Search USGSSearch

USGS · 70230409

Balancing model generality and specificity in management-focused habitat selection models for Gunnison sage-grouse

Abstract

Identifying, protecting, and restoring habitats for declining wildlife populations is foundational to conservation and recovery planning for any species at risk of decline. Resource selection analysis is a key tool to assess habitat and prescribe management actions. Yet, it can be challenging to map suitable resource conditions across a wide range of ecological contexts and use the resulting models to identify effective and universal habitat improvement actions. We developed a management-centric modeling approach that sought to balance the need to evaluate the consistency of key habitat conditions and improvement actions across multiple, distinct populations, while allowing context-specific environmental variables and spatial scales to nuance selection responses that form the basis of location-specific management prescriptions. To demonstrate this approach, we developed a set of habitat selection models for Gunnison sage-grouse ( Centrocercus minimus ), a threatened species under the U.S. Endangered Species Act. Conservation, species recovery, and habitat management efforts are needed in six isolated satellite populations (San Miguel, Crawford, Piñon Mesa, Dove Creek, Cerro Summit-Cimarron-Sims, and Poncha Pass) where environmental conditions differ, and the already small number of birds are declining. We used multi-scale and seasonal resource selection analyses to quantify relationships between environmental conditions and sites used by animals. All models included key habitat variables often altered through management actions to assess their differential influences across models. We found important similarities and differences among satellites, indicating that, although some rules of thumb are generally well-grounded, the consideration of population-specific environmental differences could increase the efficiency of local habitat improvement actions. Sage-grouse also had diverse responses to resource conditions at different scales, indicating that regional spatial (e.g., landscape) and local patch scale can differentially influence expected habitat improvements associated with where such management actions are implemented. Although context variables such as topography cannot be manipulated, sage-grouse associations revealed information that could guide the siting of improvement actions. This approach to balancing management objectives associated with habitat assessment may benefit spatially-structured populations with different environmental contexts and species with complex habitat needs and associations.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 36.80928470205937° to 38.788345355085625° latitude; -109.423828125° to -106.12792968749999° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Dorothy Saher, Michael S. O’Donnell, Cameron L. Aldridge, Julie A. Heinrichs. 2022. Balancing model generality and specificity in management-focused habitat selection models for Gunnison sage-grouse. https://doi.org/10.1016/j.gecco.2021.e01935

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Hakalau’s moving castle: How climate change and restoration are shifting an island fortress for forest birds

Hakalau Forest Unit of the Big Island National Wildlife Refuge Complex (hereafter, Hakalau) protects the largest area with the highest endemic forest bird diversity in Hawaiʻi, including four federally listed species. Hakalau’s higher elevation montane forest provides refuge from avian malaria ( Plasmodium relictum ), a primary driver of Hawaiian honeycreeper extinctions. However, recent declines in Hakalau’s birds at lower elevations could indicate that conditions have become suitable for disease vector Culex quinquefasciatus . We evaluated the statuses of Hakalau’s bird populations in the context of recent climatic changes using new survey data from point-transect distance sampling, producing abundance estimates from 1999 to 2024. We stratified our analysis across four elevation ranges (<1500 m, 1500–1700 m, 1700–1900 m, and >1900 m) and assessed trends for each species using state-space models (SSMs). We constrained population trajectories to be biologically realistic by incorporating population dynamic models within the SSMs. We observed highly species-specific abundance trends below 1500 m, predominantly stable to upward trends within 1500–1700 m, stable trends within 1700–1900 m, and upward trends above 1900 m. Declines in Hawaiʻi ʻamakihi ( Chlorodrepanis v. virens ) and endangered ʻakiapōlāʻau ( Hemignathus wilsoni ) abundance coincided with lengthening warm seasonal temperatures indicative of shrinking disease-free habitat below 1700 m. Above 1900 m, however, increases in nearly all species indicate that reforestation has likely restored disease-free habitat since 1999. While most species were stable to increasing overall, surveillance for mosquitoes and disease at lower elevations, documenting changes in habitat, and continuing bird population monitoring can help to gauge their long-term persistence at Hakalau.

Hawaii

Status assessment of peregrine falcons in North America using integrated population models

Species status assessments require an understanding of underlying population dynamics and important drivers of species demography. Large-scale assessments can be difficult due to challenges collating data obtained through different methods and different sources at multiple scales. Integrated population models (IPMs) provide a unified framework to combine multiple data sources and jointly estimate population parameters over a large spatiotemporal scale. We developed separate IPMs to estimate abundance and demographic rates for a northern (NMP) and southern (SMP) management population of peregrine falcons ( Falco peregrinus ) in North America from 2008 through 2019 (SMP) and 2020 (NMP). An outbreak of highly pathogenic avian influenza (HPAI) starting in 2021 led us to extend our modeling effort to assess its impact on these management populations by updating both IPMs using index data of population size through 2024 in a predictive framework. Survival probabilities differed drastically between first-year and after-first-year individuals in both management populations. After-first-year survival was nearly identical between the NMP and SMP, but first-year survival was lower in the SMP. Mean productivity was significantly lower in the NMP compared to the SMP, whereas the probability of breeding was similar in both management populations. Estimated total abundance for the NMP was substantially larger than the SMP, representing most of the North American peregrine population. Population growth was positive for both management populations, albeit at a slower rate for the NMP. The NMP declined from 2017 to 2018 coinciding with a drop in 2018 estimated productivity. When we extended the IPMs with updated count data through 2024, the NMP slightly declined but estimated abundance remained above levels at the start of the time series analyzed. The SMP grew at a similar rate to that predicted during the period informed by demographic data. We did not detect a continental-scale change in population size or trajectory in either management population associated with the arrival of HPAI in 2021. Further monitoring can support determination of whether the declines in the NMP were temporary, can enhance understanding of the underlying mechanisms, and can be used to guide the conservation and management of the peregrine falcon population in North America.

North America

Carcass size and ground substrate drive detection rates of avian carcasses by human surveyors and a dog team

Accurate avian mortality estimates are essential for understanding anthropogenic impacts to bird populations and informing conservation strategies. Carcass surveys are commonly conducted by human surveyors or by detection dogs, but the factors influencing surveyor detection abilities have not been fully explored. In this study, we conducted two years of detection trials in the semi-arid high desert of southern New Mexico, USA, testing 27 human surveyors and one conservation detection dog across 1096 trials with 238 carcasses representing 50 avian species. We directly compared detection abilities between surveyor types (human and dog) and identified key factors influencing detection probabilities. The conservation detection dog exhibited a significantly higher detection probability (mean = 0.87) than human surveyors (mean = 0.49, individuals ranged 0.25–0.71), consistent with previous studies. Detection probabilities for both surveyor types were influenced by carcass size and ground substrate; detection probability was higher for larger carcasses and areas with lower vegetative complexity. We discuss our results in the context of common tradeoffs faced by managers in designing carcass surveys and how guidance may vary under different scenarios. Broadly, our study provides valuable insight that can enhance wildlife mortality monitoring, ensuring more accurate mortality estimates to inform management and conservation efforts.

New Mexico