Camera trapping and spatially explicit capture–recapture for the monitoring and conservation management of lions: Insights from a globally important population in Tanzania. Issue 1 (4th February 2022)

• Record Type: Journal Article
• Authors: Strampelli, Paolo; Searle, Charlotte E.; Smit, Josephine B.; Henschel, Philipp; Mkuburo, Lameck; Ikanda, Dennis; Macdonald, David W.; Dickman, Amy J.
• Is Part Of: Ecological solutions and evidence. Volume 3:Issue 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-04
• Subjects: camera trap -- lion -- Panthera leo -- population monitoring -- Ruaha‐Rungwa -- SECR -- Tanzania -- trophy hunting; Environmental management -- Periodicals; Ecology -- Periodicals; Electronic journals; Periodicals; 333.72
• DOI: 10.1002/2688-8319.12129
• Languages: English
• ISSNs: 2688-8319

Abstract

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 km 2 ), and at relatively high densities (4.06 ± SE 1.03 per 100 km 2 ) 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 km 2, 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. Abstract : 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 show that by using xenon‐flash camera traps, combined with consistent framing and angles of photographs, it is possible to reliably identify lions and estimate population density across habitat and land management types. We present the first spatially explicit estimates for a lion population in Tanzania, and discuss in detail the methodology employed and its relevance to lion population research and monitoring.