Using spatial capture‐recapture models to inform lion ( <i>Panthera leo</i> ) management in fenced protected areas

Abstract The South African lion ( Panthera leo ) metapopulation is distributed over a network of small, fenced protected areas and requires intensive management to mimic ecological processes. As the metapopulation grows, coordinated management—supported by reliable, cost‐effective monitoring—is increasingly important. However, monitoring programs to support improved metapopulation management can be resource intensive, and optimal sampling regimes are desirable, wherein expenditure of resources is minimized without compromising the reliability of estimates and the ability to detect population trends. In this study, we conducted a follow‐up lion population survey in a small, fenced reserve in South Africa, 2 years after a management‐driven population reduction. Using optimal sampling guidelines from an initial survey in 2020, we applied Bayesian spatial capture‐recapture (SCR) models to estimate current density at 5.24 individuals/100 km 2 (95% highest posterior density interval = 4.22–6.43), a 40% decline since the 2020 estimate. By following recommendations on survey effort and minimum data objectives, informed by the 2020 survey, we demonstrate how an initial survey can be used to optimize subsequent survey effort and strike a balance between precision and resource expenditure. Our study highlights how SCR models and search‐encounter methods can be used to guide lion management in small, fenced reserves and help to inform a more coordinated approach to lion metapopulation management in South Africa.