Challenges and opportunities in population monitoring of cheetahs

Abstract

Population monitoring is key to wildlife conservation and management but is challenging at the 18 spatial and temporal extents necessary for understanding changes. Non-invasive survey methods 19 and spatial capture-recapture (SCR) models have revolutionized wildlife monitoring by providing the means to more easily acquire data at large scales and the framework to generate spatially-explicit predictions, respectively. Despite the opportunities for improved monitoring, 22 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 the changes in density of cheetahs between 2005 and 2013-2016 in the Masai Mara National Reserve (MMNR) in southwestern Kenya. Our SCR models of cheetah encounters suggested little change in cheetah density from 2005 to 2013-2016, though there was 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 included in the modeling did not substantially alter inferences about density when sample sizes were adequate (>20 spatially distinct encounters). We estimated an average cheetah density of ~1.2 31 cheetahs/100 km 2 , consistent with the impression that the MMNR provides important habitat for cheetahs in Africa. During most years and seasonal periods, the spatial distribution of vegetation greenness (a proxy for ungulate habitat quality) accounted for important variation in encounter rates. The search-encounter design used here could be applied to other regions for the purposes of cheetah monitoring. While snap-shot estimates of population size across time are useful for wildlife monitoring, open population models could identify the mechanisms behind changes and further facilitate better conservation and management decision making..

Advertising sex and individual identity by long‐distance chirps in wild‐living mature cheetahs (Acinonyx jubatus)

“…The habitat types of the study are represented by dwarf shrubs/short grassland, tall grassland, shrubland, forest, and woody/ shrubby grassland (Oindo et al, 2003). During data collection period (2014)(2015)(2016)(2017)(2018)(2019)(2020)(2021)(2022), population density of cheetahs in the Maasai-Mara National Reserve ranged from 0.61 (0.34-1.10) cheetahs/100 km 2 to 1.67 (1.00-2.80) cheetahs/100 km 2 (Linden et al, 2020). According to Prost et al (2022), cheetahs in this area belong to subspecies A. j. raineyi.…”

Message from the new Editor‐in‐Chief

“…The third image shows two male cheetahs ( Acinonyx jubatus ) resting in the Masai Mara National Reserve (MMNR) in Kenya (Linden, Green, Chelysheva, Mandere, & Dloniak, 2020). Linden et al (2020) used a search‐encounter design to survey cheetahs in the MMNR to estimate changes in their density from 2005 to 2013–2016 using spatial capture‐recapture models. Density was relatively consistent across time (~1.2 cheetahs/100 km 2 ), indicating that this region may provide important cheetah habitat in Africa.…”

Estimating animal abundance at multiple scales by spatially explicit capture–recapture

“…Currently, many researchers take advantage of our ability to identify individuals from passively collected genetic or photographic samples to enumerate animals that range widely and occur at low densities using spatially explicit capture–recapture (SECR) methods (Arandjelovic & Vigilant 2018 ; Borchers & Efford, 2008 ; Boulanger et al, 2018 ; Després‐Einspenner et al, 2017 ; Gardner et al, 2009 ; Greenspan et al, 2020 ; Humm & Clark, 2021 ; Linden et al, 2020 ; Royle et al, 2009 , 2013 ). Studies of American black bears ( Ursus americanus ) in particular have contributed to the ongoing development and testing of SECR methods, and important covariates of detectability were previously identified (Clark, 2019 ; Gardner et al, 2009 , 2010 ; Humm et al, 2017 ; Obbard et al, 2010 ; Sollmann et al, 2012 ; Sun et al, 2014 ; Wilton et al, 2014 ).…”