Geology Reports⌕ Search

USGS · 70032362

Linking landscape characteristics to local grizzly bear abundance using multiple detection methods in a hierarchical model

Abstract

Few studies link habitat to grizzly bear Ursus arctos abundance and these have not accounted for the variation in detection or spatial autocorrelation. We collected and genotyped bear hair in and around Glacier National Park in northwestern Montana during the summer of 2000. We developed a hierarchical Markov chain Monte Carlo model that extends the existing occupancy and count models by accounting for (1) spatially explicit variables that we hypothesized might influence abundance; (2) separate sub-models of detection probability for two distinct sampling methods (hair traps and rub trees) targeting different segments of the population; (3) covariates to explain variation in each sub-model of detection; (4) a conditional autoregressive term to account for spatial autocorrelation; (5) weights to identify most important variables. Road density and per cent mesic habitat best explained variation in female grizzly bear abundance; spatial autocorrelation was not supported. More female bears were predicted in places with lower road density and with more mesic habitat. Detection rates of females increased with rub tree sampling effort. Road density best explained variation in male grizzly bear abundance and spatial autocorrelation was supported. More male bears were predicted in areas of low road density. Detection rates of males increased with rub tree and hair trap sampling effort and decreased over the sampling period. We provide a new method to (1) incorporate multiple detection methods into hierarchical models of abundance; (2) determine whether spatial autocorrelation should be included in final models. Our results suggest that the influence of landscape variables is consistent between habitat selection and abundance in this system.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

T.A. Graves, Katherine C. Kendall, J. Andrew Royle, J.B. Stetz, A.C. Macleod. 2011-07-05. Linking landscape characteristics to local grizzly bear abundance using multiple detection methods in a hierarchical model. https://doi.org/10.1111/j.1469-1795.2011.00471.x

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

KEEP EXPLORING

Related USGS reports

The rising threat of lead: Trends in fatalities of California condors

Endangered species face threats that change over time, and understanding variation in the importance of threats is valuable for guiding species recovery. The reintroduced population of critically endangered California condors has faced a number of threats over the three decades since the species was first released back to the wild. We modeled interannual and interseasonal trends in the leading causes of death for wild condors. Our analysis showed strong evidence ( P = 0.971) that the estimated annual probability of death from lead toxicosis has increased since reintroduction started. This increase was most pronounced in the central California subpopulation. Adults were disproportionately affected by lead toxicosis, a trend that may be explained by increased exposure associated with age-related changes in foraging behavior that lead to decreased reliance on clean proffered food sources. Population-level mortality from trauma showed a temporary increase in 2012, and fire-related mortality was higher during the summer months. Pattens also varied across subpopulations, with the southern California subpopulation of condors showing distinct temporal peaks in deaths from trauma (in 2012) and predation (in 2010). Our analysis suggests that threats to condors have not been static over space and time. Managers can therefore use this information to adaptively manage and target mitigation efforts when and where they are the most effective.

California↗

Integrated species distribution model using historical data shows decline in a common semi-aquatic mammal

Effective conservation requires an understanding of drivers of a species' distribution as well as long-term changes in their distribution. In recent decades, advances in data collection and analysis have allowed researchers to integrate a wide range of information to model species distributions, particularly by allowing presence-only data and detection-nondetection data to be formally combined in integrated species distribution models (ISDMs). However, these models are rarely used to investigate long-term trends, which are important in evaluating a species' status. Here, we use historical presence-only data of river otters ( Lontra canadensis ; 366 latrine locations from 1999 to 2007 and 105 locations of road-killed individuals recorded from 1999 to 2020) and 919 detection-nondetection surveys from 230 sites between 2021 and 2023 to understand the current distribution of river otters in Rhode Island, USA, as well as the changes in river otter distribution over the past two decades. We found that river otters were strongly associated with key habitat features such as streams and water, positively associated with urban areas, and tolerant of some contaminants, such as lead. Furthermore, despite uncertainties in historical river otter occurrence, we found clear supporting evidence that river otter intensity of use had declined from 1999 to 2023. This decline occurred despite being protected from harvest and in contrast to range expansions in other parts of the northeastern USA throughout the second half of the 20th century. Our results suggest the utility of this approach to detect declines in species for which historical data are available and a need for better understanding the cause of river otter declines. Where monitoring consists of opportunistically collected data, species conservation could benefit by continuing to collect these data as well as introducing designed surveys, as this would allow better integration of data types, improving trend estimation and reducing the amount of (typically more expensive) designed surveys needed.

Rhode Island↗

Breeder turnover, harvest, and food affect recruitment of young nonbreeders in groups of gray wolves

Groups of cooperative breeders typically have social hierarchies, with breeders at the top guiding group decisions and influencing the behavior of subordinates in the group. Because of breeders' strong influence on group dynamics and behaviors, breeder turnover can affect the survival of remaining group members. We lack a solid understanding of the nuanced but important effects of breeder turnover on group composition. I first asked how harvest (i.e., hunting and trapping) affected rates of breeder turnover in groups of gray wolves ( Canis lupus ) in Idaho, USA, from 2008 to 2020. Then, I asked how breeder turnover, group size, and food availability affected the recruitment of 1- and 2-year-old nonbreeders into groups. Harvest was associated with an increase in breeding female, but not breeding male, turnover. Breeding female turnover was negatively associated with the probability of 1-year-old, but not 2-year-old, nonbreeders being in a group the following year. The only significant variable associated with the recruitment of 2-year-old nonbreeders into groups was sex, as males were less likely than females to be present in groups at time (t+1) . Finally, an index of prey biomass was positively associated with the probability of 1-year-olds being present in groups at time (t+1) (i.e., apparent pup survival to age 1). I show that harvest, social factors such as breeder turnover, and food availability influence the presence of young nonbreeders in groups, ultimately affecting group composition in a cooperative breeder.

Idaho↗