Research Article: Identifying Thresholds for Ecosystem-Based Management

Date Published: January 26, 2010

Publisher: Public Library of Science

Author(s): Jameal F. Samhouri, Phillip S. Levin, Cameron H. Ainsworth, Steven J. Bograd. http://doi.org/10.1371/journal.pone.0008907

Abstract: 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.

Partial Text: Ecosystem-based management (EBM) has moved to the forefront of efforts to conserve and restore marine species and ocean ecosystems. Implementing EBM requires quantitative methods and criteria that can be used to assess overall ecosystem status, evaluate trade-offs among ecosystem services, and guide management actions [1]. However, the science of EBM is young relative to that of single-species management. Practitioners of single-species management set decision criteria based on well-vetted stock assessment models [2] and population viability analysis methods [3], among other approaches. These decision criteria are measureable quantities, defined in terms of species’ attributes (e.g., abundance, size-structure) or human-induced pressures (e.g., fishing yields or rates), intended to prompt management action. Analogous decision criteria with a broader focus on community- and ecosystem-level attributes and pressures are only in a nascent stage of development [4]–[6].

One of the great challenges of transforming EBM from a philosophical approach to a set of executable management actions is the development of an appropriate toolkit [33], [55], [56]. Deciding which attributes to track in order to capture ecosystem-scale changes in status and contextualizing the values of measured attributes relative to desired ecosystem states and functions is fundamental to EBM [1], [4]. This context can be provided in a number of ways (e.g., by reference to historical baselines [41], [43], [50]), but here we introduce an approach based on utility thresholds.

Source:

http://doi.org/10.1371/journal.pone.0008907

 

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