Current and future use of indicators for ecosystem based fisheries management

Abstract

Implementing ecosystem based fisheries management (EBFM) will require a suite of ecological indices to track the state of an ecosystem, in addition to monitoring species-abundance for both economically important species, as well as species that are not targeted for harvest. However, EBFM implementation requires an examination of current methods and applications of ecological indices that are being used. This paper identifies four key uses for ecosystem indices in the context of EBFM and discusses the implications of each: (1) motivation for socio-political action, (2) information for individual users to modify their behavior, (3) implementation of decision rules for management evaluation, and (4) discovery of ecosystem functions to advance scientific knowledge. In a fisheries management context, ecological indicators will be linked to decision rules based on the definitions of both "ecosystem overfishing" and the current single-species definitions of overfishing. Two components of common ecological indicators are species weightings (i.e. catch or abundance data by species) and the species-specific ecological attributes (e.g. mortality rates, body size, trophic level). We discuss statistical issues that arise from estimating the parameters in ecological index calculations from both fishery-dependent and independent data and the potential biases introduced by using catch-per-unit-effort (CPUE) data, catch data, and abundance estimates. Given the range of biases that arise, often the best estimates of species weightings (abundances) are those derived from fish stock assessments. This implies that progress in EBFM may be best served by increasing the number of species for which single-species assessments are done and to expand the list of species to include species which may not be economically important. The policy framework exists to carry out EBFM; however, future works needs to focus on empirical management strategy simulations, as well as theoretical works to identify management criteria based on those indicators. © 2009 Elsevier Ltd. All rights reserved.