Research Article: Gopalaswamy, A. M., Karanth, K. U., Kumar, N. S., & Macdonald, D. W. (2012). Estimating tropical forest ungulate densities from sign surveys using abundance models of occupancy. Animal Conservation, 15(6), 669–679

Blog Author: Kavya Pandey

Key Highlights:

  • This study aimed to develop a practical method for counting and estimating the numbers of Asian forest animals by observing signs such as dung or tracks in the field and addressing traditional sign surveys’ limitations.
  • The research was conducted within the Bhadra Tiger Reserve in Karnataka, India, focusing on five large ungulates (hoofed animals) species, including gaur, sambhar, chital, wild pig, and muntjac.
  • Scientists have created a novel method that simulates how signs made by ungulates are left in nature and how these signs are detected to enhance the accuracy of population estimation of these animals.
  • 183 different values were tested, concerning environmental factors and data collection methods, to assess the efficacy of the model.
  • The results demonstrated that the proposed approach can achieve good estimates of the animal population when the range of daily movement of the animals is considered in the survey design.
  • Scientists recommend using this method when the goal is to find a cost-effective way to count animals, especially when their abundance is low.

In a world where majestic creatures like elephants, deer, and wild pigs face increasing threats, understanding and safeguarding their populations is more critical than ever. This study delves into the challenges faced by large ungulates in tropical forests, exploring a groundbreaking method to monitor and estimate their populations. As these animals play a crucial role in maintaining the balance of our ecosystems, this study highlights the urgency of addressing this ecological concern. It emphasizes the need for practical and efficient tools to ensure their survival in an ever-changing world.

The study focuses on five diverse ungulate species including the sambar, chital, muntjac, gaur, and wild pig in Bhadra Tiger Reserve, Karnataka, India. The decision to rely on easily detectable signs like dung or tracks simplifies the complex world of wildlife monitoring, presenting an efficient protocol for future studies. Researchers used an AOS (Abundance-Occupancy-Spatial) model, which is used to estimate the abundance of animal populations based on the signs they leave behind, such as tracks or dung. By considering these factors, the model provides a way to estimate animal abundance from indirect evidence, making it a valuable tool for monitoring wildlife populations in situations where direct observation or traditional survey methods may not be feasible.

The authors sought a better way to count these elusive animals by relying on their footprints and droppings. The forest was divided into squares, and signs of animals were found in each square. Using a special method, the total number of animals in the entire area was calculated based on these signs. Computer simulations validated the accuracy of this method, showing it to be most effective with a specific number of animal signs in each square. The authors argue that this new counting method using AOS could be a game-changer for protecting and managing these animals and their habitats.

The model designed to estimate animal numbers worked best when maintaining a balance in the number of animal groups in each area, highlighting the significance of ecological harmony. This study addresses the urgent need for dependable ways to calculate the densities of large ungulates in challenging forest settings. The influence of signs left by animals proved crucial, even in situations where detecting them wasn’t perfect. The suggested approach, using sign surveys and the AOS model, is notable for being straightforward and cost-effective. By considering the biology of the animals and their daily movements, the model becomes a potent tool, especially in cases where traditional methods have limitations. The study’s potential to apply to various animal detection techniques makes it a valuable resource, especially for researching high-priority conservation species.

In conclusion, this study opens new avenues for wildlife conservation and offers a beacon of hope for endangered forest dwellers. It also underscores the possible usefulness of this method in various animal monitoring situations and stresses the importance of ongoing research and improvement in this field.

To access the original article, click here

Keywords: detection probability, occupancy modeling, ungulate monitoring, ecological models, hierarchical models, indices of abundance, non-invasive surveys, tiger prey, tracks and dung surveys, animal home range, sign surveys.