We review fleet dynamics and fishermen behavior from an economic and sociological basis in developing fisheries, in mature fisheries near full exploitation, and in senescent fisheries that are overexploited and overcapitalized. In all cases, fishing fleets behave rationally within the imposed regulatory structures. Successful, generalist fishermen who take risks often pioneer developing fisheries. At this stage, regulations and subsidies tend to encourage excessive entry and investments, creating the potential for serial depletion. In mature fisheries, regulations often restrict season length, vessel and gear types, fishing areas, and fleet size, causing or exacerbating the race for fish and excessive investment, and are typically unsuccessful except when combined with dedicated access privileges (e.g., territorial rights, individual quotas). In senescent fisheries, vessel buyback programs must account for the fishing power of individuals and their vessels. Subsidies should be avoided as they prolong the transition towards alternative employment. Fisheries managers need to create individual incentives that align fleet dynamics and fishermen behavior with the intended societal goals. These incentives can be created both through management systems like dedicated access privileges and through market forces.

Large, S. I., Fay, G., Friedland, K. D., and Link, J. S. 2013. Defining trends and thresholds in responses of ecological indicators to fishing and environmental pressures. – ICES Journal of Marine Science, 70: 755–767. Both fishing and environmental forces can influence the structure of marine ecosystems. To further understand marine ecosystems and to implement ecosystem-based fisheries management (EBFM), an evaluation of ecosystem indicators is warranted. In this context, it is particularly important to identify thresholds where fishing and environmental pressures significantly influence ecological indicators. We empirically determined numerical values of environmental forces and fishing pressure that significantly altered the response of ecological indicators for the Northeast Shelf Large Marine Ecosystem. Generalized additive models predicted a non-linear relationship for each pressure–response pairing. With this smoother, 95% confidence intervals (CI) for estimated first and second derivatives for each relationship were determined via parametric bootstrap. A significant trend or threshold was noted when the CI for the first or second derivative was greater or less than zero, delineating the level at which pressure variables influence the rate and direction of ecosystem indicator responses. We identify reference levels where environmental forces and fishing pressure result in ecosystem change by collectively examining the responses of multiple ecological indicators. Individual indicators showed unique responses to pressures, however, similar values for the pressures were associated with significant changes for multiple indicators. These reference levels establish a foundation for implementation of EBFM.

a b s t r a c tThe Southern and Eastern Scalefish and Shark Fishery (SESSF) is a complex multi-species fishery, with 34 stock units under quota management, for which a harvest strategy framework was developed in 2005. The framework involves the application of a set of tier-based harvest control rules (HCR) designed to provide a precautionary approach to management. The harvest strategy framework has been applied from 2005 to 2007, resulting in substantial reductions in quotas across the fishery. The experience in implementing the framework, both positive and negative, is described, and general lessons are drawn. Key lessons include the importance of formally testing such strategies using management strategy evaluation, the impact of external management drivers on implementation of the approach, the need to define strategies for setting "bycatch quotas" in multi-species fisheries, and the need for flexibility and pragmatism in the early stages of implementing such an approach.

Need to Assess the Skill of Ecosystem ModelsAccelerated changes to global ecosystems call for holistic and integrated analyses of past, present and future states under various pressures to adequately understand current and projected future system states. Ecosystem models can inform management of human activities in a complex and changing environment, but are these models reliable? Ensuring that models are reliable for addressing management questions requires evaluating their skill in representing real-world processes and dynamics. Skill has been evaluated for just a limited set of some biophysical models. A range of skill assessment methods have been reviewed but skill assessment of full marine ecosystem models has not yet been attempted.Northeast US Atlantis Marine Ecosystem ModelWe assessed the skill of the Northeast U.S. (NEUS) Atlantis marine ecosystem model by comparing 10-year model forecasts with observed data. Model forecast performance was compared to that obtained from a 40-year hindcast. Multiple metrics (average absolute error, root mean squared error, modeling efficiency, and Spearman rank correlation), and a suite of time-series (species biomass, fisheries landings, and ecosystem indicators) were used to adequately measure model skill. Overall, the NEUS model performed above average and thus better than expected for the key species that had been the focus of the model tuning. Model forecast skill was comparable to the hindcast skill, showing that model performance does not degenerate in a 10-year forecast mode, an important characteristic for an end-to-end ecosystem model to be useful for strategic management purposes.Skill Assessment Is Both Possible and AdvisableWe identify best-practice approaches for end-to-end ecosystem model skill assessment that would improve both operational use of other ecosystem models and future model development. We show that it is possible to not only assess the skill of a complicated marine ecosystem model, but that it is necessary do so to instill confidence in model results and encourage their use for strategic management. Our methods are applicable to any type of predictive model, and should be considered for use in fields outside ecology (e.g. economics, climate change, and risk assessment).