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150 results for “climate extreme”
Data for: Phenotypic plasticity increases exposure to extreme climatic events that reduce individual fitness
<p>Climate models, and empirical observations, suggest that anthropogenic climate change is leading to changes in the occurrence and severity of extreme climatic events (ECEs). Effects of changes in mean climate on phenology, movement, and demography in animal and plant populations are well documented. In contrast, work exploring the impacts of ECEs on natural populations is less common, at least partially due to the challenges of obtaining sufficient data to study such rare events. Here, we assess the effect of changes in ECE patterns in a long-term study of great tits, near Oxford, over a 56-year period between 1965 and 2020. We document marked changes in the frequency of temperature ECEs, with cold ECEs being twice as frequent in the 1960s than at present, and hot ECEs being ~three times more frequent between 2010 and 2020 than in the 1960s. While the effect of single ECEs was generally quite small, we show that increased exposure to ECEs often reduces reproductive output, and that in some cases, the effect of different types of ECE is synergistic. We further show that long-term temporal changes in phenology, resulting from phenotypic plasticity, lead to an elevated risk of exposure to low-temperature ECEs early in reproduction, and hence suggest that changes in ECE exposure may act as a cost of plasticity. Overall, our analyses reveal a complex set of risks of exposure and effects as ECE patterns change and highlight the importance of considering responses to changes in both mean climate and extreme events. Patterns in exposure and effects of ECEs on natural populations remain underexplored and continued work will be vital to establish the impacts of ECEs on populations in a changing climate.</p>
The Impact of Climate Change on Extreme Winds over Northern Europe According to CMIP6: data and codes
<p>Data and codes for the paper submitted to WES "The Impact of Climate Change on Extreme Winds over Northern Europe According to CMIP6"</p> <p>Data:</p> <p>1. U50*.nc: 50-year wind with spectral correction method from 18 CMIP6 models</p> <p>2. annual_max*.nc: annual wind maxima from 18 CMIP6 models</p> <p>3. spe*.dat: example of power spectrum from the original wind speed time series from a CMIP6 model and power spectrum with spectral correction</p> <p>Codes:</p> <p>1. AnnualMax*.py : calculate extreme winds from 18 CMIP6 models</p> <p>2. XFuture-code-sharing.nb: Mathematca code for analysis of data on the effect of climate change, and pack data for plotting using MATLAB</p> <p>3. *.m: MATLAB codes for plotting figures on climate change </p> <p> </p> <p> </p>
Climate change causes declines and greater extremes in wetland inundation in a region important for wetland birds
<p>Wetland ecosystems are vital for maintaining global biodiversity, as they provide important stopover sites for many species of migrating wetland-associated birds. However, because weather determines their hydrologic cycles, wetlands are highly vulnerable to the effects of climate change. Although changes in temperature and precipitation resulting from climate change are expected to reduce inundation of wetlands, few efforts have been made to quantify how these changes will influence availability of stopover sites for migratory wetland birds. Additionally, few studies have evaluated how climate change will influence inter-annual variability or the frequency of extremes in wetland availability. For spring and fall bird migration in 7 ecoregions in the south-central Great Plains of North America, we developed predictive models associating abundance of inundated wetlands with a suite of weather and landcover variables. We then used these models to generate predictions of wetland inundation at the end of the century (2069–2099) under future climate change scenarios. Climate models predicted the average number of inundated wetlands will likely decline during both spring and fall migration periods, with declines being greatest in the eastern ecoregions of the Great Plains. However, the magnitude of predicted declines varied considerably across climate models and ecoregions, with uncertainty among climate models being greatest in the High Plains ecoregion. Most ecoregions also were predicted to experience more-frequent extremely dry years (i.e., years with extremely low wetland abundances), but the projected change in inter-annual variability of wetland inundation was relatively small and varied across ecoregions and seasons. Because the south-central Great Plains represents an important link along the migratory routes of many wetland-dependent avian species, future declines in wetland inundation and more frequent periods of only a few wetlands being inundated. resulting in an uncertain future for migratory birds as they experience reduced availability of wetland stopover habitat across their migration pathways. </p>
Dataset for: Windows of opportunity for predicting seasonal climate extremes: Pakistan floods of 2022
<p>Data required to regenerate any of the figures in Nature Communications paper "Windows of opportunity for predicting seasonal climate extremes: Pakistan floods of 2022"</p>
Data for: Tailored Forecasts Can Predict Extreme Climate Informing Proactive Interventions in East Africa
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Data from: Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics
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Data from: How climate extremes—not means—define a species' geographic range boundary via a demographic tipping point
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Data from: Graduate student reflections on learning and implementing community science methods to tackle compounding climate extremes
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Extreme drought reduces climatic disequilibrium in dryland plant communities
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Caught out in the cold: Mallard survival decreased during an extreme climatic event
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Data from: Do precipitation extremes drive growth and migration timing of a Pacific salmonid fish in Mediterranean‐climate streams?
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Data from: The impacts of climate and the extreme drought in 2018 on population growth in Swedish moth species
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Fire, drought and flooding rains: the effect of climatic extremes on bird species’ responses to time since fire
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Data from: Long-term climate and competition explain forest mortality patterns under extreme drought
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Data from: Survival and growth of three boreal conifer species transplanted to warm sites: Implications for responses to global warming and extreme climatic events
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Data from: Climatic resilience after extreme drought in Mediterranean shrubland plant communities
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Data from: Extreme insolation: climatic variation shapes the evolution of thermal tolerance at multiple scales
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Data from: Impacts of rainfall extremes predicted by climate-change models on major trophic groups in the leaf-litter arthropod community
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Data from: The adaptive potential of plant populations in response to extreme climate events
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Data for: Phenotypic plasticity increases exposure to extreme climatic events that reduce individual fitness
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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.