Lions in a coexistence landscape: Repurposing a traditional field technique to monitor an elusive carnivore. Issue 3 (1st March 2022)

• Record Type: Journal Article
• Authors: Western, Guy; Elliot, Nicholas B.; Sompeta, Steiner L.; Broekhuis, Femke; Ngene, Shadrack; Gopalaswamy, Arjun M.
• Is Part Of: Ecology and evolution. Volume 12:Issue 3(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-03-01
• Subjects: abundance -- African lion -- coexistence -- Maasailand -- noninvasive sampling -- spatially‐explicit capture‐recapture; Ecology -- Periodicals; Evolution -- Periodicals; 577.05
• DOI: 10.1002/ece3.8662
• Languages: English
• ISSNs: 2045-7758

Abstract

Abstract: Throughout Africa, lions are thought to have experienced dramatic population decline and range contraction. The greatest declines are likely occurring in human‐dominated landscapes where reliably estimating lion populations is particularly challenging. By adapting a method that has thus far only been applied to animals that are habituated to vehicles, we estimate lion density in two community areas in Kenya's South Rift, located more than 100 km from the nearest protected area (PA). More specifically, we conducted an 89‐day survey using unstructured spatial sampling coupled with playbacks, a commonly used field technique, and estimated lion density using spatial capture‐recapture (SCR) models. Our estimated density of 5.9 lions over the age of 1 year per 100 km 2 compares favorably with many PAs and suggests that this is a key lion population that could be crucial for connectivity across the wider landscape. We discuss the possible mechanisms supporting this density and demonstrate how rigorous field methods combined with robust analyses can produce reliable population estimates within human‐dominated landscapes. Abstract : African lions are thought to be declining rapidly, and particularly in human‐dominated landscapes, where they are most difficult to reliably monitor. We repurposed a traditional field technique, playbacks, and demonstrate how to incorporate the resulting data into a SCR framework to provide robust density estimates.