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Filters Date Range Past year (1) Past month (0) Past week (0) Past day (0) Custom range... To   Search Extensions ArcGIS Service Definition (1) Budget (1) Project (1) Shapefile (1) Types Citation (9) Map Service (6) OGC WFS Layer (5) OGC WMS Layer (5) Downloadable (4) More... Contacts Jordan S. Read U.S. Geological Survey - ScienceBase Anuj Karpatne Gretchen J.A. Hansen Jared Willard More... Categories Data (40) Project (1) Tag Schemes https://www.sciencebase.gov/vocab/category/NCCWSC/WildlifeandPlants (47) Tags (with Type=Wildlife and Plants ) fish (25) plants (11) birds (4) mammals (4) other wildlife (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 Near-real-time cheatgrass percent cover in the northern Great Basin, USA--2015 This dataset provides an estimate of 2015 cheatgrass percent cover in the northern Great Basin at 250 meter spatial resolution. The dataset was generated by integrating eMODIS NDVI satellite data with independent variables that influence cheatgrass germination and growth into a regression-tree model. Individual pixel values range from 0 to 100 with an overall mean value of 9.85 and a standard deviation of 12.78. A mask covers areas not classified as shrub/scrub or grass/herbaceous by the 2001 National Land Cover Database. The mask also covers areas higher than 2000 meters in elevation because cheatgrass is unlikely to exist at more than 2% cover above this threshold. Cheatgrass is an invasive grass that has invaded... Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: Bromus tectorum, Cheatgrass, MODIS, NDVI, Northwest CASC, All tags... Plants, Wildlife and Plants, annual grass, northern Great Basin, satellite data, Fewer tags Juvenile coho salmon stream survey data and associated analysis to estimate abundance and survival in Mason Creek, tributary of East Fork Lewis River, SW Washington, during summer of 2017 The files in the sub-folder "1. Juvenile coho salmon abundance and survival" consist of fish survey data and the associated analysis. The file "02_Fish survey data_all events_2019-11-27.csv" contains the actual fish survey data that was collected in Mason Creek, tributary of East Fork Lewis River, SW Washington, during summer of 2017. The protocol for the fish surveys are outline in the file "Fish Rescue Field Protocol_2017_FINAL VERSION_2017-06-01.pdf". The abundance and survival analysis can be found in the file "Juvenile MR abundance_Coho_02Contraints_2019-12-02.R". This file should be loaded through the .Rproj file "Fish Abundance.Rproj". There are many files needed to run the analysis that consist of summaries... Categories: Data; Tags: Drought, Drought, Fire and Extreme Weather, Fish, Northwest CASC, Rivers, Streams and Lakes, All tags... Water, Coasts and Ice, Wildlife and Plants, abundance, abundance, mark-recapture, mark-recapture, survival, survival, Fewer tags Weather suitability for mountain pine beetle outbreaks in whitebark pine forests, 2010-2099, Cascades Study Area Estimates of weather suitability for the occurrence of mortality in whitebark pine from mountain pine beetles as determined from a logistic generalized additive model of the presence of mortality as functions of the number of trees killed last year, the percent whitebark pine in each cell, minimum winter temperature, average fall temperature, avverage April-Aug temperature, and cummulative current and previous year summer precipitation. Analysis done at a 1km grid cell resolution. Weather suitability index calculated by summing the weather terms in the model. Calculated for 2010 through 2099 based on numerous downscaled data under several emissions scenarios. GCMs include: BCC, CanESM, CCSM, CESM, CESM-BGC, CMCC,... Categories: Data; Tags: Dendroctonus ponderosae, Forests, Landscapes, Mountain pine beetle, Northwest CASC, All tags... Oregon, Other Wildlife, Pinus albicaulis, Plants, United States, Washington, Wildlife and Plants, whitebark pine, Fewer tags Weather suitability for mountain pine beetle outbreaks in whitebark pine forests, 2010-2099, Greater Yellowstone Ecosystem Study Area Estimates of weather suitability for the occurrence of mortality in whitebark pine from mountain pine beetles as determined from a logistic generalized additive model of the presence of mortality as functions of the number of trees killed last year, the percent whitebark pine in each cell, minimum winter temperature, average fall temperature, avverage April-Aug temperature, and cummulative current and previous year summer precipitation. Analysis done at a 1km grid cell resolution. Weather suitability index calculated by summing the weather terms in the model. Calculated for 2010 through 2099 based on downscaled data from various emissions scenarios. GCMs include: BCC, CanESM, CCSM, CESM, CESM-BGC, CMCC, CNRM, Had-CC,... Categories: Data; Tags: Dendroctonus ponderosae, Forests, Greater Yellowstone Ecosystem, Idaho, Landscapes, All tags... Montana, Mountain pine beetle, Northwest CASC, Other Wildlife, Pinus albicaulis, Plants, United States, Wildlife and Plants, Wyoming, whitebark pine, Fewer tags Submerged aquatic vegetation and environmental data along a salinity gradient in Barataria Bay, Louisiana (2015) This data set includes bi-monthly data on submerged aquatic vegetation species composition, percent cover, above and below ground biomass and environmental data at coastal sites across the fresh to saline gradient in Barataria Bay, LA. This project was co-funded by the South Central Climate Adaptation Science Center and the Gulf Coast Prairie and the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperatives. An alternate reference to this product can be found here. Categories: Data; Types: Citation, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Climatology, Gulf of Mexico, Louisiana Coastal, Plants, Sea-Level Rise and Coasts, All tags... South Central CASC, USGS Science Data Catalog (SDC), Water, Coasts and Ice, Wetlands, Wildlife and Plants, aquatic vegetation, coastal zone management, coastal zones, estuary, salinity, wetland, wetland ecosystems, wetlands, Fewer tags Process-guided deep learning water temperature predictions: 3 Model inputs (meteorological inputs and ice flags) This dataset includes model inputs (specifically, weather and flags for predicted ice-cover) and 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). 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 predictions of lake water temperature Climate change has been shown to influence lake temperatures in different ways. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we focused on improving prediction accuracy for daily water temperature profiles in 68 lakes in Minnesota and Wisconsin during 1980-2018. The data are organized into these items: Spatial data - One shapefile of polygons for all 68 lakes in this study (.shp, .shx, .dbf, and .prj files) Model configurations - Model parameters and metadata used to configure models (1 JSON file, with metadata for each of 68 lakes, indexed by "site_id") Model inputs - Data formatted as model inputs for predicting temperature a. Lake... Tags: 007, 012, Ecology, Fish, Limnology, All tags... MN, Minnesota, Northeast CASC, Rivers, Streams and Lakes, US, USGS Science Data Catalog (SDC), United States, WI, Water Quality, Water Resources, 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: 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 Integrated Population Model With Climate Covariates for Three Breeding Populations of Wilson's Warbler (Cardellina pusilla) Data files in this project were used in an integrated population model for three breeding populations of Wilson’s Warbler (Cardellina pusilla). Data span the years 1992-2008. Data include counts from the North American Breeding Bird Survey (BBS; https://www.pwrc.usgs.gov/BBS/RawData/; wiwa_bbs.csv), adult capture histories (wiwa_ch.csv) and age-specific capture data (wiwa_pdat.csv) from the Monitoring Avian Productivity and Survivorship program (MAPS; http://www.birdpop.org/pages/maps.php), and covariate data derived from the ClimateNA (https://sites.ualberta.ca/~ahamann/data/climatena.html; wiwa_cmd_wt.csv and wiwa_tave_sp.csv) and National Centers for Environmental Prediction (NCEP) ⁄ National Center for Atmospheric... Categories: Data; Tags: Birds, British Columbia, California, Cardellina pusilla, Chihuahua, All tags... ClimateNA, Durango, Jalisco, Monitoring Avian Productivity and Survivorship, NCAR, NCEA, National CASC, Nayarit, Nevada, North American Breeding Bird Survey, Oregon, Sinaloa, Sonora, Southern Baja California, Washington, Wildlife and Plants, Wilson's Warbler, biota, climate, ecology, environment, ornithology, Fewer tags Future Spotted Owl Habitat Scenarios, Northwest Washington Study Area, 2007-2096 The following files are designed to be run using the Path Landscape Model software, version 3.0.4. Later versions of the software cannot run these files. To get a copy of this software, please contact Apex RMS at path@apexrms.com. 1) Path models MUST be run with the provided .MCM and .trd mulitplier files to apply the required transition probability adjustments for procesess such as insect outbreaks, wildfire, and climate change trends. Each Path database is set up with three folders: - The 'Common' folder contains a single Path scenario (also named 'Common'). The Transitions tab within the Common scenario contains the climate-smart STM. - The 'Multipliers' folder contains multipliers specific to each ownership-allocation... Categories: Data; Types: Downloadable; Tags: Birds, Drought, Fire and Extreme Weather, Fire, Forests, Grasslands and Plains, All tags... Landscapes, Northwest CASC, Pacific Coast, Pacific Northwest, Stream temperature, Washington, Wildlife and Plants, climate change, land management, state and transition modeling, vegetation change, vulnerability assessment, wildlife habitat, Fewer tags Weather suitability for mountain pine beetle outbreaks in whitebark pine forests, 2010-2099, Northern Rockies Study Area Estimates of weather suitability for the occurrence of mortality in whitebark pine from mountain pine beetles as determined from a logistic generalized additive model of the presence of mortality as functions of the number of trees killed last year, the percent whitebark pine in each cell, minimum winter temperature, average fall temperature, avverage April-Aug temperature, and cummulative current and previous year summer precipitation. Analysis done at a 1km grid cell resolution. Weather suitability index calculated by summing the weather terms in the model. Calculated for 2010 through 2099 based on numerous downscaled data under several emissions scenarios. GCMs include: BCC, CanESM, CCSM, CESM, CESM-BGC, CMCC,... Categories: Data; Tags: Dendroctonus ponderosae, Forests, Greater Yellowstone Ecosystem, Idaho, Landscapes, All tags... Montana, Mountain pine beetle, Northwest CASC, Other Wildlife, Pinus albicaulis, Plants, United States, Wildlife and Plants, Wyoming, whitebark pine, Fewer tags Seed biomass from shallow coastal water areas along a salinity gradient in Barataria Bay, Louisiana (2015) This dataset provides bi-monthly data on seed biomass collected in shallow water habitats across the fresh to saline gradient at coastal sites in Barataria Bay, Louisiana. This project was co-funded by the South Central Climate Adaptation Science Center and the Gulf Coast Prairie and the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperatives. An alternate reference to this product can be found here. Categories: Data; Types: Citation; Tags: Alabama, Climatology, Gulf of Mexico, Louisiana Coastal, Mississippi Coastal, All tags... Plants, Sea-Level Rise and Coasts, South Central CASC, Texas, USGS Science Data Catalog (SDC), Water, Coasts and Ice, Wetlands, Wildlife and Plants, coastal ecosystems, coastal zones, wetlands, 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 Process-guided deep learning water temperature predictions: 6 Model evaluation (test data and RMSE) 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... 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 1 2 3 »