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Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). While a number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently is fisheries-induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life-history traits, behaviour, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause FIE, with effects accumulating over time. Consequently, FIE may alter the utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons. An important reason this is not happening is the lack of an appropriate assessment framework. We therefore describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary consequences of fishing and evaluating the predicted evolutionary outcomes of alternative management options. EvoIA can contribute to EAF by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries.

Heino, M., Baulier, L., Boukal, D. S., Ernande, B., Johnston, F. D., Mollet, F. M., Pardoe, H., Therkildsen, N. O., Uusi-Heikkilä, S., Vainikka, A., Arlinghaus, R., Dankel, D. J., Dunlop, E. S., Eikeset, A. M., Enberg, K., Engelhard G. H., Jørgensen, C., Laugen, A. T., Matsumura, S., Nusslé, S., Urbach, D., Whitlock, R., Rijnsdorp, A. D., and Dieckmann, U. 2013. Can fisheries-induced evolution shift reference points for fisheries management? – ICES Journal of Marine Science, 70: 707–721. Biological reference points are important tools for fisheries management. Reference points are not static, but may change when a population's environment or the population itself changes. Fisheries-induced evolution is one mechanism that can alter population characteristics, leading to “shifting” reference points by modifying the underlying biological processes or by changing the perception of a fishery system. The former causes changes in “true” reference points, whereas the latter is caused by changes in the yardsticks used to quantify a system's status. Unaccounted shifts of either kind imply that reference points gradually lose their intended meaning. This can lead to increased precaution, which is safe, but potentially costly. Shifts can also occur in more perilous directions, such that actual risks are greater than anticipated. Our qualitative analysis suggests that all commonly used reference points are susceptible to shifting through fisheries-induced evolution, including the limit and “precautionary” reference points for spawning-stock biomass, Blim and Bpa, and the target reference point for fishing mortality, F0.1. Our findings call for increased awareness of fisheries-induced changes and highlight the value of always basing reference points on adequately updated information, to capture all changes in the biological processes that drive fish population dynamics.

14Trait evolution over time periods spanning generations, not millennia, is increasingly 15 observed to be above the natural baseline in populations experiencing human-induced 16 perturbations. We investigated the relative speed of trait change by comparing rates of 17 evolution in haldanes and darwins for primarily size at maturation as measured by 18 probabilistic maturation reaction norm midpoints for fish stocks from the Pacific, North 19 Atlantic, Barents Sea, Eastern Baltic, and the North Sea. Rates in haldanes for 23 stocks 20 ranged from -2.2-0.9 and from 0.5-153 in kdarwins for 26 stocks. The highest rates of 21 evolution corresponded to the most heavily exploited stocks; rates slowed after moratoria 22 were introduced. The estimated rates in fish life-history characteristics were comparable to 23 other examples of human-induced evolution, and faster than naturally-induced rates. Stocks 24 with high growth showed slower evolutionary change, even under high mortality, suggesting 25 that compensatory somatic growth can slow the rate of trait evolution. Regardless of whether 26 trait changes are due to exploitation or environmental factors, the costs of ignoring trait 27 evolution are high. As management strategies should be based upon precautionary principles, 28 the effect of changing traits must be integrated into the fisheries assessment process. 29 30