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This data set contains links that are important to each species' habitat network. Those important links are scored based on the percent currently under protection status, projected change in climate suitability by the middle of the 21st century, and projected change in percent urbanized by the middle of the 21st century. Important links were identified from all links in the networks of each species based on their Integral Index of Connectivity (dIIC). Any links with dIIC scores > 0.9 or which connected to nodes with dIIC > 0.9 were retained here as "important" links.
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UW_Olallie_photo_metadata & image files: These are the raw timelapse photographs. The date/time stamp is inaccurate for the camera deployed in the open (at the SNOTEL) due to a programming error. This timestamp is one day early (i.e., subtract 1 day from the timestamp when using these data). Also available is metadata for two timelapse cameras and their associated snow depth poles (two visible in each camera's field of view) deployed at Olallie Meadows SNOTEL during water year 2015. One camera was deployed in the open area that is the Olallie Meadows SNOTEL station (the snow pillow is in the field of view). The other camera was deployed in the adjacent forest, approximately 60 m to the southeast of the SNOTEL....
This dataset is a continuous parameter grid (CPG) of normal (average) annual precipitation data for the years 1981 through 2010 in the Pacific Northwest. Source precipitation data was produced by the PRISM Climate Group at Oregon State University.
These datasets are continuous parameter grids (CPG) of first-of-month snow water equivalent data for March through August, years 2004 through 2016, in the Pacific Northwest. Normal (average) first-of-month values for the same months, averaged across all years, are also located here. Source snow water equivalent data was produced by the Snow Data Assimilation System (SNODAS) at the National Snow and Ice Data Center.
These datasets are continuous parameter grids (CPG) of permeability (and impermeability) of surface geology in the Pacific Northwest. Source data come from work by Chris Konrad, U.S. Geological Survey (USGS), and geologic map databases produced by USGS scientists.
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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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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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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 includes stream temperatures from two data loggers installed at one site in the Little Blitzen River of SE Oregon as part of a redband trout (Oncorhynchus mykiss gairdnerii) study. The site was used as an undisturbed reference in comparison with similar temperature monitoring sites in the Willow-Whitehorse watershed that experienced a 2012 fire that burned nearly the entire watershed.
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To determine inundation patterns and calculate site-specific tidal datums, we deployed water level data loggers (Model 3001, Solinst Canada Ltd., Georgetown, Ontario, Canada and Model U-20-001-01-Ti, Onset Computer Corp., Bourne, MA, USA) at all sites over the study period. Each site had one or two loggers (n = 16). We placed loggers at the mouth and upper reaches of second-order tidal channels to capture high tides and determine seasonal inundation patterns. Water loggers collected water level readings every six minutes starting on the date of deployment and continuing to the present. We used data from the lowest elevation logger at each site to develop local hydrographs and inundation rates. We surveyed loggers...
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UI_Mica_Location: Location metadata and meteorological and snow depth observations from met towers in the Mica Creek Experimental Forest. Data were collected at 7 different station sites at approximately half-hour intervals for water years 2003-2006, with discontinuous records due to equipment malfunction or damage. Stations were located within different forest harvest treatment sections, applied to the watershed in approximately 2001, including clear-cut harvest, partial harvest, and control sections (both second growth and old growth control forests). Site Data Citation for full description of the field campaign and sites. UI_Mica_met: Metadata and associated snow depth and SWE observations from 14 manual...
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The research was conducted at eight tidal marshes in coastal estuaries spanning the Washington and Oregon coastlines from Padilla Bay in northern Washington to Bandon located at the mouth of the Coquille River in southern Oregon. The researchers performed bathymetric surveys, created digital elevation models, measured historic rates of mineral and organic matter accumulation, conducted vegetation surveys, deployed water level data loggers, and produced WARMER wetland accretion model projections for each study site. This collection contains data for all of the above across a number of different datasets. Users should investigate the metadata for each item for more information about it's purpose, methods, quality,...
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This dataset contains the result of the bioclimatic-envelope modeling of the three amphibian species -- the Sacramento Mountain Salamander (Aneides hardii), the Jemez Mountains Salamander (Plethodon neomexicanus), and the Chiricahua Leopard Frog (Lithobates chiricahuensis) -- in the South Central US using the downscaled data provided by WorldClim. We used five species distribution models (SDM) including Generalized Linear Model, Random Forest, Boosted Regression Tree, Maxent, and Multivariate Adaptive Regression Splines (MARS) and ensembles to develop the present day distributions of the species based on climate-driven models alone. We then projected future distributions of the species using data from four climate...
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This dataset contains the result of the bioclimatic-envelope modeling of the two reptile species -- Rio Grande Cooter (Pseudemys gorzugi) and Gray-Checkered Whiptail (Aspidoscelis dixoni) -- in the South Central US using the downscaled data provided by WorldClim. We used five species distribution models (SDM) including Generalized Linear Model, Random Forest, Boosted Regression Tree, Maxent, and Multivariate Adaptive Regression Splines (MARS) and ensembles to develop the present day distributions of the species based on climate-driven models alone. We then projected future distributions of the species using data from four climate models: Community Climate System Model version 4 (CCSM4), Hadley Centre Global Environment...
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Create an inventory of water-related models that have been developed for the Rio Grande/Bravo basin. The summary includes a description of model river extent, spatial and temporal resolution, time period, model type, and their possible application for testing environmental flows or climate change future alternatives.
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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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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,...
map background search result map search result map Water Monitoring Data, All Study Sites, 2011-2015 Long format snow course observations, meteorological sensor observations,locations, and associated metadata for Mica Creek, Idaho Timelapse photos at SNOTEL station, locations, and associated metadata, Ollalie Meadows, Wash., 2015 Wisconsin Lake Temperature Metrics Decreasing Clarity Projected future bioclimate-envelope suitability for amphibian species in South Central USA Projected future bioclimate-envelope suitability for reptile species in South Central USA Potential climate change impacts on alpine connectivity in the U.S. Northern Rockies Potential climate change impacts on grassland connectivity in the U.S. Northern Rockies River extent of water related models in the Rio Grande/Bravo basin Stream Temperature Data in the Little Blitzen watershed of SE Oregon, 2009-15 Important links for Black bear, Rafinesque's big-eared bat, and timber rattlesnake Field and model data for studying the effects of sea-level rise on eight tidal marshes in coastal Washington and Oregon Model input and output for hydrologic simulations in the Rio Grande Headwaters, Colorado, using the Precipitation-Runoff Modeling System (PRMS) 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 Stream Temperature Data in the Little Blitzen watershed of SE Oregon, 2009-15 Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs Timelapse photos at SNOTEL station, locations, and associated metadata, Ollalie Meadows, Wash., 2015 Long format snow course observations, meteorological sensor observations,locations, and associated metadata for Mica Creek, Idaho Model input and output for hydrologic simulations in the Rio Grande Headwaters, Colorado, using the Precipitation-Runoff Modeling System (PRMS) Water Monitoring Data, All Study Sites, 2011-2015 Field and model data for studying the effects of sea-level rise on eight tidal marshes in coastal Washington and Oregon Projected future bioclimate-envelope suitability for amphibian species in South Central USA Projected future bioclimate-envelope suitability for reptile species in South Central USA Wisconsin Lake Temperature Metrics Decreasing Clarity 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 Potential climate change impacts on alpine connectivity in the U.S. Northern Rockies Potential climate change impacts on grassland connectivity in the U.S. Northern Rockies River extent of water related models in the Rio Grande/Bravo basin Important links for Black bear, Rafinesque's big-eared bat, and timber rattlesnake