Genotype‐by‐environment interactions drive the maintenance of genetic variation in a Salmo trutta L. hybrid zone

International audienceAllopatric gene pools can evolve in different directions through adaptive and nonadaptive processes and are therefore a source of intraspecific diversity. The connection of these previously isolated gene pools through human intervention can lead to intraspecific diversity loss, through extirpation of native populations or hybridization. However, the mechanisms leading to these situations are not always explicitly documented and are thus rarely used to manage intraspecific diversity. In particular, genotype-by-environment (GxE) interactions can drive postzygotic reproductive isolation mechanisms that may result in a mosaic of diversity patterns, depending on the local environment. We test this hypothesis using a salmonid species (Salmo trutta) in the Mediterranean (MED) area, where intensive stocking from non-native Atlantic (ATL) origins has led to various outcomes of hybridization with the native MED lineage, going from MED resilience to total extirpation via full hybridization. We investigate patterns of offspring survival at egg stage in natural environments, based on parental genotypes in interaction with river temperature, to detect potential GxE interactions. Our results show a strong influence of maternal GxE interaction on embryonic survival, mediated by maternal effect through egg size, and a weak influence of paternal GxE interaction. In particular, when egg size is large and temperature is cold, the survival rate of offspring originating from MED females is three times higher than that of ATL females’ offspring. Because river temperatures show contrast at small scale, this cold adaptation for MED females’ offspring constitutes a potent postzygotic mechanism to explain small-scale spatial heterogeneity in diversity observed in MED areas where ATL fish have been stocked. It also indicates that management efforts could be specifically targeted at the environments that actively favor native intraspecific diversity through eco-evolutionary processes such as postzygotic selectio

How many cubs can a mum nurse? Maternal age and size influence litter size in polar bears

International audienc

Importance of interindividual interactions in eco‐evolutionary population dynamics: The rise of demo‐genetic agent‐based models

Corrigendum on: Volume 16, Issue 1, Evolutionary Applications, pages: 189-189, First Published online: January 18, 2023.International audienceThe study of eco-evolutionary dynamics, that is of the intertwinning between ecologi- cal and evolutionary processes when they occur at comparable time scales, is of grow- ing interest in the current context of global change. However, many eco-evolutionary studies overlook the role of interindividual interactions, which are hard to predict and yet central to selective values. Here, we aimed at putting forward models that simulate interindividual interactions in an eco-evolutionary framework: the demo- genetic agent-based models (DG-ABMs). Being demo-genetic, DG-ABMs consider the feedback loop between ecological and evolutionary processes. Being agent-based, DG-ABMs follow populations of interacting individuals with sets of traits that vary among the individuals. We argue that the ability of DG-ABMs to take into account the genetic heterogeneity—that affects individual decisions/traits related to local and instantaneous conditions—differentiates them from analytical models, another type of model largely used by evolutionary biologists to investigate eco-evolutionary feed- back loops. Based on the review of studies employing DG-ABMs and explicitly or implicitly accounting for competitive, cooperative or reproductive interactions, we illustrate that DG-ABMs are particularly relevant for the exploration of fundamental, yet pressing, questions in evolutionary ecology across various levels of organization. By jointly modelling the effects of management practices and other eco-evolutionary processes on interindividual interactions and population dynamics, DG-ABMs are also effective prospective and decision support tools to evaluate the short- and long-term evolutionary costs and benefits of management strategies and to assess potential trade-offs. Finally, we provide a list of the recent practical advances of the ABM com- munity that should facilitate the development of DG-ABMs

Importance of interindividual interactions in eco‐evolutionary population dynamics: The rise of demo‐genetic agent‐based models

International audienceThe study of eco-evolutionary dynamics, that is of the intertwinning between ecologi- cal and evolutionary processes when they occur at comparable time scales, is of grow- ing interest in the current context of global change. However, many eco-evolutionary studies overlook the role of interindividual interactions, which are hard to predict and yet central to selective values. Here, we aimed at putting forward models that simulate interindividual interactions in an eco-evolutionary framework: the demo- genetic agent-based models (DG-ABMs). Being demo-genetic, DG-ABMs consider the feedback loop between ecological and evolutionary processes. Being agent-based, DG-ABMs follow populations of interacting individuals with sets of traits that vary among the individuals. We argue that the ability of DG-ABMs to take into account the genetic heterogeneity—that affects individual decisions/traits related to local and instantaneous conditions—differentiates them from analytical models, another type of model largely used by evolutionary biologists to investigate eco-evolutionary feed- back loops. Based on the review of studies employing DG-ABMs and explicitly or implicitly accounting for competitive, cooperative or reproductive interactions, we illustrate that DG-ABMs are particularly relevant for the exploration of fundamental, yet pressing, questions in evolutionary ecology across various levels of organization. By jointly modelling the effects of management practices and other eco-evolutionary processes on interindividual interactions and population dynamics, DG-ABMs are also effective prospective and decision support tools to evaluate the short- and long-term evolutionary costs and benefits of management strategies and to assess potential trade-offs. Finally, we provide a list of the recent practical advances of the ABM com- munity that should facilitate the development of DG-ABMs