Potential for camera-traps and spatial mark-resight models to improve monitoring of the critically endangered West African lion (Panthera leo)

Abstract

West African lions are critically endangered throughout their range. Recent monitoring efforts focused on determining where remaining populations persist and obtaining preliminary population estimates to assess status across the region. However, current monitoring methods do not result in estimates that can be easily compared across sites or over time. Thus, there is a need to develop methods that allow for unbiased and precise comparable population parameter estimates for baseline and long-term monitoring. Spatial mark-resight models offer the ability to estimate lion density for a site over a standardized unit of area making estimates comparable. In addition, Bayesian inference is not constrained by asymptotic assumptions and allows for unbiased and precise estimates even with small sample sizes and low detection rates. We demonstrate the utility of Bayesian inference of a spatial mark-resight model for West African lion populations using a single-season camera trap survey at a study site in Niokolo-Koba National Park, Senegal. We estimated a site specific density of 3.02 lions/100 km2 (1.72–5.57/100 km2) based on trap-specific relocations of individuals with unique identifying natural marks, and counts of unmarked individuals at each trap. We conclude with a discussion of limitations of the current study and possible improvements on this method. We suggest immediate action including site specific monitoring within protected areas to conserve lions in this most northern part of their range. This monitoring approach can provide useful estimates over large areas providing an easily implemented and repeatable methodology for local and regional monitoring of critically endangered lion populations.