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Management Strategy Evaluation Applied to Coral Reef Ecosystems in Support of Ecosystem-Based Management



Details

  • Journal Title:
    PLOS ONE
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    Ecosystem modelling is increasingly used to explore ecosystem-level effects of changing environmental conditions and management actions. For coral reefs there has been increasing interest in recent decades in the use of ecosystem models for evaluating the effects of fishing and the efficacy of marine protected areas. However, ecosystem models that integrate physical forcings, biogeochemical and ecological dynamics, and human induced perturbations are still underdeveloped. We applied an ecosystem model (Atlantis) to the coral reef ecosystem of Guam using a suite of management scenarios prioritized in consultation with local resource managers to review the effects of each scenario on performance measures related to the ecosystem, the reef-fish fishery (e.g., fish landings) and coral habitat. Comparing tradeoffs across the selected scenarios showed that each scenario performed best for at least one of the selected performance indicators. The integrated 'full regulation' scenario outperformed other scenarios with four out of the six performance metrics at the cost of reef-fish landings. This model application quantifies the socio-ecological costs and benefits of alternative management scenarios. When the effects of climate change were taken into account, several scenarios performed equally well, but none prevented a collapse in coral biomass over the next few decades assuming a business-as-usual greenhouse gas emissions scenario.
  • Source:
    PLOS ONE
  • DOI:
  • Pubmed Central ID:
    PMC4811577
  • Document Type:
  • Place as Subject:
  • Rights Information:
    CC BY
  • Compliance:
    PMC
  • Download URL:
  • File Type:
    Filetype[PDF - 5.88 MB]
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:bfe91726660cab62aae7d56e06a5b20b144d05c53cb84b901d6004bf8303c328ee6725fac907069e0c93cfa4e916a8d8ed0e9257d93538bfcdad75e45ed12420
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