Challenges and opportunities in population monitoring of cheetahs

Population monitoring is key to wildlife conservation and management but is challenging at the spatial and temporal extents necessary for understanding changes. Noninvasive survey methods and spatial capture-recapture (SCR) models have revolutionized wildlife monitoring by providing the means to acquire data at large scales and the framework to generate spatially explicit predictions, respectively. Despite opportunities for improved monitoring, challenges can remain in the study design and model fitting phases of an SCR approach. Here, we used a search-encounter design with multi-session SCR models to collect spatially indexed photographs and estimate changes in density of cheetahs between 2005 and 2013-2016 in the Masai Mara National Reserve (MMNR) in Kenya. Our SCR models of cheetah encounters suggested little change in cheetah density from 2005 to 2013-2016, with some evidence that density fluctuated annually in the MMNR. The sampling period length (5 vs. 10 months) and timing (early, late, full year) over which spatial encounters were modeled did not alter inferences about density when sample sizes were adequate (>20 spatially distinct encounters). Our average density estimate of similar to 1.2 cheetahs/100 km(2)is consistent with the impression that the MMNR provides important cheetah habitat in Africa. During most years, spatial distribution of vegetation greenness (proxy for ungulate habitat quality) accounted for important variation in encounter rates. The search-encounter design here could be applied to other regions for cheetah monitoring. While snapshot estimates of population size across time are useful for wildlife monitoring, open population models may better identify the mechanisms behind temporal changes.