Sustainable fisheries management

Both evolutionary and ecological factors interact to influence the growth and size of fish, an IIASA study has shown. Previous work demonstrated that overfishing can lead to evolutionary changes in fish populations, but in a 2016 study the researchers show that a comprehensive perspective on evolutionary and ecological processes is needed in order to understand and manage fisheries sustainably.

Because fishers usually harvest larger fish, fish populations adapt to the pressure of heavy fishing by evolving to mature earlier and at smaller sizes. This phenomenon is concerning both for the economy and the environment: economically because smaller fish means a smaller catch for fishers, and for the environment because the broader ecosystem impacts of these changes are unclear.

Through a growing body of research, the IIASA Evolution and Ecology Program is elucidating to what extent observed changes in fish populations are caused by non-reversible genetic changes, or evolution, and to what extent the changes are phenotypic, or influenced by the environment rather than genetics. The distinction is crucial for sustainable management, since fisheries-induced genetic changes tend to be slow or impossible to reverse.

In the study, the researchers addressed this question by exploring the relative impact of two factors: density dependence, meaning that when the cod population shrinks through fishing, more food is available, so that fish can grow faster and mature earlier; and life-history evolution, meaning that a trend towards genetic changes causing earlier maturation is induced by the selective harvesting of larger fish.

Using an eco-evolutionary model that could reproduce 74 years of historical data on age and length of maturation in Northeast Arctic cod, they found that a combination of these two factors was likely responsible for the observed changes in fish size. Their carefully calibrated quantitative model also revealed that the cod population might have collapsed around 1980 had it not undergone some life-history evolution that made it more resilient to the high fishing pressures it experienced after World War II.

The study thus shows that ecological and evolutionary dynamics do not work in isolation, but rather as part of a complex system. In order to prevent fisheries collapse, it is important to understand these dynamics and how they interact.

 

Fisheries-induced evolution causes Northeast Arctic cod to mature at younger ages and smaller sizes. Blue line: Empirical observations. Green line: Eco-evolutionary model predictions. Red line: Non-evolutionary model predictions. The results suggest that without fisheries-induced evolution, high fishing pressures could have caused the stock to go extinct in the 1980s (red circle).

References

[1] Eikeset AM, Dunlop ES, Heino M, Storvik G, Stenseth NC & Dieckmann U (2016). Roles of density-dependent growth and life history evolution in accounting for fisheries-induced trait changes. Proceedings of the National Academy of Sciences of the USA 113: 15030–15035.

[2] Mollet FM, Poos JJ, Dieckmann U, Rijnsdorp AD (2016). Evolutionary impact assessment of the North Sea plaice fishery. Canadian Journal of Fisheries and Aquatic Sciences 73: 1-12

[3] Eikeset AM, Richter A, Dunlop ES, Dieckmann U, & Stenseth NC (2013). Economic repercussions of fisheries-induced evolution. Proceedings of the National Academy of Sciences 110 (30): 12259-12264.

 

 

 

Collaborators

  • Department of Biology, University of Oslo, Norway
  • Centre for Ecological and Evolutionary Synthesis, University of Oslo, Norway
  • Center for BioComplexity, Princeton University, USA
  • Princeton Environmental Institute, Princeton University, USA
  • Department of Ecology and Evolutionary Biology, Princeton University, USA
  • Aquatic Research and Monitoring Section, Ontario Ministry of Natural Resources and Forestry, Canada
  • Institute of Marine Research, Norway
  • Department of Biology, University of Bergen, Norway
  • Hjort Centre for Marine Ecosystem Dynamics, University of Bergen, Norway
  • Statistics Division, Department of Mathematics, University of Oslo, Norway