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Estimating prey abundance and distribution from camera trap data using binomial mixture models

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Abstract

Measures of absolute animal abundance may be estimated by capture-recapture, removal, or distance sampling methods. We investigate the usage of binomial mixture models to estimate local group abundance of major prey species that is frequently used as a surrogate for prey abundance to study predator or prey-mediated ecological interactions such as predator-prey relationships. We evaluate mixture models using data from a camera-trapping survey intended for a tiger Panthera tigris census in Chitwan National Park, Nepal, where the entire park was surveyed in 361 4-km2 quadrats. We chose four prey species (chital Axis axis, sambar Rusa unicolor, muntjac Muntiacus muntjac, and wild boar Sus scrofa) that collectively account for > 75% of prey biomass consumed by tigers. Abundance of prey group was modeled as a random variable with a Poisson or a negative binomial distribution, with the mean abundance affected by distance from water sources, elevation, and normalized difference vegetation index (NDVI). Except for wild boar, the top models for all other species included the hypothesized covariates while the null model was the most parsimonious model for the wild boar. The most parsimonious chital model included effects of distance from water sources (−) and elevation (−). The sambar model supported all three covariates: distance from water sources (−), elevation (+), and NDVI (+). Only distance from water sources (−) was supported by the most parsimonious muntjac model. Our abundance estimates also conformed to the results obtained from recently conducted labor-intensive distance sampling procedure. We conclude that camera-trapping survey data can be effectively utilized adopting the binomial mixture model framework to understand animal abundance-habitat relationships and estimate abundance of animal that are not identifiable individually.

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Acknowledgements

We thank the Department of National Parks and Wildlife Conservation of the Government of Nepal for permitting our involvement in the field surveys and research. The World Wildlife Fund (WWF) Nepal Program and the National Trust for Nature Conservation provided necessary field support. Megh Bahadur Pandey, Dr. Maheshwor Dhakal, and Dr. Shant Raj Jnawali were very helpful in enabling HK to garner permission for field work.We thank three anonymous reviewers for their constructive comments to help us improve the manuscript.

Funding

HK was supported by WWF’s Kathryn Fuller doctoral fellowship, a National Geographic Society Waitt grant, and by the graduate school of the University of Missouri during this research.

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Authors and Affiliations

  1. School of Natural Resources, University of Missouri, Columbia, MO, 65211, USA

    Hemanta Kafley & Matthew E. Gompper

  2. Nepal Nature Foundation, Koteshwor, Kathmandu, Nepal

    Hemanta Kafley

  3. Wildlife, Sustainability, and Ecosystem Sciences, Tarleton State University, Stephenville, TX, 76402, USA

    Hemanta Kafley

  4. National Trust for Nature Conservation, Biodiversity Conservation Center, Chitwan, Nepal

    Babu R. Lamichhane

  5. Department of National Parks and Wildlife Conservation, BabarMahal, Kathmandu, Nepal

    Rupak Maharjan & Bishnu Thapaliya

  6. School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, 48109, USA

    Nishan Bhattarai

  7. World Wildlife Fund Nepal Program, Kathmandu, Nepal

    Madhav Khadka

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  1. Hemanta Kafley
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  2. Babu R. Lamichhane
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Kafley, H., Lamichhane, B.R., Maharjan, R. et al. Estimating prey abundance and distribution from camera trap data using binomial mixture models. Eur J Wildl Res 65, 77 (2019). https://doi.org/10.1007/s10344-019-1308-0

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