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Identifying Thresholds for Ecosystem-Based Management

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  • Jameal F Samhouri
  • Phillip S Levin
  • Cameron H Ainsworth

Abstract

Background: One of the greatest obstacles to moving ecosystem-based management (EBM) from concept to practice is the lack of a systematic approach to defining ecosystem-level decision criteria, or reference points that trigger management action. Methodology/Principal Findings: To assist resource managers and policymakers in developing EBM decision criteria, we introduce a quantitative, transferable method for identifying utility thresholds. A utility threshold is the level of human-induced pressure (e.g., pollution) at which small changes produce substantial improvements toward the EBM goal of protecting an ecosystem's structural (e.g., diversity) and functional (e.g., resilience) attributes. The analytical approach is based on the detection of nonlinearities in relationships between ecosystem attributes and pressures. We illustrate the method with a hypothetical case study of (1) fishing and (2) nearshore habitat pressure using an empirically-validated marine ecosystem model for British Columbia, Canada, and derive numerical threshold values in terms of the density of two empirically-tractable indicator groups, sablefish and jellyfish. We also describe how to incorporate uncertainty into the estimation of utility thresholds and highlight their value in the context of understanding EBM trade-offs. Conclusions/Significance: For any policy scenario, an understanding of utility thresholds provides insight into the amount and type of management intervention required to make significant progress toward improved ecosystem structure and function. The approach outlined in this paper can be applied in the context of single or multiple human-induced pressures, to any marine, freshwater, or terrestrial ecosystem, and should facilitate more effective management.

Suggested Citation

  • Jameal F Samhouri & Phillip S Levin & Cameron H Ainsworth, 2010. "Identifying Thresholds for Ecosystem-Based Management," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-10, January.
  • Handle: RePEc:plo:pone00:0008907
    DOI: 10.1371/journal.pone.0008907
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    References listed on IDEAS

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    1. Marten Scheffer & Steve Carpenter & Jonathan A. Foley & Carl Folke & Brian Walker, 2001. "Catastrophic shifts in ecosystems," Nature, Nature, vol. 413(6856), pages 591-596, October.
    2. Ainsworth, C.H. & Pitcher, T.J. & Heymans, J.J. & Vasconcellos, M., 2008. "Reconstructing historical marine ecosystems using food web models: Northern British Columbia from Pre-European contact to present," Ecological Modelling, Elsevier, vol. 216(3), pages 354-368.
    3. Peter J. Mumby & Alan Hastings & Helen J. Edwards, 2007. "Thresholds and the resilience of Caribbean coral reefs," Nature, Nature, vol. 450(7166), pages 98-101, November.
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    1. Stelzenmüller, Vanessa & Vega Fernández, Tomás & Cronin, Katherine & Röckmann, Christine & Pantazi, Maria & Vanaverbeke, Jan & Stamford, Tammy & Hostens, Kris & Pecceu, Ellen & Degraer, Steven & Buhl-, 2015. "Assessing uncertainty associated with the monitoring and evaluation of spatially managed areas," Marine Policy, Elsevier, vol. 51(C), pages 151-162.
    2. Min Fan & Hideaki Shibata & Li Chen, 2018. "Assessing high impacts of climate change: spatial characteristics and relationships of hydrological ecosystem services in northern Japan (Teshio River watershed)," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(4), pages 525-552, April.
    3. D. Webster, 2013. "International fisheries: assessing the potential for ecosystem management," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 3(2), pages 169-183, June.
    4. Ofir, E. & Gal, G. & Goren, M. & Shapiro, J. & Spanier, E., 2016. "Detecting changes to the functioning of a lake ecosystem following a regime shift based on static food-web models," Ecological Modelling, Elsevier, vol. 320(C), pages 145-157.
    5. Fay, Gavin & Large, Scott I. & Link, Jason S. & Gamble, Robert J., 2013. "Testing systemic fishing responses with ecosystem indicators," Ecological Modelling, Elsevier, vol. 265(C), pages 45-55.

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