To implement ecosystem-based fisheries management (EBFM), there is a need to comprehensively examine fundamental components of fisheries ecosystems and ascertain the characteristics and strategies facilitating this more systematic approach. Coupled natural and human factors, inherent biological productivities, and systematic governance measures all influence living marine resource (LMR) and socioeconomic status within a given socio-ecological system (SES). Determining the relative prominence of these factors remains a challenge. Examining these facets to determine how much EBFM and wise LMR management occurs is timely and warranted given the many issues facing marine fisheries ecosystems. Here we characterize major United States (U.S.) marine Electronic supplementary material The online version of this article (
The increasing need to account for the many factors that influence fish population dynamics, particularly those external to the population, has led to repeated calls for an ecosystem approach to fisheries management (EAFM). Yet systematically and clearly addressing these factors, and hence implementing EAFM, has suffered from a lack of clear operational guidance. Here, we propose 13 main factors (shift in location, migration route or timing, overfishing (three types), decrease in physiology, increase in predation, increase in competition, decrease in prey availability, increase in disease or parasites and a decline in habitat quality or habitat quantity) that can negatively influence fish populations via mechanisms readily observable in ~20 population features. Using these features as part of a diagnostic framework, we develop flow charts that link probable mechanism(s) underlying population change to the most judicious management actions. We then apply the framework for example case studies that have well‐known and documented population dynamics. To our knowledge, this is the first attempt to provide a clearly defined matrix of all the probable responses to the most common factors influencing fish populations, and to examine possible diagnostics simultaneously, comparatively and relatively in an attempt to elucidate the most probable mechanisms responsible. The framework we propose aims to operationalize EAFM, thereby not only better diagnosing factors influencing fish populations, but also suggesting the most appropriate management interventions, and ultimately leading to improved fisheries. We assert the framework proposed should result in both better use of limited analytical and observational resources and more tailored and effective management actions.
The Ecosystem Approach to Management (EAM) has emerged over the past decades, largely to promote biodiversity conservation, and more recently sectoral tradeoffs in the management of marine ecosystems. To ascertain the state of practice of EAM operationalization, a workshop was held, which included a pre-workshop online survey. The survey gauged international participants’ perspectives regarding capacity, knowledge, and application of EAM. When asked about the subject, most survey respondents had a general understanding of EAM, and provided a clear definition. Major perceived challenges to EAM objectives by those surveyed included limited knowledge, conflicting interests, insufficient communication, and limited organizational legal frameworks or governance structures. Of those directly involved in an ecosystem approach, the majority responded that processes were in place or developed for application of integrated knowledge toward assessing key issues within their respective sectors (i.e. fisheries, conservation, energy), and that capacity was generally high. Our results show that most respondents, irrespective of sector or geography, see value in considering an integrated, broader ecosystem approach as they manage their sector. Although many participants were from the North Atlantic region, our results suggest that much of the international community is converging toward continued understanding of broad-scale, integrated approaches to marine resource management.
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