Michael T. Atamian | USGS Science

USGS2026

Range-wide population trend analysis for greater sage-grouse ( Centrocercus urophasianus )—Updated 1960–2025

Greater sage-grouse ( Centrocercus urophasianus ; hereafter sage-grouse) are at the center of State and national land-use policies largely because of their unique life-history traits as an ecological indicator for the health of sagebrush ecosystems. This updated population analysis provides State and Federal land and wildlife managers with the best available science to help guide management and conservation plans aimed at benefitting sage-grouse populations and the ecosystems they inhabit. This analysis relied on previously published population modeling methodology from Coates and others (2021, 2022a) and incorporates population lek count data for 1960–2025. Included in this report are methodological updates to period terminology, expanded reporting of trends across all nadir-to-nadir combinations, and revised extirpation probability estimation that utilizes every historic population nadir to forecast abundance. Each of these updates are detailed under individual Modification sections. Additional updates include simulation analyses that evaluate the effects of progressively longer exclusions of Wyoming lek count data (Wyoming Game and Fish Department has not provided access to a complete lek count data set since 2023) on trends, extirpation probabilities, and targeted annual warning system signals. State-space models estimated a 2.7-percent average annual decline in sage-grouse populations between 1966 and 2021 (Period 1–7, six population oscillations) across their geographical range. The average annual decline among climate clusters for the same number of oscillations ranged between 2.0 and 3.5 percent. Cumulative declines were 42.4, 61.7, and 77.9 percent range-wide in Period 5–7 (19 years [two oscillations]), Period 3–7 (36 years [four oscillations]), and Period 1–7 (55 years), respectively. Between 2024 and 2025 (1-year, non-trend timeframe), range-wide population size declined 1.9 percent ( 95-percent credible interval [CRI]= −4.71–1.48). Simulations of missing data from Wyoming showed that progressively longer gaps produced more negative trend estimates and higher extirpation probabilities, predominantly within Wyoming. Effects on targeted annual warning system signals were more nuanced, with missed warnings occurring inside and outside Wyoming and false warnings occurring predominantly within Wyoming.

California, Colorado, Idaho, Montana, Nevada, Nort↗

USGS2025

Evaluation of a rapid assessment function to aid monitoring and management of common ravens (Corvus corax) in Washington state

Expanding human enterprise leading to resource subsidies for generalist species has resulted in widespread increases in common raven ( Corvus corax ) populations across the Western U.S. Ravens are an efficient predator and increased population abundance has led to adverse effects to multiple sensitive prey species. In regions where problematic interactions between ravens and their prey exist, managers seek efficient and effective tools for monitoring and controlling expanding raven populations. We previously developed a Rapid Assessment Function (RAF) for managers to quickly estimate raven population density and assess the need for management actions. We developed the RAF for the Great Basin (GB RAF) by first estimating raven density using robust distance sampling protocols with >30,000 raven point count surveys from sagebrush ecosystems in California, Nevada, Idaho, and Oregon across 131 field sites and years. We then used the relationship between raven density estimates from distance sampling and n ravens observed site-year / n surveys site-year (that is, raven index) at each site-year combination to develop a function that accounts for detection probability and adjusts simple counts to provide a prediction of ‘true’ density. Our function produced reliable density estimates given approximately 50–100 surveys, thereby reducing the field-based and analytical efforts typically needed to estimate raven density, facilitating more efficient raven management in open sagebrush habitats. In this study, we sought to test our original GB RAF using data from sagebrush ecosystems outside of the Great Basin. Using raven point count data from two field site units in Washington state collected from 2016 to 2023, we calculated density estimates from distance sampling methods, comparable to what was done for previous analyses. We then used the GB RAF to generate predictions of density and compared those values to the more robust estimates from distance sampling. Additionally, we developed modified RAFs specifically for Washington data (WA RAFs) to assess how well they predicted raven density compared to the GB RAF. We found the detection curves estimated for the Washington sites largely aligned with those used to generate the original GB RAF. Furthermore, the estimates from the GB RAF exhibited similar or higher correlation with densities calculated from distance models ( Pearson’s r = 0.73) than the modified WA RAFs with 1.33 km and 1.25 km truncation distances ( Pearson’s r = 0.63 and 0.73, respectively). Producing an equivalently performing modified WA RAF would likely necessitate more data to reduce estimation error and produce more reliable estimates. These results provide evidence for the applicability of our GB RAF for more widespread use within sagebrush ecosystems, possibly negating the need for locally developed RAFs. Continued assessments of the GB RAF outside of the Great Basin would further verify its applicability across the sagebrush biome.

BioRxiv↗