Biodiv Sci ›› 2023, Vol. 31 ›› Issue (3): 22422.  DOI: 10.17520/biods.2022422

• Technology and Methodologies • Previous Articles     Next Articles

A practical guide for estimating the density of unmarked populations using camera traps

Zhenzhen Li1,2,3, Mengtian Du1,2,3, Yuanxin Zhu1,2,3, Dawei Wang1,2,3, Zhilin Li4,*(), Tianming Wang1,2,3,*()   

  1. 1 National Forestry and Grassland Administration Key Laboratory for Conservation Ecology of Northeast Tiger and Leopard National Park, Beijing 100875
    2 Ministry of Education Key Laboratory for Biodiversity Science and Engineering, Beijing 100875
    3 College of Life Sciences, Beijing Normal University, Beijing 100875
    4 Tianjin Key Laboratory of Conservation and Utilization of Animal Diversity, College of Life Sciences, Tianjin Normal University, Tianjin 300387
  • Received:2022-07-22 Accepted:2023-01-04 Online:2023-03-20 Published:2023-03-20
  • Contact: Zhilin Li,Tianming Wang


Background & Aim: Estimating population density is essential for wildlife management and conservation, but it is challenging to achieve. Camera trapping is a pervasive method used in mammal surveys and a cost-effective way to overcome this challenge, for which several methods have been described to estimate population density when individuals are indiscernible (i.e. unmarked populations). However, there are few examples of their use in China. We aim to provide a practical guide for conducting camera trap surveys to estimate the density of mammals applying the random encounter model (REM), random encounter and staying time (REST) model, time in front of the camera (TIFC) model and the camera trap distance sampling (CTDS).

Review Results: First, we provide a brief explanation about the structure and assumptions of the REM, REST, TIFC and CTDS models. Next, we describe essential steps in planning a field survey: determination of objectives, design of camera placement, and the layout of the camera station. We then develop detail-oriented instruction for conducting a field survey and analyzing the obtained visual data. Finally, for each analytical approach, we compiled the data requirements, advantages, and disadvantages of each to help practitioners navigate the landscape of abundance estimation methods.

Perspectives: Although multiple methods exist, no one method is optimal for every camera-trap data scenario. While there has been rapid improvement of camera traps in recent decades throughout China, we encourage researchers to evaluate the life history of the focal taxa, carefully define the area of the sampling frame, and enhance the use of camera trapping for estimating densities of unmarked populations.

Key words: biodiversity monitoring, camera traps, population density, population modeling, encounter-based model, distance sampling, prediction