A novel camera trapping method for individually identifying pumas by facial features.

Area of Science:

• Wildlife ecology
• Conservation biology
• Photographic identification techniques

Background:

• Capture-mark-recapture (CMR) analysis, particularly photo-CMR, is vital for estimating elusive wildlife populations.
• Photo-identification (photo-ID) is a key component of photo-CMR but is typically limited to species with distinct markings and lateral images.
• Pumas (Puma concolor) lack prominent markings, making traditional photo-ID challenging despite effective camera trap (CT) data collection.

Purpose of the Study:

• To assess the feasibility of using puma facial features for photo-ID within a CT framework.
• To determine if a novel CT accessory can improve the capture rate of puma facial images.
• To evaluate whether facial images enhance the accuracy of puma photo-ID by human observers.

Main Methods:

• A novel CT accessory using light and sound was deployed to attract pumas and capture facial images.
• Face capture rates were compared between CTs with and without the accessory.
• Inter-rater agreement (Fleiss' kappa) was calculated for photo-ID assessments using puma facial images.

Main Results:

• CTs equipped with the accessory showed significantly higher puma face capture rates (n = 208, χ² = 43.23, p ≤ .001).
• Photo-ID assessments using facial images demonstrated moderate to good agreement (Fleiss' kappa = 0.54, 95% CI = 0.48-0.60).
• The agreement using facial images was 92.90% higher than previously reported kappa values from conventional CT methods.

Conclusions:

• Facial photo-ID is feasible for pumas, an elusive species lacking pelage markings, using CTs.
• A novel CT accessory effectively increases the capture rate of facial images for photo-ID.
• This technique shows promise for expanding photo-ID applications to unmarked elusive species, improving wildlife abundance estimations.