at <a href="https://transfer.rcac.purdue.edu/file-manager?destination_id=63242aea-d3e0-4aa4-9372-0e19dd0c6539&destination_path=%2F">Globus Link2</a>. After clicking the link, users may be prompted to log in with a Purdue institutional Globus account. You can switch to your institutional account, or log in via a personal Globus ID, Gmail, GitHub handle, or ORCID ID. Alternatively, the dataset can be accessed by searching for the universally unique identifier (UUID)—"6538f53a-1ea7-4c13-a0cf-10478190b901" for CMIP6, and “63242aea-d3e0-4aa4-9372-0e19dd0c6539” for ERA5 dataset—in Globus.</p> <p><strong>Dataset Validation</strong></p> <p>We validate the bias-correction method and show that it significantly enhances the GCMs' accuracy in reproducing both the annual average and the full range of quantiles for all metrics within an ERA5 reference climate state. This dataset is expected to support future research on projected changes in mean and extreme heat stress and the assessment of related health and socio-economic impacts.</p> <p>For a detailed introduction to the dataset and its validation, please refer to our data descriptor currently under review at Scientific Data. We will update this information upon publication.</p> <p><strong><br><br><br></strong></p>
Data and code to support the paper: "Heat stress on the brown seaweed Ascophyllum nodosum: differential population sensitivity to future climate."
<p>This repository corresponds to the data and scripts required to replicate analysis presented in paper: <br> "Heat Stress on the brown Seaweed Ascophyllum nodosum: differential population sensitivity to future climate."</p> <p>It imports and analysis data on:<br> </p> <ul> <li>Growth;</li> <li>Net primary production (Npp);</li> <li>Respiration;</li> <li>Survival;</li> <li>Temperature modellation (In situ via climatic variables);</li> <li>Cummulative-product survivability hindcast and forecast;</li> <li>Population size modellation via survivability models together with demographic matricial data.</li> </ul>
Heterotrophy in parental coral colonies enhances larval survival independently of heat stress
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Evolution of sex-specific heat stress tolerance and larval Hsp70 expression in populations of Drosophila melanogaster adapted to larval crowding
<p class="BodyA">The ability to tolerate temperature stress is an important component of adult fitness. In holometabolous insects like <i>Drosophila melanogaster,</i> adult stress resistance can be affected by growth conditions experienced during the larval stages. While evolution under crowded larval conditions is known to lead to the correlated evolution of many adult traits, its consequences on adult heat stress tolerance have not been investigated. Therefore, in the present study, we assessed the adult heat stress tolerance in populations of <i>D.</i><i> </i><i>melanogaster</i> adapted to a stressful larval crowding environment. We used replicate populations of <i>D.</i><i> </i><i>melanogaster</i>, selected for adaptation to larval crowding stress (MCUs), for more than 230 generations, and their respective controls (MBs). Larvae from selected and control populations were grown under crowded and uncrowded conditions and their adult heat shock resistance at two different temperatures was measured. Further, we compared Hsp70 expression in crowded and uncrowded larvae of both populations and also measured the Hsp70 expression after a mild-heat treatment in adults of selected and control populations. Our results showed that adaptation to larval crowding leads to the evolution of Hsp70 gene expression in larval stages and improves adult heat-stress tolerance ability in males, but not in females. </p>
Data for "Heat stress reduces the contribution of diazotrophs to coral holobiont nitrogen cycling"
<p>Raw data associated with publication 'Heat stress reduces the importance of diazotrophs for coral holobiont nitrogen cycling'. </p> <p>"Rädecker_etal_16S.csv" contains sequence abundance data of annotated 16S rRNA ASVs for all five coral colonies during control or heat stress conditions at day 10 of the experiment. </p> <p>"Rädecker_etal_nifH.csv" contains sequence abundance data of annotated nifH rRNA ASVs for all five coral colonies during control or heat stress conditions at day 10 of the experiment. </p> <p>"Rädecker_etal_N2Fix.csv" contains bulk (acetylene reduction) as well as net (15N2 assimilation) measurements of microbial nitrogen fixation for all five coral colonies during control or heat stress conditions at day 10 of the experiment. </p> <p>"Rädecker_etal_NanoSIMS.csvv" contains raw mass count data of coral host and algal symbiont ROIs (15 images per treatment) for one coral colony during control or heat stress conditions at day 10 of the experiment. </p>
Effect of Exercise and Heat Stress on Acute Cardiometabolic Adaptations in Healthy Young Adults
ClinicalTrials.gov study NCT06872762. IPD Sharing: NO. Countries: 1. Publications: 0.
C. rufifacies heat stress data
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Data from: Untangling the roles of microclimate, behaviour and physiological polymorphism in governing vulnerability of intertidal snails to heat stress
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Data from: Social tipping points in animal societies in response to heat stress
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Data from: The effects of Bacillus subtilis on Caenorhabditis elegans fitness after heat stress
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Data from: Differential response to heat-stress among evolutionary lineages of an aquatic invertebrate species complex
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Data from: Carried over: heat stress in the egg stage reduces subsequent performance in a butterfly
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Evolution of sex-specific heat stress tolerance and larval Hsp70 expression in populations of Drosophila melanogaster adapted to larval crowding
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Data from: Reversible, specific, active aggregates of endogenous proteins assemble upon heat stress
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Data from: A positive genetic correlation between hypoxia tolerance and heat tolerance supports a controversial theory of heat stress
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Data from: Time of day prioritizes the pool of translating mRNAs in response to heat stress
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.