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High resolution maps of climatological parameters for analyzing the impacts of climatic changes on Swiss forests
<p>Assessing the impacts of climatic changes on forests requires the analysis of actual climatology within the forested area. In mountainous areas, climatological indices vary markedly with the micro-relief, i.e. with altitude, slope, and aspect. Consequently, when modelling potential shifts of altitudinal belts in mountainous areas due to climatic changes, maps with a high spatial resolution of the underlying climatological indices are fundamental. Here we present a set of maps of climatological indices with a spatial resolution of 25 by 25 m. The presented dataset consists of maps of the following parameters: average daily temperature high and low in January, April, July, and October as well as of the year; seasonal and annual thermal continentality; first and last freezing day; frost-free vegetation period; relative air humidity; solar radiation; and foehn conditions. The parameters represented in the maps have been selected in a knowledge engineering approach. The maps show the climatology of the periods 1961-1990 and 1981-2010. The data can be used for statistical analyses of forest climatology, for developing tree distribution models, and for assessing the impacts of climatic changes on Swiss forests.</p>
Realistic soil carbon sequestration considering food security and climate change
<p>This dataset contains soil organic carbon stocks as described in Keel et al. Global Change Biology (submitted)</p> <p>Annual soil organic carbon (SOC) stocks (t C ha-1, 0-30 cm depth) of Swiss agricultural soils simulated with the model RothC for the years 2020-2100. Simulations were performed for 240 strata (regions with similar agricultural production types, climatic conditions and clay content). The SOC stocks are weighted averages across strata for the national scale. <br> Each column contains SOC stocks for a specific combination of a climate model chains (nine in total) and an emission scenario (three in total: RCP 26, RCP 45, RCP 85) (specified in column header). </p> <p>The results include simulated SOC stocks for a baseline scenario and five soil carbon sequestration (SCS) scenarios (cover crops, biochar amendment at two rates, biochar amendment based on biomass from two agroforestry scenarios). <br> The SCS scenarios were only performed on cropland, therefore there is only a single file for grassland (the baseline scenario). <br> All simulations (i.e. baseline as well as the five scenarios) account for changes in crop shares and organic matter additions associated with growing food demand as well as climate change. </p> <p>The scenarios are described in Keel et al. Global Change Biology (submitted)</p> <p>CL_baseline: Baseline scenario for cropland (CL) <br> GL_baseline: Baseline scenario for permanent grassland (GL)<br> CL_cover_crops: Cover crop scenario for cropland <br> CL_biochar_I: Biochar I scenario for cropland <br> CL_biochar_II: Biochar II scenario for cropland <br> CL_agroforestry_I: Agroforestry I scenario for cropland <br> CL_agroforestry_II: Agroforestry II scenario for cropland </p>
Fig. 6 in Gis Modelling Of The Distribution Of Terrestrial Tortoise Species: Testudo Graeca And Testudo Hermanni (Testudines, Testudinidae) Of Eastern Europe In The Context Of Climate Change
Fig. 6. Result of the analysis of Binomial tests (CliMond 2090 (2081–2100)): A — T. graeca; B — T. hermanni.
Fig. 3 in Gis Modelling Of The Distribution Of Terrestrial Tortoise Species: Testudo Graeca And Testudo Hermanni (Testudines, Testudinidae) Of Eastern Europe In The Context Of Climate Change
Fig. 3. Niche clustering (Geographic space, CliMond 1975 (1970–2000)) from: A — T. graeca (1. T. g. ibera, 2. T. nikolskii, 3. T. g. anamurensis, 4. T. g. floweri, 5. T. g. antakyensis, 6. T. g. pallasi, 7. T. g. armenica, 8. T. g. perses, buxtoni, 9. T. g. terrestris); B — T. hermanni (1. T. h. hermanni, 2. T. h. hervegovinensis, 3. T. h. boettgeri), red circles showing the approximate ranges of subspecies according to "Turtles…, 2017" World" (2017).
Fig. 2 in Gis Modelling Of The Distribution Of Terrestrial Tortoise Species: Testudo Graeca And Testudo Hermanni (Testudines, Testudinidae) Of Eastern Europe In The Context Of Climate Change
Fig. 2. The "Ecological envelope" — relationship bio01 "Annual mean temperature", °C & bio12 "Annual precipitation", mm (DivaGis): A — T. graeca; B — T. hermanni.
Fig. 5 in Gis Modelling Of The Distribution Of Terrestrial Tortoise Species: Testudo Graeca And Testudo Hermanni (Testudines, Testudinidae) Of Eastern Europe In The Context Of Climate Change
Fig. 5. Potential (probabilistic) model of T. hermanni world expansion built in the Maxent program based on the CliMond: A — 1975 (1970–2000); B — 2090 (2081–2100)) climatic data and GBIF data (2021). Areas of the highest habitat suitability (> 0.3–0.5) are colored in red and areas of the lowest (<0.2) — in blue (SAGA GIS).
Fig. 4 in Gis Modelling Of The Distribution Of Terrestrial Tortoise Species: Testudo Graeca And Testudo Hermanni (Testudines, Testudinidae) Of Eastern Europe In The Context Of Climate Change
Fig. 4. Potential (probabilistic) model of T. graeca expansion built in the Maxent program based on the CliMond: A — 1975 (1970–2000); B — 2090 (2081–2100)) climatic data and GBIF data (2021 a). Areas of the highest habitat suitability (> 0.3–0.5) are colored in red and areas of the lowest (<0.2) — in blue (SAGA GIS).
Fig. 1. The potential distribution map for B in Long-Term Bioclimatic Modelling The Distribution Of The Fire-Bellied Toad, Bombina Bombina (Anura, Bombinatoridae), Under The Influence Of Global Climate Change
Fig. 1. The potential distribution map for B. bombina under contemporary climatic conditions. The colour gradient represents high (red) to low (green) habitat suitability for the species.
Fig. 4. The potential distribution map for B. bombina under projected 2050 in Long-Term Bioclimatic Modelling The Distribution Of The Fire-Bellied Toad, Bombina Bombina (Anura, Bombinatoridae), Under The Influence Of Global Climate Change
Fig. 4. The potential distribution map for B. bombina under projected 2050 climatic conditions. The colour gradient represents high (red) to low (green) habitat suitability for the species.
Fig 3 in Long-Term Bioclimatic Modelling The Distribution Of The Fire-Bellied Toad, Bombina Bombina (Anura, Bombinatoridae), Under The Influence Of Global Climate Change
Fig 3. Response curve showing how the logistic prediction changes as the environmental variable Bio2 (Mean diurnal temperature range, oC, X-axis) is varied, keeping all other environmental variables at their average sample value. The curve shows the mean response of the 10 replicate Maxent runs (red) and and the mean +/– one standard deviation (blue).
Replication data for Carleton et al. (Quarterly Journal of Economics, 2022), "Valuing the mortality consequences of climate change accounting for adaptation costs and benefits"
<p>This repository contains replication data for Carleton et al. (Quarterly Journal of Economics, 2022), "Valuing the mortality consequences of climate change accounting for adaptation costs and benefits". All non-confidential data inputs are included, as well as intermediate data outputs, final data outputs, and final tables and figures for all main text and supplementary tables and figures. Some input data are confidential (e.g., mortality records in some countries); therefore, intermediate regression results files are included in the upload to ensure all later stages of the analysis are fully replicable. The full data output files resulting from Monte Carlo simulations of future climate change impacts on mortality far exceed Zenodo file size limits; therefore, key aggregates of the raw output files are included here, which allow for replication of all tables and figures in the paper.</p> <ul> <li><strong>data.zip </strong>contains raw, intermediate, and final datasets</li> <li><strong>outputs.zip </strong>contains output tables and figures </li> </ul> <p>All replication code for the paper is available on a public Github repository, accessible <a href="https://github.com/ClimateImpactLab/carleton_mortality_2022">here</a>.<br><br>The manuscript and supplementary information are available at the QJE, <a href="https://doi.org/10.1093/qje/qjac020">here</a>.</p>
Supplementary data from 'Predicting the distribution of Australian frogs and their overlap with Batrachochytrium dendrobatidis under climate change'
<p><strong><span>Aim: </span></strong><span>Amphibians, with over 40% of assessed species listed as threatened, are disproportionately at risk in the global extinction crisis. Among the many factors implicated in the current and ongoing loss of amphibian biodiversity are climate change and the disease chytridiomycosis, caused by the fungus <em>Batrachochytrium dendrobatidis </em>(<em>Bd</em>). These two threats are of particular concern in Australia, where <em>Bd </em>has been implicated in the declines of at least 43 frog species, and climate change is emerging as an additional threat. Here, we explore how climate change is likely to affect the distributions of Australian frog species and <em>Bd </em>to the year 2100, as well as how the spatial and climatic niche overlap between <a>chytridiomycosis-declined </a></span><span>frogs and <em>Bd</em> could shift.</span></p> <p><strong><span>Location: </span></strong><span>Australia</span></p> <p><strong><span>Methods: </span></strong><span>We used species distribution modelling to infer the current and future distribution of 141 Australian frog species and <em>Bd</em>, under two emissions scenarios. We used metrics of niche similarity, including Schoener's D and the Niche Margin Index, to quantify predicted alterations to spatial interactions between <em>Bd</em> and frog species.</span></p> <p><strong><span>Results: </span></strong><span>Climate change is likely to have a variable impact on frog distributions in Australia, with some 23 and 47 species, primarily in southern Australia, predicted to lose at least 30% of their current distributions under low and high emissions scenarios, respectively. In contrast, 69 and 68 species, respectively, have potential to increase their distributions, primarily in northern Australia. While the distribution of <em>Bd </em>is predicted to decrease, the proportional spatial and niche overlap between <em>Bd </em>and susceptible frog species is predicted to remain little changed, and in some cases, to increase.</span></p> <p><strong><span>Main conclusions: </span></strong><span>Although effects will be variable across the continent, climate change is likely to be a threatening factor to a number of Australian frog species. Additionally, chytridiomycosis is likely to remain a significant threat to many frog species, as any reductions to the pathogen's distribution largely coincide with geographic range contractions of chytridiomycosis-susceptible species.</span></p>
Data supporting "Large-scale citizen science programs can support ecological and climate change assessments"
<p>Text file of phenology observations pulled from the USA National Phenology Network's database (www.usanpn.org) and used in this analysis. </p>
Code and data from: Experiential legacies of early-life dietary polyunsaturated fatty acid (PUFA) content on juvenile Walleye: Potential impacts from climate change
<p>Climate-induced shifts in plankton blooms may alter fish recruitment by affecting the fatty acid composition of early-life diets and corresponding performance. Early-life nutrition may immediately affect survival but may also have a lingering influence on size and growth via experiential legacies. We explored the short- and longer-term performance consequences of different concentrations of polyunsaturated fatty acids (PUFA) for juvenile Walleye (<em>Sander vitreus</em>, Mitchill 1818). For the first 10 d of feeding, juveniles were provided <em>Artemia </em>enriched with: oleic acid (low PUFA), high docosahexaenoic acid and high eicosapentaenoic acid (high PUFA), or high PUFA and a form of vitamin E (high PUFA + E). After 10 d, all fish were fed a high-quality diet and reared for an additional 27 d. Juveniles fed either high PUFA diet were 1.15-fold larger (PUFA mean ± SD = 20.0 ± 3.3 mg; PUFA + E = 19.8 ± 3.3 mg) than those fed the low PUFA (17.3 ± 2.8 mg) diet after 10 d of feeding. After 27 days, juveniles initially fed the high PUFA diet were still 1.10-1.20-fold larger (PUFA = 407.0 ± 61.6 mg; PUFA + E = 422.7 ± 58.7 mg) than those initially fed the low PUFA diet (356.5.0 ± 39.5 mg). Our findings demonstrate that fatty acid composition of juvenile Walleye diets has immediate and lingering size effects. As changes in climate continue to alter lower trophic levels, fish management and conservation may need to consider short- and long-term effects of temporal or spatial differences in early-life diet quality.</p>
Supplementary data to: Climate change threatens terrestrial water storage over the Tibetan Plateau
<p>This data archive includes the boundary of the Tibetan Plateau (TP) and river basins, and projected changes in terrestrial water storage by the mid-21<sup>st</sup> century (up to 2060). The boundary of the TP and river basins is in the shapefile (.shp) format, and all other processed data are in the geotiff (.tif) format. Please see Readme for more data information. For calculation details please see the publication.</p>
Cloudiness delays projected impact of climate change on coral reefs
<p>The increasing frequency of mass coral bleaching and associated coral mortality threaten the future of warmwater coral reefs. Although thermal stress is widely recognized as the main driver of coral bleaching, exposure to light also plays a central role. Future projections of the impacts of climate change on coral reefs have to date focused on temperature change and not considered the role of clouds in attenuating the bleaching response of corals. In this study, we develop temperature- and light-based bleaching prediction algorithms using historical sea surface temperature, cloud cover fraction and downwelling shortwave radiation data together with a global-scale observational bleaching dataset observations. The model is applied to CMIP6 output from the GFDL-ESM4 Earth System Model under four different future scenarios to estimate the effect of incorporating cloudiness on future bleaching frequency, with and without thermal adaptation or acclimation by corals. The results show that in the low emission scenario SSP1-2.6 incorporating clouds delays the bleaching frequency conditions by multiple decades in some regions, yet the majority (>70%) of coral reef cells still experience dangerously frequent bleaching conditions by the end of the century. In the moderate scenario SSP2-4.5, however, thermal stress would overwhelm the mitigating effect of clouds by mid-century. Thermal adaptation or acclimation by corals could further shift the bleaching projections by up to 40 years, yet coral reefs would still experience dangerously frequent bleaching conditions by the end of century in SPP2-4.5. The findings show that multivariate models incorporating factors like light may improve the near-term outlook for coral reefs and help identify future climate refugia, but the long-term future of coral reefs remains questionable in moderate to higher emissions scenario.</p>
Historical and future climate change fosters expansion of Australian harvester termites, Drepanotermes
<p>Past evolutionary adaptations to Australia's aridification can help us to understand potential responses of species in the face of global climate change. Here, we focus on the Australian-endemic termite genus <em>Drepanotermes</em>, which is widespread in semi-arid and arid regions of Australia. We used species delineation, phylogenetic inference, and ancestral state reconstruction to investigate the evolution of mound-building and in relation to reconstructed past climatic conditions. Our results suggest that mound-building evolved several times independently, apparently facilitating expansion into tropical and mesic regions of Australia. Strong phylogenetic signal of bioclimatic variables, especially of limiting environmental factors (e.g. precipitation of warmest quarter), indicates that climate exerts a strong selective pressure. Finally, we used environmental niche modeling to predict present and future habitat suitability for eight <em>Drepanotermes</em> species. Abiotic factors such as annual temperature contributed disproportionately to calibrations, while the inclusion of biotic factors like vegetation cover improved ecological niche models in some species. A comparison between present and future habitat suitability under two different emission scenarios revealed continued suitability of current ranges as well as substantial habitat gains for most studied species, irrespective of nesting habit, yet extensive range expansions in the near future are likely precluded by low dispersal abilities.</p>
Climate Change and 2030 Cooling Demand in Ahmedabad, India: Opportunities for Expansion of Renewable Energy and Cool Roofs (Supplemental Information)
<p>Supplemental information and analysis files for article, "Climate change and 2030 cooling demand in Ahmedabad, India: opportunities for expansion of renewable energy and cool roofs" (Original article available at: https://doi.org/10.1007/s11027-022-10019-4)</p>
Climate change alters sexual signaling in a desert-adapted frog
<p>Climate change is altering species' habitats, phenology, and behavior. Although sexual behaviors impact population persistence and fitness, climate change's effects on sexual signals are understudied. Climate change can directly alter temperature-dependent sexual signals, cause changes in body size or condition that affect signal production, or alter the selective landscape of sexual signals. We tested whether temperature-dependent mating calls of Mexican spadefoot toads (<em>Spea multiplicata</em>) had changed in concert with climate in the Southwestern U.S.A. across 22 years. We document increasing air temperatures, decreasing rainfall, and changing seasonal patterns of temperature and rainfall in the spadefoots' habitat. Despite increasing air temperatures, spadefoots' ephemeral breeding ponds have been getting colder at most elevations, and male calls have been slowing as a result. However, temperature-standardized call characters have become faster and male condition has increased, possibly due to changes in the selective environment. Thus, climate change might generate rapid, complex changes in sexual signals with important evolutionary consequences.</p>
Multi-model Hydropower Projections for the United States Federal Power Marketing Areas under CMIP5 Climate Change Conditions
<p>This dataset contains an ensemble of monthly hydropower generation projections for the United States Federal Hydropower plants for the periods of 1966-2005 (historical period) and 2011-2050 (future period). The dataset includes the monthly hydropower projections developed in (Kao et al. 2016) based on the Watershed Runoff-Energy Storage (WRES) model and is complemented with another ensemble based on the process-based Water Management Power (WMP) model.</p> <p>The hydrologic projections are estimated through a cascading modeling toolchain that include ten global climate change model projections (ACCESS1-0, BCC-CSM1-1, CCSM4, CMCC-CM, GFDL-ESM2M, MIROC5, MPI-ESM-MR, MRI-CGCM3, NorESM1-M and IPSL-CM5A-LR) under RCP8.5 scenario, which are dynamically downscaled with a regional climate model (RegCM4) ( Pal et al. 2007, Giorgi et al. 2012)), which then inform the Variable Infiltration Capacity (VIC) hydrology model (Liang et al. 1994). The ensemble of hydrologic projections is then informing two processes to translate runoff into hydropower projections. First, WRES models monthly river routing and employs a non-linear statistical approach relating monthly natural flow to hydropower generation, including processes such as spilling. Second, MOSART-WM (Voisin et al. 2013), a large-scale river routing and water management model, provides daily reservoir storage and regulated release at dam locations as well as regulated flow at run-of-the-river power plants. The WMP model then translates reservoir and regulated river dynamics into hydropower projections (Zhou et al. 2018). Those projections are further calibrated to monthly generation provided by the federal utilities. The US federal hydropower plants analyzed in this study include 132 facilities that were built and/or are operated by the US Army Corps of Engineers (USACE), the Bureau of Reclamation (Reclamation), and the International Boundary and Water Commission (IBWC). The electricity generation projected for these hydropower plants were aggregated by four Power Marketing Administrations (PMAs), including Bonneville Power Administration (BPA), Southeastern Power Administration (SEPA), Southwestern Power Administration (SWPA), and Western Area Power Administration (WAPA), and their associate subregions.</p> <p>The two files, <em>SWA9505V2_Gsim_PMA_WRES.mat</em> and <em>SWA9505V2_Gsim_PMA_WMP.mat</em>, represent model outputs from the two hydropower models, WRES and WMP respectively.</p> <p>Each file contains 6 variables:</p> <p>1) “Models”: the 10 global climate models (GCMs).</p> <p>2) “PMA_areas”: the 18 subregions of PMAs as defined in (Kao et al. 2015).</p> <p>3) “PMA_G_mn_6605”: 1966-2005 projected monthly hydropower generation for each PMA sub-regions. Dimension: (12 [months], 40 [years], 18 [subregions], 10 [GCMs]). Unit: MWH.</p> <p>4) “PMA_G_mn_1150”: Same as “PMA_G_mn_6605”, but for 2011-2050 projected hydropower generation.</p> <p>5) “PMA_G_yr_6605”: 1966-2005 projected annual hydropower generation. Dimension: (40 [years], 18 [subregions], 10 [GCMs]) . Unit: MWH.</p> <p>6) “PMA_G_yr_1150”: Same as “PMA_G_yr_6605”, but for 2011-2050 projected hydropower generation.</p> <p>The following journal paper details the method in creating the dataset:</p> <p><strong>Impacts of Climate Change on Subannual Hydropower Generation: A Multi-model Assessment of the United States Federal Hydropower Plants</strong></p> <p><strong>Zhou et al. (2022) Preparing for submission to Environmental Research Letters.</strong></p>
ScienceDex guides
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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.