Dynamic minimum set problem for reserve design: Heuristic solutions for large problems

Conversion of wild habitats to human dominated landscape is a major cause of biodiversity
loss. An approach to mitigate the impact of habitat loss consists of designating reserves
where habitat is preserved and managed. Determining the most valuable areas to preserve
in a landscape is called the reserve design problem. There exists several possible formulations
of the reserve design problem, depending on the objectives and the constraints. In this
article, we considered the dynamic problem of designing a reserve that contains a desired
area of several key habitats. The dynamic case implies that the reserve cannot be designed
in one time step, due to budget constraints, and that habitats can be lost before they are
reserved, due for example to climate change or human development. We proposed two heuristics strategies that can be used to select sites to reserve each year for large reserve
design problem. The first heuristic is a combination of the Marxan and site-ordering algorithms
and the second heuristic is an augmented version of the common naive myopic heuristic.
We evaluated the strategies on several simulated examples and showed that the
augmented greedy heuristic is particularly interesting when some of the habitats to protect
are particularly threatened and/or the compactness of the network is accounted for.