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121 results for “Global climate change”
The decreasing/increasing prevalence of the terms "global warming" and "climate change" in news media discourse
<p>I will drop this here as a simple curiosity without much further comment: The decreasing/increasing prevalence of the terms <em>global warming</em> and <em>climate change</em> in news media discourse.</p> <p>https://davidrozado.substack.com/p/gwacc</p>
MAgPIE model input data sets: Climate change-driven global land-use system adaptation under CMIP6-based crop model projections
<p>These MAgPIE input data sets include harmonized crop yield projections from several crop models (9 crop models and 5 climate models). Additionally, regional, validation, and calibration data sets are also reported.</p>
Supplementary material 2 from: Duquesne E, Fournier D (2024) Connectivity and climate change drive the global distribution of highly invasive termites. NeoBiota 92: 281-314. https://doi.org/10.3897/neobiota.92.115411
Occurrences of the 22 invasive termites as well as their source
Supplementary material 1 from: Duquesne E, Fournier D (2024) Connectivity and climate change drive the global distribution of highly invasive termites. NeoBiota 92: 281-314. https://doi.org/10.3897/neobiota.92.115411
Supplementary tables and figures (S1 to S7)
Figure 1 in How can global climate change influence the geographic distribution of the eucalyptus yellow beetle? Modeling and prediction for Brazil
Figure 1. Current potential geographic distribution of Costalimaita ferruginea determined by the algorithm Envelope Score (AUC = 0.808). The numbers 1 to 5 represent the Brazilian biomes, being 1 = Amazônia, 2 = Caatinga, 3 = Cerrado, 4 = Pantanal, 5 = Mata Atlântica e 6 = Pampa.
Figures 1–7 in Potential distribution of the guava psyllid Triozoida limbata (Hemiptera, Psylloidea), today and in global climate change scenarios
Figures 1–7. Triozoida limbata: 1- Habitus of adult; 2- head; 3- male terminalia, in profile; 4- female terminalia, in profile; 5- habitus of immature; 6- open leaf roll gall on guava with immature specimens; 7- leaf roll galls on guava.
Data from: Global change on the Roof of the World: vulnerability of Himalayan otter species to land-use and climate alterations
<p>Climate Change Vulnerability Assessment (CCVA) prescribes the quantification of species vulnerability based on three components: sensitivity, adaptive capacity and exposure. Such assessments should be performed through combined approaches that integrate trait-based elements (e.g., measures of species sensitivity such as niche width) with correlative tools quantifying exposure (magnitude of changes in climate within species habitat). Furthermore, as land-use alterations may increase climate impacts on biodiversity, CCVAs should focus on both climate and land-use change effects. Unfortunately, most of such assessments have so far focused exclusively on exposure to climate change. </p> <p>We evaluated the vulnerability of three otter species occurring in the Himalayan region, i.e. <i>Aonyx cinereus, Lutra lutra </i>and<i> Lutrogale perspicillata</i>, to 2050 climate and land-use through the recently-proposed Climate Niche Factor Analysis (CNFA) framework combined with Species Distribution Models.</p> <p>Future climate and land-use change will reduce (6 – 15%) and shift (10 – 18%) the geographic range of the three species in the Himalaya, with land-use alterations exerting far more severe effects than climate change. Among vulnerability components, sensitivity played a greater role than exposure in determining the vulnerability of the otters. Specifically, the most specialist species, <i>L. perspicillata</i> showed the highest vulnerability in comparison with the most generalist, <i>L. lutra</i>.</p> <p>Our results underline how coupling climate and land-use change components in CCVAs can generate diverging predictions of species vulnerability compared to approaches relying on climate change only. Moreover, intrinsic components, such as species sensitivity, proved significantly more important in determining vulnerability than extrinsic metrics such as habitat exposure.</p> <p>The dataset contains XY coordinates of Himalayan otter species used in the study. Since Himalayan otters are listed as threatened or vulnerable in several of the regions covered by the study, original coordinates were rounded to 1 degree. Specific data sources are provided in the coupled table.</p>
Supplemental Material for the paper "Tropical Cyclones and Climate Change: Global Landfall Frequency Projections Derived from Knutson et al 2020"
<p>As described in the paper.</p> <p> </p>
Key data used in "Western North Pacific tropical cyclone activity modulated by phytoplankton feedback under global warming" submitted to Nature Climate Change
<p>Key data</p>
Climate change impacts on global cattle yield
<p>This code is used to analyze the response of global cattle meat yield to climate change.</p>
Data from: Coupling of palaeontological and neontological reef coral data improves forecasts of biodiversity responses under global climatic change
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Data from: A global test for phylogenetic signal in shifts in flowering time under climate change
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Combined effects of global climate change and nutrient enrichment on the physiology of three temperate maerl species
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Data from: Global change on the Roof of the World: vulnerability of Himalayan otter species to land-use and climate alterations
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Data from: Phenotypic interactions between tree hosts and invasive forest pathogens in the light of globalization and climate change
Invasive pathogens can cause considerable damage to forest ecosystems. Lack of coevolution is generally thought to enable invasive pathogens to bypass the defence and/or recognition systems in the host. Although mostly true, this argument fails to predict intermittent outcomes in space and time, underlining the need to include the roles of the environment and the phenotype in host–pathogen interactions when predicting disease impacts. We emphasize the need to consider host–tree imbalances from a phenotypic perspective, considering the lack of coevolutionary and evolutionary history with the pathogen and the environment, respectively. We describe how phenotypic plasticity and plastic responses to environmental shifts may become maladaptive when hosts are faced with novel pathogens. The lack of host–pathogen and environmental coevolution are aligned with two global processes currently driving forest damage: globalization and climate change, respectively. We suggest that globalization and climate change act synergistically, increasing the chances of both genotypic and phenotypic imbalances. Short moves on the same continent are more likely to be in balance than if the move is from another part of the world. We use Gremmeniella abietina outbreaks in Sweden to exemplify how host–pathogen phenotypic interactions can help to predict the impacts of specific invasive and emergent diseases. This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'.
Codes for "Intensifying Inverse KE Cascade Over Energetic Oceans Under Global Warming" By Geng et al. Submitted to Nature Climate Change
<p>This repository contains the necessary codes for the study of "Intensification of Oceanic Inverse Energy Cascade Under Global Warming" .</p> <p>Specifically, this repository contains the following items:</p> <p>(1) The codes for computing the global kinetic energy cascade, the four metrics of inverse KE cascade and their trends.</p> <p>(2) The function codes needed for coarse-graining filtering and trend analysis.</p> <p>(3) Necessary data for running the programs at MATLAB.</p>
Data from: Phenotypic interactions between tree hosts and invasive forest pathogens in the light of globalization and climate change
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Synthetic Assessment of Global Distribution of Vulnerability to Climate Change: Maps and Data, 2005, 2050, and 2100
The Synthetic Assessment of Global Distribution of Vulnerability to Climate Change: Maps and Data, 2005, 2050, and 2100 data set consist of maps and vulnerability index to climate change of 100 countries based on the Vulnerability-Resilience Indicator Model (VRIM), which not only presents sensitivity to climate change stresses but allows the division of indicators into components that reflects sensitivity and adaptive capacity. It was produced in collaboration with the Wesleyan University, Joint Global Change Research Institute, University of Illinois and the Columbia University Center for International Earth Science Information Network (CIESIN).
Effects of Climate Change on Global Food Production from SRES Emissions and Socioeconomic Scenarios
The Effects of Climate Change on Global Food Production from SRES Emissions and Socioeconomic Scenarios is an update to a major crop modeling study by the NASA Goddard Institute for Space Studies (GISS). The initial study was published in 1997, based on output of HadCM2 model forced with greenhouse gas concentration from the IS95 emission scenarios in 1997. Results of the initial study are presented at SEDAC's Potential Impacts of Climate Change on World Food Supply: Data Sets from a Major Crop Modeling Study, released in 2001. The co-authors developed and tested a method for investigating the spatial implications of climate change on crop production. The Decision Support System for Agrotechnology Transfer (DSSAT) dynamic process crop growth models, are specified and validated for one hundred and twenty seven sites in the major world agricultural regions. Results from the crop models, calibrated and validated in the major crop-growing regions, are then used to test functional forms describing the response of yield changes in the climate and environmental conditions. This updated version is based on HadCM3 model output along with GHG concentrations from the Special Report on Emissions Scenarios (SRES). The crop yield estimates incorporate some major improvements: 1) consistent crop simulation methodology and climate change scenarios; 2) weighting of model site results by contribution to regional and national, and rainfed and irrigated production; 3) quantitative foundation for estimation of physiological CO2 effects on crop yields; 4) Adaptation is explicitly considered; and 5) results are reported by country rather than by Basic Linked System region. The data are produced by A. Iglesias and C. Rosenzweig and the maps are produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
Extreme events changes over China under 1.5-4°C global warming targets: projected by an ensemble of regional climate model simulations
<p>This file is for the upload of data for 2019JD031057R.</p>
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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.