Capturing Ecosystem Services, Stakeholders' Preferences and Trade-Offs in Coastal Aquaculture Decisions: A Bayesian Belief Network Application
被引:47
作者:
Schmitt, Laetitia Helene Marie
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机构:
Univ York, Dept Econ & Related Studies, Ctr Hlth Econ, York YO10 5DD, N Yorkshire, EnglandUniv York, Dept Econ & Related Studies, Ctr Hlth Econ, York YO10 5DD, N Yorkshire, England
Schmitt, Laetitia Helene Marie
[1
]
Brugere, Cecile
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Univ York, Stockholm Environm Inst, York YO10 5DD, N Yorkshire, EnglandUniv York, Dept Econ & Related Studies, Ctr Hlth Econ, York YO10 5DD, N Yorkshire, England
Brugere, Cecile
[2
]
机构:
[1] Univ York, Dept Econ & Related Studies, Ctr Hlth Econ, York YO10 5DD, N Yorkshire, England
[2] Univ York, Stockholm Environm Inst, York YO10 5DD, N Yorkshire, England
Aquaculture activities are embedded in complex social-ecological systems. However, aquaculture development decisions have tended to be driven by revenue generation, failing to account for interactions with the environment and the full value of the benefits derived from services provided by local ecosystems. Trade-offs resulting from changes in ecosystem services provision and associated impacts on livelihoods are also often overlooked. This paper proposes an innovative application of Bayesian belief networks - influence diagrams - as a decision support system for mediating trade-offs arising from the development of shrimp aquaculture in Thailand. Senior experts were consulted (n = 12) and primary farm data on the economics of shrimp farming (n = 20) were collected alongside secondary information on ecosystem services, in order to construct and populate the network. Trade-offs were quantitatively assessed through the generation of a probabilistic impact matrix. This matrix captures nonlinearity and uncertainty and describes the relative performance and impacts of shrimp farming management scenarios on local livelihoods. It also incorporates export revenues and provision and value of ecosystem services such as coastal protection and biodiversity. This research shows that Bayesian belief modeling can support complex decision-making on pathways for sustainable coastal aquaculture development and thus contributes to the debate on the role of aquaculture in social-ecological resilience and economic development.