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Copyright of Western North American Naturalist is the property of Monte L. Bean Life Science Museum and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Shrub volume is used to calculate numerous, essential ecological indicators in rangeland ecosystems such as biomass, fuel loading, wildlife habitat, site productivity, and ecosystem structure. Field techniques for biomass estimation, including destructive sampling, ocular estimates, and allometric techniques, use shrub height and canopy widths to estimate volume and translate it to biomass with species‐specific allometric equations. These techniques are time‐consuming and pose challenges, including removal of plant material and training of observers. We compared canopy volume estimates from field‐based measurements with drone‐collected canopy volume estimates for seven dominant shrub species within mountain big sagebrush (Artemisia tridentata subsp. vaseyana) plant communities in southern Idaho, USA. Canopy height and two perpendicular width measurements were taken from 103 shrubs of varying sizes, and volume was estimated using a traditional allometric equation. Overlapping aerial images captured with a DJI Mavic 2 Professional drone were used to create a 3D representation of the study area using structure‐from‐motion photogrammetry. Each shrub was extracted from the point cloud, and volume was estimated using allometric and volumetric methods. The volumetric method, which involved converting point clouds to raster canopy height models with 2.5‐ and 5‐cm grid cells, outperformed the allometric method (R2 > 0.7) and was more reproducible and robust to user‐related variability. Drone‐estimated volume best‐matched field‐estimated volume (R2 > 0.9) for three larger species: A. tridentata subsp. tridentata, A. tridentata subsp. vaseyana, and Purshia tridentata. The volume of smaller shrubs (canopy widths <1 m) was slightly overestimated from drone‐based models. We argue that drone‐based models provide a suitable alternative to field methods, while having the added benefit of being less time‐consuming, with fewer limitations, and more easily scaled to larger study areas than traditional field techniques. Finally, we demonstrate a proof of concept for automating canopy volume estimates using point‐cloud‐based automatic shrub detection algorithms. These findings demonstrate that drone‐collected images can be used to assess shrub canopy volume for at least five upland sagebrush steppe shrub species and support the integration of drone data collection into rangeland vegetation monitoring. [ABSTRACT FROM AUTHOR]

The main population of ~5000 threatened Gunnison sage-grouse (GUSG; Centrocercus minimus) in Colorado depends on sagebrush plants that are killed by wildfires, with recovery taking decades, so frequent fire is a threat, but did it occur historically? Early land surveys showed that the historical (preindustrial) fire rotation (FR), the expected period to burn area equal to a focal land area, was 90–143 years in GUSG ranges, which is not classed as frequent fire (≤25 years). However, recent research, based on fire scars on trees at ten sites near sagebrush, suggested some frequent fire historically in the main population. That study was not spatial, essential to estimate FR, so spatial data were created in GIS with land-survey reconstructions, survey dates, fire-scar sites, mapped sagebrush, and Thiessen polygons around sites. The previous study assumed fires that burned 2+ sites likely burned across sagebrush. Historical FRs were calculated several ways over a common period. A recovery estimate of FR was 90–135 years, a land-survey estimate was 82–131 years, and three spatial scar-based estimates were 93–107 years, showing agreement. However, the comparison found that only 8.8% of the land-survey fire area was detected at fire-scar sites. Detailed analysis showed that 10 fire-scar sites were insufficient to detect historical fire sizes and distributions across the large 168,753 ha sagebrush area. Adequate fire reconstruction could require ~45–60 fire-scar sites, making it feasible to study only ~30,000 ha of sagebrush. Using the two remaining methods, which cross-validate, showed frequent fire did not occur historically in the study area, as historical FRs were 82–135 years. [ABSTRACT FROM AUTHOR]

The persistence of threatened wildlife species depends on successful conservation and restoration of habitats, but climate change and other stressors make these tasks increasingly challenging. Applying climate change vulnerability analyses to contemporary wildlife management can be difficult because most analyses predict direct effects of future climate on wildlife species at broad geographic scales, rather than assessing their habitats at local scales (<1 km) that correspond to site‐specific habitat management actions. We present a framework that synthesizes vegetation‐focused vulnerability assessments to assess multiple effects on wildlife species' diverse habitat needs, providing a scenario‐driven climate vulnerability assessment that maps differences in vulnerability of populations within a species' range. Our flexible habitat‐centered synthesis approach leverages available spatial datasets describing projected exposure to vegetation changes due to climate change and other potentially synergistic stressors, reclassifies and weights them based on available estimates of species' sensitivity to these changes, and recombines them to create <1‐km resolution maps of overall species vulnerability and threat‐specific habitat vulnerability. To demonstrate its potential to guide decision‐making, we applied this approach to the Gunnison sage‐grouse (Centrocercus minimus), a federally threatened habitat specialist that depends on sagebrush and mesic habitats that are imperiled by climate change. We mapped six threats forecasted out to the year 2070: direct effects of climate on (1) sagebrush cover loss and (2) mesic habitat drying, indirect changes in invasion risk from (3) pinyon–juniper conifers and (4) annual grasses, and potentially synergistic risk of (5) development and (6) wildfire. We then assessed species vulnerability for each of the eight extant populations under three climate scenarios: Optimistic, Continuation, and Pessimistic. We found that the extent of cumulative species vulnerability due to multiple habitat changes was far greater than the extent of any single habitat vulnerability. Over 75% of critical habitats were at risk under the Pessimistic scenario, and nearly two thirds of habitats were at high risk for three or more threats. Invasive species were the most widespread threat, highlighting the importance of indirect effects of climate change. We illustrate how our approach can be applied to the existing management planning strategies to better prioritize conservation of habitats for the persistence of threatened species. [ABSTRACT FROM AUTHOR]