Camera trapping and spatially explicit capture–recapture for the monitoring and conservation management of lions: Insights from a globally important population in Tanzania

Abstract

Accurate and precise estimates of population status are required to inform and evaluate conservation management and policy interventions. Although the lion (Panthera leo) is a charismatic species receiving increased conservation attention, robust status estimates are lacking for most populations. While for many large carnivores population density is often estimated through spatially explicit capture–recapture (SECR) applied to camera trap data, the lack of pelage patterns in lions has limited the application of this technique to the species. Here, we present one of the first applications of this methodology to lion, in Tanzania's Ruaha‐Rungwa landscape, a stronghold for the species for which no empirical estimates of status are available. We deployed four camera trap grids across habitat and land management types, and we identified individual lions through whisker spots, scars and marks, and multiple additional features. Double‐blind identification revealed low inter‐observer variation in photo identification (92% agreement), due to the use of xenon‐flash cameras and consistent framing and angles of photographs. Lion occurred at highest densities in a prey‐rich area of Ruaha National Park (6.12 ± SE 0.94 per 100 km2), and at relatively high densities (4.06 ± SE 1.03 per 100 km2) in a community‐managed area of similar riparian‐grassland habitat. Miombo woodland in both photographic and trophy hunting areas sustained intermediate lion densities (1.75 ± SE 0.62 and 2.25 ± SE 0.52 per 100 km2, respectively). These are the first spatially explicit density estimates for lion in Tanzania, including the first for a trophy hunting and a community‐managed area, and also provide some of the first insights into lion status in understudied miombo habitats. We discuss in detail the methodology employed, the potential for scaling‐up over larger areas, and its limitations. We suggest that the method can be an important tool for lion monitoring and explore the implications of our findings for lion management.

Trends and biases in African large carnivore population assessments: identifying priorities and opportunities from a systematic review of two decades of research

“…The observed paucity of estimates for African wild dog is likely a result of the species being less well-known compared to the felids ( Macdonald et al, 2015 ), and a combination of ecological and methodological factors. African wild dogs are social, low density species, with very large home ranges that often range outside of PA boundaries ( Creel & Creel, 2002 ); as a result, survey methods often employed for other species ( e.g ., camera trapping combined with capture-recapture modelling; Strampelli et al, 2022b ) are challenging to apply to African wild dogs, while others ( e.g ., call-ins) are less suitable due to behavioural characteristics. Indeed, although rapid assessment methods such as spoor counts have occasionally been employed to survey populations ( Henschel et al, 2020 ), approximately half of published density estimates were obtained through resource-intensive long-term studies or citizen-science approaches, highlighting the difficulty associated with surveying the species rapidly.…”

Habitat use of and threats to African large carnivores in a mixed‐use landscape

“…For leopards, the lack of significant covariate effects at the home range scale confirmed that, as long as some prey are available, the species can persist across a range of habitats (Estes, 1991;Strampelli et al, 2018). In contrast, finer scale habitat use by leopard was significantly associated with availability of cover, as noted by Miller et al (2018).…”

“…At the home range scale, the species was strongly associated with areas farther from large rivers (Figure 2 ), but that nonetheless exhibited relatively high levels of prey availability. Although areas near large rivers host the highest prey concentrations in the dry season (TAWIRI, 2019 ), they also exhibit the highest densities of dominant sympatric predators, including lions (Strampelli et al., 2022 ). Wild dogs can be suppressed in areas of high lion and spotted hyaena density (Creel & Creel, 1998 ); by indicating avoidance of (or inability to persist in) these high‐prey but also high‐competitor areas, our results provide further evidence for such effects.…”

“…Instead, wild dogs appeared to be associated with areas that still had relatively high prey availability, but had lower densities of sympatric predators. Mean wild dog site use was significantly greater in miombo woodlands (Figure 3), where sympatric competitor densities are lower (Searle et al, 2021;Strampelli et al, 2022). This is likely to also be a result of competitor avoidance or of greater survival as a result of kleptoparasitism and direct mortality being minimized in woodlands (Creel & Creel, 1998;Mills & Gorman, 1997).…”

Index‐based large carnivore population density and abundance estimates for the Ruaha‐Rungwa conservation complex in Tanzania

“…Nevertheless, we believe that there is value in sharing our estimates, given the complete lack of empirical landscape‐scale population estimates for Ruaha‐Rungwa's large carnivores. Going forward, however, we recommend exploring instead the scalability of methods that can provide greater levels of precision, such as spatially explicit capture‐recapture (SECR) models applied to data from camera traps (e.g., Strampelli, Henschel, Dickman et al, 2022) or direct sightings (e.g., Elliot & Gopalaswamy, 2016), which have typically been applied over smaller areas. Alternatively, where scalability proves challenging or too resource‐intensive, we recommend considering the estimation of alternative robust status parameters (e.g., occupancy; Strampelli, Henschel, Searle et al, 2022) from track data to monitor population status over large scales.…”