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Publicly accessible open spaces provide valuable opportunities for people to exercise, play, socialize, and build community. People are more likely to use public open spaces that are close (ideally within walking distance) to their homes, and larger open spaces often provide more amenities. To assess the potential benefit of creating new open space in the southeast US, we identified areas without access to open space within a certain distance category (in this case, 0.5 miles). Then, for each 30-meter pixel in the study area, we then totaled the number of people within 0.5 miles who do not currently have access to open space within that distance. This represents the number of people who would benefit from new open...
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Publicly accessible open spaces provide valuable opportunities for people to exercise, play, socialize, and build community. People are more likely to use public open spaces that are close (ideally within walking distance) to their homes. To assess the spatial distribution of access to open space for recreation in the southeastern United States, we constructed an index of open space access based on the size of the largest publicly accessible open space within 10 miles of each point on the landscape, using three distance categories to represent whether people can reach the open spaces by walking (within 0.5 mile), via a short drive (within 3 miles), or via a longer drive (within 10 miles). Using the open space access...
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Wild insect pollination has significant positive effects on pollinator-dependent crop production. To assess the spatial distribution of demand for wild insect pollination, we mapped pollinator-dependent crops based on the 2011Cropland Data Layer.
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This dataset includes electrical resistance data from a network of 50 data loggers that was installed throughout the Willow-Whitehorse watershed of SE Oregon in September 2014. Data loggers were downloaded in August 2015 and September 2016. These data loggers were used as “electrical resistance” (ER) sensors, following Chapin et al. 2014. The sensors were Onset HOBO Pendant temperature data loggers that were modified to monitor streamflow intermittency and determine the timing of stream drying.
The American Fisheries Society and the Human Dimensions Research Unit of Cornell University have been engaged by NCCWSC to lead 5-year reviews of the CSCs. The purpose of the CSC review and evaluation is to: 1. Evaluate the effectiveness of each CSC in meeting project goals. 2. Assess the level of scientific contribution and achievement at each CSC with respect to climate modeling, climate change impacts assessments, vulnerability and adaptation of fish, wildlife and their habitats, and collaborative development of adaptation strategies for regional stakeholders, and education and training of graduate and post‐doctoral fellows 3. Evaluate the competencies and efficiencies of each host university in managing...
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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).
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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...
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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...
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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...
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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...
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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...
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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,...
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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,...
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A combination of citizen science inventories and expert assessments will be used to collect critical baseline information on known spring and seep resources using the Spring Ecosystem Inventory and Assessment Protocols and adapting them as needed for the unique arid Sky Island ecosystems. The assessment will collect information on channel morphology, riparian and wetland vegetation, water quality, aquatic macroinvertebrates, and wildlife. This information will be combined with historic data from cooperating agencies (Pima County, Santa Cruz County, USFS, NPA, USGS, USFWS, BLM, and AGFD) in a regional, on-line database to provide a landscape level context for managing resources, which was previously unavailable due...
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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).
The American Fisheries Society and the Human Dimensions Research Unit of Cornell University have been engaged by NCCWSC to lead 5-year reviews of the CSCs. The purpose of the CSC review and evaluation is to: 1. Evaluate the effectiveness of each CSC in meeting project goals. 2. Assess the level of scientific contribution and achievement at each CSC with respect to climate modeling, climate change impacts assessments, vulnerability and adaptation of fish, wildlife and their habitats, and collaborative development of adaptation strategies for regional stakeholders, and education and training of graduate and post‐doctoral fellows 3. Evaluate the competencies and efficiencies of each host university in managing...
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Recreational birding is a popular activity in the United States. To assess the spatial distribution of recreational birding in the southeast, we combined two data sources: eBird (Sullivan et al. 2009) and the National Survey of Fishing, Hunting, and Wildlife-associated Recreation (NSFHWAR; US Department of Interior, Fish and Wildlife Service, and Department of Commerce 2011). We used spatial birding data from eBird to distribute the state-level NSFHWAR birding data by county and land protection status. This information was used to identify priority counties for conservation of birding areas. These are counties with a high level of birding activity where at least 90% of birding activity takes place on unprotected...
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This dataset contains inputs for a numerical groundwater-flow model of the Upper San Pedro Basin in southeastern Arizona and Northern Sonora, Mexico.
A combination of citizen science inventories and expert assessments will be used to collect critical baseline information on known spring and seep resources using the Spring Ecosystem Inventory and Assessment Protocols and adapting them as needed for the unique arid Sky Island ecosystems. The assessment will collect information on channel morphology, riparian and wetland vegetation, water quality, aquatic macroinvertebrates, and wildlife. This information will be combined with historic data from cooperating agencies (Pima County, Santa Cruz County, USFS, NPA, USGS, USFWS, BLM, and AGFD) in a regional, on-line database to provide a landscape level context for managing resources, which was previously unavailable due...
Categories: Data, Project; Types: ArcGIS REST Map Service, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: 2011, AZ-02, AZ-03, Arizona, Arizona, All tags...


map background search result map search result map Springs and Seeps Inventory, Assessment, and Management Planning Project Near-real-time cheatgrass percent cover in the northern Great Basin, USA--2015 Groundwater flow model of Northern Arizona by Pool and others, 2011 Electrical resistance data from the Willow-Whitehorse watersheds of southeast Oregon, USA, 2014-2016 Springs and Seeps Inventory, Assessment, and Management Planning Project Sea Level Rise Systematic Mapping Literature Review Weather suitability for mountain pine beetle outbreaks in whitebark pine forests, 2010-2099, Cascades Study Area Weather suitability for mountain pine beetle outbreaks in whitebark pine forests, 2010-2099, Greater Yellowstone Ecosystem Study Area Pollinator-Dependent Crops in the Southeast United States (2011) Conservation Priorities for Recreational Birding in the Southeast United States, by County (2011) Process-guided deep learning water temperature predictions: 3 Model inputs (meteorological inputs and ice flags) Process-guided deep learning water temperature predictions: 2 Model configurations (lake metadata and parameter values) Process-guided deep learning water temperature predictions: 5c All lakes historical prediction data Process-guided deep learning water temperature predictions: 3c All lakes historical inputs Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs 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 Conservation Priorities for Open Space Recreation Access in the Southeast United States, by Census Block Group (2018) Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs 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 Electrical resistance data from the Willow-Whitehorse watersheds of southeast Oregon, USA, 2014-2016 Springs and Seeps Inventory, Assessment, and Management Planning Project Springs and Seeps Inventory, Assessment, and Management Planning Project Weather suitability for mountain pine beetle outbreaks in whitebark pine forests, 2010-2099, Greater Yellowstone Ecosystem Study Area Weather suitability for mountain pine beetle outbreaks in whitebark pine forests, 2010-2099, Cascades Study Area Groundwater flow model of Northern Arizona by Pool and others, 2011 Sea Level Rise Systematic Mapping Literature Review Process-guided deep learning water temperature predictions: 3 Model inputs (meteorological inputs and ice flags) Process-guided deep learning water temperature predictions: 2 Model configurations (lake metadata and parameter values) Process-guided deep learning water temperature predictions: 5c All lakes historical prediction data Process-guided deep learning water temperature predictions: 3c All lakes historical inputs Near-real-time cheatgrass percent cover in the northern Great Basin, USA--2015 Pollinator-Dependent Crops in the Southeast United States (2011) Conservation Priorities for Recreational Birding in the Southeast United States, by County (2011) Conservation Priorities for Open Space Recreation Access in the Southeast United States, by Census Block Group (2018)