Search for: All records

Abstract Estimating spatiotemporal patterns of population density is a primary objective of wildlife monitoring programs. However, estimating density is challenging for species that are elusive and/or occur in habitats with limited visibility. In such situations, indirect measures (e.g., nests, dung) can serve as proxies for counts of individuals. Scientists have developed approaches to estimate population density using these “indirect count” data, although current methods do not adequately account for variation in sign production and spatial patterns of animal density. In this study, we describe a modified hierarchical distance sampling model that maximizes the information content of indirect count data using Bayesian inference. We apply our model to assess the status of chimpanzee and elephant populations using counts of nests and dung, respectively, which were collected along transects in 2007 and 2021 in western Uganda. Compared with conventional methods, our modeling framework produced more precise estimates of covariate effects on expected animal density by accounting for both long‐term and recent variations in animal abundance and enabled the estimation of the number of days that animal signs remained visible. We estimated a 0.98 probability that chimpanzee density in the region had declined by at least 10% and a 0.99 probability that elephant density had increased by 50% from 2007 to 2021. We recommend applying our modified hierarchical distance sampling model in the analysis of indirect count data to account for spatial variation in animal density, assess population change between survey periods, estimate the decay rate of animal signs, and obtain more precise density estimates than achievable with traditional methods. 

Niche theory predicts that ecologically similar species can coexist through multidimensional niche partitioning. However, owing to the challenges of accounting for both abiotic and biotic processes in ecological niche modelling, the underlying mechanisms that facilitate coexistence of competing species are poorly understood. In this study, we evaluated potential mechanisms underlying the coexistence of ecologically similar bird species in a biodiversity-rich transboundary montane forest in east-central Africa by computing niche overlap indices along an environmental elevation gradient, diet, forest strata, activity patterns and within-habitat segregation across horizontal space. We found strong support for abiotic environmental habitat niche partitioning, with 55% of species pairs having separate elevation niches. For the remaining species pairs that exhibited similar elevation niches, we found that within-habitat segregation across horizontal space and to a lesser extent vertical forest strata provided the most likely mechanisms of species coexistence. Coexistence of ecologically similar species within a highly diverse montane forest was determined primarily by abiotic factors (e.g. environmental elevation gradient) that characterize the Grinnellian niche and secondarily by biotic factors (e.g. vertical and horizontal segregation within habitats) that describe the Eltonian niche. Thus, partitioning across multiple levels of spatial organization is a key mechanism of coexistence in diverse communities.