Maturation reaction norm evolution under varying conditions of eco-evolutionary change

Author:

Gobin Jenilee1,Fox Michael G.2,Dunlop Erin S.13

Affiliation:

1. Environmental and Life Sciences Graduate Program, Trent University, 1600 West Bank Drive, Peterborough, ON K9J 7B8, Canada.

2. Trent School of the Environment and Department of Biology, Trent University, 1600 West Bank Drive, Peterborough, ON K9J 7B8, Canada.

3. Aquatic Research and Monitoring Section, Ontario Ministry of Natural Resources and Forestry, DNA Bldg., 2140 East Bank Drive, Trent University, Peterborough, ON K9J 8N8, Canada.

Abstract

Probabilistic maturation reaction norms (PMRNs) are commonly used to infer evolution of maturation age and size in wild fish stocks, but how well estimates from phenotypic data actually reflect underlying genotypes is debated. We used an eco-genetic model of a commercially harvested freshwater fish to simulate populations undergoing various levels of fisheries-induced evolution and density-dependent feedback and evaluated effects on the estimation of PMRNs. We estimated PMRNs from phenotypic data sampled from simulated populations (age, length, and maturation status of individuals), as is done for wild stocks, and compared estimates with the known maturation genotypes of individuals in the simulated population. PMRN estimates were robust to changes in the strength of density-dependent growth and high levels of fisheries-induced evolution. However, our ability to detect slower rates of evolution was limited, especially when individuals matured within a narrow range of ages. Furthermore, low numbers of immature or mature individuals within a given age class limited our ability to robustly estimate midpoints for more than one or two ages, despite our large sample sizes (n = 200 randomly sampled individuals of each age per year), highlighting a challenge with this approach. Nonetheless, this study suggests that the widely applied method of estimating PMRNs from readily available phenotypic data to detect underlying evolution of maturation schedule is robust to some key factors that vary in wild populations.

Publisher

Canadian Science Publishing

Subject

Aquatic Science,Ecology, Evolution, Behavior and Systematics

Reference78 articles.

1. How fast is fisheries‐induced evolution? Quantitative analysis of modelling and empirical studies

2. Brenden, T.O., Brown, R.W., Ebener, M.P., Reid, K., and Newcomb, T. 2013. Great Lakes commercial fisheries: historical overview and prognoses for the future. In Great Lakes Fisheries Policy and Management. 2nd edition. Edited by W.W. Taylor, A.J. Lynch, and N.J. Leonard. Michigan State University Press, East Lansing, Mich. pp. 339–397.

3. The Role of Fisheries-Induced Evolution

4. The role of genetics in fisheries management under the E.U. common fisheries policy

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