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274 results for “climate change responses”
Data for manuscript: Ecological lags govern the pace and outcome of plant community responses to 21st century climate change
<p>These data were used in the analyses reported in Block et al. "Ecological lags govern the pace and outcome of plant community responses to 21st century climate change".</p>
Fig. 3 in Regional uniqueness of tree species composition and response to forest loss and climate change
Fig. 3 | Response of tree species to climate change across biomes. The median absolute latitude and median elevation shift among species, fraction of lost and gained species, and change in taxonomic and phylogenetic composition under climate change were computed for each forest ecoregion. The boxplots show statistics for n = 239 ecoregions for Tropical Moist Broadleaf Forests, n = 14 ecoregions for Tropical Coniferous Forests, n = 55 ecoregions for Tropical Dry Broadleaf Forests, n = 26 ecoregions for Boreal Forests, n = 91 ecoregions for Temperate Broadleaf Forests, n = 49 ecoregions for Temperate Conifer Forests and n = 61 ecoregions for Mediterranean Forests. The center line of the boxplots shows the median, the box limits the quartiles, the whiskers 1.5 times the interquartile range, and the points the outliers.Changes are computed between predicted distributions with climate variables for 1981-2010 and climate projections for 2071-2100 under climate change scenario SSP 5.85. Changes in composition are computed as the Euclidean distance between scaled NMDS and evoPCA values computed at the ecoregion level. Source data are provided as a Source Data file.
Fig. 2 in Regional uniqueness of tree species composition and response to forest loss and climate change
Fig. 2 | Species occupancy range distribution and loss. a Distributions of species occupancy range sizes globally (gray) and constrained to forests (at least 10% tree cover, color) for species in each forest biome. b Boxplot of relative range reduction across species in each forest biome with the center line showing the median, the box limits the quartiles, the whiskers 1.5 times the interquartile range, and the points the outliers. The distributions and boxplots are computed for n = 6810 species for Tropical Moist Broadleaf Forests, n = 588 species for Tropical Coniferous Forests, n = 1101 species for Tropical Dry Broadleaf Forests, n = 54 species for Boreal Forests, n = 1744 species for Temperate Broadleaf Forests, n = 178 species for Temperate Conifer Forests and n = 580 species for Mediterranean Forests. c Global map of median species range size constrained to forests, created with QGIS110. The gray base map corresponds to all areas for which model predictors were available. d Plot of species' median latitude against range size constrained to forests, colored by point density, where red indicates the highest density. Source data are provided as a Source Data file.
Fig. 1 in Regional uniqueness of tree species composition and response to forest loss and climate change
Fig. 1 | Gradients in taxonomic and phylogenetic composition show a near- a, c. Scatter plot of taxonomic and phylogenetic ordinations in environmental unique biodiversity signature of every single location on the planet. Taxonomic space, a 2-dimensional space made up of the 2 first axes of a PCA of the environcomposition is represented by a 3-axis non-metric dimensional scaling (NMDS) and mental variables used for species distribution modeling: mean annual temperature phylogenetic beta-diversity is represented by the 3 first axes of a phylogenetic (MAT), temperature seasonality (T season), annual precipitation (Annual P), preordination (evoPCA). Both the taxonomic and phylogenetic ordinations are com- cipitation seasonality (P season), growing season length (GSL), net primary proputed on the global community matrix derived from the modeled distributions of ductivity (NPP),silt content (Silt),coarse fragments (CF),and soil pH (pH).b, d. Map n = 10,590 tree species sampled at a resolution of 100 km, resulting in n = 12,548 of taxonomic and phylogenetic ordinations in geographical space. Source data are sites. The 3 axes of each ordination are mapped to red, green, and blue with provided as a Source Data file. The maps were created with QGIS110 and the gray minimum and maximum values corresponding to the 10th and 90th percentiles. base map corresponds to all areas for which model predictors were available.
Fig. 3 in Phytoplankton Responses To Climate Change In The Large Lakes Of The Baltic Sea Basin
Fig. 3. Phytoplankton biomass structure in the Lake Peipsi (Lake Peipsi - left and Lake Pihkva - right column) for August 2004-2014.
Fig. 5 in Phytoplankton Responses To Climate Change In The Large Lakes Of The Baltic Sea Basin
Fig. 5. Average monthly (a – July, b – August) summer air temperature over Lake Peipsi catchment area for 1989–2014.
Data from: Integrating genomic data and simulations to evaluate alternative species distribution models and improve predictions of glacial refugia and future responses to climate change
<p>Climate change poses a threat to biodiversity, and it is unclear whether species can adapt to or tolerate new conditions, or migrate to areas with suitable habitats. Reconstructions of range shifts that occurred in response to environmental changes since the last glacial maximum from species distribution models (SDMs) can provide useful data to inform conservation efforts. However, different SDM algorithms and climate reconstructions often produce contrasting patterns, and validation methods typically focus on accuracy in recreating current distributions, limiting their relevance for assessing predictions to the past or future. We modeled historically suitable habitat for the threatened North American tree green ash (<em>Fraxinus pennsylvanica</em>) using 24 SDMs built using two climate models, three calibration regions, and four modeling algorithms. We evaluated the SDMs using contemporary data with spatial block cross-validation and compared the relative support for alternative models using a novel integrative method based on coupled demographic-genetic simulations. We simulated genomic datasets using habitat suitability of each of the 24 SDMs in a spatially-explicit model. Approximate Bayesian Computation (ABC) was then used to evaluate the support for alternative SDMs through comparisons to an empirical population genomic dataset. Models had very similar performance when assessed with contemporary occurrences using spatial cross-validation, but ABC model selection analyses consistently supported SDMs based on the CCSM climate model, an intermediate calibration extent, and the generalized linear modeling algorithm. Finally, we projected the future range of green ash under four climate change scenarios. Future projections using the SDMs selected via ABC suggest only minor shifts in suitable habitat for this species, while some of those that were rejected predicted dramatic changes. Our results highlight the different inferences that may result from the application of alternative distribution modeling algorithms and provide a novel approach for selecting among a set of competing SDMs with independent data.</p>
Figure 3. The effective population size through recent time for 3 in Comparative analyses of past population dynamics between two subterranean zokor species and the response to climate changes
Figure 3. The effective population size through recent time for 3 clades of Gansu zokor (Eospalax cansus).
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>
Cereal yield response to climate change in key grain producing areas of the Northern Hemisphere
<p>Vulnerability mapping is a field of increasing importance as we search for an ecologically and economically sustainable<br> climate-smart land-use system, which is necessary for the development of green infrastructure and agricultuVulnerability<br> mapping is a growing field with increasing importance in developing an ecologically and economically sustainable climate-smart land-use system, which may serve the advancement of green infrastructure and agricultural production. The<br> transformation of the climatic regime has an undeniable impact on plant production, but we rarely have long enough data<br> series to scrutinize the unfolding effects of the microregional patterns of the global climate-cereal yield relationship. To fill this<br> gap, I will analyze three regions of the Northern Hemisphere under continental climate, which represent key landscapes<br> concerning global food production and security, contributing a multi-way knowledge transfer through training, teaching, and<br> different form of communication activities. The relationship between climate indices, maize, and wheat yields will be analyzed<br> applying high geographical resolution data from Northern China, Hungary, and northern states of the US Midwest at a<br> landscape scale by Köppen-Geiger zones using linear, local, and spatial regression and bootstrap resampling tests and<br> developed data visualization techniques. This offers a unique opportunity to comparatively analyze the differences in<br> climate-cereal yield associations by landscape types and regions. The expected results will provide highly supportive factors<br> for planning and managing an ecologically and economically sustainable land-use system. The intended publications,<br> lectures, and collaborative actions will have a positive impact on domestic and EU research. The planned training and the<br> expected results of the action will further strengthen my career opportunities and put me in a position where I will be<br> considered for a tenured position at a research institution in Hungary.</p>
Data from: Species-specific traits mediate avian demographic responses under past climate change
<p>Anticipating species' responses to environmental change is a<span> pressing mission in biodiversity conservation. Despite decades of research investigating how climate change may affect population sizes, historical context is lacking and the traits which mediate demographic sensitivity to changing climate remain elusive. We use whole-genome sequence data to reconstruct the demographic histories of 263 bird species over the past million years and identify networks of interacting morphological and life-history traits associated with changes in effective population size (<em>N<sub>e</sub></em>) in response to climate warming and cooling. Our results identify direct and indirect effects of key traits representing survival, reproduction, and dispersal processes on long-term demographic responses to climate change and highlight traits most likely to influence population responses to ongoing climate warming.</span></p>
Data for: Simulated climate change causes asymmetric responses in insect life history timing potentially disrupting a classic ecological speciation system
<p>Climate change may alter phenology within populations with cascading consequences for community interactions and ongoing evolutionary processes. Here, we measured the response to climate change in two sympatric, recently diverged (~170 years) populations of <em>Rhagoletis</em> <em>pomonella</em> flies specialized on different host fruits (hawthorn and apple) and their parasitoid wasp communities. We tested whether warmer temperatures affect dormancy regulation and its consequences for synchrony across trophic levels and temporal isolation between divergent populations. Under warmer temperatures, both fly populations developed earlier. However, warming significantly increased the proportion of maladaptive pre-winter development in apple, but not hawthorn, flies. Parasitoid phenology was less affected, potentially generating ecological asynchrony. Observed shifts in fly phenology under warming may decrease temporal isolation, potentially limiting ongoing divergence. Our findings of complex sensitivity of life-history timing to changing temperatures predict that coming decades may see multifaceted ecological and evolutionary changes in temporal specialist communities.</p>
Interaction matters: Bottom-up driver interdependencies alter the projected response of phytoplankton communities to climate change, links to model results
<p>This dataset provides the output of ten model simulations with the global ocean biogeochemical model FESOM-REcoM necessary to reproduce the findings of Seifert et al. (2023). In addition to information on the mesh, the dataset contains 5-year means of global phytoplankton biomass, chlorophyll, net primary production, growth rates, limitations, carbonate system parameters (dissolved inorganic carbon, CO2 partial pressure, total alkalinity), temperature, photosynthetically active radiation, and mixed layer depths.</p> <p>File names refer to the figures in the paper where the respective data are used. See “readme” for detailed information on the dataset and separate files.</p>
Data for: Local adaptation of seed and seedling traits along a natural aridity gradient may both predict and constrain adaptive responses to climate change
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Data and code from: Decades of historical outbreak cycles in a multivoltine insect reveal a plastic phenological response to climate change
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Data for: Growing faster, longer or both? Modelling plastic response of Juniperus communis growth phenology to climate change
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Data from: Species-specific traits mediate avian demographic responses under past climate change
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Date From: The myriad of complex demographic responses of terrestrial mammals to climate change and gaps of knowledge: A global analysis
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Data for: Simulated climate change causes asymmetric responses in insect life history timing potentially disrupting a classic ecological speciation system
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Data from: Beyond resilience: Responses to changing climate and disturbance regimes in temperate forest landscapes across the Northern Hemisphere
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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
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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.