کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1053645 1485073 2013 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Understanding the sources of uncertainty to reduce the risks of undesirable outcomes in large-scale freshwater ecosystem restoration projects: An example from the Murray–Darling Basin, Australia
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
Understanding the sources of uncertainty to reduce the risks of undesirable outcomes in large-scale freshwater ecosystem restoration projects: An example from the Murray–Darling Basin, Australia
چکیده انگلیسی


• We model uncertainty in achieving ecological outcomes under the Basin Plan.
• We compare a simplistic ecosystem condition proxy and an ecosystem state metric.
• Both metrics report improvements in the ecosystem health of the Coorong.
• Managing to the simplistic metric may not fully account for ecosystem complexity.
• Incorporating risk analysis information could be helpful for decision-making.

There are a growing number of large-scale freshwater ecological restoration projects world-wide. Assessments of the benefits and costs of restoration often exclude an analysis of uncertainty in the modelled outcomes. To address this shortcoming we explicitly model the uncertainties associated with measures of ecosystem health in the estuary of the Murray–Darling Basin, Australia and how those measures may change with the implementation of a Basin-wide Plan to recover water to improve ecosystem health. Specifically, we compare two metrics – one simple and one more complex – to manage end-of-system flow requirements for one ecosystem asset in the Basin, the internationally important Coorong saline wetlands. Our risk assessment confirms that the ecological conditions in the Coorong are likely to improve with implementation of the Basin Plan; however, there are risks of a Type III error (where the correct answer is found for the wrong question) associated with using the simple metric for adaptive management.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Environmental Science & Policy - Volume 33, November 2013, Pages 97–108
نویسندگان
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