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Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management

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  • Matteo Convertino
  • L James Valverde Jr

Abstract

Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of threatened and endangered species. The PDA approach demonstrates the advantages of integrated, top-down management, versus bottom-up management approaches.

Suggested Citation

  • Matteo Convertino & L James Valverde Jr, 2013. "Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-14, June.
    • Handle: RePEc:plo:pone00:0065056
    DOI: 10.1371/journal.pone.0065056
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    References listed on IDEAS

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    1. Chu-Agor, M.L. & Muñoz-Carpena, R. & Kiker, G.A. & Aiello-Lammens, M.E. & Akçakaya, H.R. & Convertino, M. & Linkov, I., 2012. "Simulating the fate of Florida Snowy Plovers with sea-level rise: Exploring research and management priorities with a global uncertainty and sensitivity analysis perspective," Ecological Modelling, Elsevier, vol. 224(1), pages 33-47.
    2. Mark C. Andersen & Bruce Thompson & Kenneth Boykin, 2004. "Spatial Risk Assessment Across Large Landscapes with Varied Land Use: Lessons from a Conservation Assessment of Military Lands," Risk Analysis, John Wiley & Sons, vol. 24(5), pages 1231-1242, October.
    3. Igor Linkov & Susan Cormier & Joshua Gold & F. Kyle Satterstrom & Todd Bridges, 2012. "Using Our Brains to Develop Better Policy," Risk Analysis, John Wiley & Sons, vol. 32(3), pages 374-380, March.
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    Cited by:

    1. Jorge Salas & Víctor Yepes, 2020. "Enhancing Sustainability and Resilience through Multi-Level Infrastructure Planning," IJERPH, MDPI, vol. 17(3), pages 1-22, February.
    2. Jun Zhao & Bo Shen, 2019. "The Strategies for Improving Energy Efficiency of Power System with Increasing Share of Wind Power in China," Energies, MDPI, vol. 12(12), pages 1-22, June.
    3. Kleczkowski, Adam & Ellis, Ciaran & Hanley, Nick & Goulson, David, 2017. "Pesticides and bees: Ecological-economic modelling of bee populations on farmland," Ecological Modelling, Elsevier, vol. 360(C), pages 53-62.
    4. Valentina Ferretti & Gilberto Montibeller, 2019. "An Integrated Framework for Environmental Multi‐Impact Spatial Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 257-273, January.
    5. Wang, Q. & Poh, K.L., 2014. "A survey of integrated decision analysis in energy and environmental modeling," Energy, Elsevier, vol. 77(C), pages 691-702.
    6. Chunshan Zhou & Shijie Li & Shaojian Wang, 2018. "Examining the Impacts of Urban Form on Air Pollution in Developing Countries: A Case Study of China’s Megacities," IJERPH, MDPI, vol. 15(8), pages 1-18, July.
    7. Contreras-Reyes, Javier E. & López Quintero, Freddy O. & Wiff, Rodrigo, 2018. "Bayesian modeling of individual growth variability using back-calculation: Application to pink cusk-eel (Genypterus blacodes) off Chile," Ecological Modelling, Elsevier, vol. 385(C), pages 145-153.
    8. Marek Vach & Pavla Vachová, 2016. "Stochastic Identification of Stability of Competitive Interactions in Ecosystems," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-12, May.
    9. Tobias Fasth & Samuel Bohman & Aron Larsson & Love Ekenberg & Mats Danielson, 2020. "Portfolio Decision Analysis for Evaluating Stakeholder Conflicts in Land Use Planning," Group Decision and Negotiation, Springer, vol. 29(2), pages 321-343, April.
    10. Convertino, Matteo & Annis, Antonio & Nardi, Fernando, 2019. "Information-theoretic Portfolio Decision Model for Optimal Flood Management," Earth Arxiv k5aut, Center for Open Science.

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