Filters: Tags: Golden Eagle (X)
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Road densities derived from the TIGER data were analyzed to determine the relationship between road density and golden eagle potential suitable habitat. The quality of a HUC in relation to road density was defined as good (3), fair (2), or poor (1). The score indicates the threat level for each attribute. A low score indicates a low threat, a medium score indicates a medium threat, and a high score indicates a high threat to the species. The values for each score were characterized in relation to road density by >10 km/km2 = good, 5-10 km/km2 = fair, and 2 = poor.
This data set contains the output values for the golden eagle threat assessment in relation to the 6th Level HUC unit. These values were created using the analysis tools in the associated toolbox (MIR_Golden_Eagle_Analysis_175407.tbx). This data layer contains the output values for all of the change agents used in the analysis of the golden eagle.
This dataset contains detection-nondetection data for territorial pairs of Golden Eagles at survey sites randomly selected from a grid of equal-sized (13.9 km2) hexagonal sample cells overlaid across the region of interest in Coastal Southern California during 2016 and 2017. We partitioned surveys within seasons based on approximate transition dates for stages in the breeding cycle of golden eagles in the study region: courtship (15 Dec-28 Feb), incubation (1 Mar-30 Apr), nestling (1 May-15 Jun), and the fledging-dependency period (16 June-Jul 30), totaling 4 possible sampling periods per year. This dataset also describes the proportion of land-cover types from four general categories (urban, open grassland, scrub...
This dataset consists of polygons representing Golden Eagle Areas for the Western Oregon Plan Revision (WOPR).BLM: (Bureau of Land Management) WOPR: (Western Oregon Plan Revision) WLD: (Wildlife) GEAGLE: (Golden Eagle) PRMP: (Proposed Resource Management Plan) This data is a PRMP release version of the data wld_aa_a_geagle_poly.
There is widespread evidence that multiple drivers of global change, such as habitat degradation, invasive species, and climate change, are influencing wildlife. Understanding how these drivers interact with and affect species may be difficult because outcomes depend on the magnitude and duration of environmental change and the life history of the organism. In addition, various environmental drivers may be evaluated and managed at different spatial scales. We used a historical dataset from 1991 to 1994 and current information from 2010 to 2012 to examine whether occupancy patterns of wintering raptors were consistent with regional changes in distribution or habitat conditions within a local management unit, the...
This data set contains the output values for the golden eagle threat assessment in relation to the 6th Level HUC unit. These values were created using the analysis tools in the associated toolbox (MIR_Golden_Eagle_Analysis_175407.tbx). This data layer contains the output values for all of the change agents used in the analysis of the golden eagle.
This data set contains the output values for the golden eagle threat assessment in relation to the 6th Level HUC unit. These values were created using the analysis tools in the associated toolbox (MIR_Golden_Eagle_Analysis_175407.tbx). This data layer contains the output values for all of the change agents used in the analysis of the golden eagle.
The overall score was used to contrast the NGB ecoregion to highlight analysis units within golden eagle modeled habitat based on the cumulative indicator score.
Types: Downloadable;
Tags: BLM,
Bureau of Land Management,
Cumulative Indicator Score,
DOI,
Geospatial,
The 'Golden Rule Prospect' file is part of the Grover Heinrichs mining collection. Grover was the Vice President of Heinrichs GEOEXploration, located in Tucson, Arizona. The collection contains over 1,400 folders including economic geology reports, maps, photos, correspondence, drill logs and other related materials. The focus of much of the information is on the western United States, particularly Arizona, but the collection also includes files on mining activity throughout the United States, foreign countries, and 82 mineral commodities.
This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. Maricopa410 is located in T2N R9E Sec 36 C in the Goldfield - 7.5 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.
This dataset represents current terrestrial intactness values (estimated at the 1km level) within the modeled distribution of theGolden eagle (Aquila chrysaetos).Terrestrial intactness is high in areas where development is low, vegetation intactness is high, and fragmentation is low. Consequently, this dataset serves as a general* indication of habitat quality within the distribution of this conservation element. Estimates of current terrestrial intactness were generated by an EEMS fuzzy logic model that integrates multiple measures of landscape development and vegetation intactness, including agriculture development (from LANDFIRE EVT v1.1), urban development (from LANDFIRE EVT v1.1 and NLCD Impervious Surfaces),...
This data set contains the output values for the golden eagle threat assessment in relation to the 6th Level HUC unit. These values were created using the analysis tools in the associated toolbox (MIR_Golden_Eagle_Analysis_175407.tbx). This data layer contains the output values for all of the change agents used in the analysis of the golden eagle.
Agricultural areas data were extracted from the REA Cropland data layer and analyzed to determine the distance from golden eagle potential suitable habitat. The quality of a HUC in relation to distance to agricultural areas was defined as good (3), fair (2), or poor (1). The score indicates the threat level for each attribute. A low score indicates a low threat, a medium score indicates a medium threat, and a high score indicates a high threat to the species. The values for each score were characterized in relation to distance from agricultural areas by >5km = good, 1-5km = fair, and
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