Using bear rub data and spatial capture-recapture models to estimate trend in a brown bear population

Abstract

Trends in population abundance can be challenging to quantify during range expansion and contraction, when there is spatial variation in trend, or the conservation area is large. We used genetic detection data from natural bear rubbing sites and spatial capture-recapture (SCR) modeling to estimate local density and population growth rates in a grizzly bear population in northwestern Montana, USA. We visited bear rubs to collect hair in 2004, 2009—2012 (3,579—4,802 rubs) and detected 249—355 individual bears each year. We estimated the finite annual population rate of change 2004—2012 was 1.043 (95% CI = 1.017—1.069). Population density shifted from being concentrated in the north in 2004 to a more even distribution across the ecosystem by 2012. Our genetic detection sampling approach coupled with SCR modeling allowed us to estimate spatially variable growth rates of an expanding grizzly bear population and provided insight into how those patterns developed. The ability of SCR to utilize unstructured data and produce spatially explicit maps that indicate where population change is occurring promises to facilitate the monitoring of difficult-to-study species across large spatial areas.

Consequences of ignoring variable and spatially-autocorrelated detection probability in spatial capture-recapture

“…Some sources of spatial heterogeneity in detection probability are known, such as when sampling effort is recorded during camera trapping and non-invasive DNA sampling (Royle et al 2009; Efford et al 2013). Others are suspected and can be modeled with spatial covariates, such as habitat proxies for vulnerability to detection (Bischof et al 2017; Kendall et al 2019). SCR models are well-suited for these situations of variable detectability, as studies are usually configured into discrete detection locations referred to as detectors (or traps), which are distributed across a study area.…”

“…Nonetheless, in many wildlife monitoring studies, spatial heterogeneity in detection probability remains partially unknown. Unaccounted environmental factors may impact exposure to detectors; for example, site-specific characteristics may affect visibility, or local climate can influence genotyping success rate of non-invasively collected DNA samples (Efford et al 2013; Kendall et al 2019). Survey effort may also vary across the study area unbeknownst to the investigator.…”

Brown Bear Density and Estimated Harvest Rates in Northwestern Alaska

“…Several approaches have been used to successfully estimate bear density and monitor populations including demographic projection models (Saether et al 1998, Garshelis et al 2005, Gervasi and Ciucci 2018, capture-mark-resight (Miller et al 1997, McClintock et al 2006, genetic markers analyzed in a mark-recapture (Mowat and Strobeck 2000;Gervasi et al 2008;Kendall et al 2008Kendall et al , 2009Ciucci et al 2015) or spatial capture-recapture (Bischof et al 2016, Murphy et al 2016, Kendall et al 2019 framework, line transect distance sampling (Becker and Quang 2009, Walsh et al 2010, Becker and Christ 2015, and the integration of multiple data types (Gervasi et al 2012, Popescu et al 2017). Capture-mark-resight has been used extensively throughout Alaska but requires physically marking individuals prior to conducting surveys.…”

An evaluation of noninvasive sampling techniques for Malayan sun bears

“…Abundance or density estimation is also possible when individuals can be identified from genetic samples obtained from hair or feces, which can additionally be used to examine geographic isolation and connectivity, inbreeding, and parentage and kin structure (Taberlet et al 1997;Woods et al 1999;Wilson et al 2003;Schwartz et al 2007;Kendall et al 2009Kendall et al , 2019Dumond et al 2015;Palomares et al 2017). Although successfully applied in numerous bear studies worldwide (e.g., Zhan et al 2006, Kendall et al 2009, Dutta et al 2015, Murphy et al 2017, genetic sampling of sun bears is fraught with challenges. Fresh scats of this species are difficult to locate in tropical regions, where precipitation and insects rapidly decompose feces and genetic material may degrade rapidly from exposure to sunlight, warm temperatures, and humidity (Stetz et al 2014, Dumond et al 2015.…”

“…Fresh scats of this species are difficult to locate in tropical regions, where precipitation and insects rapidly decompose feces and genetic material may degrade rapidly from exposure to sunlight, warm temperatures, and humidity (Stetz et al 2014, Dumond et al 2015. Furthermore, commonly used hair-sampling devices, such as barbedwire corrals (Kendall and McKelvey 2012), may be ineffective for sun bears that typically possess short guard hairs (S.T. Wong, unpublished data).…”