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Low-trophic level species account for more than 30% of global fisheries production and contribute substantially to global food security. We used a range of ecosystem models to explore the effects of fishing low-trophic level species on marine ecosystems, including marine mammals and seabirds, and on other commercially important species. In five well-studied ecosystems, we found that fishing these species at conventional maximum sustainable yield (MSY) levels can have large impacts on other parts of the ecosystem, particularly when they constitute a high proportion of the biomass in the ecosystem or are highly connected in the food web. Halving exploitation rates would result in much lower impacts on marine ecosystems while still achieving 80% of MSY.

There is broad consensus that the main problem facing fisheries globally is too many boats chasing too few fish. Unfortunately it is also possible to argue that there are too many proposed solutions and not enough practical answers to improving fisheries management. There is a deepening divide between those who propose alternative regulatory controls on fishers, including establishing large areas permanently closed to fishing, and those who argue for better alignment of incentives combined with broad participation of resource users in fishery management decisions (in simple terms, between top down and bottom up systems of governance). However despite the choice of policy instruments used, a consistent outcome is that resource users behave in a manner that is often unintended by the designers of the management system. Hence whilst uncertainty is broadly recognized as a pervasive feature of fisheries management, to date most of the attention has focussed on only part of that uncertainty – scientific uncertainty about the status of exploited resources. The effect of uncertainty generated on the human side of fisheries science and management has received much less attention. However, the uncertainty generated by unexpected resource user behaviour is critical as it has unplanned consequences and leads to unintended management outcomes. Using empirical evidence of unexpected resource user behaviour and reviewing current responses to unexpected management outcomes, we identify different approaches that both improve prediction of human behaviour in fisheries systems and identify management measures that are more robust to these sources of uncertainty. However, unless the micro scale drivers of human behaviour that contribute to macro scale implementation uncertainty are communicated effectively to managers and considered more regularly and in greater depth, unanticipated responses to management actions will continue to undermine management systems and threaten the sustainability of fisheries.

Concern about the impact of fishing on ecosystems and fisheries production is increasing (1, 2). Strategies to reduce these impacts while addressing the growing need for food security (3) include increasing selectivity (1, 2): capturing species, sexes, and sizes in proportions that differ from their occurrence in the ecosystem. Increasing evidence suggests that more selective fishing neither maximizes production nor minimizes impacts (4-7). Balanced harvesting would more effectively mitigate adverse ecological effects of fishing while supporting sustainable fisheries. This strategy, which challenges present management paradigms, distributes a moderate mortality from fishing across the widest possible range of species, stocks, and sizes in an ecosystem, in proportion to their natural productivity (8), so that the relative size and species composition is maintained.

Introduction 172A brief overview of Atlantis 172Biophysical 173Industry and socioeconomic 173Monitoring and assessment 174 Applications to date 174Lessons learned about EBM in practice 174 EBM in practice 174Monitoring in support of EBM 180Lessons learned about using models to inform EBM 181 Abstract Models are key tools for integrating a wide range of system information in a common framework. Attempts to model exploited marine ecosystems can increase understanding of system dynamics; identify major processes, drivers and responses; highlight major gaps in knowledge; and provide a mechanism to 'road test' management strategies before implementing them in reality. The Atlantis modelling framework has been used in these roles for a decade and is regularly being modified and applied to new questions (e.g. it is being coupled to climate, biophysical and economic models to help consider climate change impacts, monitoring schemes and multiple use management). This study describes some common lessons learned from its implementation, particularly in regard to when these tools are most effective and the likely form of best practices for ecosystem-based management (EBM). Most importantly, it highlighted that no single management lever is sufficient to address the many trade-offs associated with EBM and that the mix of measures needed to successfully implement EBM will differ between systems and will change through time. Although it is doubtful that any single management action will be based solely on Atlantis, this modelling approach continues to provide important insights for managers when making natural resource management decisions.

Ecosystem objectives in fisheries management usually flow from high-level national policies or strategies and international agreements. Consequently they are often broadly stated and hence are difficult to incorporate directly in management plans. Predicting the results of any management action is very uncertain because the dynamics of ecosystems are complex and poorly understood. Methods to design and evaluate operational management strategies have advanced considerably in the past decade. These management-strategy-evaluation (MSE) methods rely on simulation testing of the whole management process using performance measures derived from operational objectives. The MSE approach involves selecting (operational) management objectives, specifying performance measures, specifying alternative management strategies, and evaluating these using simulation. The MSE framework emphasizes the identification and modelling of uncertainties, and propagates these through to their effects on the performance measures. The framework is outlined and illustrated by three ecosystem-related applications: management of benthic habitats and broad fish community composition; by-catch of species of high conservation value; and foodchain interactions and dependencies. Challenges to be overcome before broader ecosystem-related objectives can be fully handled are discussed briefly.

2005. Which ecological indicators can robustly detect effects of fishing? e ICES Journal of Marine Science, 62: 540-551.Many ecological indicators have been proposed to detect and describe the effects of fishing on marine ecosystems, but few have been evaluated formally. Here, simulation models of two marine systems off southeastern Australia (a large marine embayment, and an EEZscale regional marine ecosystem) are used to evaluate the performance of a suite of ecological indicators. The indicators cover species, assemblages, habitats, and ecosystems, including quantities derived from models such as Ecopath. The simulation models, based on the Atlantis framework, incorporate the effects of fishing from several fishing gears, and also the confounding impacts of other broad-scale pressures on the ecosystems (e.g. increased nutrient loads). These models are used to provide fishery-dependent and fisheryindependent pseudo-data from which the indicators are calculated. Indicator performance is quantified by the ability to detect and/or predict trends in key variables of interest (''attributes''), the true values of which are known from the simulation models. The performance of each indicator is evaluated across a range of ecological and fishing scenarios. Results suggest that indicators at the community level of organization are the most reliable, and that it is necessary to use a variety of indicators simultaneously to detect the full range of impacts from fishing. Several key functional groups provide a good characterization of ecosystem state, or indicate the cause of broader ecosystem changes in most instances.

Stakeholders increasingly expect ecosystem assessments as part of advice on fisheries management. Quantitative models to support fisheries decision‐making may be either strategic (‘big picture’, direction‐setting and contextual) or tactical (focused on management actions on short timescales), with some strategic models informing the development of tactical models. We describe and review ‘Models of Intermediate Complexity for Ecosystem assessments’ (MICE) that have a tactical focus, including use as ecosystem assessment tools. MICE are context‐ and question‐driven and limit complexity by restricting the focus to those components of the ecosystem needed to address the main effects of the management question under consideration. Stakeholder participation and dialogue is an integral part of this process. MICE estimate parameters through fitting to data, use statistical diagnostic tools to evaluate model performance and account for a broad range of uncertainties. These models therefore address many of the impediments to greater use of ecosystem models in strategic and particularly tactical decision‐making for marine resource management and conservation. MICE are capable of producing outputs that could be used for tactical decision‐making, but our summary of existing models suggests this has not occurred in any meaningful way to date. We use a model of the pelagic ecosystem in the Coral Sea and a linked catchment and ocean model of the Gulf of Carpentaria, Australia, to illustrate how MICE can be constructed. We summarize the major advantages of the approach, indicate opportunities for the development of further applications and identify the major challenges to broad adoption of the approach.