Spatial optimization of protected area placement incorporating ecological, social and economical criteria

We describe two approaches for spatial optimization of protected area placement, both based on maximizing an objective function that incorporates ecological, social, and economical criteria. Of these, a seed cell selection procedure works by evaluating potential cells for protection one by one, picking the one that maximizes the objective function, adding seed cells. This continues to full protection of the project area. The other is a Monte Carlo approach, which uses a likelihood sampling procedure based on weighted importance layers of conservation interest to evaluate alternative protected area sizing and placement. This is similar to the objective function of Marxan, a priority-selection decision-support tool based on optimization algorithms using geographic information system data. The two approaches are alternative options in a common spatial optimization module, which uses the time- and spatial-dynamic Ecospace model for the evaluations. The optimizations are implemented as components of the Ecopath with Ecosim approach and software. In a case study, we find that there can be protected area zoning that will accommodate economical and social factors, without causing ecological deterioration. We also find a tradeoff between including cells of special conservation interest, and the economic and social interests. While this does not need to be a general feature, it emphasizes the need to use modeling techniques to evaluate the tradeoff.