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Identifying Thresholds for Ecosystem-Based Management
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 man...
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2811186/ https://www.ncbi.nlm.nih.gov/pubmed/20126647 http://dx.doi.org/10.1371/journal.pone.0008907 |
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author | Samhouri, Jameal F. Levin, Phillip S. Ainsworth, Cameron H. |
author_facet | Samhouri, Jameal F. Levin, Phillip S. Ainsworth, Cameron H. |
author_sort | Samhouri, Jameal F. |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2811186 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28111862010-02-02 Identifying Thresholds for Ecosystem-Based Management Samhouri, Jameal F. Levin, Phillip S. Ainsworth, Cameron H. PLoS One Research Article 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. Public Library of Science 2010-01-26 /pmc/articles/PMC2811186/ /pubmed/20126647 http://dx.doi.org/10.1371/journal.pone.0008907 Text en This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. |
spellingShingle | Research Article Samhouri, Jameal F. Levin, Phillip S. Ainsworth, Cameron H. Identifying Thresholds for Ecosystem-Based Management |
title | Identifying Thresholds for Ecosystem-Based Management |
title_full | Identifying Thresholds for Ecosystem-Based Management |
title_fullStr | Identifying Thresholds for Ecosystem-Based Management |
title_full_unstemmed | Identifying Thresholds for Ecosystem-Based Management |
title_short | Identifying Thresholds for Ecosystem-Based Management |
title_sort | identifying thresholds for ecosystem-based management |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2811186/ https://www.ncbi.nlm.nih.gov/pubmed/20126647 http://dx.doi.org/10.1371/journal.pone.0008907 |
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