LAUSR

ABSTRACT Natural habitats continue to dwindle due to a variety of natural and human-induced stressors. In response, sufficient land must be set aside for conservation to preserve long-term biodiversity. In this paper, we propose a bi-objective optimization model to form spatially cohesive nature reserves by minimizing the distance from habitat patches to the center of their reserve, while simultaneously maximizing the ecological condition of the patches set aside for preservation. Our model can accommodate multiple reserves which, combined with a minimum separation distance requirement, enforces backup coverage to mitigate the possible effects of natural and anthropogenic stressors. The model fully capitalizes on GIS functionalities to extract information on spatial relationships and visualize optimization results. Given the complexity of the separation constraint, we propose a genetic algorithm (GA) and a two-phase heuristic where the GA solves the selection of the reserves, while a solver attempts to optimize the allocation of patches to the selected reserves. The behavior of our model and its sensitivity to the parameters are illustrated on a simulated data set, while its real-world problem-solving capabilities are demonstrated on a case study in New Hampshire. Our model provides an alternative modeling tool for conservation planning, particularly when backup reserves are desired.