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284 results for “Future climate”
Data from: Predicting range shifts of Davidia involucrata Ball. under future climate change
<p>Understanding and predicting how species will respond to climate change is crucial for biodiversity conservation. Here, we assessed future climate change impacts on the distribution of a rare and endangered plant species, Davidia involucrate in China, using the most recent global circulation models developed in the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC6). We assessed the potential range shifts in this species by using an ensemble of species distribution models (SDMs). The ensemble SDMs exhibited high predictive ability and suggested that the temperature annual range, annual mean temperature, and precipitation of the driest month are the most influential predictors in shaping distribution patterns of this species. The projections of the ensemble SDMs also suggested that D. involucrate is very vulnerable to future climate change, with at least one-third of its suitable range expected to be lost in all future climate change scenarios and will shift to the northward of high-latitude regions. Similarly, at least one-fifthof the overlap area of the current nature reserve networks and projected suitable habitat is also expected to be lost. These findings suggest that it is of great importance to ensure that adaptive conservation management strategies are in place to mitigate the impacts of climate change on D. involucrate.</p>
Data for global agricultural water scarcity assessment incorporating blue and green water availability under future climate change
<p>This dataset is for the publication Global agricultural water scarcity assessment incorporating blue and green water availability under future climate change by Liu et al., 2022 (Earth's Future, doi: <a href="http://doi.org/10.1029/2021EF002567">10.1029/2021EF002567</a>).</p> <p>Three observation-based global meteorological datasets, namely PGMFD v.2, GSWP3, and WFDEI, were used to calculate ETc over the baseline period. The bias-corrected climate projections of four GCMs (namely GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5) provided by the ISIMIP phase 2b (ISIMIP2b) were used to calculate the ETc over the future period.</p> <p> </p> <p>Liu, X., Liu, W., Tang, Q., Liu, B., Wada, Y., & Yang, H. (2022). Global agricultural water scarcity assessment incorporating blue and green water availability under future climate change. Earth's Future, 10, e2021EF002567. <a href="https://doi.org/10.1029/2021EF002567">https://doi.org/10.1029/2021EF002567</a></p>
Climate change and energy policy control the future of Myanmar's rivers
<p>This data repository holds input and output data for the paper Jin XY., Chowdhury, A.K., Dang, T.D., Deshmukh, R. and Galelli, S. “Climate change and energy policy control the future of Myanmar's rivers”. See Readme for more details. </p>
Figure 2 in Niche evolution and diversification in Middle Eastern stream salamanders (Paradactylodon): vulnerability to future climate change
Figure 2. Recent (A: 1970-2000) and future (2081-2100) habitat suitability of Paradactylodon species based on the consensus model under optimistic (B: ssp126) and pessimistic (C: ssp585) scenarios.
Figure 1 in Niche evolution and diversification in Middle Eastern stream salamanders (Paradactylodon): vulnerability to future climate change
Figure 1. Study area. The occurrence records of Paradactylodon species with different colors are shown on the map.
Figure 3 in Niche evolution and diversification in Middle Eastern stream salamanders (Paradactylodon): vulnerability to future climate change
Figure 3. Panels (A-D) illustrate the niche overlap values between two species distribution ranges (see table 3), along the
Data for manuscript "Substantial Contraction of Dense Shelf Water in the Ross Sea under Future Climate Scenarios"
<p>Relevant data shown in figures of the manuscript "Substantial Contraction of Dense Shelf Water in the Ross Sea under Future Climate Scenarios"</p>
Future Projections and Life Cycle Assessment of End-of-life Tires to Energy Conversion in Hong Kong: Environmental, Climate and Energy Benefits for Regional Sustainability
<p>The dataset presents the findings of the study "Future Projections and Lifecycle Assessment of End-of-life Tires to Energy Conversion in Hong Kong: Environmental, Climate and Energy Benefits for Regional Sustainability". The data results are contained in the files "Results_data.xlsx" and "LCIs and LCA results.zip," while the "Figures data.xlsx" file includes the data needed for plotting. </p>
Data from: Future suitability of habitat in a migratory ungulate under climate change
With climate change, the effect of global warming on snow cover is expected to cause range expansion and enhance habitat suitability for species at their northern distribution limits. However, how this depend on landscape topography and sex in size-dimorphic species remains uncertain, and is further complicated for migratory animals following climate-driven seasonal resource fluctuations across vast landscapes. Using 11 years of data from a partially migratory ungulate at their northern distribution ranges, the red deer (Cervus elaphus), we predicted sex-specific summer and winter habitat suitability in diverse landscapes under medium and severe global warming. We found large increases in future winter habitat suitability, resulting in expansion of winter ranges as currently unsuitable habitat became suitable. Even moderate warming decreased snow cover substantially, with no suitability difference between warming scenarios. Winter ranges will hence not expand linearly with warming, even for species at their northern distribution limits. Although less pronounced than in winter, summer ranges also expanded and more so under severe warming. Summer habitat suitability was positively correlated with landscape topography and ranges expanded more for females than males. Our study highlights the complexity of predicting future habitat suitability for conservation and management of size-dimorphic, migratory species under global warming.
Data from: Climatic thresholds shape northern high-latitude fire regimes and imply vulnerability to future climate change
Boreal forests and arctic tundra cover 33% of global land area and store an estimated 50% of total soil carbon. Because wildfire is a key driver of terrestrial carbon cycling, increasing fire activity in these ecosystems would likely have global implications. To anticipate potential spatiotemporal variability in fire-regime shifts, we modeled the spatially explicit 30-yr probability of fire occurrence as a function of climate and landscape features (i.e. vegetation and topography) across Alaska. Boosted regression tree (BRT) models captured the spatial distribution of fire across boreal forest and tundra ecoregions (AUC from 0.63–0.78 and Pearson correlations between predicted and observed data from 0.54–0.71), highlighting summer temperature and annual moisture availability as the most influential controls of historical fire regimes. Modeled fire–climate relationships revealed distinct thresholds to fire occurrence, with a nonlinear increase in the probability of fire above an average July temperature of 13.4°C and below an annual moisture availability (i.e. P-PET) of approximately 150 mm. To anticipate potential fire-regime responses to 21st-century climate change, we informed our BRTs with Coupled Model Intercomparison Project Phase 5 climate projections under the RCP 6.0 scenario. Based on these projected climatic changes alone (i.e. not accounting for potential changes in vegetation), our results suggest an increasing probability of wildfire in Alaskan boreal forest and tundra ecosystems, but of varying magnitude across space and throughout the 21st century. Regions with historically low flammability, including tundra and the forest–tundra boundary, are particularly vulnerable to climatically induced changes in fire activity, with up to a fourfold increase in the 30-yr probability of fire occurrence by 2100. Our results underscore the climatic potential for novel fire regimes to develop in these ecosystems, relative to the past 6000–35 000 yr, and spatial variability in the vulnerability of wildfire regimes and associated ecological processes to 21st-century climate change.
Figure 4 in Will future anthropogenic climate change increase the potential distribution of the alien invasive Cuban treefrog (Anura: Hylidae)?
Figure 4. Maps of the potential distribution of O. septentrionalis as expected for 2020, 2050 and 2080 assuming A2a and B2a conditions. Maps show mean values of Maxent values derived from models projected onto CCCMA, CISRO and HADCM3 scenarios.
Figure 3 in Will future anthropogenic climate change increase the potential distribution of the alien invasive Cuban treefrog (Anura: Hylidae)?
Figure 3. Comparison between the known distribution of O. septentrionalis (A) (source: Johnson (2007)) and model prediction in Florida (B). Spread history of O. septentrionalis is indicated.
Figure 2 in Will future anthropogenic climate change increase the potential distribution of the alien invasive Cuban treefrog (Anura: Hylidae)?
Figure 2. Potential distribution of O. septentrionalis under current climate conditions within the Caribbean. Higher Maxent values suggest higher climatic suitability. Native records are indicated as points and invasive records as triangles.
Figure 1 in Will future anthropogenic climate change increase the potential distribution of the alien invasive Cuban treefrog (Anura: Hylidae)?
Figure 1. Comparison of climatic conditions at native and invasive records of Osteopilus septentrionalis. Native records used for model building are indicated in black, invasive records in grey.
Potential distribution prediction of Amaranthus palmeri S. Watson in China under current and future climate scenarios
<p>The vicious invasive alien plant <a name="_Hlk99445053"></a><em>Amaranthus palmeri</em> poses a serious threat to ecological security and food security due to its strong adaptability, competitiveness, and herbicide resistance. Predicting its potential habitats under current and future climate change is critical for monitoring and early warning. In this study, we used two sets of climate data, namely, WorldClim1.4 and RCPs (the historical climate data of WorldClim version 1.4 and future climate data of RCPs), WorldClim2.1 and SSPs (the historical climate data of WorldClim version 2.1 and future climate data of SSPs), to analyze the dominant environmental variables affecting the habitat suitability and predict the potential distribution of <em>A. palmeri </em>to climate change in China based on the MaxEnt model. The results show that (i) Temperature has a greater impact on the distribution of <em>A. palmeri</em>. The relative contributions of temperature-related variables count to 70 % or more, and the annual mean temperature (bio1) reached more than 40 %. (ii) At present, the potentially suitable area is widely distributed in the central-east and parts of southwest China, and the high suitable area is focused on the North China Plain. The potential suitable area predicted by WorldClim1.4 and WorldClim2.1 both accounts for about 31% of China's total land area. (iii) Future climate change will expand the suitable habitats to high latitudes and altitudes. The overall suitable area maximum increased to 44.93% under SSPs and 38.91% under RCPs. We conclude that climate change would increase the risk of <em>A. palmeri</em> expanding to high latitudes and altitudes, the results have practical implications for the effective long-term management in response to the global warming of <em>A. palmeri</em>.</p>
Preserving the woody plant tree of life in China under future climate and land-cover changes
<p><span>The tree of life (TOL) is severely threatened by climate and land-cover changes. Preserving the TOL is urgent, but has not been included in the post-2020 global biodiversity framework. Protected areas (PAs) are fundamental for biological conservation. However, we know little about the effectiveness of existing PAs in preserving the TOL of plants and how to prioritize PA expansion for better TOL preservation under future climate and land-cover changes. Here, using high-resolution distribution maps of 8732 woody species in China and phylogeny-based Zonation, we find that current PAs perform poorly in preserving the TOL </span><span>both at the present and in the 2070s</span><span>. The geographical coverage of TOL branches by current PAs is ca. 9%, and < 3% of the identified priority areas for preserving the TOL are currently protected. Interestingly, the geographical coverage of TOL branches by PAs will be improved from 9% to 52–79% by the identified priority areas for PA expansion. Human pressures in the identified priority areas are high, leading to high costs for future PA expansion. We thus suggest that besides nature reserves and national parks, other effective area-based conservation measures should be considered. Our study argues for the inclusion of preserving the TOL in the post-2020 conservation framework and provides references for decision-makers </span><span>to preserve the Earth's evolutionary history.</span></p>
Multi-model ensemble bias-corrected precipitation dataset for historical and future climate (1961–2099) in China
<p>本文基于耦合模式比较项目第六阶段(CMIP6)的27个全球气候模式(GCM),采用随机森林(RF)模型和EQM方法整合27个大气监测模型的降水模拟数据,进一步修正中国综合月降水数据。修正后的降水资料在月降水量和极端降水量方面均明显优于原GCM降水资料。数据以 GeoTIFF 格式,其中嵌入了具有 1° 空间分辨率的地理配准信息。LST在GeoTIFF中的单位是mm。压缩文件被命名为历史文件.zip、SSP126.zip、SSP245.zip 和 SSP585.zip。压缩文件中的每个文件都命名为“yyyymm.tif”,其中“yyyy”和“mm”分别表示年份和月份。例如,文件“196101.tif”存储了 1961 年 1 月中国每月降水量。</p>
FIG. 2 in Clearing up the Crystal Ball: Understanding Uncertainty in Future Climate Suitability Projections for Amphibians
FIG. 2.—Mean predicted change in suitable climate for amphibian species by citation and model parameters from the meta-analysis. Points represent means and bars represent 95% confidence intervals. Mean predicted change in suitable climate was calculated for each amphibian order within each study for each of the model settings, including Representative Concentration Pathway, Year, and Dispersal Limitation. Triangles indicate estimates from the case study, and circles indicate all other studies. A color version of this figure is available online.
FIG. 1 in Clearing up the Crystal Ball: Understanding Uncertainty in Future Climate Suitability Projections for Amphibians
FIG. 1.—Map of countries for which suitable climate has been projected under future climate scenarios for at least one amphibian species. Colors represent the number of studies in which a given country was included. A color version of this figure is available online.
FIG. 3 in Clearing up the Crystal Ball: Understanding Uncertainty in Future Climate Suitability Projections for Amphibians
FIG. 3.—Percent change in climate suitability predicted for each species in the case study. For each species, predicted percent change in climate suitability is shown for the year 2050 under 13 general circulation models and two representative concentration pathways (2.6, 8.5) climate scenarios for both the default Maxent species distribution models (SDMs; regularization multiplier ¼ 1; open red boxes) and the best-fit SDM (Akaike information criterion; ΔAICc ¼ 0; shaded blue boxes) for three levels of dispersal: no dispersal, limited, or unlimited. Boxplots show median, interquartile range, and minimum and maximum values. A color version of this figure is available online.
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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)
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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.