Spatial Patterns of Breeding Success of Grizzly Bears Derived from Hierarchical Multistate Models

• Published in: Conservation Biology
• Main Authors: FISHER, JASON T., WHEATLEY, MATTHEW, MACKENZIE, DARRYL
• Other Authors: Provincial Parks Division, Government of Alberta, Alberta Innovates-Technology Futures, Alberta Biodiversity Monitoring Institute
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2014
• Subjects: Canada; Ursus arctos
• Online Access: http://dx.doi.org/10.1111/cobi.12302; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fcobi.12302; http://onlinelibrary.wiley.com/wol1/doi/10.1111/cobi.12302/fullpdf

Abstract Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears ( Ursus arctos ) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low‐elevation wetlands or mid‐elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy—herbaceous alpine ecotones—were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. Patrones Espaciales del Éxito Reproductivo de ...