Geology ReportsSearch

USGS · 70216495

Managing for multiple species: Greater sage‐grouse and sagebrush songbirds

Abstract

Human activity has altered 33–50% of Earth's surface, including temperate grasslands and sagebrush rangelands, resulting in a loss of biodiversity. By promoting habitat for sensitive or wide‐ranging species, less exigent species may be protected in an umbrella effect. The greater sage‐grouse ( Centrocercus urophasianus ; sage‐grouse) has been proposed as an umbrella for other sagebrush‐obligate species because it has an extensive range that overlaps with many other species, it is sensitive to anthropogenic activity, it requires resources over large landscapes, and its habitat needs are known. The efficacy of the umbrella concept, however, is often assumed and rarely tested. Therefore, we surveyed sage‐grouse pellet occurrence and sagebrush‐associated songbird abundance in northwest Colorado, USA, to determine the amount of habitat overlap between sage‐grouse and 4 songbirds (Brewer's sparrow [ Spizella breweri ], sage thrasher [ Oreoscoptes montanus ], sagebrush sparrow [ Artemisiospiza nevadensis ]), and green‐tailed towhee [ Pipilo chlorurus ]). During May and June 2013–2015, we conducted standard point count breeding surveys for songbirds and counted sage‐grouse pellets within 300 10‐m radius plots. We modeled songbird abundance and sage‐grouse pellet occurrence with multi‐scaled environmental features, such as sagebrush cover and bare ground. To evaluate sage‐grouse as an umbrella for sagebrush‐associated passerines, we determined the correlation between probability of sage‐grouse pellet occurrence and model‐predicted songbird densities per sampling plot. We then classified the sage‐grouse probability of occurrence as high (probability >0.5) and low (probability ≤0.5) and mapped model‐predicted surfaces for each species in our study area. We determined average songbird density in areas of high and low probability of sage‐grouse occurrence. Sagebrush cover at intermediate scales was an important predictor for all species, and ground cover was important for all species except sage thrashers. Areas with a higher probability of sage‐grouse occurrence also contained higher densities of Brewer's sparrows, green‐tailed towhees, and sage thrashers, but predicted sagebrush sparrow densities were lower in these areas. In northwest Colorado, sage‐grouse may be an effective umbrella for Brewer's sparrows, green‐tailed towhees, and sage thrashers, but sage‐grouse habitat does not appear to capture areas that support high sagebrush sparrow densities. A multi‐species focus may be the best management and conservation strategy for several species of concern, especially those with conflicting habitat requirements.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 40.219° to 41.0035° latitude; -109.0514° to -107.3119° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Jennifer M. Timmer, Cameron L. Aldridge, Maria E Fernandez-Gimenez. 2019-05-13. Managing for multiple species: Greater sage‐grouse and sagebrush songbirds. https://doi.org/10.1002/jwmg.21663

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

KEEP EXPLORING

Related USGS reports

Validating antler- and movement-based estimates of caribou reproduction using video camera collars

Wildlife agencies invest substantial resources in monitoring ungulate reproductive rates given ongoing concerns about population trends and their implications for management. For barren-ground caribou ( Rangifer tarandus ) in the North American Arctic, data on parturition and neonate survival have traditionally been collected using visual observations of antler retention and calf presence from small, fixed-wing aircraft. However, these surveys are weather-dependent, expensive, and dangerous, motivating the development of movement-based approaches that infer reproductive events from global positioning system (GPS) location data. We had the unique opportunity to use video camera collars to validate both antler- and movement-based methods for estimating reproduction in barren-ground caribou, using data from the Porcupine (2018–2023) and Western Arctic (2021, 2023) herds in Alaska, USA, and Yukon, Canada. For the movement-based approaches, we assessed individual-based and population-based methods, which both inferred parturition following a sharp decline in movement and inferred calf loss following a sharp increase in movement. We investigated these approaches using rarified 1-, 2-, 4-, and 8-hour fix intervals. Based on video collar observations, we found that antler retention at the onset of the calving period was highly accurate for predicting parturition (96% accuracy) but became unreliable as calving progressed, as approximately 80% of parturient females shed their antlers during the calving period. In contrast, both movement methods performed marginally for estimating caribou parturition (~70% accuracy), with estimates from the individual-based method exhibiting greater bias than those from the population-based method. The individual-based method also poorly predicted neonate survival (≤49% accuracy for detecting parturition and calf fate for the Porcupine Herd). Video data revealed that inaccuracies with the movement methods often occurred when caribou bedded during storms, rested after traversing mountainous terrain, lost a calf shortly after birth, or increased movement to evade insects. These results have important implications for management agencies using antler- and movement-based methods to estimate caribou reproduction, particularly when informing assessments of population decline or recovery. Our results demonstrate the utility of video collar data for validating reproductive monitoring approaches and provide insights into how these approaches can be improved.

Alaska, Yukon

Ringtail (Bassariscus astutus) survival in southwestern Oregon

The effective conservation and management of small carnivore populations requires understanding species’ life-history traits and identifying important vital rates that drive population trajectories. However, many of these species are rare or elusive and of state or federal conservation concern, and demographic information is often lacking and difficult to obtain. At the northern limit of their range in Oregon, USA, ringtail ( Bassariscus astutus ) occupy mid-elevation forests and are a species of conservation concern because of their limited distribution and suspected low density. We initiated a radio-telemetry study in 2020 to estimate monthly and annual survival of ringtail in southwest Oregon. We monitored 26 ringtail from November 2020 to October 2022 and estimated survival rates using a known-fate framework and Program MARK. Model-averaged monthly survival estimates ranged from lows of 0.963 (SE = 0.022, 95% CI = 0.887–0.988) in spring (Feb–May) of 2021 to highs of 0.980 (SE = 0.018, 95% CI = 0.889–0.997) in summer (Jun–Oct) of 2022. Model-averaged estimates of annual survival were 0.695 (SE = 0.176, 95% CI = 0.310–0.920) during 2020–2021 and 0.728 (SE = 0.168, 95% CI = 0.336–0.934) during 2021–2022. Predation was the leading cause of mortality, but notably, no mortalities could be attributed to avian predation. Survival rates were much higher within forested landscapes in Oregon than for populations in the southwestern United States, which may have implications for regional conservation and management strategies.

Oregon

Linking distribution and return-on-investment models to optimize woody management for prairie grouse in Nebraska

Grasslands in Nebraska, USA, face threats from agricultural conversion, urban development, and woody encroachment, all of which negatively affect prairie grouse ( Tympanuchus spp.) populations. To optimize conservation planning, Nebraska wildlife agencies developed probabilistic area-based surveys for greater prairie-chicken ( T. cupido ) and sharp-tailed grouse ( T. phasianellus ) to sample landscapes across a range of environmental conditions. This design improves historical surveys and enables the development of distribution models that quantitatively define habitat associations and support scenario-based conservation planning. Using survey data collected during 2020–2022, we modeled prairie grouse occurrence and abundance as functions of land cover, topography, and climate using Bayesian logistic and zero-inflated negative binomial models with regularized horseshoe priors. We then conducted a maximum potential return-on-investment analysis of woody cover treatments, assuming sustained treatment success, relative to projected impacts of woody encroachment on prairie grouse populations by 2050. Among modeled associations were a positive association with grasslands having low woody cover and a negative association with grasslands having high woody cover. Across the 3-year period, median estimated annual populations were 142,380 for greater prairie-chicken (range of 95% CIs across years = 68,821–277,615) and 64,154 for sharp-tailed grouse (range of 95% CIs across years = 27,550–146,559). Under projected woody encroachment, mean predicted population declines were 10% for greater prairie-chicken (range of 95% CIs = 7–14%) and 6% for sharp-tailed grouse (range of 95% CIs = 5–7%). Areas with high prairie grouse density and low treatment costs in 2021, and high projected woody encroachment and population loss by 2050, offered the greatest return on investment for woody management. Return on investment was greatest in the northwestern Shortgrass Prairie ecoregion (northwestern Nebraska) for sharp-tailed grouse and the eastern Sandhills ecoregion (central Nebraska) for both species. These models underscore the value of evidence-based, quantitative approaches for prioritizing conservation actions on working lands. Scenario-based modeling could be extended to guide other treatments, such as optimizing restoration (e.g., Conservation Reserve Program) or incentivizing grassland persistence in areas with predicted climate resilience.

Nebraska