Wildlife population monitoring depends on accurate counts of individual animals or artefacts of behavior (e.g., nests or dung), but also must account for potential biases in the likelihood to encounter these animals or artefacts. In indirect surveying, which depends largely upon artefacts of behavior, likelihood to encounter indirect signs of a species is derived from both artefact production and decay. Although environmental context as well as behavior contribute to artefact abundance, variability in behaviors relevant to artefact abundance is rarely considered in population estimation. Here we demonstrate how ignoring behavioral variability contributes to overestimation of population size of a highly endangered great ape endemic only to the Democratic Republic of the Congo, the bonobo (Pan paniscus). Variability in decay of signs of bonobo presence (i.e., nests) is well documented and linked to environmental determinants. Conversely, a single metric of sign production (i.e., nest construction) is commonly used to estimate bonobo density, assumed to be representative of bonobo nest behavior across all contexts. We estimated nest construction rates from three bonobo groups within the Kokolopori Bonobo Reserve and found that nest construction rates in bonobos to be highly variable across populations as well as seasonal within populations. Failure to account for behavioral variability in nest construction leads to potentially severe degradation in accuracy of bonobo population estimates of abundance, accounting for a likely overestimation of bonobo numbers by 34%, and in the worst cases as high as 80% overestimation. Using bonobo nesting as an example, we demonstrate that failure to account for inter- and intra-population behavioral variation compromises our ability to monitor population change or reliably compare contributors to population decline or persistence. We argue that variation in sign production is but one of several potential ways that behavioral variability can affect conservation monitoring, should be measured across contexts whenever possible, and must be considered in population estimation confidence intervals. With increasing attention to behavioral variability as a potential tool for conservation, conservationists must also account for the impact that behavioral variability across time, space, individuals, and populations can play upon precision and accuracy of wildlife population estimation.
Comparison of grizzly bear hair-snag and scat sampling along roads to inform wildlife population monitoring