Roles of density-dependent growth and life history evolution in accounting for fisheries-induced trait changes

• Published in: Proceedings of the National Academy of Sciences
• Main Authors: Eikeset, A.M., Dunlop, E.S., Heino, M., Storvik, Geir, Stenseth, N.C., Dieckmann, U.
• Format: Article in Journal/Newspaper
• Language: English
• Published: National Academy of Sciences 2016
• Subjects: Arctic; Arctic cod; Gadus morhua; Northeast Arctic cod
• Online Access: https://pure.iiasa.ac.at/id/eprint/14117/; https://pure.iiasa.ac.at/id/eprint/14117/1/PNAS-2016-Eikeset-15030-5.pdf; https://doi.org/10.1073/pnas.1525749113

The relative roles of density dependence and life history evolution in contributing to rapid fisheries-induced trait changes remain debated. In the 1930s, northeast Arctic cod (Gadus morhua), currently the world’s largest cod stock, experienced a shift from a traditional spawning-ground fishery to an industrial trawl fishery with elevated exploitation in the stock’s feeding grounds. Since then, age and length at maturation have declined dramatically, a trend paralleled in other exploited stocks worldwide. These trends can be explained by demographic truncation of the population’s age structure, phenotypic plasticity in maturation arising through density-dependent growth, fisheries-induced evolution favoring faster-growing or earlier-maturing fish, or a combination of these processes. Here, we use a multitrait eco-evolutionary model to assess the capacity of these processes to reproduce 74 y of historical data on age and length at maturation in northeast Arctic cod, while mimicking the stock’s historical harvesting regime. Our results show that model predictions critically depend on the assumed density dependence of growth: when this is weak, life history evolution might be necessary to prevent stock collapse, whereas when a stronger density dependence estimated from recent data is used, the role of evolution in explaining fisheries-induced trait changes is diminished. Our integrative analysis of density-dependent growth, multitrait evolution, and stock-specific time series data underscores the importance of jointly considering evolutionary and ecological processes, enabling a more comprehensive perspective on empirically observed stock dynamics than previous studies could provide.