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284 results for “Future climate”
Data from: Predicting range shifts of the giant pandas under future climate and land use scenarios
<p><span><strong>Aim</strong>:</span><span> Understanding and predicting how species will respond to global environmental change (i.e., climate and land use change) is essential to efficiently inform conservation and management strategies for authorities and managers. Here, we assessed the combined effect of future climate and land use change on the potential range shifts of the giant pandas (<em>Ailuropoda melanoleuca</em>). </span></p> <p><span><strong>Location</strong>:</span><span> Sichuan Province, China.</span></p> <p><span><strong>Methods</strong>: </span><span>We used ensemble species distribution models (SDMs) to forecast range shifts of the giant pandas by the 2050s and 2070s under four combined climate and land use change scenarios. We also</span><span> compared the differences in </span><span>distributional changes of giant pandas among the five mountains in the study area. </span></p> <p><span><strong>Results</strong>: </span><span>Our ensemble SDMs exhibited good model performance in terms of both AUC (0.931) and TSS (0.747), and suggested that precipitation seasonality, annual mean temperature, the proportion of forest cover and total annual precipitation are the most important factors in shaping the current distribution patterns for the giant pandas. Our projections of future species distribution also suggested a range expansion under an optimistic greenhouse gas emission, while suggesting a range contraction under a pessimistic greenhouse gas emission. Moreover, we found that there is considerable variation in the projected range change patterns among the five mountains in the study area. Especially, the suitable habitat of the giant panda is predicted to increase under all scenarios in Minshan mountains, while is predicted to decrease under all scenarios in Daxiangling and Liangshan mountains, indicating the vulnerability of the giant pandas at low latitudes. </span></p> <p><span><strong>Main conclusions</strong>: </span><span>Our findings highlight the importance of an integrated approach that combines climate and land use change to predict the future species distribution and the need for a spatial explicit consideration of the projected range change patterns of target species for guiding conservation and management strategies. </span></p>
Global Catastrophic Effects on Future Climate due to Increasing Total Solar Irradiance. A General Atmospheric Circulation Analysis.
<p>10-yr CESM run with standard TSI (BGCN_T31_g37.cam.h0*)</p> <p>10-yr CESM run with TSI +10% (BGCN_T31_g37_TSI10p.cam.h0*)</p>
MDM data for "Wind driven ocean circulation changes can amplify future cooling of the North Atlantic warming hole" - submitted to Journal of Climate
<p>Data files for MDM simulation used in Journal of Climate submission, "Wind driven ocean circulation changes can amplify future cooling of the North Atlantic warming hole"</p>
Effect of Soil Moisture on Future Heatwaves over Eastern China: Convection-Permitting Regional Climate Simulations
<p>Data used in the manuscript "Effect of Soil Moisture on Future Heatwaves Over Eastern China: Convection-Permitting Regional Climate Simulations" which will be submitted to Journal of Geophysical Research: Atmospheres.</p>
Data from: Future climatically suitable areas for bats in South Asia
<p>Climate change majorly impacts biodiversity in diverse regions across the world, including South Asia, a megadiverse area with heterogeneous climatic and vegetation regions. However, climate impacts on bats in this region are not well‐studied, and it is unclear whether climate effects will follow patterns predicted in other regions. We address this by assessing projected near‐future changes in climatically suitable areas for 110 bat species from South Asia. We used ensemble ecological niche modelling with four algorithms (random forests, artificial neural networks, multivariate adaptive regression splines and maximum entropy) to define climatically suitable areas under current conditions (1970–2000). We then extrapolated near future (2041–2060) suitable areas under four projected scenarios (combining two global climate models and two shared socioeconomic pathways, SSP2: middle‐of‐the‐road and SSP5: fossil‐fuelled development). Projected future changes in suitable areas varied across species, with most species predicted to retain most of the current area or lose small amounts. When shifts occurred due to projected climate change, new areas were generally northward of current suitable areas. Suitability hotspots, defined as regions suitable for >30% of species, were generally predicted to become smaller and more fragmented. Overall, climate change in the near future may not lead to dramatic shifts in the distribution of bat species in South Asia, but local hotspots of biodiversity may be lost. Our results offer insight into climate change effects in less studied areas and can inform conservation planning, motivating reappraisals of conservation priorities and strategies for bats in South Asia.</p>
Output data for: Flammable Futures – Storylines of climatic impacts on wildfire events and palm oil plantations in Indonesia
<p>This repository contains the output data associated with the publication "Flammable Futures – Storylines of climatic impacts on wildfire events and palm oil plantations in Indonesia". It contains the FLAM modeled burned area and the GLOBIOM output, as well as the a downscaling grid.</p> <p>Descriptions of the results can be found in the publication (DOI will follow).</p>
FIGURE 4 in Southern Africa's Great Escarpment as an amphitheater of climate-driven diversification and a buffer against future climate change in bats
FIGURE 4 (Continued)
FIGURE 2 in Southern Africa's Great Escarpment as an amphitheater of climate-driven diversification and a buffer against future climate change in bats
FIGURE 2 (Continued)
AkiraSMori/BiodProd-ProtectArea: Analyses for "Biodiversity protection and its future benefits to society are intertwined with climate change action"
<div> <h2>Abstract</h2> <a href="https://github.com/AkiraSMori/BiodProd-ProtectArea/blob/main/README.md#abstract"></a></div> <p>Biodiversity loss and climate change are incontrovertibly intertwined, yet the nuanced interplay between these global challenges is often understated in policy dialogues. Here, we illustrate that conservation through protected areas can effectively preserve primary productivity and carbon capture in forests worldwide, which directly depend on tree diversity. However, we also discover that failing to mitigate future climate change has the potential to diminish the effectiveness of terrestrial protected areas in conserving tree diversity-dependent forest productivity, especially in warmer biomes. This holds true even under the most optimized selection of protected areas designed to meet the global biodiversity target of 30% protection by 2030. Thus, climate change mitigation is critical for the success of many conservation actions aimed at achieving global targets; otherwise, existing and future efforts to conserve biodiversity and their benefits to society could be in vain. Addressing anthropogenic climate change will sustain the many biodiversity-derived ecosystem benefits to society.</p>
Dataset to reproduce the paper "A new framework to evaluate urban design using urban microclimatic modelling in future climatic conditions"
<p>This dataset has been generated with the paper " A new framework to evaluate urban design using urban microclimatic<br> modelling in future climatic conditions" (https://doi.org/10.3390/su10041134). A Python notebook is also included to conduct the analysis.</p> <ol> <li>Data analysis - Sustainability paper.ipynb : Python notebook</li> <li>Geneva_Eur11_TDY_2010_2039 : Climate file for the year 2039 obtained from RCA4</li> <li>Geneva_Eur11_TDY_2010_2039_cim : Climate file for the year 2039 obtained from RCA4-CIM</li> <li>Geneva_Eur11_TDY_2010_2039 : Climate file for the year 2069 obtained from RCA4</li> <li>Geneva_Eur11_TDY_2010_2069_cim : Climate file for the year 2069 obtained from RCA4-CIM</li> <li>Geneva_Eur11_TDY_2010_2099 : Climate file for the year 2099 obtained from RCA4</li> <li>Geneva_Eur11_TDY_2010_2099_cim : Climate file for the year 2099 obtained from RCA4-CIM</li> <li>heating_2039 : Heating demand from CitySim for the year 2039</li> <li>heating_2039_cim : Heating demand from CitySim-CIM for the year 2039</li> <li>heating_2069 : Heating demand from CitySim for the year 2069</li> <li>heating_2069_cim : Heating demand from CitySim-CIM for the year 2069</li> <li>heating_2099 : Heating demand from CitySim for the year 2099</li> <li>heating_2099_cim : Heating demand from CitySim-CIM for the year 2099</li> <li>heating_2099_minP : Heating demand from CitySim for the year 2099 with Minergie-P scenario</li> <li>heating_2099__minP_cim : Heating demand from CitySim-CIM for the year 2099 with Minergie-P scenario</li> <li>cooling_2039 : Cooling demand from CitySim for the year 2039</li> <li>cooling_2039_cim : Cooling demand from CitySim-CIM for the year 2039</li> <li>cooling_2069 : Cooling demand from CitySim for the year 2069</li> <li>cooling_2069_cim : Cooling demand from CitySim-CIM for the year 2069</li> <li>cooling_2099 : Cooling demand from CitySim for the year 2099</li> <li>cooling_2099_cim : Cooling demand from CitySim-CIM for the year 2099</li> <li>cooling_2099_minP : Cooling demand from CitySim for the year 2099 with Minergie-P scenario</li> <li>cooling_2099__minP_cim : Cooling demand from CitySim-CIM for the year 2099 with Minergie-P scenario</li> <li>temp_cim : simulated temperature from CIM using Meteonorm</li> <li>temp_meteonorm : temperature from Meteonorm</li> <li>u_cim : simulated wind speedfrom CIM using Meteonorm</li> <li>u_meteonorm : wind speed from Meteonorm</li> </ol> <p> </p>
Figure 1 in The potential effects of future climate change on suitable habitat for the Taiwan partridge (Arborophila crudigularis): an ensemble-based forecasting method
Figure 1. Modeled range and presence records for Arborophila crudigularis.
Dwelling conversion and energy retrofit modify building anthropogenic heat emission under past and future climates: a case study of London terraced houses
<p>This archive includes the data used (e.g. Time use survey (UK-TUS) data), model files (idf files for running EnergyPlus) and codes for analysis in the paper (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.enbuild.2024.114668" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.enbuild.2024.114668</a>).</p> <p>Files in this archive should include:</p> <ul> <li>Time use survey data analysis</li> </ul> <p>o Main dataset: TUS_activity.zip</p> <p>o Code: TUS_clustering_code.zip</p> <p>o Output: InternalHeatProfile.zip</p> <ul> <li>Building energy modeling </li> </ul> <p>o Main dataset (run in EnergPlus 9.4): IDFfiles.zip</p> <p>o Output: Eplus_output.zip</p> <ul> <li>PostProcess analysis</li> </ul> <p>o Code: QF_analysis_code.zip</p> <p>o Output: QF_output.zip</p> <p> </p> <p>Note: this version currently only includes the outputs of all processes, the main dataset and code will be updated later.</p>
Data output from Projecting future climate change impacts on the distribution of pelagic squid in the Southern Ocean
<p>Data output from Projecting future climate change impacts on the distribution of pelagic squid in the Southern Ocean:<br>Rasters, R models and scripts</p>
Data used in "Revealing dominant patterns of aerosols regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations" (Li et al., Atmos. Chem. Phys. 2024)
<p>This dataset contains the processed EMAC simulation used as input to the clustering algorithm and the resulting regimes discussed in Li et al. (<em>Atmos. Chem. Phys.</em>, 2024).</p>
Data from: Current distributions and future climate‐driven changes in diatoms, insects and fish in U.S. streams
<span>Aim</span> <p class="abstract_para">Biodiversity on Earth is threatened by climate change. Despite the vulnerability of freshwater habitats to human impacts, most climate change projections have focused on terrestrial systems. Here, we examined how the current distributions and biodiversity of stream taxa might change under mitigated, stabilizing and increasing greenhouse gas emissions.</p> <span>Location</span> <p class="abstract_para">Conterminous USA.</p> <span>Time period</span> <p class="abstract_para">Present day to 2070.</p> <span>Major taxa studied</span> <p class="abstract_para">Stream diatoms, insects and fish.</p> <span>Methods</span> <p class="abstract_para">We developed species distribution models for 336 freshwater taxa from 1,227 distinct stream localities using water chemistry, watershed and climatic variables. Models based only on climate were used to project changes in the distributions and biodiversity of cold‐ versus warm‐water taxa under representative concentration pathways (RCPs) ranging from 2.6 to 8.5 W/m<sup>2</sup>.</p> <span>Results</span> <p class="abstract_para">In all three organismal groups, climate emerged as the strongest predictor of species distributions, providing comparable explanatory power to water chemistry and watershed variables combined. The RCP‐based projections suggested a widespread expansion of warm‐water taxa, outpacing the decline of cold‐water taxa. Consequently, overall species richness would increase, but beta diversity would decrease drastically with the severity of climate change. A closer look at individual taxa and functional guilds revealed that vulnerable cold‐water taxa included: (a) diatom guilds forming the base and bulk of the biofilm; (b) environmentally sensitive insects, characteristic of unimpacted streams; and (c) ecologically and recreationally important salmonids, which were forecast to diminish dramatically in source habitats. Warm‐water fish projected to increase their distributions include bait bucket release minnows and dominant predators.</p> <span>Main conclusions</span> <p class="abstract_para">Our results suggest potentially devastating impacts of climate change on stream ecosystems, with the restructuring of diatom, insect and fish communities, diminished distributions of functionally important taxa and widespread expansion of warm‐water taxa, giving rise to biotic homogenization. Given that the magnitude of these biotic shifts depends on the severity of climate change, appropriate current policy decisions are necessary to preserve freshwater ecosystems.</p>
Climate change threatens the future of rainforest ringtail possums by 2050
<p><span>Aim</span></p> <p>The increasing frequency and intensity of extreme weather escalate the pressure of global warming on biodiversity. Globally, synergistic effects of multiple components of climate change have driven local extinctions and community collapses, raising concern about the irreversible deterioration of ecosystems. Here, we disentangle the pressure of different climatic components on the population dynamics of a tropical community of marsupials in a World Heritage Area.</p> <p><span>Location</span></p> <p>The Australian Wet Tropics.</p> <p><span>Method</span></p> <p>We analyse the potential influence of climate change in different dimensions, quantifying the effect of spatial differences in temperature exposure and observed increases in temperature and frequency of extreme heatwaves.</p> <p><span>Results</span></p> <p>We find a strong negative effect of climate change on population dynamics, particularly extreme heatwaves, resulting in a rapid and severe decline in ringtails' population size in the last three decades.</p> <p><span>Main conclusions</span></p> <p>Forecasted increases in temperature and heatwaves threaten the collapse of the community by 2050, with ringtail possums falling below population viability thresholds within two decades.</p>
Using landscape genomics to delineate future adaptive potential for climate change in the Yosemite Toad (Anaxyrus canorus)
<p>An essential goal in conservation biology is delineating population units that maximize the probability of species persisting into the future and adapting to future environmental change. However, future-facing conservation concerns are often addressed using retrospective patterns that could be irrelevant. We recommend a novel landscape genomics framework for delineating future "Geminate Evolutionary Units" (GEUs) in a focal species: (1) identify loci under environmental selection, (2) model and map adaptive conservation units that may spawn future lineages, (3) forecast relative selection pressures on each future lineage, and (4) estimate their fitness and likelihood of persistence using geo-genomic simulations. Using this process, we delineated conservation units for the Yosemite toad (<em>Anaxyrus</em> <em>canorus</em>), a U.S. federally threatened species that is highly vulnerable to climate change. We used a genome-wide dataset, redundancy analysis, and Bayesian association methods to identify 24 candidate loci responding to climatic selection (R<sup>2</sup> ranging from 0.09–0.52), after controlling for demographic structure. Candidate loci included genes such as MAP3K5, involved in cellular response to environmental change. We then forecasted future genomic response to climate change using the multivariate machine learning algorithm Gradient Forests. Based on all available evidence, we found three GEUs in Yosemite National Park, reflecting contrasting adaptive optima: YF-North (high winter snowpack with moderate summer rainfall), YF-East (low to moderate snowpack with high summer rainfall), and YF-Low-Elevation (low snowpack and rainfall). Simulations under the RCP 8.5 climate change scenario suggest that the species will decline by 29% over 90 years, but the highly diverse YF-East lineage will be least impacted for two reasons: (1) geographically it will be sheltered from the largest climatic selection pressures, (2) its standing genetic diversity will promote a faster adaptive response. Our approach provides a comprehensive strategy for protecting imperiled non-model species with genomic data alone and has wide applicability to other declining species.</p>
Future supply of boreal forest ecosystem services is driven by management rather than by climate change
<p><span>Forests provide a wide variety of ecosystem services (ES) to society. The boreal biome is experiencing the highest rates of warming on the planet and increasing demand for forest products. To foresee how to maximize the adaptation of boreal forests to future warmer conditions and growing demands of forest products, we need a better understanding of the relative importance of forest management and climate change on the supply of ecosystem services. Here, using Finland as a boreal forest case study, we assessed the potential supply of a wide range of ES (timber, bilberry, cowberry, mushrooms, carbon storage, scenic beauty, species habitat availability and deadwood) given seven management regimes and four climate change scenarios. We used the forest simulator SIMO to project forest dynamics for 100 years into the future (2016–2116) and estimate the potential supply of each service using published models. Then, we tested the relative importance of management and climate change as drivers of the future supply of these services using generalized linear mixed models. Our results show that the effects of management on the future supply of these ES were, on average, eleven times higher than the effects of climate change across all services but greatly differed among them (from 0.53 to 24 times higher for timber and cowberry, respectively). Notably, the importance of these drivers substantially differed among biogeographical zones within the boreal biome. The effects of climate change were 1.6 times higher in northern Finland than in southern Finland, whereas the effects of management were the opposite – they were three times higher in the south compared to the north. We conclude that new guidelines for adapting forests to global change should account for regional differences and the variation in the effects of climate change and management on different forest ES.</span></p>
Data from: More future synergies and less trade‐offs between forest ecosystem services with natural climate solutions instead of bioeconomy solutions
<p>To reach the Paris Agreement, societies need to increase the global terrestrial carbon sink. There are many climate change mitigation solutions (CCMS) for forests, including increasing bioenergy, bioeconomy and protection. Bioenergy and bioeconomy solutions use climate-smart, intensive management to generate high quantities of bioenergy and bioproducts. Protection of (semi-)natural forests is a major component of 'natural climate solution' (NCS) since forests store carbon in standing biomass and soil. Furthermore, protected forests provide more habitat for biodiversity and non-wood ecosystem services (ES). We investigated the impacts of different CCMS and climate scenarios, jointly or in isolation, on future wood ES, non-wood ES, and regulating ES for a major wood provider for the international market. Specifically, we projected future ES given by three CCMS scenarios for Sweden 2020-2100. In the long term, fulfilling the increasing wood demand through bioenergy and bioeconomy solutions will decrease ES multifunctionality, but the increased stand age and wood stocks induced by rising greenhouse gas (GHG) concentrations will partially offset these negative effects. Adopting bioenergy and bioeconomy solutions will have a greater negative impact on ES supply than adopting NCS. Bioenergy or bioeconomy solutions, as well as increasing GHG emissions, will reduce synergies and increase trade-offs in ES. NCS, by contrast, increases the supply of multiple ES in synergy, even transforming current ES trade-offs into future synergies. Moreover, NCS can be considered an adaptation measure to offset negative climate change effects on the future supplies of non-wood ES. In boreal countries around the world, forestry strategies that integrate NCS more deeply are crucial to ensure a synergistic supply of multiple ES.</p>
Assessing Future Hydrological Impacts of Climate Change on High-Mountain Central Asia: Insights from a Stochastic Soil Moisture Water Balance Model
<p>Dataset accompanying the publication "Assessing Future Hydrological Impacts of Climate Change on High-Mountain Central Asia: Insights from a Stochastic Soil Moisture Water Balance Model"</p> <p> </p>
ScienceDex guides
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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.