Is unreliable science guiding bobcat management in Wyoming and other western U.S. states?

Abstract

Abstract Wildlife managers require defensible and transparent population estimates to justify species management. Statistical population reconstruction (SPR) is being widely adopted to estimate wildlife population sizes from hunter harvest data. We assessed factors influencing variation in SPR population estimates produced for bobcats in Wyoming, USA. Specifically, we tested whether prey availability, hunter/trapper effort, the number of bobcats killed or the methods used to classify the age and sex of bobcats (‘classification protocol’) best explained changing SPR abundance estimates. We then quantified the relative magnitude of these effects on SPR model outputs. Classification protocol had the strongest impact on SPR abundance estimates, such that a shift to visual age and sex classifications by trappers/hunters resulted in overestimates of bobcat abundance. The Wyoming bobcat SPR population estimates were likely unreliable and we suggest that spatially explicit integrated population models may be a better approach to obtaining defensible estimates upon which to establish scientific management of this charismatic carnivore.

Keywords

• bobcat
• conservation
• harvest metrics
• Lynx rufus
• statistical population reconstruction
• trapping