Improving population analysis using indirect count data: A case study of chimpanzees and elephants

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, that were collected along transects in 2007 and 2021 in western Uganda. Compared to conventional methods, our modeling framework produced more pr..., , , # Data from: Improving population analysis using indirect count data: a case study of chimpanzees and elephants

[https://doi.org/10.5061/dryad.4j0zpc8nz](https://doi.org/10.5061/dryad.4j0zpc8nz)

## Description of the data and file structure

title: \"Improving population analysis using indirect count data: a case study of chimpanzees and elephants\"

\# General description

This dataset (five folders) contains indirect count data for chimpanzees (i.e, nests) and elephants (i.e., dung) for the 2007 and 2021 survey periods, covariates, and model outputs. The datasets were used to estimate the population density of chimpanzees and elephants, and their trend in Maramagambo and Kalinzu Forest Reserves located in western Uganda (east Africa) across two survey periods (i.e., 2007 and 2021).

All the datasets are in .csv format and .Rdata format (i.e., output from R programing software).

\# Methods

\* Data collection/generation: see manuscript and associated code for details

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