Balanced harvest has been proposed to reduce fishing impact on ecosystems while simultaneously maintaining or even increasing fishery yield. The concept has attracted broad interest, but also received criticisms. In this paper, we examine the theory, modelling studies, empirical evidence, the legal and policy frameworks, and management implications of balanced harvest. The examination reveals unresolved issues and challenges from both scientific and management perspectives. We summarize current knowledge and address common questions relevant to the idea. Major conclusions include: balanced harvest can be expressed in several ways and implemented on multiple levels, and with different approaches e.g. métier based management; it explicitly bridges fisheries and conservation goals in accordance with international legal and policy frameworks; modelling studies and limited empirical evidence reveal that balanced harvest can reduce fishing impact on ecosystem structure and increase the aggregate yield; the S. Zhou (&) CSIRO Oceans and Atmosphere, Rev Fish Biol Fisheries (2019) 29:711-733 https://doi.org/10.1007/s11160-019-09568-w( 0123456789().,-volV) (0123456789().,-volV) extent of balanced harvest is not purely a scientific question, but also a legal and social choice; a transition to balanced harvest may incur short-term economic costs, while in the long-term, economic results will vary across individual fisheries and for society overall; for its application, balanced harvest can be adopted at both strategic and tactical levels and need not be a full implementation, but could aim for a ''partiallybalanced'' harvest. Further objective discussions and research on this subject are needed to move balanced harvest toward supporting a practical ecosystem approach to fisheries.

Abstract. A food web is an ecological network and its topological description consists of the list of nodes, i.e., trophospecies, the list of links, i.e., trophic interactions, and the direction of interactions (who is the prey and who is the predator). Food web topologies are widely used in ecology to describe structural properties of communities or ecosystems. The selection of trophospecies and trophic interactions can be realized in different manners so that many different food webs may be constructed for the same community. In the Barents Sea, many simple food webs have been constructed. We present a comprehensive food web topology for the Barents Sea ecosystem, from plankton to marine mammals. The protocol used to compile the data set includes rules for the selection of taxa and for the selection and documentation of the trophic links. The resulting topology, which includes 244 taxa and 1589 trophic links, can serve as a basis for topological analyses, comparison with other marine ecosystems, or as a basis to build simulation models of the Barents Sea ecosystem. The data set consists of three related tables: (1) the list of taxa, (2) the list of pairwise interactions, and (3) the list of bibliographical references.

Using end-to-end models for ecosystem-based management requires knowledge of the structure, uncertainty and sensitivity of the model. The Norwegian and Barents Seas (NoBa) Atlantis model was implemented for use in ‘what if’ scenarios, combining fisheries management strategies with the influences of climate change and climate variability. Before being used for this purpose, we wanted to evaluate and identify sensitive parameters and whether the species position in the foodweb influenced their sensitivity to parameter perturbation. Perturbing recruitment, mortality, prey consumption and growth by +/- 25% for nine biomass-dominating key species in the Barents Sea, while keeping the physical climate constant, proved the growth rate to be the most sensitive parameter in the model. Their trophic position in the ecosystem (lower trophic level, mid trophic level, top predators) influenced their responses to the perturbations. Top-predators, being generalists, responded mostly to perturbations on their individual life-history parameters. Mid-level species were the most vulnerable to perturbations, not only to their own individual life-history parameters, but also to perturbations on other trophic levels (higher or lower). Perturbations on the lower trophic levels had by far the strongest impact on the system, resulting in biomass changes for nearly all components in the system. Combined perturbations often resulted in non-additive model responses, including both dampened effects and increased impact of combined perturbations. Identifying sensitive parameters and species in end-to-end models will not only provide insights about the structure and functioning of the ecosystem in the model, but also highlight areas where more information and research would be useful—both for model parameterization, but also for constraining or quantifying model uncertainty.

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The purpose of this paper is to investigate the influence of horizontal grid resolution in a physical model on an embedded primary production model. The area for the experiment was along the west coast of Norway, from 60• N to 70• N, an area of high mesoscale activity. The HYbrid Coordinate Ocean Model was coupled with the NORWegian ECOlogical Model system, and run in a nested system, consisting of three model grids with horizontal resolution of 50 km, 16 km and 4.5 km (hereafter: COARSE, MEDIUM and FINE) in the focus area. Two main results were obtained, first, the composition of the phytoplankton functional groups changed with increasing model grid resolution. In FINE, the diatoms produced a larger part (60%) of the total annual primary production than the flagellates, whereas in COARSE and MEDIUM, the primary production from the two phytoplankton groups were equal. This was explained by a higher transport of silicate into the euphotic layer in FINE compared to the other two. Second, the differences in the primary production first became large when the resolution of the model grid reached the Rossby radius of deformation. Whereas the total net primary production in MEDIUM only was 5% larger than in COARSE, the total net primary production in FINE was 20% higher than in COARSE. This was explained by the models ability to resolve mesoscale activity.