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2,260 results for “climate change”
Dataset to the manuscript "Deciduous tundra shrubs shift toward more acquisitive light absorption strategy under climate change treatments"
<p>The three datasets were used for the statistical analysis for the manuscript entitled "Deciduous tundra shrubs shift toward more acquisitive light absorption strategy under climate change treatments".</p>
Additional online material for publication: Frames and Narratives in scientific press releases on ocean climate change and ocean plastic.
<p>This is the additional material for the publication of paper: Frames and Narratives in scientific press releases on ocean climate change and ocean plastic. The paper is currently under submission. </p> <p>Included with the material is a codebook used to code narrative- and frame variables in scientific press releases and a cross-tabulate showing the frame variables that were coded per press release. </p> <p>For questions about the material, or information about how to reference to the material, please contact Aike Vonk (a.n.vonk@uu.nl).</p>
Climate change threats to the global functional diversity of freshwater fish
<p>This dataset provides supplementary information for the paper entitled "Climate change threats to the global functional diversity of freshwater fish".</p> <p> </p> <p><strong>Fish trait data</strong></p> <p>fish_traits_removed.csv<br> - species with missing trait values were removed<br> - species coverage: 3,792</p> <p>fish_traits_imputed.csv<br> - missing trait values were imputed<br> - species coverage: 11,425</p> <p>Traits<br> - HLrel = relative head length<br> - BDrel = relative body depth<br> - Troph = trophic level<br> - K = relative growth rate</p> <p><br> <strong>Geospatial data</strong></p> <p>Files<br> Data under the assumption of no dispersal<br> - SR.tif: species richness<br> - FRic.tif: functional richness<br> - FEve.tif: functional evenness<br> - FDiv.tif: functional divergence<br> - FRic_loss.tif: functional richness loss<br> - FEve_loss.tif: functional evenness loss<br> - FDiv_loss.tif: functional divergence loss</p> <p>Data under the assumption of maximal dispersal<br> - SR_dispersal.tif: species richness<br> - FRic_dispersal.tif: functional richness<br> - FEve_dispersal.tif: functional evenness<br> - FDiv_dispersal.tif: functional divergence<br> - FRic_loss_dispersal.tif: functional richness loss<br> - FEve_loss_dispersal.tif: functional evenness loss<br> - FDiv_loss_dispersal.tif: functional divergence loss</p> <p>Layers<br> - imp_*: missing trait values were imputed<br> - rem_*: species with missing trait values were removed<br> - *_hist: historical reference scenario<br> - *_1p5: warming level of 1.5°C<br> - *_2p0: warming level of 2.0°C<br> - *_3p2: warming level of 3.2°C<br> - *_4p5: warming level of 4.5°C</p> <p>Spatial resolution: 0.08333333, 0.08333333 (x, y)<br> Spatial extent: -180, 180, -60, 85 (xmin, xmax, ymin, ymax)<br> Coordinate reference system: WGS84</p>
Direct and indirect effects of climate and land use change on food webs in lakes and streams
<p>Here, we provide the data and code necessary to reproduce the workflow and analysis in: Barbosa and Siqueira. Direct and indirect effects of climate and land use change on food webs in lakes and streams. A preprint is available at https://doi.org/10.1101/2022.04.18.488700</p> <p>We compiled multicontinental data to investigate how climate and land use change are related to the structure of freshwater food webs, considering the inherent differences in lentic and lotic ecosystems. We analyzed the direct and indirect relationships between land use intensity, and temperature and precipitation changes, and food webs using multi-group structural equation modeling. Freshwater food webs were obtained from three sources: the Mangal interaction database, using the rmangal package in R, the GlobAl databasE of traits and food Web Architecture (GATEWAY) version 1.0, and the Interaction Web Data Base (IWDB). We also included food webs acquired from a search in the Web of Science Core Collection. Land use data was compiled from the global ESA CCI database, an annually generated land cover product at 300 m resolution for the period 1992 – 2015. Climate data was compiled from the TerraClimate database, a monthly generated product for climate and climatic water balance for global terrestrial surfaces at ~ 4 km for the period 1958 – 2015. </p>
Data for "Climate change is shifting and narrowing prescribed fire windows in the Western United States"
<p><strong>The data archived here represent two types of information used in the publication “Climate change is shifting and narrowing prescribed fire windows in the Western United States” by Swain et al. 2023:</strong></p> <p>1) The meteorological and vegetation dryness/fuel moisture data (as described within the file) extracted from prescribed fire burn plans around the Western United States (drawn from entities such as the U.S. Forest Service, U.S. National Park Service, and The Nature Conservancy) between 2002 and 2022. This data is provided in tabular form, both as an .xlsx file and a .csv file for the convenience of the user. In addition to the specific values from each burn plan, summaries of median values for forested and non-forested landscapes are provided as well.</p> <p>2) The number of days on which environmental conditions (i.e., weather and vegetation fuel moistures) are acceptable for prescribed fire according to the composite metric described in Swain et al. 2023 (known as “RxDays”). Underlying RxDay definitions are different for forest and non-forested landscapes. This data is provided in geospatially explicit (gridded) form as NetCDF files, which are a self-describing file format. Each file is provided as a single 3-dimensional hypercube (i.e., dimensions of time, latitude, and longitude, respectively; units and details described within the file) corresponding to the number of RxDays per calendar month.</p> <p>One file is provided for each climate model iteration (as identified in each filename); these represent projected RxDays at monthly scale between 1981 and 2060 using an RCP 4.5 climate forcing trajectory. An additional file (rx_gridMET.nc) is provided that represents the same values from an atmospheric reanalysis dataset, which represents a best estimate of observed RxDay values (1981-2020).</p>
Dataset "What children know and want to know about climate change: a prior-knowledge self-assessment"
<p>Dataset: Responses to two open questionnaires: Questionnaire1: "What do you know about climate change?"; Questionnaire 2: "Waht do you want to know about climate change?" Applied to middle school students, from the ages of 10 (5<sup>th</sup> grade) until the ages of 13 (8<sup>th</sup> grade), at schools "Escola Básica e Secundária Dr. Pascoal José de Mello" and "Escola Nº 2 de Avelar" from the municipality of Ansião at the central region of Portugal. The survey was applied to students both individually (n=106) and in group (n= 60), encompassing a total of 417 students. Due to logistical reasons, it was no possible to gather individual questionnaires for the 5<sup>th</sup> grade.</p> <p> </p>
Climate Change Risk Assessment Dataset for Serbian Agriculture
<p>This dataset contains the assessment of observed climate change to the agriculture in Serbia. Data are given on a lat/lon gird with 0.01° horizontal resolution in geotif format. Climatic and bioclimatic indices, as well as risk occurrence frequencies are calculated using interpolated daily observations of temperature and precipitation over Serbia in the period 1998-2017. Statistical significance of the climate indices change, change in category of viticultural indices and increase in risk occurrence is given as well. Analyzed species are: vine grape, fruits (peaches, apricots, cherries, plums, apples, pears and quinces) and crops (corn, sunflower, sugar beet and winter wheat). Calculated climatic indices are: mean annual, vegetational and summer temperature and precipitation; bioclimatic indices: Winkler index, Huglin index, Dryness index, and Cool nights index; risks: drought, frost in the beginning of vegetation, low temeperature during winter, high temperature during summer and intensive rainfall.</p>
Chironomid taxa relative abundance information and lake identifiers for: Changes in midge assemblages reflect climate and trophic gradients across north temperate and boreal lakes since the pre-industrial period
<p>File 1: Relative abundances for chironomid taxa used in the manuscript: Changes in midge assemblages reflect climate and trophic gradients across north temperate and boreal lakes since the pre-industrial period. Lake_ID corresponds to the lake IDs attributed to each lake sampled as part of the LakePulse Network</p> <p>File 2: Lake_ID, lake name, latitude, longitude, sampling date, province, and ecozone for the 69 lakes examined in the manuscript: Changes in midge assemblages reflect climate and trophic gradients across north temperate and boreal lakes since the pre-industrial period. </p>
Data and code for Haberle, Hackenberger et al.: Effects of climate change on gilthead seabream aquaculture in the Mediterranean
<p>The submission was prepared to accompany the publication Haberle, Hackenberger et al. "Effects of climate change on gilthead seabream aquaculture in the Mediterranean" in Aquaculture (https://doi.org/10.1016/j.aquaculture.2023.740052).</p> <p>The simulations source code is available through GitHub repository at:<br> https://github.com/QuantEcoLab/SparusSim_Haberle_et_al_2023</p> <p>The Zanodo archive contains GeoTIFF images underlying the figures in the publication, with the corresponding description in the Readme file.</p>
Data and code for "Climate change shapes richness-evenness relationships in a subalpine grassland experiment"
<p>Aggregated Biodiversity metrics derived from the biodiversity data collected from the ClimGrass experiment at the Agricultural Research and Education Centre (AREC) in Raumberg-Gumpenstein. Data and code needed to reproduce the analyses in "Climate change shapes richness-evenness relationships in a subalpine grassland experiment" are included.</p>
Dataset for Disturbance: a double-edged sword for restoration in a changing climate: Western Oregon and Washington upland prairies 2019-2020
Data associated with the paper submitted to Restoration Ecology in November 2021: Disturbance: a double-edged sword for restoration in a changing climate Alejandro Brambila1, Paul B. Reed1, Scott D. Bridgham1, Bitty A. Roy1, Bart R. Johnson2, Laurel Pfeifer-Meister1 and Lauren M. Hallett1 1. Institute of Ecology and Evolution, University of Oregon 2. Department of Landscape Architecture, University of Oregon In this project, we used this data to test how fire disturbance, designed to enhance restoration seeding success, combines with climate and initial vegetation conditions to shift perennial versus annual grass dominance and overall community diversity in Pacific Northwest grasslands. We seeded both native and introduced perennial grasses and native forbs in paired, replicated burned-unburned plots in three sites along a latitudinal climate gradient from southern Oregon to Washington. Past restoration and climate manipulations at each site had increased the variation of starting conditions between plots. This data is to be used with the script, full_disturbance_script.R, which can be accessed at https://github.com/HallettLab/hops. Includes the tables: plotkey.csv spkey.csv mixkey.csv vegplot.csv vegplot2020.csv
Climate Change Impacts for 14 Tree Species in Southwest Colorado
Forest management traditionally has been based on expectation of a steady climate. In the face of a changing climate, management requires projections of changes in the distribution of the climatic niche of the major species and strategies for applying the projections. We prepared climatic habitat models incorporating heatload as a topographic predictor for the 14 upland tree species of southwestern Colorado, USA, an area that has already seen substantial climate impacts. Models were trained with over 800,000 points of known presence and absence. Using 11 climate scenarios for the decade around 2060, we classified and mapped change for each species. Projected impacts are extensive. Except for the low-elevation woodland species, persistent habitat is rare. Most habitat is lost or threatened and is poorly compensated by emergent habitat. Three species may be locally extirpated. Nevertheless, strategies are described that can use the projections to apply management where it is likely to be most effective, to facilitate or assist migration, to favor species likely to be suited in the future, and to identify potential climate refugia.
Projected climate and canopy change lead to thermophilization and homogenization of forest floor vegetation in a hotspot of plant species richness, Berchtesgaden National Park, Bavaria, Germany
Mountain forests are plant diversity hotspots, but changing climate and increasing forest disturbances will likely lead to far-reaching plant community change. Projecting future change, however, is challenging for forest understory plants, which respond to forest structure and composition as well as climate. Here, we jointly assessed effects of both climate and forest change, including wind and bark beetle disturbances, using the process-based simulation model iLand in a protected landscape in the northern Alps (Berchtesgaden National Park, Germany), asking: (1) How do understory plant communities respond to 21st-century change in a topographically complex mountain landscape, representing a hotspot of plant species richness? (2) How important are climatic changes (i.e., direct climate effects) versus forest structure and composition changes (i.e., indirect climate effects and recovery from past land use) in driving understory responses at landscape scales? Stacked individual species distribution models fit with climate, forest, and soil predictors (248 species currently present in the landscape, derived from 150 field plots stratified by elevation and forest development, overall AUC = 0.86) were driven with projected climate (RCP4.5 and RCP8.5) and modeled forest variables to predict plant community change. Nearly all species persisted in the landscape in 2050, but on average 8% of the species pool was lost by the end of the century. By 2100, landscape mean species richness and understory cover declined (-13% and -8%, respectively), warm-adapted species increasingly dominated plant communities (i.e., thermophilization, +12%), and plot-level turnover was high (62%). Subalpine forests experienced the greatest richness declines (-16%), most thermophilization (+17%), and highest turnover (67%), resulting in plant community homogenization across elevation zones. Climate rather than forest change was the dominant driver of understory responses. The magnitude of unabated 2
Data and code from: A mixture of grass-legume cover crop species may ameliorate water stress in a changing climate, a greenhouse experiment at Dickinson College in Carlisle, PA, USA, 2021.
Data and R code associated with a greenhouse study investigating the influence of water stress on growth, root traits, and biomass of rye and crimson clover seedlings grown separately or together. Data were collected in the Dr. Inge P. Stafford Greenhouse of Dickinson College (Carlisle PA, USA) in June 2021.
Macrosystems EDDIE Module 1: Climate Change Effects on Lake Temperatures
Climate change is modifying the thermal structure of lakes around the globe. Because it is difficult to predict how lakes will respond to the many different aspects of climate change (e.g., altered temperature, precipitation, wind, etc.), many researchers are using models to manipulate climate scenarios and simulate lake responses. Lake simulation models provide a powerful tool for exploring the sensitivity of lake thermal structure characteristics to weather. In this module, students will learn how to set up a lake model (General Lake Model; GLM) and "force" the model with climate scenarios of their own design to test hypotheses about how lakes may change in the future. Once students have mastered running one climate scenario for their lake, they will learn how to use distributed computing tools to scale up and run hundreds of different climate scenarios for their lakes. The overarching goal of this module is for students to explore new modeling and computing tools while learning fundamental concepts about how climate change will affect lakes. The A-B-C structure of this module makes it flexible and adaptable to a range of student levels and course structures. This dataset contains instructional materials and the files necessary to run the complete module. Readers are referred to the GLM science manual (Hipsey et al. 2014) for further details on model configuration.
Site environmental, climate, water levels and temperatures, vegetation cover, and GIS change detection for assessing permafrost change in fens on the Tanana Flats, central Alaska
This data package provides data used to assess the roles of climate extremes, ecological succession, and hydrology in repeated permafrost aggradation and degradation in fens on the Tanana Flats, central Alaska. The package provides data on site environmental information, Fairbanks climate, vegetation cover, water levels and temperatures, as well as GIS files for fen change detection. The Site data include information on observers, locations, geomorphology, hydrology, soils, vegetation, and disturbance. The table has numerous fields that uses coding for class characteristics and these codes are described in the metadata as well as compiled in the ELS_Arctic_Boreal_Site_Soil_Veg_Code_Sheet_2020.docx. Alaska Climate records for Fairbanks (UAF Experiment Station) from 1904 to 2019 were acquired from the National Oceanic and Atmospheric Administration (https://www.ncdc.noaa.gov/cdo-web/). Additional data were obtained for the Nenana station (about 70 km southwest of Fairbanks), to fill in small data gaps (particularly precipitation/snow depth ruler measurements) in the Fairbanks record. We attributed the data with fields for summer (May-September) and winter periods (November-March) and hydrologic year (October-September) and calculated mean air temperature, precipitation, and snow depth by seasonal period (average of daily values) and year. The broad summer and winter periods were of interest because warmer and wetter summers increase soil heat input and warmer and snowier winters reduce soil heat loss. Fen hydrology data include information on fen water level/pressure and temperatures collected every two hours at seven sites within fens from 2011 to 2014. Vegetation composition and cover of fens, scrub, and forests was sampled to assess effects of thermokarst on vegetation change. Plant cover was determined by point-sampling at 100 points (including repetitive “hits” for all layers) distributed along 5 equally spaced rows (4-m long, 20 points per row) across the 10-m l
The role of down-slope water and nutrient fluxes in the response of Arctic hill slopes to climate change, output from MBLGEMIII for typical tussock-tundra hill slope near Toolik Field Station, Alaska.
Output data sets of the MBL-GEM III model for a typical tussock-tundra hill slope. The model is described in two papers: Le Dizès, S., Kwiatkowski B.L., Rastetter E.B., Hope A., Hobbie J.E., Stow D., Daeschner S., 2003 Modelling biogeochemical responses of tundra ecosystems to temporal and spatial variations in climate in the Kuparuk River Basin (Alaska), Journal of Geophysical Research Vol. 108 No. D2 10.1029/2001JD000960. Rastetter, E.B., B. L. Kwiatkowski, S. Le Dizès, and J.E. Hobbie. 2004. The Role of Down-Slope Water and Nutrient Fluxes in the Response of Arctic Hill Slopes to Climate Change. Biogeochemistry 69:37-62.
The role of fire in the carbon dynamics of the boreal forest I. - Response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach (2003-2100).
The boreal forest contains large reserves of carbon, and across this region wildfire is a common occurrence. To improve the understanding of how wildfire influences the carbon dynamics of this region, methods were developed to incorporate the spatial and temporal effects of fire into the Terrestrial ecosystem Model (TEM). The historical role of fire on carbon dynamics of the boreal region was evaluated within the context of ecosystem responses to changing atmospheric CO2 and climate. These results show that the role of historical fire on boreal carbon dynamics resulted in a net carbon sink; however, fire plays a major role in the interannual and decadal scale variation of source/sink relationships. To estimate the effects of future fire on boreal carbondynamics, spatially and temporally explicit empirical relationships between climate andfire were quantified. Fuel moisture, monthly severity rating, and air temperature explained a significant proportion of observed variability in annual area burned. These relationships were used to estimate annual area burned for future scenarios of climate change and were coupled to TEM to evaluate the role of future fire on the carbon dynamics of the North American boreal region for the 21st Century. Simulations with TEM indicate that boreal North America is a carbon sink in response to CO2 fertilization, climate variability, and fire, but an increase in fire leads to a decrease in the sink strength. While this study highlights the importance of fire on carbon dynamics in the boreal region, there are uncertainties in the effects of fire in TEM simulations. These uncertainties are associated with sparse fire data for northern Eurasia, uncertainty in estimating carbon consumption, and difficulty in verifying assumptions about the representation of fires that occurred prior to the start of the historical fire record. Future studies should incorporate the role of dynamic vegetation to more accurately represent post-fire successional pr
Assessment of the Vulnerability of Permafrost Carbon to Climate Change: A Sensitivity Analysis among Models
This activity is a comparison of how large-scale models represent permafrost carbon dynamics into the future (2010-2299). Model responses were evaluated at several temporal scales. To the extent possible, we standardized driver data and simulation procedures among the models. However, the protocol has been set up so that each model can build upon the procedures used to produce the outputs for historical analysis (1960- 2009) that was published in McGuire et al. 2016 (Global Biogeochemical Cycles 30:1015-1037, doi:10.1002/2016GB005405). Note that this comparison is an offline model comparison in which we assessed the sensitivity of the responses of the models to somewhat standardized forcing data. The activity compared among the models: Carbon dynamics: Predictions of average annual C fluxes (GPP, NPP, RH, CH4 fluxes, disturbance-related emissions, dissolved organic carbon export, lateral land used fluxes, etc.) and major pools for the northern permafrost region for the 2010-2299 period. Soil thermal dynamics: Predictions of annual soil thermal and hydrological dynamics at prescribed depths and the maximum annual active layer depth (in permafrost locations) for the 2010-2299 time period. The spatial simulation data for this project are are available through the National Snow and Ice Data Center (doi: 10.5067/ZRL5WJKN01XM).
Hubbard Brook Experimental Forest: microbial biomass and activity at Climate Change Across Seasons Experiment (CCASE) plots, 2015
This data set includes measurements of microbial biomass and activity measured on the Climate Change Across Seasons Experiment (CCASE) plots in May 2015. Reference (or control) plots are shared with the collaborating Northern Forest DroughtNet experiment. There are six plots total (each 11 x 14m). Two are warmed 5 degrees C throughout the growing season (Plots 3 and 4). Two others are warmed 5 degrees C in the growing season and have snow removed during winter to induce soil freeze/thaw cycles (Plots 5 and 6). Four kilometers (2.5 mi) of heating cable are buried in the soil to warm these four plots. Two additional plots serve as controls for our experiment (Plots 1 and 2). This data set includes measurements of microbial biomass and activity. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
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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.
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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.