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This map depicts the proportion of non-Sage-grouse habitat with 18km of each pixel. The map was produced using a moving window analysis on the Distribution of Non-Sage Grouse Habitat in the Conservation Assessment Area with a search radius of 18km. The product of the moving window was the mean pixel value within the window. This map has a 540m resolution.
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In 'Simulation to evaluate response of population models to annual trends in detectability', we provide data and R code necessary to create simulation scenarios and estimate trends with different population models (Monroe et al. 2019). Literature cited: Monroe, A. P., G. T. Wann, C. L. Aldridge, and P. S. Coates. 2019. The importance of simulation assumptions when evaluating detectability in population models. Ecosphere 10(7):e02791. 10.1002/ecs2.2791, http://onlinelibrary.wiley.com/doi/10.1002/ecs2.2791/full.
The following habitat management areas were used in the creation of this feature class: PHMA: Areas identified as having the highest habitat value for maintaining sustainable GRSG populations and include breeding, late brood-rearing, and winter concentration areas. GHMA: Areas that are occupied seasonally or year-round and are outside of PHMAs. IHMA: Areas in Idaho that provide a management buffer for and that connect patches of PHMAs. IHMAs encompass areas of generally moderate to high habitat value habitat or populations but that are not as important as PHMAs. OHMA: Areas in Nevada and Northeastern California, identified as unmapped habitat in the Proposed RMP/Final EIS, that are within the Planning Area and...
A regularly raised concern for wind farms is the number of species and rate of bird and bat collisions with turbines. Australian regulators require, at some operating wind farms, the monitoring of bird and bat collisions. Although monitoring is becoming more commonplace, the area recommended for searching beneath turbines is inconsistent, with many guidelines both in Australia and overseas being based on conjecture rather than empirical evidence. This has the potential to bias survey results, reduce confidence in the data collected, and preclude meaningful comparisons between sites. By having a measure of the range of the fall zone of a bird or bat, a survey can be designed that ensures that an adequate area is...
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In 2007 the Governor's Sage-Grouse Conservation Implementation Team identified a set of priorities needed for sage-grouse conservation in Wyoming. One of these priorities was an immediate need for information on the sage-grouse habitats in Wyoming. This database represents the results of the Wyoming Governor's Sage-Grouse Conservation Initiative: Habitat Mapping Project presenting the most complete and timely database possible for Wyoming as of 2009.
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This data set represents greater sage-grouse populations to be used in work for the US Fish and Wildlife (USFWS) 2015 Status Review for the greater sage-grouse. Populations do not represent occupied habitat. Population polygons are meant to coarsely identify areas of occupation based on encircling groups of leks. Boundaries taken from BLM/WAFWA revised population boundaries (‘COT_SG_Populations_2014_WAFWA_UT’ data layer). The original data layer was slightly modified for the USFWS 2015 Status Review. Modifications include dissolving populations across State boundaries and merging several polygons together. Five additional polygons were added to the data set including four polygons in Utah and one polygon in Canada....
Emerging applications of ecosystem resilience and resistance concepts in sagebrush ecosystems allow managers to better predict and mitigate impacts of wildfire and invasive annual grasses. Soil temperature and moisture strongly influence the kind and amount of vegetation, and consequently, are closely tied to sagebrush ecosystem resilience and resistance (Chambers et al. 2014). Soil taxonomic temperature and moisture regimes can be used as indicators of resilience and resistance at landscape scales to depict environmental gradients in sagebrush ecosystems that range from cold/cool-moist sites to warm-dry sites. We aggregated soil survey spatial and tabular data to facilitate broad-scale analyses of resilience and...
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Our 2010 statewide connectivity analysis identified broad-scale priority areas for connectivity conservation. More detailed, finer-scale analyses will give land managers the information they need to begin prioritizing and implementing conservation actions. The Columbia Plateau (Appendix A, Fig. 1) was selected for the first ecoregional-scale analysis for two reasons. First, several climate models suggest that the Columbia Plateau Ecoregion in Washington is likely to be a stronghold of shrubsteppe ecosystems under climate change. Second, despite the high level of habitat loss and fragmentation in the ecoregion, our statewide analysis identified previously undocumented patterns and opportunities for multiple-species...
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Burrowing Owl, CA-1, California, California, Climate Change, All tags...
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Sage-grouse core areas are habitats associated with 1) Montana's highest densities of sage-grouse (25% quartile), based on male counts and/or 2) sage-grouse lek complexes and associated habitat important to sage-grouse distribution.The data are intended for display of sage grouse core areas in Montana. The data are intended for initial resource review and conservation planning. For evaluating or reviewing site specific applications Montana Fish, Wildlife & Parks (FWP) recommends contacting the appropriate FWP Regional office.These are the Montana SageGrouse Core Areas 2010 polygons for Idaho-SW Montana Greater Sage Grouse Subregion. Areas that overlap into Idaho do not apply to Idaho and may represent difference...
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This data set represents Greater Sage-Grouse Current Range to be used in work for the USFWS 2015 Status Review for the Greater Sage-Grouse. Current Range is defined as areas believed to be currently occupied. Therefore this data set represents occupied habitat for Greater Sage-Grouse. Current range for this data set was created by compiling the following data and information Schroeder et al. 2004 current range Priority Areas for Conservation (PACs) identified in the Conservation Objectives Team (COT) Report, 2013. One small polygon from the Schroeder et al. 2004 current range was removed as it was determined that it no longer represents current range. Determination made from information from Oregon Department...
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These data represent an resource selection function (RSF) for translocated sage-grouse in North Dakota during the brooding season. Human enterprise has led to large‐scale changes in landscapes and altered wildlife population distribution and abundance, necessitating efficient and effective conservation strategies for impacted species. Greater sage‐grouse (Centrocercus urophasianus; hereafter sage‐grouse) are a widespread sagebrush (Artemisia spp.) obligate species that has experienced population declines since the mid‐1900s resulting from habitat loss and expansion of anthropogenic features into sagebrush ecosystems. Habitat loss is especially evident in North Dakota, USA, on the northeastern fringe of sage‐grouse’...
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This metadata references the polygonal ARC/INFO GIS cover showing the current and historic distribution of potential habitat, or range, of the Greater Sage-grouse (Centrocercus urophasianus) and Gunnison Sage-grouse (Centrocercus minimus) in Western North America. This data was initially researched and compiled by Dr. Michael A. Schroeder, research biologist for the Washington State Department of Fish and Wildlife. The initial draft of current and historic range data was mapped and submitted to state, federal, or provincial natural resource agencies and other experts for review, comment, and editing. The final product represents the best available science and expert review available at the time of compilation.Definition...
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This map depicts regions within the range of the Greater Sage-grouse that are non-Sage-grouse habitat. This information was complied using coverage of sagebrush for the western United States and a coverage of grassland habitats within 5km of an active Sage-grouse lek. This map has a 540m resolution.
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This web map application for the NRCS-funded Sage Grouse Initiative visualizes, distributes, and interactively analyzes spatial data produced by the SGI's science team.
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We use locations from previously released radio-marked greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) in a resource selection function framework to evaluate habitat selection following translocation and identify areas of seasonal habitat to inform habitat management and potential restoration needs. We also evaluate possible changes in seasonal habitat since the late 1980s using spatial data provided by the Rangeland Analysis Platform coupled with resource selection modeling results. Our results serve as critical baseline information for habitat used by translocated individuals across life stages in this study area, and will inform future evaluations of population performance and potential...
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Emerging applications of ecosystem resilience and resistance concepts in sagebrush ecosystems allow managers to better predict and mitigate impacts of wildfire and invasive annual grasses. Soil temperature and moisture strongly influence the kind and amount of vegetation, and consequently, are closely tied to sagebrush ecosystem resilience and resistance (Chambers et al. 2014, 2016). Soil taxonomic temperature and moisture regimes can be used as indicators of resilience and resistance at landscape scales to depict environmental gradients in sagebrush ecosystems that range from cold/cool-moist sites to warm-dry sites. We aggregated soil survey spatial and tabular data to facilitate broad-scale analyses of resilience...
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Sage-grouse habitat areas divided into proposed management categories within Nevada and California project study boundaries. MANAGEMENT CATEGORY DETERMINATION The process for category determination was directed by the Nevada Sagebrush Ecosystem Technical team. Sage-grouse habitat was determined from a statewide resource selection function model and first categorized into 4 classes: high, moderate, low, and non-habitat. The standard deviations (SD) from a normal distribution of RSF values created from a set of validation points (10% of the entire telemetry dataset) were used to categorize habitat ‘quality’ classes. High quality habitat comprised pixels with RSF values < 0.5 SD, Moderate > 0.5 and < 1.0 SD, Low...
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Circuitscape software (v4.0, www.circuitscape.org) was applied to a range-wide habitat similarity index map for sage-grouse to model pathways between all priority areas of conservation network. We assumed that individual sage-grouse would move more easily through areas meeting their habitat requirements and used a scaled inverse of our mapped habitat scores as resistance to sage-grouse movements among the priority areas. Resistance values ranged from 1 representing the lowest resistance/highest habitat value to 100 (high resistance/lowest habitat value). Circuitscape (McRae et al. 2008) was run using the pairwise mode to calculate connectivity between all pairs of priority areas. Priority areas were treated as focal...


map background search result map search result map Wyoming Governors Sage-Grouse Conservation Initiative: Habitat Mapping Project SW Montana Greater Sage-grouse Core Areas Distribution of Non-Sage-grouse Habitat in the Conservation Assessment Area Proportion of Non-Sage-grouse Habitat Within an 18-km Radius Distribution of the Sage-grouse in North America Sage-grouse Management Categories in Nevada and NE California (August 2014) Dataset: Index of Relative Ecosystem Resilience and Resistance across Sage-Grouse Management Zones Greater Sage-Grouse 2015 USFWS Status Review Current Range Greater Sage-Grouse 2015 USFWS Status Review Populations Potential movement pathways between priority areas of conservation for sage-grouse, Results from Circuitscape modeling process Washington Connectivity: Columbia Basin Simulation to evaluate response of population models to annual trends in detectability Sage Grouse Initiative (SGI) Interactive Map Geospatial Information and Predictive Maps of Greater Sage-grouse Habitat Selection in Southwestern North Dakota, USA Brooding RSF of Translocated Greater Sage-grouse in North Dakota, 2017 - 2018 Geospatial Information and Predictive Maps of Greater Sage-grouse Habitat Selection in Southwestern North Dakota, USA Brooding RSF of Translocated Greater Sage-grouse in North Dakota, 2017 - 2018 SW Montana Greater Sage-grouse Core Areas Wyoming Governors Sage-Grouse Conservation Initiative: Habitat Mapping Project Simulation to evaluate response of population models to annual trends in detectability Sage-grouse Management Categories in Nevada and NE California (August 2014) Washington Connectivity: Columbia Basin Greater Sage-Grouse 2015 USFWS Status Review Current Range Greater Sage-Grouse 2015 USFWS Status Review Populations Distribution of the Sage-grouse in North America Proportion of Non-Sage-grouse Habitat Within an 18-km Radius Potential movement pathways between priority areas of conservation for sage-grouse, Results from Circuitscape modeling process Distribution of Non-Sage-grouse Habitat in the Conservation Assessment Area Dataset: Index of Relative Ecosystem Resilience and Resistance across Sage-Grouse Management Zones Sage Grouse Initiative (SGI) Interactive Map