Assessing the impacts of fisheries-induced evolution

Options Magazine, Summer 2011:

Pressure from large-scale commercial fishing, as well as intense recreational and sport fishing, is accelerating evolution in some fish populations and threatening the sustainability of fisheries. Scientists are responding with tools to conduct evolutionary impact assessments that can lead to better management of fisheries.

Photo Bluehead wrasse © 2005 Ken Clifton,

Photo Bluehead wrasse © 2005 Ken Clifton,

For more than a decade, IIASA’s Ulf Dieckmann has recognized that the natural pace of Darwinian evolution was being accelerated in oceans and lakes by large-scale commercial fishing operations and individual anglers. And although most fisheries scientists and managers thought of evolutionary change as a centuries-long process, Dieckmann and his colleagues in the Evolution and Ecology Program (EEP) noted in their research that it could happen within decades, through a phenomenon called rapid contemporary evolution, or more specifically, fisheries-induced evolution (FIE).

At its core, FIE is driven by reproductive success—fishing alters which fish can reproduce most successfully. Fish with suitable genetic programs tend to thrive, while those not adapted to the conditions created by fishing, don’t. “What fisheries are really affecting most is the longevity of fish,” Dieckmann says. “Anything that is programmed to happen late in life is less likely to happen if there is heavy fishing. The advantage of reproducing at an older age is lost when there is no old age.”

The mechanism of fisheries-induced evolution is fairly straightforward: remove the bigger and older fish from a population through fishing and, from a Darwinian perspective, the evolutionary balance shifts toward fish that reproduce earlier. This promotes, as Dieckmann puts it, a “live fast, die young” approach to life.

Building blocks in an evolutionary impact assessment (EvoIA)-When devising a specific EvoIA, practitioners can go through up to four tasks. For carrying out each task, different modules are available. While the tasks are usually carried out in the order indicated by the arrows, not every EvoIA will necessarily cover all tasks. Also the shown modules can be flexibly combined according to needs and data availability.

Theoretical biologist Dieckmann and an international group of collaborators have accumulated the scientific evidence necessary to convince many in the fishing-management profession that fisheries-induced evolution is real. As a result, the focus of scientists in national fisheries research agencies is shifting toward a serious examination of how important evolutionary impacts are to maintaining sustainable fisheries. Instead of balking at the idea of rapid induced evolution, they are now engaging in conversations about “the utility of doing this, about the costs and benefits of making evolutionary impact assessment part of the system,” Dieckmann says.

The next step for researchers is quantifying the potential ecological and economic damage rapid evolution can cause, and providing managers with the tools needed to integrate the impacts of FIE into their standard assessment practices. To that end, an international expert group of IIASA scientists and collaborators, working under the auspices of the International Council for the Exploration of the Sea (ICES), has developed a framework that provides the building blocks fisheries managers need to conduct evolutionary impact assessments (EvoIA) for the fish populations they oversee.

The EvoIA framework is based on four modules that enable managers to estimate changes in the genetic traits of fish stocks, study the resultant effects on stock dynamics, account for the socioeconomic implications for stakeholders, and finally, use those insights to identify alternative management strategies that best achieve evolutionarily sustainable fisheries.

The first module, trait estimation, allows fisheries managers to examine patterns of growth, maturation, and reproduction and to evaluate whether observed phenotypic changes have an evolutionary basis. This is necessary since phenotypic changes typically also include non-genetic responses to environmental change, which cannot be passed on from one generation to the next. By analyzing correlations with environmental variables and by estimating selection pressures, managers can get a sense of which changes are likely to have been caused by FIE. Genetic changes, which are not only cumulative over the years but also very difficult to reverse, can thus be singled out for managerial attention.

The population-dynamics module enables flexible examinations of the demography and evolution of fish stocks. The module provides models that make it easy to “switch off” evolution, so as to compare the impacts of a management measure between a real evolving fish population and the hypothetical case of a non-evolving stock. In conjunction with the socioeconomic module described below, this enables quantifying the ecological and economic costs (or, sometimes, benefits) of FIE.

The socioeconomic module looks at the implications of the evolutionary impacts of fishing on the services provided by an ecosystem, quantifying their socioeconomic utility. By coupling a biological model of a fish stock to a socioeconomic model describing what different stakeholders—be they individual anglers, commercial fishing enterprises, coastal communities, consumers, or conservation groups—derive from that stock, managers can investigate how alternative management strategies translate into societal costs and benefits.

Finally, management-strategy evaluation allows fisheries managers to consider what they should do about FIE and make that a part of their overall management objectives. Such evaluations take the biological and socioeconomic consequences of alternative management strategies as inputs, and return the strategy that best agrees with given objectives.

“We have developed the EvoIA approach to enable fisheries scientists and managers to integrate evolutionary assessments into their standard routines for stock assessment,” Dieckmann says of the framework that, for the first time, allows a structured approach for assessing the evolutionary consequences of fishing.

In stressing the importance of EvoIAs, Dieckmann says, “the particularly insidious feature of FIE is that genetic changes accumulate. They build up and get worse over time. As fish in a population mature at younger and younger ages, they often reproduce less efficiently.”

First-time spawners produce fewer offspring - When females of Northeast Arctic cod spawn for the first time today, they produce fewer eggs than they did decades ago.

That is bad for the sustainability of both the fish population and the fishery. And once FIE has occurred, it is hard to reverse. “There is an asymmetry in the evolutionary response,” Dieckmann says. “FIE may cause genetic change within just a few decades, but even if fishing is stopped, the genetic recovery will usually occur only at a snail’s pace.”

Detecting FIE and using the framework for quantifying its ecological and economic impacts currently requires relatively advanced tools and research skills. “What we would like to do next is to make EvoIAs more accessible,” says Dieckmann. To do that the researchers are creating a “model in a box” that will be simple enough for non-experts to use, yet sophisticated enough to give useful information about FIE in a particular fishery. 

Print this page

Last edited: 11 June 2014


Ulf Dieckmann

Principal Research Scholar Exploratory Modeling of Human-natural Systems Research Group - Advancing Systems Analysis Program

Principal Research Scholar Systemic Risk and Resilience Research Group - Advancing Systems Analysis Program

Principal Research Scholar Cooperation and Transformative Governance Research Group - Advancing Systems Analysis Program


International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313