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Sediment toxicity testing and prospective risk assessment of organic chemicals

N. J. Diepens

Published 2015 in Unknown venue

ABSTRACT

While providing an option for development in coastal areas, shrimp farming is usually associated with high environmental cost due to the loss of mangrove forest and high social cost as farmers suffer heavy financial losses due to disease outbreaks. Planning shrimp farming requires to integrate risk as well as social and environmental cost. This thesis, using the Mekong Delta as a case, presents an approach to investigate, with local stakeholders, options to plan a resilient and sustainable shrimp farming sector. First, Olivier Joffre analyzed the different shrimp production systems from economic point of view before analyzing farmer’s strategies and providing insights on drivers that will push or, at the opposite, constraint farmers to choose integrated mangrove shrimp systems. This knowledge was integrated in an Agent Based Model (ABM) that was calibrated using Role Playing Games (RPG). The effect of future scenarios and different policies on the farmers’ decisions was tested using a combination of RPG and ABM. For one coastal district of the Mekong Delta, the results showed that promotion of intensification of shrimp production has a high social cost and decreases the total production in the study area after 10 years. Policies for supporting the spread of integrated mangrove-shrimp systems, such as Payment for Ecosystem Services, or access to an organic value chain, are not strong enough to influence farmers’ decision toward adopting these systems. Without any adaptation to climate change a sharp decrease of the production is expected. The approach brought local farmers’ knowledge to the attention of decision makers.

PUBLICATION RECORD

  • Publication year

    2015

  • Venue

    Unknown venue

  • Publication date

    Unknown publication date

  • Fields of study

    Geography, Economics, Environmental Science

  • Identifiers
    DOI 10.18174/359114
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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