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

Harris, Linda R., Watts, Matthew E., Nel, Ronel, Schoeman, David S. and Possingham, Hugh P. (2014) Using multivariate statistics to explore trade-offs among spatial planning scenarios. Journal of Applied Ecology, 51 6: 1504-1514. doi:10.1111/1365-2664.12345


Author Harris, Linda R.
Watts, Matthew E.
Nel, Ronel
Schoeman, David S.
Possingham, Hugh P.
Title Using multivariate statistics to explore trade-offs among spatial planning scenarios
Journal name Journal of Applied Ecology   Check publisher's open access policy
ISSN 1365-2664
0021-8901
Publication date 2014-12-01
Year available 2014
Sub-type Article (original research)
DOI 10.1111/1365-2664.12345
Volume 51
Issue 6
Start page 1504
End page 1514
Total pages 11
Place of publication Oxford United Kingdom
Publisher Wiley-Blackwell Publishing
Language eng
Formatted abstract
1. Scenario 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.

2. 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.

3. 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 locked a priori into the solutions was more important and resulted in significantly larger and more costly reserves.

4. 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.
Keyword Complete hierarchical cluster analysis
Marxan
Non-metric multidimensional scaling
Protected areas
Reserve design
Sandy beaches
Scenario planning
Site destruction
Spatial prioritization
Systematic conservation planning
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Biological Sciences Publications
 
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