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Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Extensions Shapefile (5) Raster (3) Types Citation (11) Downloadable (8) Map Service (8) OGC WFS Layer (5) OGC WMS Layer (5) More... Contacts U.S. Geological Survey Jordan S. Read Jordan S Read Gretchen J.A. Hansen Alison P. Appling More... Tag Types Wildlife and Plants (37) Tags (with Scheme=https://www.sciencebase.gov/vocab/category/NCCWSC/WildlifeandPlants) fish (25) mammals (5) plants (4) birds (3) View Results as: JSON ATOM CSV

Process-guided deep learning water temperature predictions: 2 Model configurations (lake metadata and parameter values) This dataset provides model specifications used to estimate water temperature from a process-based model (Hipsey et al. 2019). The format is a single JSON file indexed for each lake based on the "site_id". This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD). Categories: Data; Tags: 007, 012, Fish, MN, Minnesota, All tags... Northeast CASC, Rivers, Streams and Lakes, US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs This dataset includes model inputs that describe local weather conditions for Sparkling Lake, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other time periods). There are two comma-delimited files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of... Categories: Data; Tags: 007, 012, Fish, Northeast CASC, Rivers, Streams and Lakes, All tags... US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Process-guided deep learning water temperature predictions: 5c All lakes historical prediction data Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models were configured and calibrated with training data to reduce root-mean squared error. Uncalibrated models used default configurations (PB0; see Winslow et al. 2016 for details) and no parameters were adjusted according to model fit with observations. Deep Learning (DL) models were Long Short-Term Memory artificial recurrent neural network models which used training data to adjust model structure and weights for temperature predictions (Jia et al. 2019). Process-Guided Deep Learning (PGDL) models were DL models with an added... Categories: Data; Tags: 007, 012, Fish, MN, Minnesota, All tags... Northeast CASC, Rivers, Streams and Lakes, US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Process-guided deep learning water temperature predictions: 3c All lakes historical inputs This dataset includes model inputs that describe weather conditions for the 68 lakes included in this study. Weather data comes from gridded estimates (Mitchell et al. 2004). There are two comma-separated files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of lake temperature model inputs and outputs... Categories: Data; Tags: 007, 012, Fish, MN, Minnesota, All tags... Northeast CASC, Rivers, Streams and Lakes, US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Wisconsin Lake Temperature Metrics Decreasing Clarity It is well recognized that the climate is warming in response to anthropogenic emission of greenhouse gases. Over the last decade, this has had a warming effect on lakes. Water clarity is also known to effect water temperature in lakes. What is unclear is how a warming climate might interact with changes in water clarity in lakes. As part of a project at the USGS Office of Water Information, several water clarity scenarios were simulated for lakes in Wisconsin to examine how changing water clarity interacts with climate change to affect lake temperatures at a broad scale. This data set contains the following parameters: year, WBIC, durStrat, max_schmidt_stability, mean_schmidt_stability_JAS, mean_schmidt_stability_July,... Categories: Data; Types: Citation; Tags: 007, 012, Fish, Northeast CASC, Rivers, Streams and Lakes, All tags... US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, Wisconsin, climate change, environment, hydrodynamic model, inlandWaters, lakes, limnology, water clarity, water quality, water temperature, Fewer tags Informing adaptation strategies for maintaining landscape connectivity for Northern Rockies wildlife in the face of climate change 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,... Categories: Data; Tags: Alpine, Connectivity, Environment and Conservation, Forestry, Forests, All tags... Grasslands and Plains, Idaho, Land Use Change, Landscapes, Mammals, Montana, North Central CASC, Rocky Mountains, USGS Science Data Catalog (SDC), United States, Wildlife Biology, Wildlife and Plants, Wyoming, climate change, environment, natural resource management, Fewer tags Model configuration: A large-scale database of modeled contemporary and future water temperature data for 10,774 Michigan, Minnesota and Wisconsin Lakes Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum... Categories: Data; Types: Citation; Tags: 007, 012, Fish, IA, IL, All tags... IN, Illinois, Illinois, Indiana, Indiana, Iowa, Iowa, MI, MN, Michigan, Michigan, Minnesota, Minnesota, Northeast CASC, Rivers, Streams and Lakes, SD, South Dakota, South Dakota, US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, Wisconsin, climate change, environment, inlandWaters, modeling, reservoirs, temperate lakes, thermal profiles, water, Fewer tags Process-guided deep learning water temperature predictions: 4a Lake Mendota detailed training data This dataset includes compiled water temperature data from an instrumented buoy on Lake Mendota, WI and discrete (manually sampled) water temperature records from North Temperate Lakes Long-TERM Ecological Research Program (NTL-LTER; https://lter.limnology.wisc.edu/). The buoy is supported by both the Global Lake Ecological Observatory Network (gleon.org) and the NTL-LTER. This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD). Categories: Data; Tags: 007, 012, Fish, Northeast CASC, Rivers, Streams and Lakes, All tags... US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags 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 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... Categories: Data; Types: Citation, Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Aquatic habitats, Connecticut, Data Visualization & Tools, Delaware, Fish, All tags... Illinois, Indiana, Iowa, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, New Jersey, New York, Northeast CASC, Ohio, Pennsylvania, Rhode Island, Rivers, Streams and Lakes, Science Tools For Managers, Vermont, Virginia, Washington D.C., Water, Coasts and Ice, West Virginia, Wildlife and Plants, Wisconsin, climate change, drainage basins, habitat fragmentation, inlandWaters, land use and land cover, rivers, streams, water quality, Fewer tags Environmental DNA (eDNA) data from aquatic habitats in Oregon and Nevada, 2017 The data sets contains hierarchical taxonomic identification information for DNA sequences detected in water samples from 5 locations. Categories: Data; Tags: Aquatic Biology, Decision-Making Support and Tools, Ecology, Mammals, Nevada, All tags... Northwest CASC, Oregon, Rivers, Streams and Lakes, USGS Science Data Catalog (SDC), Wildlife Biology, aquatic, biodiversity, biota, eDNA, environmental DNA, inlandWaters, Fewer tags Process-guided deep learning water temperature predictions: 6c All lakes historical evaluation data This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB) models were configured and calibrated with training data to reduce root-mean squared error. Uncalibrated models used default configurations (PB0; see Winslow et al. 2016 for details) and no parameters were adjusted according to model fit with observations. Deep Learning (DL) models were Long Short-Term Memory artificial recurrent neural network models which used training data to adjust model structure and weights for temperature predictions (Jia et al. 2019). Process-Guided Deep Learning (PGDL) models were DL models with an added physical constraint for... Categories: Data; Tags: 007, 012, Fish, MN, Minnesota, All tags... Northeast CASC, Rivers, Streams and Lakes, US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Process-guided deep learning water temperature predictions: 3a Lake Mendota inputs This dataset includes model inputs that describe local weather conditions for Lake Mendota, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other time periods). There are two comma-delimited files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of lake... Categories: Data; Tags: 007, 012, Fish, Northeast CASC, Rivers, Streams and Lakes, All tags... US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags West Portrillo Mountains Scaled Quail Brood Survival 2014-2015 Grassland birds are among the most imperiled bird guilds in North America. Scaled quail (Callipepla squamata) are a semi-arid grassland bird whose populations have declined over the past half century. We monitored scaled quail in New Mexico to study the effects of habitat, temperature and precipitation on survival of scaled quail adults, nests, and broods. Categories: Data; Tags: Birds, Drought, Drought, Fire and Extreme Weather, National CASC, New Mexico, All tags... Wildlife and Plants, scaled quail, southwestern US, southwestern United States, Fewer tags West Portrillo Mountains Scaled Quail Adult Survival 2014-2015 Grassland birds are among the most imperiled bird guilds in North America. Scaled quail (Callipepla squamata) are a semi-arid grassland bird whose populations have declined over the past half century. We monitored scaled quail in New Mexico to study the effects of habitat, temperature and precipitation on survival of scaled quail adults, nests, and broods. Categories: Data; Tags: Birds, Drought, Drought, Fire and Extreme Weather, National CASC, New Mexico, All tags... Wildlife and Plants, scaled quail, southwestern US, southwestern United States, Fewer tags Process-guided deep learning water temperature predictions: 1 Spatial data (GIS polygons for 68 lakes) This dataset provides shapefile of outlines of the 68 lakes where temperature was modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD). Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: 007, 012, Fish, MN, Minnesota, All tags... Northeast CASC, Rivers, Streams and Lakes, US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Process-guided deep learning water temperature predictions: 4 Training data This dataset includes compiled water temperature data from a variety of sources, including the Water Quality Portal (Read et al. 2017), the North Temperate Lakes Long-TERM Ecological Research Program (https://lter.limnology.wisc.edu/), the Minnesota department of Natural Resources, and the Global Lake Ecological Observatory Network (gleon.org). This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD). Categories: Data; Tags: 007, 012, Fish, MN, Minnesota, All tags... Northeast CASC, Rivers, Streams and Lakes, US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Process-guided deep learning water temperature predictions: 6a Lake Mendota detailed evaluation data This dataset includes "test data" compiled water temperature data from an instrumented buoy on Lake Mendota, WI and discrete (manually sampled) water temperature records from North Temperate Lakes Long-TERM Ecological Research Program (NTL-LTER; https://lter.limnology.wisc.edu/). The buoy is supported by both the Global Lake Ecological Observatory Network (gleon.org) and the NTL-LTER. The dataset also includes Lake Mendota model erformance as measured as root-mean squared errors relative to temperature observations during the test period. This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD). Categories: Data; Tags: 007, 012, Fish, Northeast CASC, Rivers, Streams and Lakes, All tags... US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Evaluating Adaptive Capacity of Desert Bighorn Sheep to Climate Change: Identifying Genetic to Climate Adaptations in Native and Reintroduced Populations-SNP Matrix 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... Categories: Data; Tags: Arizona, California, Genetic capacity, Mammals, National CASC, All tags... Nevada, Wildlife and Plants, desert bighorn sheep, Fewer tags Temperature data: A large-scale database of modeled contemporary and future water temperature data for 10,774 Michigan, Minnesota and Wisconsin Lakes Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum... Categories: Data; Types: Citation; Tags: 007, 012, Fish, IA, IL, All tags... IN, Illinois, Illinois, Indiana, Indiana, Iowa, Iowa, MI, MN, Michigan, Michigan, Minnesota, Minnesota, Northeast CASC, Rivers, Streams and Lakes, SD, South Dakota, South Dakota, US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, Wisconsin, climate change, environment, inlandWaters, modeling, reservoirs, temperate lakes, thermal profiles, water, Fewer tags Reference period and projected environmental suitability scores-Oaks 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.... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Climate Change, Drought, Fire and Extreme Weather, Environmental Suitability Models, Fire, LANDFIRE, All tags... MAXENT, New Mexico, Oklahoma, Plants, South Central CASC, Texas, Wildlife and Plants, Fewer tags 1 2 »