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

Area of Science:

• Wildlife ecology
• Population dynamics
• Conservation genetics

Background:

• Quantifying population trends during range shifts or in large areas is difficult.
• Grizzly bear populations present unique monitoring challenges due to their size and movement patterns.

Purpose of the Study:

• To estimate population density and growth rates in a grizzly bear population using genetic data.
• To apply spatial capture-recapture (SCR) modeling to understand population changes in northwestern Montana.

Main Methods:

• Utilized genetic detection data from natural bear rubbing sites.
• Employed spatial capture-recapture (SCR) modeling to analyze data collected from 2004-2012.
• Estimated local density and population growth rates with spatially explicit outputs.

Main Results:

• Estimated a finite annual population rate of change of 1.043 (95% CI = 1.017-1.069) for grizzly bears between 2004 and 2012.
• Observed a shift in population density distribution from concentrated northern areas in 2004 to a more even spread by 2012.
• Demonstrated the effectiveness of genetic sampling and SCR modeling for estimating spatially variable growth rates.

Conclusions:

• Genetic sampling and SCR modeling provide a robust method for monitoring difficult-to-study species across large areas.
• This approach offers valuable insights into the spatial dynamics of expanding populations, facilitating conservation efforts.
• The study successfully mapped population changes, aiding in the understanding of grizzly bear range dynamics.