The loss of tiger habitat and the greater dependency of tiger populations on multiple use forests has led to an increase in conflict between tiger and human forest use. Gaining a better understanding of this conflict through a combination of fieldwork and modeling is critical to the survival of tiger populations in these forests. TIGMOD is an individual-based spatially explicit, object-oriented model that simulates key aspects of tiger behavior and its interactions with wild and domestic prey through stochastic processes. It is a dynamic model driven by changes in states of tigers or prey that trigger the behavior and interactions appropriate to these changes. The model permits users to run the simulation based on different scenarios that explore the relationship between prey densities and tiger survivability, as well as those that examine the relationship between villager attitudes towards tiger killing of domestic prey and the likelihood of poisoning a tiger. Model output includes number of tigers born, starved, or poisoned, and number of wild and domestic prey killed. Model simulation results agree well with field observations and data in terms of prey density versus tiger survivability, number of days between two consecutive prey kills, simulated movement of tiger traversal of its home range, and number of cubs born per breeding female tiger. This study shows that tiger populations are sustainable at low density of domestic prey but not sustainable if domestic prey density increases to three or more per square kilometer. Additionally, change in behavior and attitudes of villagers towards tigers, such as increasing guarding of livestock and higher tolerance of domestic prey kills will significantly reduce tiger mortality caused by poisoning. TIGMOD is a useful tool for analyzing the interaction between tigers and humans in multiple use forests. It provides a means of understanding the right balance between forest use by tigers and use by villagers, which can lead to implementation of management strategies that optimize both.
- Dynamic simulation
- Individual-based object-oriented model
- Tiger-human interaction