Using occupancy modeling to inform endangered riparian brush rabbit recovery in the San Joaquin Valley, California

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Authors:
Haley Mirts, Erin Hagen, Julie Rentner

Publication Date:
2021

Abstract/Summary:
The riparian brush rabbit (Sylvilagus bachmani riparius) is one of California’s most imperiled mammals. The species is endemic to riparian forests of the San Joaquin Valley, however, less than 10% of these historic riparian forests remain. Since the early 2000s, River Partners has worked in conjunction with The Riparian Brush Rabbit Working Group, a collaborative of non-profit, academic, private and agency organizations, to build and restore riparian brush rabbit habitat. Through this successful partnership, over 1200 hectares of habitat has been planted in the San Joaquin River corridor, and translocations led to successful establishment of brush rabbits in restored habitat at the San Joaquin River National Wildlife Refuge. In June 2020, we confirmed a new population of riparian brush rabbit at nearby Dos Rios Ranch using randomly placed camera traps. After 520 trap nights, we used Royle-Nichols occupancy modeling to estimate population size (R 4.0.2). After opportunistically capturing and marking individuals from the population, we repeated the camera trapping to compare population estimates resulting from occupancy modeling and capture-mark-recapture estimates. These efforts reinforce the utility of passive detection methods for endangered species study and recovery, demonstrating the utility of camera traps to document rare mammal presence and to differentiate focal species from congeners in the same environment, and de-emphasize the need to capture, handle and mark individuals for population estimation. Next, we will apply occupancy modelling to assess relative impacts of vegetation variables as a step to inform future habitat restoration efforts and translocations within the species’ historic range.

Resource Type:
Conference Presentation, SER2021

Pre-approved for CECs under SER's CERP program

Source:
SER2021