Biology subjects

Govaert, L.

Publications and source records attributed to Govaert, L..

5 recordsLinked to original sources

bioRxiv2026

Eco-evolutionary dynamics in competitive systems: Rescue or murder?

Rapid evolution in response to changing environments can have beneficial (e.g. evolutionary rescue) or detrimental (e.g. evolutionary suicide) outcomes for the survival of one species. Responses of multi-species systems are even harder to predict, but important to consider. We simulate eco-evolutionary dynamics in one- and two-species systems, with two traits per species: physiological performance (associated with abiotic pressure) and defense against interference competition (associated with biotic pressure). In the single-species system, evolution is consistently beneficial, enabling evolutionary rescue. In contrast, in the two-species system, evolution can be simultaneously beneficial and detrimental, because rescue of one species can lead to evolutionary murder of the other. Notably, the pattern of rescue and murder was largely independent of different ecological and evolutionary scenarios, indicating that evolutionary murder might be common in competitive systems. Our study enables exploration of eco-evolutionary dynamics in more complex biotic settings, extending understanding of species responses to abiotic and biotic changes.

ecology↗

bioRxiv2025

Environmental complexity constrains evolutionary adaptation across taxa

Complex environments combining multiple stressors are the new norm worldwide. Adaptive evolution will be critical to population persistence under these combined challenges, but how environmental complexity affects the pace of evolution remains poorly understood. Using a meta-experimental evolution approach, we exposed 14 species, from bacteria to unicellular eukaryotes and plants, to single stressors and their pairwise combinations for multiple generations, while keeping the overall stress level comparable. Populations evolving under combined stressors tended to have lower fitness increase in the selective environments, higher fitness reductions in the control environment, and shallower relation between initial maladaptation and fitness gain, than under single stressors. However, these responses varied with species and stressor type. Accounting for such constraints on evolutionary dynamics should prove crucial for the management of biodiversity. Significance StatementA pressing challenges for modern science and society in the face of ongoing global change is understanding what limits the capacity of living organisms to adapt to complex environments combining multiple stressors. To answer to this question, we conducted a large-scale meta-experimental evolution design across a diversity of organisms, exposing them for multiple generations to either single or combined-stress treatments. Combined stressors led to less adaptive fitness gain than single stressors, and imposed additional costs through reduced fitness in non-stressful conditions. This unique combination of meta-experimental approach with a careful distinction between environmental complexity and overall stress allowed us to gain robust quantitative evidence on how environmental complexity can impact the pace of evolution.

evolutionary biology↗

bioRxiv2025

Persistence and near persistence via trait evolution: pathways to coexistence

Modern coexistence theory relies on the invasion criterion: each species must be able to increase when rare in a resident community at ecological equilibrium. However, when considering trait evolution, for example of competing species, this concept must be refined to account for evolution potentially feeding back on population dynamics. We analyze a model of two competing species whose quantitative traits evolve under stabilizing selection, assuming fixed but potentially unequal intraspecific trait variances. Using persistence theory, we derive conditions under which both species persist for all initial trait values, and we introduce the concept of near persistence, in which coexistence holds for a specific, biologically relevant, subset of initial trait configurations. Our analysis reveals that equal trait variances between species, which is commonly assumed in previous work, yield highly specific outcomes and obscure a broader set of coexistence scenarios that emerge under asymmetric trait variation. We identify fifteen distinct qualitative dynamical regimes as a function of initial conditions and trait variances. Moreover, we show that invasion analysis must often be performed at multiple eco-evolutionary equilibria, as invader dynamics may converge to different trait values depending on the ecological and evolutionary context. We discuss the biological implications of these results and perspectives for future work.

ecology↗

bioRxiv2019

Quantifying eco-evolutionary contributions to trait divergence in spatially structured systems

Ecological and evolutionary processes can occur at similar time scales, and hence influence one another. There has been much progress in the development of metrics that quantify contributions of ecological and evolutionary components to trait change over time. However, many empirical evolutionary ecology studies document genetic differentiation among populations structured in space. In both time and space, the observed differentiation in trait values among populations and communities can be the result of interactions between non-evolutionary (phenotypic plasticity, changes in the relative abundance of species) and evolutionary (genetic differentiation among populations) processes. However, the tools developed so far to quantify ecological and evolutionary contributions to trait change are implicitly addressing temporal dynamics because they require directionality of change from an ancestral to a derived state. Identifying directionality from one site to another in spatial studies of eco-evolutionary dynamics is not always possible and often not desired. We here suggest three modifications to existing metrics so they allow the partitioning of ecological and evolutionary contributions to changes in population and community trait values across landscapes. Applying these spatially modified metrics to published empirical examples shows how these metrics can be used to generate new empirical insights and to facilitate future comparative analyses. The possibility to apply eco-evolutionary partitioning metrics to populations and communities in real landscapes is critical as it will broaden our capacity to quantify eco-evolutionary interactions as they occur in nature.

ecology↗

bioRxiv2018

The shape of density dependence and the relationship between population growth, intraspecific competition and equilibrium population density

The logistic growth model is one of the most frequently used formalizations of density dependence affecting population growth, persistence and evolution. Ecological and evolutionary theory and applications to understand population change over time often include this model. However, the assumptions and limitations of this popular model are often not well appreciated. Here, we briefly review past use of the logistic growth model and highlight limitations by deriving population growth models from underlying consumer-resource dynamics. We show that the logistic equation likely is not applicable to many biological systems. Rather, density-regulation functions are usually non-linear and may exhibit convex or both concave and convex curvatures depending on the biology of resources and consumers. In simple cases, the dynamics can be fully described by the continuous-time Beverton-Holt model. More complex consumer dynamics show similarities to a Maynard Smith-Slatkin model. Importantly, we show how population-level parameters, such as intrinsic rates of increase and equilibrium population densities are not independent, as often assumed. Rather, they are functions of the same underlying parameters. The commonly assumed positive relationship between equilibrium population density and competitive ability is typically invalid. As a solution, we propose simple and general relationships between intrinsic rates of increase and equilibrium population densities that capture the essence of different consumer-resource systems. Relating population level models to underlying mechanisms allows us to discuss applications to evolutionary outcomes and how these models depend on environmental conditions, like temperature via metabolic scaling. Finally, we use time-series from microbial food chains to fit population growth models and validate theoretical predictions. Our results show that density-regulation functions need to be chosen carefully as their shapes will depend on the study systems biology. Importantly, we provide a mechanistic understanding of relationships between model parameters, which has implications for theory and for formulating biologically sound and empirically testable predictions.

ecology↗