Description
In California, urbanization is a leading cause of habitat fragmentation. Although the consequences of a loss of landscape connectivity are typically described at a local extent, regional analyses, particularly for wide-ranging species, can be used to identify management priorities. We monitored trends in the abundance and density of bobcats through motionsensor cameras to measure potential effects of landscape fragmentation at the local scale and performed a landscape level bobcat genetic analysis across southern California, including two outgroups from northern California for comparison. Spatial capture-recapture (SCR) models are widely used to estimate population abundance and density from pictures taken at camera traps. We paired SCR with spatial partial identity models (SPIM) to estimate density of bobcats from camera traps located in three study areas in San Diego County (SD) across an urbanization gradient. We found that locally in SD, the area with the highest level of urbanization had lower bobcat density than the more natural study area, and that these densities were lower than estimates from published studies with comparable methodological approaches. With an inter-lab validation methodology, we performed a comprehensive analysis using 19 microsatellite loci for 118 individuals and 11 loci for 422 individuals. We then conducted hierarchical analyses of population genetic structure and examined how pairwise genetic distance of all population clusters aligned with geographic distance using the 19 loci dataset. Lastly, we employed a landscape genetic analysis based on resistance to determine which features of the landscape likely play a role in determining the patterns of genetic structure we observed among bobcats in southern California. Regionally in southern California, we found that some populations were constrained by major freeways and development, while populations with no clear major anthropogenic barriers to movement between them were genetically similar. Through our landscape genetic analysis, we found permeability to be the strongest predictor of the observed patterns of genetic variation across southern California bobcats. Our results highlight the importance of analyzing population parameters and genetic patterns at multiple scales, and underscore how the differences between local and regional patterns may require site-specific conservation and management actions in increasingly developed areas.
