Trophic scaling and occupancy analysis reveals a lion population limited by human pressure in the Limpopo National Park, Mozambique.

<p>Trophic scaling and occupancy analysis reveals a lion population limited by human pressure</p> <p>in the Limpopo National Park, Mozambique.</p> <p>Authors: Kristoffer T. Everatt1*, Leah Andresen1 , Michael J. Somers1,2</p> <p>Affiliations:</p> <p>Centre for Wildlife Management, University of Pretoria, Pretoria, South AfricaCentre for Invasion Biology, University of Pretoria, Pretoria, South Africa</p> <p>*To whom correspondence should be addressed: kteveratt@gmail.com</p> <p>Abstract</p> <p>The African lion (Panthera leo) has suffered drastic population and range declines over the last few decades and is listed by the IUCN as vulnerable to extinction. Conservation management requires reliable population estimates, however these data are lacking for many of the continent’s remaining lion populations. It is possible to estimate lion populations using a trophic scaling approach based on relatively easy to obtain aerial prey data. However, such inferences assume that a predator population is subject only to bottom-up regulation, and are thus likely to produce biased estimates in systems with considerable top-down anthropogenic pressures. Here we provide baseline data on the status of lions in a developing National Park in Mozambique that is impacted by humans and livestock. We compare a direct density estimate using call-ups with an estimate derived from trophic scaling. We then use replicated detection/non-detection surveys to estimate the proportion of area occupied by lions, and hierarchical ranking of covariates to provide inferences on the relative contribution of prey resources and anthropogenic factors influencing lion occurrence. Direct density estimates were less than 1/3 of the estimate derived from prey resources (0.99 lions/100 km2 vs. 3.05 lions/100 km2). The proportion of area occupied by lions was Ψ = 0.436 (SE = 0.127), or approximately 44% of a 2400 km2 sample of potential habitat. Although lions were strongly predicted by a greater probability of encountering prey resources, the greatest contributing factor to lion occurrence was a strong negative association with agro-pastoralist settlement areas. Finally, our empirical abundance estimate is approximately a third of a published abundance estimate derived from opinion surveys. Altogether, our results describe a lion population that is held below resource-based carrying capacity by anthropogenic factors, and highlight the limitations of trophic scaling and opinion surveys for estimating predator populations exposed to anthropogenic pressures. Our study provides the first empirical quantification of a population that future change can be measured against.