Aaron C. Pratt | Geology Reports

USGS2024

Free-roaming horses exceeding appropriate management levels affect multiple vital rates in greater sage-grouse

Since the passage of the Wild Free-Roaming Horses and Burros Act of 1971, federal agencies have been responsible for managing free-roaming equids in the United States. Over the last 20 years, management has been hampered by direct opposition from advocacy groups, budget limitations, and a decline in the public’s willingness to adopt free-roaming horses ( Equus caballus ). As a result, free-roaming equid numbers have increased to more than 3 times the targeted goal of 26,785 (horses and burros [ E. asinus ] combined), the cumulative sum of the Appropriate Management Levels (AML) for all 177 designated Herd Management Areas (HMA) managed by the Bureau of Land Management. Recent research in the Great Basin has implicated these increases as one of the drivers of greater sage-grouse ( Centrocercus urophasianus ) population declines, due to habitat impacts exacerbated by ongoing drought conditions. To evaluate potential demographic mechanisms driving these declines, we compiled survival data from 4 studies in central Wyoming, USA, including 995 adult female (first year breeders or older) sage-grouse during the breeding season, 1,075 nests, 372 broods, and 136 juveniles (i.e., overwinter survival for fledged young), across a 15-year window (2008–2022). During this period, we also obtained population information for free-roaming horses from 9 HMAs used by individual grouse in our sample. Population estimates of free-roaming horses for these HMAs ranged from 59–700% of the maximum appropriate management level (AML max ). Sage-grouse monitored outside of HMAs represented control populations and, because we assumed they were not exposed to populations of free-roaming horses, values of AML max were set to zero for all grouse located outside of HMAs. To evaluate whether free-roaming horses were negatively impacting sage-grouse, we modeled daily survival of breeding age females, nest, broods, and juveniles. We found strong or moderate evidence that overabundant free-roaming horses negatively impacted nest, brood, and juvenile survival. When horse abundance increased to 300% from 100% of AML max , survival was reduced 8.1%, 18.3%, 18.2%, and 18.2% for nests, early broods (≤20 days after hatch), late broods (>20 days to 35 days after hatch), and juveniles, respectively. These results indicate increasing free-roaming horse numbers affected vital rates for critical life stages of sage-grouse, and that maintaining free-roaming horse numbers below AML max would minimize impacts to sage-grouse populations.

Wyoming↗

USGS2014

Habitat prioritization across large landscapes, multiple seasons, and novel areas: an example using greater sage-grouse in Wyoming

Animal habitat selection is an important and expansive area of research in ecology. In particular, the study of habitat selection is critical in habitat prioritization efforts for species of conservation concern. Landscape planning for species is happening at ever-increasing extents because of the appreciation for the role of landscape-scale patterns in species persistence coupled to improved datasets for species and habitats, and the expanding and intensifying footprint of human land uses on the landscape. We present a large-scale collaborative effort to develop habitat selection models across large landscapes and multiple seasons for prioritizing habitat for a species of conservation concern. Greater sage-grouse ( Centrocercus urophasianus , hereafter sage-grouse) occur in western semi-arid landscapes in North America. Range-wide population declines of this species have been documented, and it is currently considered as “warranted but precluded” from listing under the United States Endangered Species Act. Wyoming is predicted to remain a stronghold for sage-grouse populations and contains approximately 37% of remaining birds. We compiled location data from 14 unique radiotelemetry studies (data collected 1994–2010) and habitat data from high-quality, biologically relevant, geographic information system (GIS) layers across Wyoming. We developed habitat selection models for greater sage-grouse across Wyoming for 3 distinct life stages: 1) nesting, 2) summer, and 3) winter. We developed patch and landscape models across 4 extents, producing statewide and regional (southwest, central, northeast) models for Wyoming. Habitat selection varied among regions and seasons, yet preferred habitat attributes generally matched the extensive literature on sage-grouse seasonal habitat requirements. Across seasons and regions, birds preferred areas with greater percentage sagebrush cover and avoided paved roads, agriculture, and forested areas. Birds consistently preferred areas with higher precipitation in the summer and avoided rugged terrain in the winter. Selection for sagebrush cover varied regionally with stronger selection in the Northeast region, likely because of limited availability, whereas avoidance of paved roads was fairly consistent across regions. We chose resource selection function (RSF) thresholds for each model set (seasonal × regional combination) that delineated important seasonal habitats for sage-grouse. Each model set showed good validation and discriminatory capabilities within study-site boundaries. We applied the nesting-season models to a novel area not included in model development. The percentage of independent nest locations that fell directly within identified important habitat was not overly impressive in the novel area (49%); however, including a 500-m buffer around important habitat captured 98% of independent nest locations within the novel area. We also used leks and associated peak male counts as a proxy for nesting habitat outside of the study sites used to develop the models. A 1.5-km buffer around the important nesting habitat boundaries included 77% of males counted at leks in Wyoming outside of the study sites. Data were not available to quantitatively test the performance of the summer and winter models outside our study sites. The collection of models presented here represents large-scale resource-management planning tools that are a significant advancement to previous tools in terms of spatial and temporal resolution.

Wyoming↗