Understanding African Wild Dog Movement
In January of 2018 I spent two weeks in South Africa’s uMkhuze Game Reserve as a volunteer with the conservation group WildlifeACT. Many animals in the reserve are equipped with tracking or radio collars and every morning and evening we would use VHF radio telemetry to track wildlife throughout the park, paying special attention to the lions, cheetahs, and wild dogs so as to monitor their health and welfare. In the afternoons we would record camera trap data and compile notes from our previous work to create a database of animal movements and notes.
After my time with the project, I received tracking collar data from individual wild dogs in Somkhanda Game Reserve and used programming language R to examine the movement patterns and known locations of the dogs. Studying the data revealed the distance covered between observations, the turn angle between consecutive points, the elevation of the dog at each observation, and if the animal was using a road as a corridor for travel.
This project is still very much a work in progress, however the ultimate goal is to create a context-sensitive correlated random walk model that simulates the movement of the dogs. Using the known observations and patterns as parameters, the hope is to create a simulated agent that “chooses” a path on a raster based cell-by-cell approach where each cell contains environmental characteristics. If I can get an agent that is influenced by these factors to move in the same way as the recorded movement of the dogs, conclusions about the ways in which the dogs select their path of travel can be made. Understanding how environmental factors correlate to the observed movement patterns of wild dogs strengthens knowledge of their behavior and has a broad range of implications for management strategies.