Using multivariate statistics to explore trade‐offs among spatial planning scenarios

Abstract

SummaryScenario planning can be useful to guide decision‐making under uncertainty. While systematic conservation planning can create protected‐area networks for multiple and complex reserve–design scenarios, planners rarely compare different reserve networks explicitly, or quantify trade‐offs among scenarios.We demonstrate the use of multivariate statistics traditionally applied in community ecology to compare reserves designed under different scenarios, using conservation planning for beaches in South Africa as an example. Twelve reserve–design scenarios were run in Marxan in a hierarchical experimental design with three levels: including/excluding the probability of site destruction; two different cost types; and three different configurations of existing terrestrial and marine reserves.Multivariate statistics proved to be useful tools in the conservation planning context. In our case study, they showed that the trade‐off associated with including the probability of site destruction during coastal reserve design depended on the cost type: if the cost is related to the site‐destruction probability then reserves are significantly larger; if not, then reserves are significantly more costly. In both cases, the configuration of existing reserves lockeda prioriinto the solutions was more important and resulted in significantly larger and more costly reserves.Synthesis and applications. This study demonstrates a novel application of multivariate statistical tools to robustly quantify potential trade‐offs among diverse sets of reserve–design scenarios. These statistics can be applied: to support negotiations with stakeholders and decision‐makers regarding reserve configurations in the face of uncertainty; in reserve–design sensitivity analyses; and in priority setting for future research and data collection to improve conservation plans.