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Location Folder Show Tree ROOT _ScienceBase Catalog __National and Regional Climate Adaptation Science Centers ___Northeast CASC FY 2012 Projects FY 2013 Projects FY 2014 Projects FY 2015 Projects FY 2016 Projects More... Filters Date Range Past year (5) Past month (0) Past week (0) Past day (0) Custom range... To   Search Extensions Shapefile (6) Types Citation (10) Map Service (7) OGC WFS Layer (7) OGC WMS Layer (7) Downloadable (6) Shapefile (6) OGC WMS Service (1) Contacts U.S. Geological Survey Jordan S. Read Jordan S Read Gretchen J.A. Hansen Alison P. Appling More... Categories Data Release - Revised (1) Tag Types Theme (35) Place (35) Science Themes (29) Water, Coasts and Ice (29) Organization (29) Wildlife and Plants (25) Harvest Set (8) More... Tag Schemes none (22) U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST (22) ISO 19115 Topic Category (34) Common geographic areas (8) None (10) https://www.sciencebase.gov/vocab/category/NCCWSC/ScienceThemes (29) Department of Commerce, 1995, Countries, Dependencies, Areas of Special Sovereignty, and Their Principal Administrative Divisions, Federal Information Processing Standard (FIPS) 10-4, Washington, D.C., National Institute of Standards and Technology (22) More... View Results as: JSON ATOM CSV Browse Folder

A Synthesis of Climate Change Vulnerability Assessment Rankings for Species of Greatest Conservation Need in the Northeast US from 2010-2023 This dataset details individual species and natural habitat vulnerability rankings, including contextual study-specific information. This data was collected from original publications found through a literature search. Information is cumulative to include climate change vulnerability assessment (CCVA) results summarized in Staudinger et al. (2015) and published as of December 2023. Categories: Data; Tags: CCVA, Climate Change Vulnerability Assessment, Climatology, Connecticut, Delaware, All tags... Eastern United States, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Northeast United States, Pennsylvania, RSGCN, Regional Species of Greatest Conservation Need, Rhode Island, SGCN, SWAP, Species of Greatest Conservation Need, State Wildlife Action Plans, USGS Science Data Catalog (SDC), Vermont, Virginia, West Virginia, biota, habitat vulnerability rankings, Fewer tags 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 Inundation observations and inundation model predictions for vernal pools of the northeastern United States 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... Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Hydrology, Maine, Maryland, Massachusetts, New Hampshire, All tags... New Jersey, New York, Northeast CASC, Other Water, Pennsylvania, USGS Science Data Catalog (SDC), Water Resources, Water, Coasts and Ice, West Virginia, Wetlands, environment, hydrology, inlandWaters, vernal pools, wetland ecosystems, Fewer tags Inundation observations, climate data, and landscape attributes for vernal pools of the northeastern United States 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. Categories: Data; Tags: Maine, Maryland, Massachusetts, New Hampshire, New Jersey, All tags... New York, Northeast CASC, Other Water, Pennsylvania, Water, Coasts and Ice, West Virginia, Wetlands, environment, hydrology, inlandWaters, vernal pools, wetland ecosystems, Fewer tags A Remote Sensing Approach to Characterize Winter Water Level Drawdown Patterns in Lakes This data release consists of four datasets that were used for evaluating winter drawdown patterns in 166 Massachusetts lakes greater than 0.3 km2 surface area. The first dataset (“Water area and level.csv”) provides water area and water level time series data of 166 lakes from 2016 to 2021. Water area and water level time-series data were derived from European Space Agency’s Sentinel 1 synthetic aperture radar satellite sensor using the JavaScript code in Google Earth Engine platform. Details of this code were described in the software release (https://doi.org/10.5066/P9ZA5I1U). The second dataset (“Water area interpolated.csv”) is the linearly-interpolated daily water area time series data of the 166 lakes from... Categories: Data; Tags: Massachusetts, USGS Science Data Catalog (SDC), environment, hydrology, lake, All tags... natural resource management, remote sensing, water level measurements, 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 Inundation predictions for vernal pools of the northeastern United States at various seasonal time points under various weather and climate scenarios 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... Categories: Data; Tags: Maine, Maryland, Massachusetts, New Hampshire, New Jersey, All tags... New York, Northeast CASC, Other Water, Pennsylvania, Water, Coasts and Ice, West Virginia, Wetlands, environment, hydrology, inlandWaters, vernal pools, wetland ecosystems, Fewer tags Passive Integrated Transponder data for daily survival model in the West Brook, Whately, MA, 2000-2015 Recapture data for trout in a stream. Format is appropriate for CJS modelling. Categories: Data; Tags: Aquatic Biology, Ecology, Northeast CASC, Rivers, Streams and Lakes, Survival, All tags... Trout, USGS Science Data Catalog (SDC), Water, Coasts and Ice, Whately, MA, 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 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: 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 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 1 2 »