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The remaining 25% of the population area would be available for development with some level of stipulations and regulations, but likely at a reduced level. The strength of this approach is that it uses biological information to identify core areas with the objective of protecting the most important breeding areas. It also enables managers, at the landscape scale, to map and analyze the risks and necessary conservation measures for each core area. The limitation of this approach is that it focuses on breeding abundances. For sage-grouse the relative abundance data is drawn from spring lek counts of males. Thus, habitat conservation measures may be biased towards breeding and nesting only. Lek data have limitations as well including: variable sampling effort both spatially and temporally and detection probabilities have not been estimated for ground or aerial counts. Notwithstanding, these are the best data available for mapping sage-grouse distributions. Because the method outlined by Doherty et al. (in press) focuses on breeding habitats and ODFWs lek data is prone to variable sampling, an additional and complementary method was used to approximate seasonal use ranges, referred to as connectivity corridors. Using a home range estimator local and seasonal connectivity corridors were estimated. Thus, it is important to clarify some definitions about the mapping approach in Oregon. This document refers to Doherty's \"core areas\" (i.e., 25, 50, 75, 100%) as lek density strata. Lek density 25-75% polygons and the intersection of 100% strata and local connectivity polygons collectively define a \"core area.\"", "mapName": "Sage Grouse NEW", "description": "Core Area Approach to Habitat Mitigation for Greater Sage-Grouse in Oregon: The goal of these recommendations is to protect essential habitats to meet habitat and population objectives identified in this Plan. The objective of these recommendations is to avoid, minimize, or mitigate for impacts on sage-grouse habitats from energy development, its associated infrastructure or other industrial/commercial developments. The rapid increase in energy development across the West in recent years has initiated a landscape approach to wildlife conservation, referred to as core areas (Doherty et al. in press). The landscape approach prioritizes habitats based on measures that assess sage-grouse population and habitat relative abundance, and provides protection for a minimum of 75% of the population. The remaining 25% of the population area would be available for development with some level of stipulations and regulations, but likely at a reduced level. The strength of this approach is that it uses biological information to identify core areas with the objective of protecting the most important breeding areas. It also enables managers, at the landscape scale, to map and analyze the risks and necessary conservation measures for each core area. The limitation of this approach is that it focuses on breeding abundances. For sage-grouse the relative abundance data is drawn from spring lek counts of males. Thus, habitat conservation measures may be biased towards breeding and nesting only. Lek data have limitations as well including: variable sampling effort both spatially and temporally and detection probabilities have not been estimated for ground or aerial counts. Notwithstanding, these are the best data available for mapping sage-grouse distributions. Because the method outlined by Doherty et al. (in press) focuses on breeding habitats and ODFWs lek data is prone to variable sampling, an additional and complementary method was used to approximate seasonal use ranges, referred to as connectivity corridors. Using a home range estimator local and seasonal connectivity corridors were estimated. 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