Geology Reports⌕ Search

USGS · 70041947

Hierarchical distance-sampling models to estimate population size and habitat-specific abundance of an island endemic

Abstract

Population size and habitat-specific abundance estimates are essential for conservation management. A major impediment to obtaining such estimates is that few statistical models are able to simultaneously account for both spatial variation in abundance and heterogeneity in detection probability, and still be amenable to large-scale applications. The hierarchical distance-sampling model of J. A. Royle, D. K. Dawson, and S. Bates provides a practical solution. Here, we extend this model to estimate habitat-specific abundance and rangewide population size of a bird species of management concern, the Island Scrub-Jay ( Aphelocoma insularis ), which occurs solely on Santa Cruz Island, California, USA. We surveyed 307 randomly selected, 300 m diameter, point locations throughout the 250-km 2 island during October 2008 and April 2009. Population size was estimated to be 2267 (95% CI 1613-3007) and 1705 (1212-2369) during the fall and spring respectively, considerably lower than a previously published but statistically problematic estimate of 12 500. This large discrepancy emphasizes the importance of proper survey design and analysis for obtaining reliable information for management decisions. Jays were most abundant in low-elevation chaparral habitat; the detection function depended primarily on the percent cover of chaparral and forest within count circles. Vegetation change on the island has been dramatic in recent decades, due to release from herbivory following the eradication of feral sheep ( Ovis aries ) from the majority of the island in the mid-1980s. We applied best-fit fall and spring models of habitat-specific jay abundance to a vegetation map from 1985, and estimated the population size of A. insularis was 1400-1500 at that time. The 20-30% increase in the jay population suggests that the species has benefited from the recovery of native vegetation since sheep removal. Nevertheless, this jay's tiny range and small population size make it vulnerable to natural disasters and to habitat alteration related to climate change. Our results demonstrate that hierarchical distance-sampling models hold promise for estimating population size and spatial density variation at large scales. Our statistical methods have been incorporated into the R package unmarked to facilitate their use by animal ecologists, and we provide annotated code in the Supplement.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 33.96° to 34.08° latitude; -119.92° to -119.52° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Scott T. Sillett, Richard B. Chandler, J. Andrew Royle, Marc Kéry, Scott A. Morrison. 2012. Hierarchical distance-sampling models to estimate population size and habitat-specific abundance of an island endemic. https://doi.org/10.1890/11-1400.1

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

KEEP EXPLORING

Related USGS reports

Improving predictions of insect harassment for barren-ground caribou in the Arctic

Many populations of barren-ground caribou ( Rangifer tarandus ) have declined or are declining, which is concerning given their ecological role in Arctic ecosystems and their societal role in northern communities. Insect harassment is an important driver of the behavior, energetics, and demographic rates of caribou, and yet, due to challenges in predicting harassment, there is limited understanding of how it is responding to changing Arctic conditions. We investigated environmental correlates of mosquito (Culicidae) and oestrid fly (Oestridae) harassment for the Porcupine caribou herd, with the aim of improving our ability to predict harassment. We collected field observations of mosquito activity and used video collars to detect oestrid fly activity across the summer range, which spans the Alaska–Yukon border. Additionally, we documented the composition of harassing insects collected in malaise traps using DNA metabarcoding. We developed predictive mosquito and oestrid fly harassment models using remotely sensed variables relevant to the insects' biology within a nonlinear modeling framework. We then used the top mosquito and oestrid fly models to hindcast predictions of harassment during 1950–2024 and investigate long-term changes in severity and phenology. The top mosquito harassment model included wind speed, temperature, days since snowmelt, precipitation, topographic position, and soil moisture. The top oestrid fly harassment model included temperature, cumulative growing degree days, and time of day. Harassment of both insects was limited at low temperatures (<10°C), with mosquitoes being additionally limited at high temperatures (>22°C) and wind speeds (>7 m/s). The phenology of mosquito and oestrid fly harassment exhibited curvilinear trends across the summer, peaking in midsummer based on the number of days since snowmelt and cumulative growing degree days, respectively. Mosquito harassment also increased with greater soil moisture, precipitation, and at lower relative elevations. Hindcasting indicated that insect harassment notably intensified and advanced over time. Intensifying harassment could decrease caribou foraging opportunities and body condition, and advancing harassment is likely to increasingly overlap with the calving season when calves are most vulnerable. Our results highlight climate-driven changes in insect harassment and provide improved indices for predicting harassment in the Arctic for future applications.

Alaska↗

Application of close-kin mark–recapture to an American black bear population using harvest samples

Close-kin mark–recapture (CKMR) offers a promising alternative to traditional mark–recapture methods for estimating wildlife population parameters. CKMR estimates demographic parameters by identifying genetic relationships between individuals, effectively “recapturing” parental genotypes through their offspring's genetic profiles. One key advantage of CKMR over traditional methods is the ability to estimate abundance without recapture, facilitating the use of lethally collected biological samples. Here, we present an application of CKMR to a terrestrial species using samples collected from harvested individuals. We analyzed genetic data from 1767 American black bears ( Ursus americanus ) harvested over two consecutive years in Michigan's Upper Peninsula. Using Genotyping-in-Thousands by sequencing (GT-seq), we identified parent-offspring pairs and developed sex-specific models tailored to black bear reproductive biology and management strategies. Female population estimates aligned with our expectations, based on prior knowledge of the population. In contrast, male population estimates deviated from expectations, potentially due to an unmodeled combination of factors pertaining to male reproductive biology and sampling bias. Our study not only demonstrates the viability of using harvest-based CKMR for monitoring of terrestrial wildlife populations, but also highlights the need for careful model specification. By providing a novel method to estimate demographic parameters and population size, CKMR using harvest samples can inform management decisions and harvest quotas. This approach leverages existing management practices involving collection of genetic samples, such as mandatory harvest registrations and health monitoring programs. Our findings contribute to the growing body of CKMR applications and expand its use to terrestrial species management.

Michigan↗

Listening for extinction: Range-wide occupancy highlights critical risks and priorities for northern spotted owls

The northern spotted owl ( Strix occidentalis caurina ) continues to decline across its range, threatened by habitat disturbances and invasive barred owls ( Strix varia ). We conducted a range-wide spotted owl occupancy assessment using 2.1 million h of passive acoustic recordings from 4081 survey stations within 1027 randomly selected 5-km 2 hexagons across six physiographic regions. Applying multistate occupancy models, we estimated probabilities of landscape use (by at least one northern spotted owl) and pair occupancy (occupied by both a male and a female), while accounting for imperfect and sex-biased detection probability. Detection probability of pairs was low in most regions, primarily due to undetected females, but increased with survey effort. If management decisions can only be made when there is a high probability of detecting both sexes when they are present, then longer surveys are one approach to support the decisions. Landscape use and pair occupancy were positively associated with old-growth forest structure and topographic diversity. We also found a pronounced latitudinal gradient in spotted owl landscape use rates with estimated mean landscape use of 0.17 (SE = 0.03) and 0.16 (SE = 0.02) in the two most northern regions, and 0.54 (SE = 0.04) and 0.52 (SE = 0.05) in the two most southern regions. Pair occupancy rates were higher in southern regions (0.29, SE = 0.03, 0.43, SE = 0.05) and very low in northern regions (0.04, SE = 0.01, 0.03, SE = 0.01). In contrast to spotted owls, barred owls were detected in 90% of northern hexagons and 50% of southern hexagons, and barred owl calling intensity was over eight times higher than spotted owls. These results highlight extinction risks in several regions and suggest that management actions, such as spatially targeted barred owl control and protection of structurally complex habitats, have a narrow temporal window in which they can be effective in lowering the probability of regional extirpations. We generated predictive maps of landscape use and pair occupancy, which could help guide regional conservation strategies. This study demonstrates how passive acoustic monitoring and machine learning can be used for broad-scale ecological monitoring, identifying extinction risk thresholds, supporting adaptive management, and improving conservation outcomes for wide-ranging and elusive species that can reliably be detected through unique vocalizations.

California, Oregon, Washington↗