Abstract

Wildlife managers delineate priority areas for species to define critical habitat and to prioritize management efforts. Each method used to identify priority areas involves data that can be unavailable or expensive to obtain. Therefore, it is of interest to compare spatial efficiency between methods used for defining priority areas. We compared priority areas created using different methods and data types. We used resource selection function (RSF) models to predict areas of high use and generated a map depicting ≥ 90% predicted use in three seasons; it was 1,143 km2, encompassed 91% of nests, 68% of summer locations, and 71% of winter locations. We compared the RSF priority area to priority areas developed using two alternative methods: (1) modified conservation buffer, and (2) utilization distribution (UD) models. The modified conservation buffer method was used by South Dakota Game, Fish and Parks in 2014 to delineate a priority area by buffering active lek sites by 6.4 km, including connectivity corridors defined via expert opinion, and known high use areas. The priority area generated by the modified conservation buffer method was 3,977 km2, encompassed 95% of nest locations, 92% of spring/summer locations, and 99% of winter locations. Lastly, we developed a priority area using combined UDs from radio-tracking data gathered during spring/summer, and winter and included a lek buffer encompassing 90% of known nest-sites. This priority area was 3,498 km2, encompassed 99% of nests, 98% of spring/summer locations, and 97% of winter locations. The priority area generated by RSF models was the smallest and encompassed the least number of nests and spring/summer and winter locations but was considered the most spatially efficient; it had the most nests, spring/summer locations, and winter locations per 100 km2. The UD and modified conservation buffer methods created priority areas that were similar in size and spatial efficiency. The modified conservation buffer method encompassed >90% of known sage-grouse locations and nests, indicating that in the absence of detailed movement data and more sophisticated modeling, the method can be sufficient in developing an adequate priority area.

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