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382 results for “Climate impacts”
Figure 3 in Ensemble distribution modeling of the Mesopotamian spiny-tailed lizard, Saara loricata (Blanford, 1874), in Iran: an insight into the impact of climate change
Figure 3. Model of habitat suitability for the species based on the present climatic data (A) and 2.6 (B) and 8.5 (C) scenarios of the CCSM for the future.
Figure 1 in Ensemble distribution modeling of the Mesopotamian spiny-tailed lizard, Saara loricata (Blanford, 1874), in Iran: an insight into the impact of climate change
Figure 1. The presence records (black dots) used for the development of a maximum entropy model for predicting the habitat suitability of the Mesopotamian spiny-tailed lizard.
Estimating future climate change impacts on human mortality and crop yields via air pollution: supplemental files
<p>Atmospheric chemistry model output and other gridded data sets necessary to estimate human mortality and crop yield losses associated with future climate change, as used in Murray et al. [PNAS, 2024] doi:10.1073/pnas.2400117121.</p>
Impact of Grid Resolution on Wave-mean Flow Interactions with High Resolution Mars Global Climate Model Simulations
<p>This dataset contains NetCDF files necessary to replicate results from the 2024 paper "<em>Impact of Grid Resolution on Wave-mean Flow Interactions with High Resolution Mars Global Climate Model Simulations</em>"</p> <p>The dataset contains NetCDF files with 1 year of zonally-averaged NASA Ames Mars Global Climate Model (MGCM) fields with 5-sol binning for each of the simulations presented in the paper: </p> <ul> <li>a "low-resolution" simulation with no parameterization for gravity waves</li> <li>a "high-resolution" simulation with no parameterization for gravity waves</li> <li>a "low-resolution" simulation with parameterizations for orographic and non-orographic gravity waves</li> </ul> <p>Also included are:</p> <ul> <li>a file describing the coordinates for the MGCM's vertical grids used in the study </li> <li> atmospheric fields not provided in the other NetCDF files and necessary to replicate figures 3 and supplemental figure FS2 from the paper.</li> <li>a README.txt detailing the content of each file in the dataset</li> </ul>
Data and analysis and plotting scripts for Swaminathan et al., "Regional Impacts Poorly Constrained by Climate Sensitivity"
<p>The datasets included here are of the plotted data from the figures of the paper entitled "Regional Impacts Poorly Constrained by Climate Sensitivity", by Ranjini Swaminathan, Jacob Schewe, Jeremy Walton, Klaus Zimmermann, Colin Jones, Richard A. Betts, Chantelle Burton, Chris D. Jones, Matthias Mengel, Christopher Reyer, Andrew G. Turner & Katja Weigel, submitted for publication in Earth's Futures. Scripts used for plotting and analysis are also included.</p>
Data and analysis code for Repo et al., "Contrasting forest management strategies: impacts on biodiversity and ecosystem services under changing climate and disturbance regimes"
<p>This repository contains analysis code and pre-processed data for the study "Contrasting forest management strategies: impacts on biodiversity and ecosystem services under changing climate and disturbance regimes" by Repo et al.<br>Data processing and analysis mainly done by Aapo Jantunen, Katharina Albrich<br>Due to respository space limitations, the original model outputs are archived in the Finnish "Allas" data storage service. For access, contact katharina.albrich@luke.fi<br>The code used to process the raw data is included here for reproducibility.</p> <p>If you are interested in using iLand, visit https://iland-model.org/ and https://iland-model.org/iland-book/ for information on using the model and a guide to setting up a landscape.</p> <p><span>This work was supported by the Ministry of Agriculture and Forestry by funding project Future multifunctional forests and their disturbance risk in the changing climate (Foster) through the “Catch the Carbon” initiative (<span>project number VN/28654/2020)</span>. A.R. has been supported by the grant [TRACY Trade-offs and synergies in land-based climate change mitigation and biodiversity conservation decision 322066 by the Academy of Finland.], J. H by the grant [CASCADE - Changing Disturbance Regimes and Forest Landscapes of Fennoscandia 342569 by the Academy of Finland]. </span></p> <p> </p>
Data from ATTRICI 1.1 - counterfactual climate for impact attribution
<p>Data as produced and presented in the publication</p> <pre><strong>ATTRICI v1.1 - counterfactual climate for impact attribution</strong></pre> <p>in Geoscientific Model Development.</p> <p>Abstract:</p> <p>Attribution in its general definition aims to quantify drivers of change in a system. According to IPCC WGII a change in a natural, human or managed system is attributed to climate change by quantifying the difference between the observed state of the system and a counterfactual baseline that characterizes the system’s behavior in the absence of climate change, where “climate change refers to any long-term trend in climate, irrespective of its cause". Impact attribution following this definition remains a challenge because the counterfactual baseline cannot be observed. Process-based and empirical impact models can fill this gap as they allow to simulate the counterfactual climate impact baseline. In those simulations, the models are forced by observed direct (human) drivers such as land use changes, changes in water or agricultural management but a counterfactual climate without long-term changes. We here present ATTRICI (ATTRIbuting Climate Impacts), an approach to construct the required counterfactual stationary climate data from observational (factual) climate data. Our method identifies the long-term shifts in the considered daily climate variables that are correlated to global mean temperature change assuming a smooth annual cycle of the associated scaling coefficients for each day of the year. The produced counterfactual climate datasets are used as forcing data within the impact attribution set-up of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). Our method preserves the internal variability of the observed data in the sense that factual and counterfactual data for a given day have the same rank in their respective statistical distributions. The associated impact model simulations allow for quantifying the contribution of climate change to observed long-term changes in impact indicators and for quantifying the contribution of the observed trend in climate to the magnitude of individual impact events. Attribution of climate impacts to anthropogenic forcing would need an additional step separating anthropogenic climate forcing from other sources of climate trends, which is not covered by our method.</p>
FOCI model output used in the study by Ivanciu et al. - Twenty-first century Southern Hemisphere impacts of ozone recovery and climate change from the stratosphere to the ocean
<p>This dataset comprises the output from simulations with the coupled climate model FOCI (Flexible Ocean and Climate Infrastructure, Matthes et al., 2020) used in the analysis presented in the study by Ivanciu et al., 2021 “Twenty-first century Southern Hemisphere impacts of ozone recovery and climate change from the stratosphere to the ocean”. Four ensembles of three simulations each were performed: FixODS (II012, II014, II016), FixGHG (II013, II015, II017), INTERACT_O3 (SW128, II010, II011) and PRESC_O3 (JH027, II037, JH039). A detailed description of the simulations can be found in the above-mentioned manuscript.</p>
Long-Term Demographic Trends in Prehistoric Italy: climate impacts and regionalised socio-ecological trajectories (dataset and R script)
<p>The present digital archive is the outcome of the paper: <strong>Palmisano, A., Bevan, A., Kabelindde, A., Roberts, N., and Shennan, S., 2021. <a href="https://doi.org/10.1007/s10963-021-09159-3">Long-Term Demographic Trends in Prehistoric Italy: climate impacts and regionalised socio-ecological trajectories</a>. <em>Journal of World Prehistory, 34 (3)</em>, </strong>381-432<strong>.</strong></p> <p>The dataset included here provides a collection of <strong>4,010</strong> radiocarbon dates from <strong>947</strong> archaeological sites for a period spanning between 11,000 and 1500 BP. In addition, the digital archive related to this paper provides reproducible analyses in the form of one script written in R statistical computing language.</p> <p>List of versions:</p> <ul> <li><strong>1.0.</strong> 4 August 2021 - First public release of the dataset on Zenodo. </li> </ul>
Data from: Fertiliser application modulates the impact of interannual climate fluctuations and plant-to-plant interactions on the dynamics of annual species in a Mediterranean grassland
<p><span><strong><span>Background:</span></strong><span> Climate and land-use changes, which include the application of various types of organic and inorganic fertilisers, have been reducing the species diversity of Mediterranean grasslands and threatening their conservation. Annual plants are one of the most diverse functional groups of species in these grasslands, despite suffering competitive pressure from perennial herbaceous and woody species, and they are essential for ecosystem functioning and stability. </span></span></p> <p><span><strong><span>Aims:</span></strong><span> To quantify how fertilisation modulates the impact of plant-to-plant interactions and climate fluctuations on the dynamics of annuals in Mediterranean grasslands. We hypothesised that the application of sewage sludge would increase competition between functional groups, reducing the abundance of annuals in the long-term, but would buffer the negative impacts of drought on the year-to-year fluctuation of the diversity of annuals.</span></span></p> <p><span><strong><span>Methods:</span></strong><span> In a semi-natural species-rich Mediterranean grassland in northern Spain, we analysed the changes in the taxonomical and functional composition and diversity of annuals over 14 years in response to variations in the abundance of perennial herbaceous and woody species, climate fluctuations, and fertilisation with sewage sludge. We quantified separately the patterns of year-to-year fluctuations and long-term trends. </span></span></p> <p><span><strong><span>Results:</span></strong><span> The frequency and diversity of annuals decreased with a higher abundance of perennial herbaceous species, drought in June, and cold winters. The addition of sewage sludge decreased the abundance of annuals in the long-term, seemed to promote competition between annuals and other functional groups at an interannual scale, and mitigated the negative effects of drought and cold.</span></span></p> <p><span><span><strong>Conclusions:</strong> Fertilisation influences differently the temporal response of annuals to climate fluctuations and plant-to-plant interactions.</span></span></p>
Impact of climate warming on phenological asynchrony of plankton dynamics across Europe
<p>This dataset includes all data as well as the scripts used to produce figures from both the main text and the supporting information from Gronchi et al. (2023) "Impact of climate warming on phenological asynchrony of plankton dynamics across Europe".</p> <p> </p> <p>Detailed description:</p> <p>Data_TDM_Validation.csv: file containing observed versus simulated timings of TDM for 18 lakes of western Europe.</p> <p>result_full_reference.mat and result_full_const_4C_warming.mat contain the 31-years medians of the lake phenologies for the 16 different simulated lake types and for both the reference and the constant +4°C climate scenario.</p> <p>The two scripts Plot_Fig_1_and_3.m and Plot_Supplement.m are responsible for the production, after treatment of the data, of figures 1 and 3 from the main text and most of the supplement respectively. These scripts include a detailed description of the variables used for producing these figures.</p> <p>Figures 2, 4, S1, S2 and S3 were done with R. For each of these figures there is their respective R script and the reorganized dataset used to produce them.</p> <p> </p> <p>Because of the large size of the inputs and outputs files analyzed in this study we only included the scripts (Output_Generation_Example.m and lakelayerdepth_1.m) and the data ( Meteo_Era_52.5_13.5.dat; Z30_ST00_KW06_52.5_13.5.LST Z30_ST00_KW06_52.5_13.5.Temp) necessary for generation of the phenology medians for one specific lake type at the reference scenario as example. The full dataset (~4To) can be given upon request.</p> <p>Ackowledgment: This product includes color specifications and designs developed by Cynthia Brewer (http://colorbrewer.org/)</p> <p> </p> <p> </p>
Lunar eclipses illuminate timing and climate impact of medieval volcanism
<p>This repository contains all the data and codes needed to reproduce the results and figures from the article "Lunar Eclipses Illuminate Timing and Climate Impacts of the Middle Ages" published in Nature.<br> <br> For more information, we refer the user to the readme file entitled "Guillet_et_al_Nature2023_Readme.txt".<br> <br> If you have any queries, please feel free to contact us: sebastien.guillet@unige.ch<br> <br> Thank you very much ;-)</p>
Lunar eclipses illuminate timing and climate impact of medieval volcanism
<p>This repository contains all the data and codes needed to reproduce the results and figures from the article "Lunar Eclipses Illuminate Timing and Climate Impacts of the Middle Ages" published in Nature.<br> <br> For more information, we refer the user to the readme file entitled "Guillet_et_al_Nature2023_Readme.txt".<br> <br> If you have any queries, please feel free to contact us: sebastien.guillet@unige.ch<br> <br> Thank you very much ;-)</p>
Figure 1 in Impact of climatic factors on sexual size dimorphism in ground beetle Pterostichus melanarius (Illiger, 1798) (Coleoptera, Carabidae)
Figure 1. Elytra length variation in P. melanarius from different habitats (a – females, b – males). Habitats are designated as follows: 1 – meadow, 2 – birch-forest, 3 – elm, 4 – oak-wood, 6 – pine forest, 7 – willow, 8 – shrubs, 9 – lawn, 10 – fir-forest, 11 – garden, 12 – rape field.
Model simulation data used in "The global impact of the transport sectors on the atmospheric aerosol and the resulting climate effects under the Shared Socioeconomic Pathways (SSPs)" (Righi et al., Earth Syst. Dynam., 2023)
<p>This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (<i>Earth Syst. Dynam.</i>, 2023). For details see the README.md file.</p>
Fig. 1 in Adaptations of tenebrionid beetles to Mediterranean sand dune environments and the impact of climate change (Coleoptera: Tenebrionidae)
Fig. 1 – Relationship between activity and temperature in some tenebrionid species in Palestine investigated by Bodenheimer (1934). Activity intensity is expressed by the following rank scale: (1) cold-torpor, (2) only weak, occasional movements of legs and antennae, (3) crawling with interruptions, (4) normal activity, (5) high activity, (6) excited activity, (1) heat-torpor, (0) heat-death. Redrawn from Fattorini (2008) with corrections. Inset: Zophosis punctata (photo S. Fattorini).
Fig. 2 in Adaptations of tenebrionid beetles to Mediterranean sand dune environments and the impact of climate change (Coleoptera: Tenebrionidae)
Fig. 2 – Diel and monthly activity patterns of tenebrionid beetles of Mediterranean dunes. A, diel activity of Erodius siculus in Latium (Central Italy) in May 1997; B, diel activity of Pimelia bipunctata in Latium (Central Italy) in March 1997; C, diel activity of Pimelia bipunctata in the same locality in May 1997. In these experiments, activity was measured as number of individuals intercepted by pitfall traps per hour in single days. After counting, beetles were immediately released. N: number of trapped individuals per hour. Ta: ambient temperature (°C), Ti: soil internal (3-4 cm depth) temperature (°C), Ts: soil surface temperature (°C). D, Phenological patterns of Erodius siculus in Latium (Central Italy) and Sicily (Southern Italy). Phenologies are expressed as number of locations in which the species has been recorded in each month over a period of a century (from 1897 to 1997). A and D are based on Di Stefano & Fattorini (2002). B and C are based on Fattorini & Di Stefano (2004). Photos: courtesy of L. Di Biase.
Dataset corresponding to the « Reasons for concern » about climate change impacts from all IPCC reports (TAR to AR6)
<p>This data corresponds to all the "burning embers" diagrams for the "Reasons for Concern" published in IPCC reports (and the related paper Smith et al. 2009 for AR4) until AR6 (thus including TAR, AR4, AR5, SR1.5 and AR6). For TAR to SR1.5, the data is the result of extracting information from the original figures, as presented in the related technical document <a href="https://doi.org/10.5281/zenodo.3992856">10.5281/zenodo.3992856</a>. As also explained in the Supplementary Information of Zommers et al. (2020), the data does not come directly from the IPCC, although it is based on the assessment provided in the IPCC reports listed in the references. For IPCC AR6, the source is the supplementary material of chapter 16. Details regarding specific values provided in the dataset are explained alongside the values in the main file: "RFCs-ALL-2023_05_12.xlsx". </p> <p>The main file includes the parameters needed to produce a diagram that supplements figure 3 from Zommers et al. (2020) with AR6 data and the confidence levels from previous reports when available. The Excel files in RFCs-2023-UsageExamples.zip contain the same data with different parameters, so that uploading these files to the Ember Factory (<a href="https://climrisk.org/emberfactory">https://climrisk.org/emberfactory</a>) produces different figures - including a comparison between AR5 and AR6 (as in IPCC AR6 Synthesis Report, but with AR5 confidence levels included). The resulting diagrams are also provided.</p>
The potential impact of climate change on European renewable energy droughts
<p>The file contains a supplementary material for an article entitled <em>The potential impact of climate change on European renewable energy droughts</em> (currently under review):</p> <p>The projected change of the total number of drought days for a wind, solar and hybrid generator in relation to the reference period as predicted by the models considered</p> <p> </p>
Data from: The impacts of climate change, energy policy, and traditional ecological practices on future firewood availability for Diné (Navajo) People
<p>These data are part of a data portal that accompanies the special issue 'Climate change adaptation needs a science of culture,' published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit <a href="https://doi.org/10.5061/dryad.bnzs7h4h4"><strong>https://doi.org/10.5061/dryad.bnzs7h4h4</strong></a>.</p> <p>The files consist of the code of an agent-based model (ABM) in a NetLogo, detailed documentation of the ABM in a standard format, and a table of data exported from the simulation experiment reported on in the paper. By downloading the Netlogo file, one could not only rerun the experiment we report on and recreate the data table but toggle parameters or edit the model to explore other dynamics.</p>
ScienceDex guides
Understand access before you commit
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.