Katja Enberg

Implications of fisheries-induced evolution for stock rebuilding and recovery

Worldwide depletion of fish stocks has led fisheries managers to become increasingly concerned about rebuilding and recovery planning. To succeed, factors affecting recovery dynamics need to be understood, including the role of fisheries‐induced evolution. Here we investigate a stock’s response to fishing followed by a harvest moratorium by analyzing an individual‐based evolutionary model parameterized for Atlantic cod Gadus morhua from its northern range, representative of long‐lived, late‐maturing species. The model allows evolution of life‐history processes including maturation, reproduction, and growth. It also incorporates environmental variability, phenotypic plasticity, and density‐dependent feedbacks. Fisheries‐induced evolution affects recovery in several ways. The first decades of recovery were dominated by demographic and density‐dependent processes. Biomass rebuilding was only lightly influenced by fisheries‐induced evolution, whereas other stock characteristics such as maturation age, spawning stock biomass, and recruitment were substantially affected, recovering to new demographic equilibria below their preharvest levels. This is because genetic traits took thousands of years to evolve back to preharvest levels, indicating that natural selection driving recovery of these traits is weaker than fisheries‐induced selection was. Our results strengthen the case for proactive management of fisheries‐induced evolution, as the restoration of genetic traits altered by fishing is slow and may even be impractical.

Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management

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.

Variation in aggressive behaviour and growth rate between populations and migratory forms in the brown trout, Salmo trutta

Aggressiveness of juvenile salmonid populations has been suggested to correlate positively with the time the fish spend in the stream. Consequently, resident populations are expected to be more aggressive than migratory populations. Aggressiveness and growth rate have been found to correlate positively at the individual level, but no studies have compared populations. We studied variation in aggressiveness and growth in 10 Finnish brown trout populations differing in their migratory behaviour (sea-run, lake-run and resident). Contrary to expectations, we found the sea-run populations to be more aggressive than the lake-run and resident populations. As all the study fish were reared under similar conditions, it is likely that the differences in aggression have a genetic basis. We also found a positive correlation between aggression and growth rate among the populations. This result supports earlier findings of a positive connection between aggressiveness and growth rate, but is, to our knowledge, the first time this phenomenon has been observed at the population level.

Toward Darwinian fisheries management

Table of contents

Do dominants have higher heterozygosity? Social status and genetic variation in brown trout, Salmo trutta

A key question of evolutionary importance is what factors influence who becomes dominant. Individual genetic variation has been found to be associated with several fitness traits, including behaviour. Could it also be a factor influencing social dominance? We investigated the association between social status and the amount of intra-individual genetic variation in juvenile brown trout (Salmo trutta). Genetic variation was estimated using 12 microsatellite loci. Dominant individuals had higher mean heterozygosity than subordinates in populations with the longest hatchery background. Heterozygosity–heterozygosity correlations did not find any evidence of inbreeding; however, single-locus analysis revealed four loci that each individually differed significantly between dominant and subordinate fish, thus giving more support to local than general effect as the mechanism behind the observed association between genetic diversity and a fitness-associated trait. We did not find any significant relation between mean d2 and social status, or internal relatedness and social status. Our results suggest that individual genetic variation can influence dominance relations, but manifestation of this phenomenon may depend on the genetic background of the population.

Evolution of growth in Gulf of St Lawrence cod

Fishing is often size selective such that the likelihood of capture increases with body size. It has therefore been postulated that fishing could favour evolution of slower growth because smaller size would reduce exposure to fishing gear (e.g. [Ricker 1981][1]). A recent study by Swain et al . ([

Life-history implications of the allometric scaling of growth.

Several phenomenological descriptions, such as the von Bertalanffy growth model, have been widely used to describe size-at-age and individual growth across a diverse range of organisms. However, for modelling life histories, as opposed to just growth, biologically and mechanistically meaningful growth models, based on allocation decisions, have become increasingly important. This is because fitness is determined by survival and reproduction, which are not addressed directly in phenomenological growth models. To elucidate these considerations, we take as a starting point the biphasic growth model by Quince et al. (2008a, J. Theor. Biol. 254:197) which has the advantage that the underlying allometric scaling of net energy intake can be freely chosen. First, we reformulate this model such that individual size is given in meaningful units of length and weight, facilitating the model׳s interpretation and application. Second, we show that even though different allometric scaling relationships can produce practically identical growth trajectories, the accompanying reproductive investments are highly dependent on the chosen allometric exponent. Third, we demonstrate how this dependence has dramatic consequences for evolutionary predictions, in particular with regard to the age and size at maturation. These findings have considerable practical relevance, because empirically observed allometric exponents are often uncertain and systematically differ from those assumed in current standard growth models.

Harvesting Strategies in a Fish Stock Dominated by Low-frequency Variability: The Norwegian Spring-spawning Herring (Clupea harengus)

Heavy positively autocorrelated natural fluctuations in a fisheries stock level are problematic for fisheries management, and collapses in the stock dynamics are difficult to avoid. In this paper, we compare three different harvesting strategies (proportional harvesting, threshold harvesting, and proportional threshold harvesting) in an autocorrelated and heavily fluctuating fishery — the Norwegian spring-spawning herring (Clupea harengus) — in terms of risk of quasi-extinction, average annual yield, and coefficient of variation of the yield. Contrary to general expectations, we found that the three strategies produce comparable yields and risks of quasi-extinction. The only observable difference was slightly higher yield and variation in the proportional threshold strategy when the yield is optimized. Thus, it remains an open question as how to characterize the circumstances when it is particularly needful to apply threshold levels in harvest policies.

Letter to the editor: The role of fisheries-induced evolution

In their Policy Forum (“Managing evolving fish stocks,” 23 November 2007, p. [1247][1]), C. Jorgensen et al. propose evolutionary impact assessments (EvoIAs) as a general tool for managing evolving resources. The basis for their proposal is that fisheries-induced evolution (FIE) is the most

Modelling and interpreting fish bioenergetics: a role for behaviour, life‐history traits and survival trade‐offs

Bioenergetics is used as the mechanistic foundation of many models of fishes. As the context of a model gradually extends beyond pure bioenergetics to include behaviour, life-history traits and function and performance of the entire organism, so does the need for complementing bioenergetic measurements with trade-offs, particularly those dealing with survival. Such a broadening of focus revitalized and expanded the domain of behavioural ecology in the 1980s. This review makes the case that a similar change of perspective is required for physiology to contribute to the types of predictions society currently demands, e.g. regarding climate change and other anthropogenic stressors.