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NOTE: A newer version of this database is available at https://doi.org/10.5066/P9973SMC. Inland fishes provide important ecosystem services to communities worldwide and are especially vulnerable to the impacts of climate change. Fish respond to climate change in diverse and nuanced ways, which creates challenges for practitioners of fish conservation, climate change adaptation, and management. Although climate change is known to affect fish globally, a comprehensive online, public database of how climate change has impacted inland fishes worldwide and adaptation or management practices that may address these impacts does not exist. We conducted an extensive, systematic primary literature review to identify peer-reviewed...
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The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) was used to assess the effects of changing climate and land disturbance on seasonal streamflow in the Rio Grande Headwaters (RGHW) region. Three applications of PRMS in the RGHW were used to simulate 1) baseline effects of climate, 2) effects of bark-beetle induced tree mortality, and 3) effects of wildfire, on components of the hydrologic cycle and subsequent seasonal streamflow runoff from April through September for water years 1980 through 2017. PRMS input files and select PRMS output variables for each simulation are contained in this data release to accompany the journal article.
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This data release includes data-processing scripts, data products, and associated metadata for a study to model the hydrology of several hundred vernal pools (i.e., seasonal pools or ephemeral wetlands) across the northeastern United States. More information on this study is available from the project website. This data release consists of several components: (1) an input dataset and associated metadata document ("pool_inundation_observations_and_climate_and_landscape_data"); (2) an annotated R script which processes the input dataset, performs inundation modeling, and generates model predictions ("annotated_R_script_for_pool_inundation_modeling.R"); and (3) a model prediction dataset and associated metadata document...
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The dataset provided here and described in this metadata document consists of several components: (1) pool-specific attributes including name and geographic location, (2) time-varying inundation observations collected between May 2004 and July 2016; (3) landscape attributes associated with pool locations including geologic, soil, and landcover characteristics; (4) short- and medium-term weather and climate variables for time periods (for example, 5-days and 6-months) immediately preceding the dates of inundation observations; and (5) long-term (30-year average) climate variables associated with pool locations.
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Abstract (from http://www.springerplus.com/content/3/1/589): The growing quality and availability of spatial map layers (e.g., climate, geology, and land use) allow stream studies, which historically have occurred over small areas like a single watershed or stream reach, to increasingly explore questions from a landscape perspective. This large-scale perspective for fluvial studies depends on the ability to characterize influences on streams resulting from throughout entire upstream networks or catchments. While acquiring upstream information for a single reach is relatively straight-forward, this process becomes demanding when attempting to obtain summaries for all streams throughout a stream network and across...
Establishing connections among natural landscapes is the most frequently recommended strategy for adapting management of natural resources in response to climate change. The U.S. Northern Rockies still support a full suite of native wildlife, and survival of these populations depends on connected landscapes. Connected landscapes support current migration and dispersal as well as future shifts in species ranges that will be necessary for species to adapt to our changing climate. Working in partnership with state and federal resource managers and private land trusts, we sought to: 1) understand how future climate change may alter habitat composition of landscapes expected to serve as important connections for wildlife,...
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These data were generated with MAXENT 3.3.3k freeware (Phillips et al. 2011) using climate data and fire probability data for for three time periods: reference (1900-1929), mid-century (2040-2069) and late century (2070-2099), and community occurrence point data extracted from LANDFIRE Environmental Site Potential (ESP). Future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. In MAXENT, we used the logistic output format (generating presence probabilities between 0 and 1), a random test percentage of 30 (using 70 % of the occurrence points to generate the suitability model and 30 % of the occurrence points to validate it), and a jackknife test to measure variable importance....
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The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) was used to assess the effects of changing climate and land disturbance on seasonal streamflow in the Rio Grande Headwaters (RGHW) region. Three applications of PRMS in the RGHW were used to simulate 1) baseline effects of climate (see RGHW-PRMS_baseline_input.zip), 2) effects of bark-beetle induced tree mortality (see RGHW-PRMS_BB_input.zip), and 3) effects of wildfire (see RGHW-PRMS_fire_input.zip), on components of the hydrologic cycle by hydrologic response unit (HRU) and subsequent seasonal streamflow runoff from April through September for water years 1980 through 2017. PRMS input files (control, climate-by-hru, data, parameter, dynamic...
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The dataset provided here and described in this metadata document contains predicted wetness probability (PWP) values for vernal pools under a variety of weather and climate conditions at several seasonal time points, generated using inundation models as described in the processing steps section of this metadata document and in the annotated R script included in this data release ("annotated_R_script_for_pool_inundation_modeling.R"). PWP values represent the predicted likelihood of a pool holding water according to a specified inundation threshold, as defined in this metadata document. PWP values can theoretically range from 0 (pool is predicted to have no chance of inundation) to 1 (pool is predicted to have 100...
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This dataset represents results from this study attributed to the Hydrologic Unit Code (HUC) 12 watershed boundaries. Human impacts occurring throughout the Northeast and Midwest United States, including urbanization, agriculture, and dams, have multiple effects on the region’s streams which support economically valuable stream fishes. Changes in climate are expected to lead to additional impacts in stream habitats and fish assemblages in multiple ways, including changing stream water temperatures. To manage streams for current impacts and future changes, managers need region-wide information for decision-making and developing proactive management strategies. Our project met that need by integrating results...
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We compiled and analyzed a database of burn permits for prescribed fires conducted in Florida and Georgia from 2006-2016. The dataset contains the number of permitted burns and expected acres burned by county in the two states for every day in the 11 year period. Also included are the county-wide average daily weather conditions for temperature and relative humidity, calculated from the University of Idaho gridMet dataset.
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Streamflow Permanence Probability (SPP) rasters represent the raw streamflow permanence probabilities produced by the PRObability of Streamflow PERmanence (PROSPER) model, annually for years 2004 through 2016, and overall mean and standard deviation. The PROSPER model is a GIS raster-based empirical model of probabilistic predictions of a stream channel having year-round flow for any unregulated and minimally-impaired stream channel in the Pacific Northwest region, U.S. The model provides predictions of annual streamflow permanence probabilities at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions and static physiographic variables associated with the upstream basin. Predictions...
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The northern Gulf of Mexico coast spans two major climate gradients and represents an excellent natural laboratory for developing climate-influenced ecological models. In this project, we used these zones of remarkable transition to develop macroclimate-based models for quantifying the regional responses of coastal wetland ecosystems to climate variation. In addition to providing important fish and wildlife habitat and supporting coastal food webs, these coastal wetlands provide many ecosystem goods and services including clean water, stable coastlines, food, recreational opportunities, and stored carbon. Our objective was to examine and forecast the effects of macroclimatic drivers on wetland ecosystem structure...
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The northern Gulf of Mexico coast spans two major climate gradients and represents an excellent natural laboratory for developing climate-influenced ecological models. In this project, we used these zones of remarkable transition to develop macroclimate-based models for quantifying the regional responses of coastal wetland ecosystems to climate variation. In addition to providing important fish and wildlife habitat and supporting coastal food webs, these coastal wetlands provide many ecosystem goods and services including clean water, stable coastlines, food, recreational opportunities, and stored carbon. Our objective was to examine and forecast the effects of macroclimatic drivers on wetland ecosystem structure...
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Natural selection may result in local adaptation to different environmental conditions across the range of a species. Understanding local adaptation, in turn, informs management decisions such as translocation to restore locally-extinct populations. We used a landscape genomics approach to detect genetic signatures of selection related to climatic variation among desert bighorn sheep populations across their indigenous range in the western United States. This approach allowed us to investigate broad patterns of both neutral and adaptive genetic variation across very different environments. Analyses suggested that ancestry and isolation by distance were the most significant forces driving genetic variation in desert...
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Streamflow Permanence Class (SPC) rasters represent the classification of the raw streamflow permanence probabilities produced by the PRObability of Streamflow PERmanence (PROSPER) model into categorical wet and dry classes, annually for years 2004 through 2016, and overall mean. Raw probabilities were classified into a -5 (dry) to +5 (wet) scale based on the spatially variable threshold (i.e., value that predicts the wet/dry break point) and confidence interval rasters. In general, the farther a raw probability value is from the threshold value for a given pixel, the farther the categorical value is from zero for that pixel. For example, a raw probability that is less than the threshold value minus the critical...
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These data were generated with MAXENT 3.3.3k freeware (Phillips et al. 2011) using climate data and fire probability data for for three time periods: reference (1900-1929), mid-century (2040-2069) and late century (2070-2099), and community occurrence point data extracted from LANDFIRE Environmental Site Potential (ESP). Future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. In MAXENT, we used the logistic output format (generating presence probabilities between 0 and 1), a random test percentage of 30 (using 70 % of the occurrence points to generate the suitability model and 30 % of the occurrence points to validate it), and a jackknife test to measure variable importance....
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Fire in the western U.S. poses one of the greatest threats to human and ecological communities alike. In fact, fire management is the largest single expenditure of land management funds on federal lands. Now, climate change is altering wildfire patterns. Climate change in the West is creating warmer and drier conditions, resulting in an increase in the amount of dead vegetation available to fuel fires. This project sought to assess the vulnerability of forests in the southwestern U.S. to climate change and wildfire, in order to understand how these ecosystems might become altered as a result. Researchers (a) examined how climate change impacts wildfires in the region, to better understand fire risk; (b) identified...
These datasets consists of responses to a standardized, web-based survey of partners and potential partners of the regional Climate Adaptation Science Center (CASC). An initial sample for the survey was compiled from science producers and science users identified by the CASC, Landscape Conservation Cooperative staff and steering committee members with regions that overlapped with the CASC's region, and members of the AFWA Climate Science Committee. The survey documented the ways in which partners were engaged with the CASC and the factors affecting their engagement. The survey questions were developed based on insights from the focus groups conducted during the reviews of three previous CASCs and a review of the...


map background search result map search result map The Vulnerability of Forests to Climate Change and Wildfire in the Southwestern U.S. An approach for aggregating upstream catchment information to support research and management of fluvial systems across large landscapes U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Macroclimate Vegetation Data Section 1 (2013-2014) U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Macroclimate Landscape and Climate Data (2013-2014) Fishtail huc12: Indices and supporting data characterizing the current (1961-2000) and future (2041-2080) risk to fish habitat degradation in the Northeast Climate Science Center region Reference period and projected environmental suitability scores Reference period and projected environmental suitability scores-Oaks Streamflow Permanence Class (SPC) rasters (PROSPER) Streamflow Permanence Probability (SPP) rasters (PROSPER) Evaluating Adaptive Capacity of Desert Bighorn Sheep to Climate Change: Identifying Genetic to Climate Adaptations in Native and Reintroduced Populations-SNP Matrix Prescribed Fire Permit Records for Georgia and Florida Model input and output for hydrologic simulations in the Rio Grande Headwaters, Colorado, using the Precipitation-Runoff Modeling System (PRMS) Model input for Precipitation-Runoff Modeling System simulations in the Rio Grande Headwaters, Colorado, for water years 1980 through 2017 Inundation observations and inundation model predictions for vernal pools of the northeastern United States Inundation observations, climate data, and landscape attributes for vernal pools of the northeastern United States Inundation predictions for vernal pools of the northeastern United States at various seasonal time points under various weather and climate scenarios Model input and output for hydrologic simulations in the Rio Grande Headwaters, Colorado, using the Precipitation-Runoff Modeling System (PRMS) Model input for Precipitation-Runoff Modeling System simulations in the Rio Grande Headwaters, Colorado, for water years 1980 through 2017 Evaluating Adaptive Capacity of Desert Bighorn Sheep to Climate Change: Identifying Genetic to Climate Adaptations in Native and Reintroduced Populations-SNP Matrix U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Macroclimate Vegetation Data Section 1 (2013-2014) U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Macroclimate Landscape and Climate Data (2013-2014) Prescribed Fire Permit Records for Georgia and Florida Inundation observations and inundation model predictions for vernal pools of the northeastern United States Inundation observations, climate data, and landscape attributes for vernal pools of the northeastern United States Inundation predictions for vernal pools of the northeastern United States at various seasonal time points under various weather and climate scenarios The Vulnerability of Forests to Climate Change and Wildfire in the Southwestern U.S. Streamflow Permanence Class (SPC) rasters (PROSPER) Streamflow Permanence Probability (SPP) rasters (PROSPER) Fishtail huc12: Indices and supporting data characterizing the current (1961-2000) and future (2041-2080) risk to fish habitat degradation in the Northeast Climate Science Center region An approach for aggregating upstream catchment information to support research and management of fluvial systems across large landscapes Reference period and projected environmental suitability scores Reference period and projected environmental suitability scores-Oaks