Identifying restoration priorities for wetlands based on historical distributions of biodiversity features and restoration suitability
Journal Publication ResearchOnline@JCUAbstract
Wetland restoration is a major objective of environmental management worldwide. We present a frameworkat the regional level that prioritizes historical biodiversity and restoration suitability. The goal of the framework is to maximize biodiversity gains from restoration while minimizing the cost. We used C-Plan, a prioritization tool for systematic conservation planning (SCP), to balance the biodiversity gains withthe costs of restoration, or restoration suitability. We overlaid historical spatial data from 1995 to estimate historical distributions of 91 biodiversity features. These features were used to conduct an irreplaceability analysis to assess the restoration value of historical biodiversity. We then modelled restoration suitability based on environmental data of six criteria. Finally, we applied a complementarity analysis to achieve the quantitative targets of all biodiversity features while minimizing the cost of restoration. We tested this framework in the highly degraded wetlands ofSanjiang Plain, China. By applying our framework to Sanjiang Plain, we successfully identified areas with both high restoration value and high restoration suitability. The area of this cost-effective plan was an extension of 4620 km2, covering 80% of the disappearing wetlands and 4% of the total Sanjiang Plain. Compared to the restoration value-only plan, which had an extension of 4486 km2, the cost-effective plan covered a little more area to achievethe targets forall biodiversity features but with lower implementation costs where the proportion of high restoration suitability increases from 43% to 50%.Our prioritization framework can be used to analyse regional restoration efforts in other regions and ecosystems, and inform planners on how to maximize biodiversity gains while minimizing costs.
Journal
Journal of Environmental Management
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Volume
231
ISBN/ISSN
1095-8630
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Pages Count
10
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Publisher
Elsevier
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EISSN
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DOI
10.1016/j.jenvman.2018.10.057