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Free keywords:
animal survey; comparative evaluation; monitoring; Pan troglodytes verus; spatial-explicit capture-recapture
Abstract:
The extension of distance sampling methods to accommodate observations from camera traps has recently enhanced the potential to remotely monitor multiple species without the need of additional data collection (sign production and decay rates) or individual identification. However, the method requires that the proportion of time is quantifiable when animals can be detected by the cameras. This can be problematic, for instance, when animals spend time above the ground, which is the case for most primates. In this study, we aimed to validate camera trap distance sampling (CTDS) for the semiarboreal western chimpanzee (Pan troglodytes verus) in Taï National Park, Côte d'Ivoire by estimating abundance of a population of known size and comparing estimates to those from other commonly applied methods. We estimated chimpanzee abundance using CTDS and accounted for limited availability for detection (semiarboreal). We evaluated bias and precision of estimates, as well as costs and efforts required to obtain them, and compared them to those from spatially explicit capture-recapture (SECR) and line transect nest surveys. Abundance estimates obtained by CTDS and SECR produced a similar negligible bias, but CTDS yielded a larger coefficient of variation (CV?=?39.70% for CTDS vs. 1%/19% for SECR). Line transects generated the most biased abundance estimates but yielded a better coefficient of variation (27.40?27.85%) than CTDS. Camera trap surveys were twice more costly than line transects because of the initial cost of cameras, while line transects surveys required more than twice as much time in the field. This study demonstrates the potential to obtain unbiased estimates of the abundance of semiarboreal species like chimpanzees by CTDS. HIGHLIGHTS Camera trap distance sampling produced accurate density estimates for semiarboreal chimpanzees. Availability for detection must be accounted for and can be derived from the activity pattern.
