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2,260 results for “climate change”
Fig. 3 in Adaptations, life-history traits and ecological mechanisms of parasites to survive extremes and environmental unpredictability in the face of climate change
Fig. 3. Flow chart outlining factors that can influence the response of parasites to climate change.
Climate Change Adaptive Resilience Analysis Dataset
<p><span>Greenhouse gas escalation and severely deteriorated environment with global warming and climate change impose substantial difficulties in energy resilience for adaption and mitigation of climate change and zero-carbon transitions. However, uncertainties in supply-demand from climate change and climate-adaptive resilience for electrified and integrative PV-battery-building systems remain unclear. In this research, following </span><span>zero-energy building design principles and innovative U-value/M-value battery sizing methods</span><span>, a </span><span>tailored</span><span> </span><span>‘kWp-kWh-m<sup>2</sup>’ design approach is proposed with </span><span>intrinsic relationships of prosumer-storage</span><span> to achieve renewable self-sufficiency and avoid battery oversizing</span><span> in both centralized and distributed forms.<a name="OLE_LINK1"></a> Comprehensive analysis is conducted by assessing economic-environmental indicators, such as levelized costs of storage, net present values, decarbonization potentials, and policy incentives, followed by the evaluation of provincial system configurations considering energy system variations across diverse climate change conditions and geographic areas. </span><span>Results reveal significant regional variations induced by climatic conditions, resource availability, local grid energy structure, and electricity prices. Notably, the long-term economic-ecological viability of the proposed PV-battery-building system is highlighted, especially with optimal battery integrations. As climate change progresses, the research provides invaluable guidelines for zero-energy transitions from optimal system design, provincial-level system configurations, and performance evaluation, guiding the strategic investment and targeted policy interventions towards sustainability transformations.</span></p> <p><span>The comprehensive dataset encompasses 25-year time series of instantaneous photovoltaic (PV) generation, building electricity demand, PV-battery system performance, and battery capacity sizing procedures across five distinct climatic regions in China. This data accounts for the impacts of different climate change scenarios, including the typical year as well as the Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 for the years 2020, 2030, 2060, and 2100. </span></p>
Modelling environmental suitability of sorghum, wheat and maize in Europe under climate change (Code & data)
<p><span>Wheat and maize play an important role as crops for human consumption and animal feed in Europe. To guarantee food security and the stability of the agricultural sector in Europe, it is crucial to determine how climate change will impact the environmental suitability and thus the potential geographic distribution of these crops. Sorghum, a crop that originates in Africa, has seen a recent increase in cultivation in Europe. Due to its tolerance to more extreme climate conditions and its versatility of use, it might inherit a high potential as an alternative crop. </span></p> <p><span>Occurrence data of sorghum, wheat and maize as well as several environmental variables were used as input data for an ensemble modelling approach that averages machine learning models for species distribution modelling (SDM). CHELSA served as a source for present bioclimatic conditions and future climate scenarios, namely SSP126 and SSP370 for the period 2041-2070, and HSWD supplied soil variables, since both climate and soil influence crop development. A set of models was evaluated to select the best performing models for the ensemble modelling. The ensemble models were extrapolated to the future scenarios to predict geographic shifts of suitable cultivation areas due to climate change and analyze sorghum’s potential as an alternative crop. </span></p> <p><span>Under the climate scenarios, the three crops saw a shift of suitability in Europe with losses in Southern Europe and expansions of suitable environmental conditions in the northeast of Europe. Sorghum was the crop with the highest potential to replace maize and wheat in Southern Europe in areas where they lose suitability under climate change. Therefore, sorghum confirmed its function as an alternative crop. It also was the crop that benefits consistently from climate change, growing its total suitable area in Europe under both climate scenarios. Maize loses total suitable area in Europe in both climate scenarios but kept the highest amount of total suitable area in Europe in all projected time periods. </span></p> <p><span>The outcome of this study is of high importance for European farmers and policy makers as it enables them to apply effective adaptation and mitigation strategies that will support crop production under future climate conditions. <br></span></p>
Estimating future climate change impacts on human mortality and crop yields via air pollution: supplemental files
<p>Atmospheric chemistry model output and other gridded data sets necessary to estimate human mortality and crop yield losses associated with future climate change, as used in Murray et al. [PNAS, 2024] doi:10.1073/pnas.2400117121.</p>
Data and analysis code for Repo et al., "Contrasting forest management strategies: impacts on biodiversity and ecosystem services under changing climate and disturbance regimes"
<p>This repository contains analysis code and pre-processed data for the study "Contrasting forest management strategies: impacts on biodiversity and ecosystem services under changing climate and disturbance regimes" by Repo et al.<br>Data processing and analysis mainly done by Aapo Jantunen, Katharina Albrich<br>Due to respository space limitations, the original model outputs are archived in the Finnish "Allas" data storage service. For access, contact katharina.albrich@luke.fi<br>The code used to process the raw data is included here for reproducibility.</p> <p>If you are interested in using iLand, visit https://iland-model.org/ and https://iland-model.org/iland-book/ for information on using the model and a guide to setting up a landscape.</p> <p><span>This work was supported by the Ministry of Agriculture and Forestry by funding project Future multifunctional forests and their disturbance risk in the changing climate (Foster) through the “Catch the Carbon” initiative (<span>project number VN/28654/2020)</span>. A.R. has been supported by the grant [TRACY Trade-offs and synergies in land-based climate change mitigation and biodiversity conservation decision 322066 by the Academy of Finland.], J. H by the grant [CASCADE - Changing Disturbance Regimes and Forest Landscapes of Fennoscandia 342569 by the Academy of Finland]. </span></p> <p> </p>
Linked collectors and determiners for: Potential indicator species of climate changes occurring in Québec, Part 1: the small brown lacewing fly Micromus posticus (Walker) (Neuroptera: Hemerobiidae).
Natural history specimen data linked to collectors and determiners held within, "Potential indicator species of climate changes occurring in Québec, Part 1: the small brown lacewing fly Micromus posticus (Walker) (Neuroptera: Hemerobiidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/8260db39-8776-4ad6-bd80-46e4e1168bf7">https://bionomia.net/dataset/8260db39-8776-4ad6-bd80-46e4e1168bf7</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/8260db39-8776-4ad6-bd80-46e4e1168bf7">https://gbif.org/dataset/8260db39-8776-4ad6-bd80-46e4e1168bf7</a>. Formatted as a Frictionless Data package.
Japanese Small-scale fishers adaptive capacity and furthest response to climate change
<p>The database contains data collected from 25 communities along the western coast of Shikoku, Japan, between January and March 2023. It includes values of adaptive capacity indicators aligned with the adaptive capacity domains outlined by Cinner and Barnes (2019). Additionally, the dataset captures fishers' responses to climate change, following the adaptation pathways proposed by Fedele et al. (2019) and Ojea et al. (2020).<br><br>References: </p> <p>Fedele, G., Donatti, C. I., Harvey, C. A., Hannah, L. & Hole, D. G. Transformative adaptation to climate change for sustainable social-ecological systems. <em>Environmental Science & Policy</em> <strong>101</strong>, 116–125 (2019).</p> <p>Cinner, J. E. & Barnes, M. L. Social Dimensions of Resilience in Social-Ecological Systems. <em>One Earth</em> <strong>1</strong>, 51–56 (2019).</p> <p>Ojea, E., Lester, S. E. & Salgueiro-Otero, D. Adaptation of Fishing Communities to Climate-Driven Shifts in Target Species. One Earth 2, 544–556 (2020).</p>
Oriental Honey-Buzzards Dataset | Climate change leads to range contraction for the Oriental Honey-Buzzards: How to point out the future conservation strategies?
<p>This dataset contains raster data (.TIF) in probability and binary outputs of oriental honey-buzzards distribution within the wintering and breeding areas under changing climate.</p> <p><strong>File Size</strong>: ~184 MB (13.8 MB in compressed ZIP file)</p> <p><strong>Format File</strong>:</p> <p><em>ohb_A_B_C</em>.tif (.tfw; .XML; .dbf)</p> <p><strong>A</strong>: breeding or wintering</p> <p><strong>B</strong>: timepoint and scenario. e.g., 2050ssp5 or 2010ssp2</p> <p><strong>C</strong>: binary or probability outputs. e.g., bin or prob. <em>Note: for binary maps, value 0: non-suitable areas for OHB and value 1: suitable areas for OHB</em></p> <p>For further inquiries. Please contact: aryo_acondro@apps.ipb.ac.id</p>
Climate Change Awareness in the Arab Barometer Wave 5 Survey
<p>The Arab Barometer Wave V 2018-2019 is based on a nationally representative probability sample of the population aged 18 and above. In most countries, the sample includes 2,400 citizens. The data were conducted in face-to-face public opinion surveys (CAPI and PAPI). See technical reports by country for country-specific information. You can find the data, codebooks and all relevant information on the Arab Barometer website.</p> <p>Our dataset contains country weighted counts of different answer options and the re-weighted values of the answers given to the Arab Barometer Wave 5 question:</p> <p>Q108 : How serious a problem do you think the following issues are: Is climate change a very serious problem, a somewhat serious problem, not a very serious problem, not at all a serious problem?</p> <p>Get the country averages and aggregates from Zenodo</p> <p>Get the plot in jpg or png from figshare.</p> <p> </p> <p>See the detailed PDF documentation.</p>
FOCI model output used in the study by Ivanciu et al. - Twenty-first century Southern Hemisphere impacts of ozone recovery and climate change from the stratosphere to the ocean
<p>This dataset comprises the output from simulations with the coupled climate model FOCI (Flexible Ocean and Climate Infrastructure, Matthes et al., 2020) used in the analysis presented in the study by Ivanciu et al., 2021 “Twenty-first century Southern Hemisphere impacts of ozone recovery and climate change from the stratosphere to the ocean”. Four ensembles of three simulations each were performed: FixODS (II012, II014, II016), FixGHG (II013, II015, II017), INTERACT_O3 (SW128, II010, II011) and PRESC_O3 (JH027, II037, JH039). A detailed description of the simulations can be found in the above-mentioned manuscript.</p>
Supporting data for Tebaldi et al. 2021 - Nature Climate Change
<p>This is the dataset underpinning the paper "Extreme Sea Levels at Different Global Warming Levels" accepted in Nature Climate Change in 2021. Information about the paper as well as the supporting code used to process and analyze the data can be found at: https://github.com/DOE-ICoM/tebaldi-etal_2021_natclimchange.</p>
Supplementary data: "Future operation of hydropower in Europe under high renewable penetration and climate change"
<p>This dataset contains modelled inflow time series described in the paper "Future operation of hydropower in Europe<br> under high renewable penetration and climate change".</p> <p>The inflow is derived from ten different combinations of five General Circulation Models and two Regional Climate Models at the beginning of the century ("Hydro_inflow_BOC_(...).csv"), 1991 - 2020, and at the end of the century ("Hydro_inflow_EOC_(...).csv"), 2071 - 2100, under three CO2-emissions scenarios (RCP2.6, RCP4.5, and RCP8.5). The ensemble mean for each emissions scenario is presented as well.</p> <p>The historical data that is not confidential is given as well. See "data_sources" for sources.</p>
Climate change exposure and vulnerability of the global protected area estate from an international perspective
<p>Aim: Protected areas are essential to conserve biodiversity and ecosystem benefits to society under increasing human pressures of the Anthropocene. Anthropogenic climate change, however, threatens the enduring effectiveness of protected areas in conserving biodiversity and providing ecosystem services, because it modifies and redistributes biodiversity with unknown consequences for ecosystem functioning within protected areas. Here we assess (1) the climate change exposure of the global terrestrial protected area estate and (2) the climate change vulnerability of national protected area estates.</p> <p>Location: Terrestrial protected areas worldwide.</p> <p>Methods: We calculated local climate change exposure as predicted climate anomalies between the present and 2070 using ten global climate models, two emission scenarios (RCP 4.5 and 8.5) and the finest spatial resolution available for global climate projections (approx. 1 km). We estimated the climate change vulnerability of national protected area estates by analysing countrywide relationships between protected areas' climate anomalies and other protected area characteristics, i.e. area, elevation, terrain ruggedness, human footprint and irreplaceability for globally threatened species.</p> <p>Results: We found predicted climate anomalies highest in protected areas of (sub-)tropical countries. The correlations between climate anomalies and protected area characteristics strongly differ between countries. Globally, protected areas showing large climate anomalies tend to be at high elevation and highly irreplaceable for threatened species, increasing climate change vulnerability. These protected areas are relatively large in area, of high topographic heterogeneity and less pressured by humans, decreasing climate change vulnerability.</p> <p>Main conclusion: This study reveals potential hotspots of climate change impact inside the terrestrial protected area estate. It thus supports and guides climate-smart conservation policy and management, particularly national to local authorities, to ensure the future effectiveness of protected areas in preserving biodiversity and ecosystem benefits under climate change.</p>
Fig. 2 in Projected Climate Change Effects On Nuthatch Distribution And Diversity Across Asia
Fig. 2. Model predictions of species distribution area retained (gray) and lost (black) due to climate change for two example species, Sitta tephronota (white triangles, western area) and S. frontalis (dotted squares, eastern area).
Fig. 1. Occurrence points for 12 in Projected Climate Change Effects On Nuthatch Distribution And Diversity Across Asia
Fig. 1. Occurrence points for 12 Sitta species and one Tichodroma species used in this study. Sitta solangiae and S. victoriae each had fewer than 5 occurrence points and were excluded from the analysis.
Fig. 3 in Projected Climate Change Effects On Nuthatch Distribution And Diversity Across Asia
Fig. 3. Model predictions regarding number and percent of nuthatch species lost due to climate change, along with estimated current and future species richness for nuthatches. Shading ramps range from white (minimum) to dark gray (maximum) as follows: number of species lost 0-5, percent of species lost 0-100, and current and future species richness 0-9 species.
Fig. 4 in Modelling the change in the distribution of the black-shanked douc, Pygathrix nigripes (Milne-Edwards) in the context of climate change: Implications for conservation
Fig. 4. The predicted distribution of the black-shanked douc (P. nigripes) generated by the MaxEnt software under the RCP8.5 scenario. BGM = Bu Gia Map National Park; CYS = Chu Yang Sin National Park; CT = Cat Tien National Park; HB = Hon Ba Nature Reserve; KL-SM = Kalon-Song Mao Nature Reserve; KT = Krong Trai Nature Reserve; NK = Nam Ka Nature Reserve; NN = Nam Nung Nature Reserve; NC = Nui Chua National Park; NO = Nui Ong Nature Reserve; TK = Takou Nature Reserve; VC = Vinh Cuu Nature Reserve.
Fig. 2 in Modelling the change in the distribution of the black-shanked douc, Pygathrix nigripes (Milne-Edwards) in the context of climate change: Implications for conservation
Fig. 2. The predicted distribution of the black-shanked douc (P. nigripes) generated by the MaxEnt software under the RCP4.5 scenario. BGM = Bu Gia Map National Park; CYS = Chu Yang Sin National Park; CT = Cat Tien National Park; HB = Hon Ba Nature Reserve; KL-SM = Kalon-Song Mao Nature Reserve; KT = Krong Trai Nature Reserve; NK = Nam Ka Nature Reserve; NN = Nam Nung Nature Reserve; NC = Nui Chua National Park; NO = Nui Ong Nature Reserve; TK = Takou Nature Reserve; VC = Vinh Cuu Nature Reserve.
Fig. 3 in Modelling the change in the distribution of the black-shanked douc, Pygathrix nigripes (Milne-Edwards) in the context of climate change: Implications for conservation
Fig. 3. Response curve plots illustrate the dependence of predicted potential distribution on the three most important environmental variables for the black-shanked douc (P. nigripes). The curve shows the mean response of 10 replicates by MaxEnt (red line) and the standard deviation (blue band).
Fig. 1. The 472 in Modelling the change in the distribution of the black-shanked douc, Pygathrix nigripes (Milne-Edwards) in the context of climate change: Implications for conservation
Fig. 1. The 472 points recorded for the black-shanked douc (P. nigripes) that were used in this study. BGM = Bu Gia Map National Park; CYS = Chu Yang Sin National Park; CT = Cat Tien National Park; HB = Hon Ba Nature Reserve; KL-SM = Kalon-Song Mao Nature Reserve; KT = Krong Trai Nature Reserve; NK = Nam Ka Nature Reserve; NN = Nam Nung Nature Reserve; NC = Nui Chua National Park; NO = Nui Ong Nature Reserve; TK = Takou Nature Reserve; VC = Vinh Cuu Nature Reserve.
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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.