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An approach for ensuring minimum protected area size in systematic conservation planning
Authors:Robert J. Smith  Enrico Di Minin  Daniel B. Segan
Affiliation:a Durrell Institute of Conservation and Ecology, University of Kent, Canterbury, Kent CT2 7NR, United Kingdom
b Australian Rivers Institute, Nathan Campus, Nathan, Griffith University, Queensland 4111, Australia
c The Ecology Centre, Centre for Applied Environmental Decision Analysis, The University of Queensland, Brisbane, Queensland 4072, Australia
Abstract:One of the most efficient approaches for designing protected area (PA) networks is to use systematic conservation planning software. A number of software packages are available and all of them include a spatial cost or constraint component in their prioritisation algorithms, which allow the user to determine the level of fragmentation of the final PA system. Many conservation planners want to set minimum PA size thresholds, as small PAs are less viable and more expensive to manage, but this can only be achieved with existing software packages by repeatedly reducing the fragmentation levels of the PA system until every PA meets the threshold. Such an approach is inefficient because it increases the size of every PA, not just the smaller ones. Here we describe MinPatch, a software package developed to overcome this problem by manipulating outputs from the Marxan conservation planning software, so that every PA meets the user-defined size threshold. We then investigate the impacts of this approach with a dataset from the Maputaland Centre of Endemism, and find that using MinPatch to meet the PA thresholds is a much more efficient approach than using Marxan alone. We also show that setting a minimum PA threshold can have important effects on where new PAs are located when compared with Marxan outputs. Based on these results, we recommend that conservation planners use MinPatch whenever they want each PA in a network to meet a minimum size threshold.
Keywords:Protected areas   Marxan   Systematic conservation planning   Viability
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