Phenotypic plasiticity as a cause and consequence of population dynamics

Publisher
Wiley
Abstract
Predicting how species respond to dynamically changing and novel environments is crucial for guiding conservation and mitigation strategies, as well as deepening our understanding of complex species-environment processes. Phenotypic plasticity is a mechanism of trait variation demonstrably important in determining how individuals and populations adapt to environmental change. For individuals, the effects of phenotypic plasticity can be quantified by measuring environment-trait relationships but from these alone it is often difficult to predict how phenotypic plasticity affects populations. Variation in the life-history traits expressed by individuals may alter population processes, and this in turn can induce further variation in individuals. This feedback between individual state and population response means that the assumption that environment trait relationships validated for individuals are representative of how populations respond to environmental change risks mischaracterising the effect of environmental change on populations. Predicting the effect of phenotypic plasticity on populations necessitates the development and utilisation of specialised predictive tools able to integrate empirically verified mechanisms of trait variation into a population's dynamical processes. Here we derive a novel general mathematical framework linking trait variation due to phenotypic plasticity to population dynamics, which is intuitive and readily parametrised. Applying the framework to the classical example of Nicholson's blowflies, we demonstrate how seemingly sensible predictions about how environment-trait relationships generalise to population responses break down in the context of a populations dynamical processes. This demonstrates the need to account for the effects of trait variation when making predictions about population responses to environmental change and reveals phenotypic plasticity to be a rich source of population dynamical behaviours
Year
2021
Category
Refereed journal