A Computational Approach for Designing Tiger Corridors in India

TL;DR

This paper presents a novel computational method combining game theory, graph theory, and automata to design effective tiger corridors in India, aiming to mitigate habitat fragmentation and support tiger conservation.

Contribution

It introduces a new integrated model for designing wildlife corridors using game theory, graph theory, and automata specifically tailored for tiger habitat connectivity.

Findings

Identified key parameters affecting tiger populations.

Constructed a graph model of habitat patches and corridors.

Demonstrated the model's potential for effective corridor design.

Abstract

Wildlife corridors are components of landscapes, which facilitate the movement of organisms and processes between intact habitat areas, and thus provide connectivity between the habitats within the landscapes. Corridors are thus regions within a given landscape that connect fragmented habitat patches within the landscape. The major concern of designing corridors as a conservation strategy is primarily to counter, and to the extent possible, mitigate the effects of habitat fragmentation and loss on the biodiversity of the landscape, as well as support continuance of land use for essential local and global economic activities in the region of reference. In this paper, we use game theory, graph theory, membership functions and chain code algorithm to model and design a set of wildlife corridors with tiger (Panthera tigris tigris) as the focal species. We identify the parameters which would affect the tiger population in a landscape complex and using the presence of these identified parameters construct a graph using the habitat patches supporting tiger presence in the landscape complex as vertices and the possible paths between them as edges. The passage of tigers through the possible paths have been modelled as an Assurance game, with tigers as an individual player. The game is played recursively as the tiger passes through each grid considered for the model. The iteration causes the tiger to choose the most suitable path signifying the emergence of adaptability. As a formal explanation of the game, we model this interaction of tiger with the parameters as deterministic finite automata, whose transition function is obtained by the game payoff.