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This data release contains time-lapse imagery taken at U.S. Geological Survey (USGS) stream gaging stations with associated hydrologic and meteorological data related to each image. These data are to help improve the development of models in detecting water elevation at a given stream gaging station. Images of the water surface and surroundings at USGS stream gaging stations were taken at varying time intervals ranging between every five minutes to an hour. Cameras used include trail cameras, web cameras, and the custom river imagery sensing (RISE) camera. Time-lapse images for each USGS stream gaging station are provided in compressed files (file extension .7z). These files are named in a format to identify the...
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A total of 27 temperature sensors were deployed along the lower 90 miles of the Yakima River at 7 locations where cold water had been previously observed. These 7 cold-water areas had 3 to 6 temperature sensors installed to document the extent and duration of these cold-water areas and their impacts on mainstem temperatures of the Lower Yakima River. Cold-water areas included the mouths of tributaries, alongside channels, and within alcoves. Sensor deployments ranged from 1 to 2 years beginning in October 2018. All temperature data are included in the Yakima.temperatures.zip folder. Details of each monitoring location are provided in the site.locs.csv file. In addition to the raw data and site location information,...
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This R code (Nest_Cards_QC.R) is used to process the raw legacy nest card data (1985 - 2019) and produce the quality controlled legacy nest card data for analysis and sharing. This code does not quality control the double searched plots (R2 plots in 1995-99), which is done in the file ‘PrepData.R’. Basic operations include transforming missing value to a common code, transforming other variable to match the data dictionary for nest cards, and resolving non-unique observer initials. The code requires the raw data (“1985-2019_Nest Cards_10-24-19_cleaned.xlsx”) and the table of observer names (“Observer Names_1985-2019_10-24-19.xlsx”). The code writes the QC nest card file “Nest_Cards_1985_2019_QC.csv”. Mostly obseration...
Categories: Data, Software; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, All tags...
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This is the quality controlled YKD salinity data for fixed and random plots 2006 - 2019. These data are quality controlled using the R code in the file ‘YKDsalinity_QC.R’ to produce the data used for analysis and sharing (‘YKDsalinity_QC.R’). These data should be what is used for analysis or distributed on request.
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The data herein are geochemical (from X-Ray fluorescence spectrometry), grain size (percent clay, silt, sand), lithological (loss on ignition data), bathymetric, reconstructed IVT, and radioactive isotopes (14-C, 210-Pb, 226-Ra, and 137-Cs). These data were collected from sediments from Leonard Lake, Mendocino County, California, USA starting in 2014. Together, these data provide evidence for a record of extreme precipitation going back three millennia, showing regional pluvial and drought cycles.
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These are the images associated with the project, including: (1) OriginalImages: original 863 images provided to West Inc from USFWS and others for model training; (2) YoloSliced: 1897 programmatically cropped original images used for training a YOLO Model (300 x 300 pixels); (3) OriginalImages_Box: 785 annotated images; (4) YoloSliced_Box: 1897 annotated sliced images.
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Annual assessment of nesting populations of geese on the Yukon-Kuskokwim Delta (YKD) provides information for biologists, participants in cooperative goose management plans, and Pacific Flyway technical committees. A ground-based sampling procedure has been used since 1986 to estimate the number of total nests, active nests, and eggs for cackling geese, emperor geese, greater white-fronted geese, and spectacled eiders. Annual information on the size of the nesting population and potential number of young produced contributes long term data needed to understand goose and eider population ecology and better manage these species. The survey has been the primary method of measuring recovery status for the western population...
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Continuous 15-minute time-series suspended-sediment concentration (SSC) data computed from U.S. Geological Survey (USGS) instream turbidity data using a YSI 6-series multi-parameter water quality sonde for the North Mokelumne River near Walnut Grove, California, USGS station #11336685. A model archive summary describes the development of a continuous 15-minute SSC time-series regression model.
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FY2014Although the future of sage grouse depends on the future of sagebrush, we have limited ability to anticipate impacts of climate change on sagebrush populations. Current efforts to forecast sagebrush habitat typically rely on species distribution models (SDMs), which suffer from a variety of well-known weaknesses. However, by integrating SDMs with complementary research approaches, such as historical data analysis and mechanistic models, we can provide increased confidence in projections of habitat change. Our goal is to forecast the effect of climate change on the distribution and abundance of big sagebrush in order to inform conservation planning, and sage grouse management in particular, across the Intermountain...
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The Climate Adaptation Science Centers (CASCs) partner with natural and cultural resource managers, tribes and indigenous communities, and university researchers to provide science that helps fish, wildlife, ecosystems, and the communities they support adapt to climate change. The CASCs provide managers and stakeholders with information and decision-making tools to respond to the effects of climate change. While each CASC works to address specific research priorities within their respective region, CASCs also collaborate across boundaries to address issues within shared ecosystems, watersheds, and landscapes.
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Yellowstone National Park (YNP; Wyoming, Montana, and Idaho, USA) contains more than 10,000 hydrothermal features, several lakes, and four major watersheds. For more than 140 years, researchers at the U.S. Geological Survey and other scientific institutions have investigated the chemical compositions of hot springs, geysers, fumaroles, mud pots, streams, rivers, and lakes in YNP and surrounding areas. Water chemistry studies have revealed a range of compositions including waters with pH values ranging from about 1 to 10, surface temperatures from ambient to superheated values of 95°C, and elevated concentrations of silica, lithium, boron, fluoride, mercury, and arsenic. Hydrogeochemical data from YNP research have...
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FY2019Multijurisdictional, international landscape with many shared priorities but lacks landscape (inter-jurisdictional) perspective. Landscape conservation design process will provide landscape context and future scenarios to support coordinated conservation investment.FY2020Entering Phase 2 of a 3-year project, a Landscape Conservation Design (LCD) will deliver a set of strategies that the Crown Managers Partnership and dozens of stakeholders can deploy to achieve desired ecological conditions based on defined, measurable resource outcomes across the Crown of the Continent ecosystem. LCD is a holistic, participatory process bringing stakeholders together to define a desired future for the Crown landscape and...
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The data are a long-term (1980-present), daily reanalysis of reference evapotranspiration, covering the globe at a spatial resolution of 0.625° Longitude x 0.5° Latitude. Reference evapotranspiration is a measure of evaporative demand, or the "thirst of the atmosphere", basically how much moisture from the surface could evaporate into overpassing air, assuming (i) that enough water is available to evaporate and (ii) the surface is covered with a specific reference crop that completely shades the ground (some other conditions also apply). For this dataset, reference evapotranspiration is derived from the daily implementation of the Penman-Monteith reference evapotranspiration equation (Monteith, 1965) as codified...
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R code that takes in the nest capture history data (chdata.csv), reformats it for model fitting in Program Mark via the R package RMark. A series of models of increasing complexity are fit and compared using AIC. Output is written to text files for each model but is generally not used or saved. Code can be run to generate model results and R workspaces/ object to inspect parameter estimates. The primary purpose of this code is to explore model structures for predicting detection and as an attempt to reproduce historically used parameter estimates in past nest plot reports (e.g., Fischer et al. 2017 and earlier). Results from ‘Model 7’ are most similar to detection estimates used in the past.
Categories: Data, Software; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, BIOLOGICAL CLASSIFICATION, BIOLOGICAL CLASSIFICATION, All tags...
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These are the observer names, observer initials, year, and unique observer number for all observe that collected data on the YKD nest plot project from 1985 to 2019. This data is used with the nest card data to in various ways, but primarily to calculate cumulative observer experience for nest detection rates. This file is also used for quality control and reconciling non-unique observer initials across years.
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, All tags...
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This R code (YKDsalinity_QC.R) is used to process the raw legacy salinity data for fixed and random plots (2006 - 2019) and produce the quality controlled legacy salinity data for analysis and sharing (YKDsalinity_QC.csv). Basic operations include transforming missing value to a common code, transforming other variables to match the data dictionary, and cleaning spatial location issues. Of special note is that this QC process discover significant error in location data due to a variety of reasons so the random plot centers are added to the data table and should be used for analysis. The code requires the raw data (“Official_YKD.SALINITY.DATA.MASTER.2020.csv”), a definition of the nest plot study area (“NestPlotStudyAreaBoundary.geojson”),...
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This is the YKD egg observation data reformatted from the nest card data (‘Nest_Cards_1985_2019_QC.csv’). The file eggs.R is used to produce this data set, and then this is further summarized into yearly stats on mean initiation and hatch dates to produce the file yearstats.csv.
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, All tags...
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From 1995 to 1999, a subset of nest plots were searched twice by field crews to estimate nest detection probability by mark-recapture methods. Over the five years, 30 plots were searched twice and over 2700 unique nests were found. From these data, nest detection probability is estimated using a Huggins-type mark recapture model where individual-level covariate effects of nest and observer attributes were estimated. These estimates are then used to predict nest detection rates in other years based on covariates of nests and observers. Nest detection rates are then applied to annual plot search to estimate nest populations for each species in the sampled area.
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, All tags...
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A Groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). The GW-NDST relies on several support models, including machine-learning models that require numerous GIS input files. This data release contains all GIS files required to run the GW-NDST and its machine-learning support models. The GIS files are packaged into three ZIP files (WI_County.zip, WT-ML.zip, and WI_Buff1km.zip) which are contained in this data release. Before running the GW-NDST, these ZIP...
map background search result map search result map 2024 CASC Regions Forecasting Changes in Sagebrush Distribution and Abundance Under Climate Change: Integration of Spatial, Temporal, and Mechanistic Models Crown of the Continent Landscape Conservation Design Temperature data collected from the Lower Yakima River from October 2018 to October 2020 Imagery training dataset for the River Imagery Sensing (RISE) application Model Archive Summary for Turbidity Derived Suspended-Sediment Concentrations at USGS Station 11336685; North Mokelumne River near Walnut Grove, California (2011 - 2015) GIS files required to run the Groundwater Nitrate Decision Support Tool for Wisconsin Historic Water Chemistry Data for Thermal Features, Streams, and Rivers in the Yellowstone National Park Area, 1883-2021 Global reference evapotranspiration for food-security monitoring (ver. 2.1, April 2024) Geochemical, grain size, lithological, bathymetric, reconstructed integrated vapor transport, and age model data for Leonard Lake, Mendocino County Automated Sea Duck Counts from Aerial Imagery: Imagery Files Alaska Yukon Delta Detection Model Fitting Code Using R and RMark Alaska Yukon Delta Double Observer Nest Plot Detection Alaska Yukon Delta Nest Plot Distance Sampling Field Protocol Alaska Yukon Delta Nest Plot Survey Legacy Nest Card Quality Control R Code Alaska Yukon Delta Nest Plot Survey Observer Names 1985 - 2019 Alaska Yukon Delta Salinity Quality Control R Code Alaska Yukon Delta Pond Salinity Data 2006 - 2019 Alaska Yukon Delta Tidy Egg Data 1985 - 2019 Alaska Yukon Delta Nest Plot Survey Model Archive Summary for Turbidity Derived Suspended-Sediment Concentrations at USGS Station 11336685; North Mokelumne River near Walnut Grove, California (2011 - 2015) Temperature data collected from the Lower Yakima River from October 2018 to October 2020 Alaska Yukon Delta Pond Salinity Data 2006 - 2019 Geochemical, grain size, lithological, bathymetric, reconstructed integrated vapor transport, and age model data for Leonard Lake, Mendocino County Alaska Yukon Delta Detection Model Fitting Code Using R and RMark Alaska Yukon Delta Double Observer Nest Plot Detection Alaska Yukon Delta Nest Plot Distance Sampling Field Protocol Alaska Yukon Delta Nest Plot Survey Legacy Nest Card Quality Control R Code Alaska Yukon Delta Nest Plot Survey Observer Names 1985 - 2019 Alaska Yukon Delta Salinity Quality Control R Code Alaska Yukon Delta Tidy Egg Data 1985 - 2019 Alaska Yukon Delta Nest Plot Survey Historic Water Chemistry Data for Thermal Features, Streams, and Rivers in the Yellowstone National Park Area, 1883-2021 Crown of the Continent Landscape Conservation Design GIS files required to run the Groundwater Nitrate Decision Support Tool for Wisconsin Forecasting Changes in Sagebrush Distribution and Abundance Under Climate Change: Integration of Spatial, Temporal, and Mechanistic Models Imagery training dataset for the River Imagery Sensing (RISE) application Automated Sea Duck Counts from Aerial Imagery: Imagery Files 2024 CASC Regions Global reference evapotranspiration for food-security monitoring (ver. 2.1, April 2024)