| Popis: |
In the last decade, marine ecosystem models have been increasingly used to project interspecific biodiversity under various global change and management scenarios, considering ecological dynamics only. However, fish populations may also adapt to climate and fishing pressures, via evolutionary changes, leading to modifications in their life-history that could either mitigate or worsen, or even make irreversible, the impacts of these pressures. Building on the multispecies individual-based model Bioen-OSMOSE, an eco-evolutionary fish community model, Ev-Osmose, has been developed to account for evolutionary dynamics together with physiological and ecological dynamics in fish diversity projections. A gametic inheritance module describing the individuals’ genetic structure has been implemented. The genetic structure is defined by finite numbers of loci and alleles per locus that determine the genetic variability of growth, maturation and reproductive effort. Climate change and fishing activities will generate selection pressures on fish life-history traits that will respond through microevolution. This paper is an overview of the Ev-OSMOSE model. To illustrate the ability of the Ev-OSMOSE model to represent realistic fish community dynamics, genotypic and phenotypic traits’ mean and variance and consistent evolutionary patterns, we applied the model to the North Sea ecosystem. The simulated outputs are confronted to observed data of commercial catch, maturity ogives and length at age and to estimates of biomass for each modeled species. In addition to the evaluation of their mean value, the emerging traits’ variability is confronted to length-at-age and maturity data. To ensure the consistency of genetic inheritance and the resulting evolutionary patterns, we assessed the transmission of traits’ genotypic value across cohorts. Overall, the state of the modelled ecosystem was convincing at all these different biological levels. These results open perspectives for using Ev-OSMOSE in different marine regions to project the eco-evolutionary impact of various global change and management scenarios on different biological levels. |
