Environmental stochasticity drives adaptation to cooler thermal optima

Thermal reaction norms, or thermal performance curves (TPCs), describe how ectothermic organisms respond to temperature variation. Here, we investigate how stochastic environmental noise, by modulating competitive interactions among individuals with differing TPC shapes, can drive long-term evolutionary changes in thermal performance. We develop a Ricker competition model within the framework of adaptive dynamics to examine how environmental variability—arising from both periodic and stochastic temperature fluctuations—influences the evolution of TPCs. Competitive interactions are temperature-dependent, with competition coefficients defined by the ratio of individuals’ thermal performance at the prevailing temperature. TPCs are modelled using a beta probability density function. Previous results from periodically (i.e. deterministically) fluctuating environments established that the thermal optimum converges on the mean environmental temperature, while performance breadth collapses under constant conditions. In contrast, we show that under stochastic environments, increasing thermal noise broadens TPCs and shifts the thermal optimum leftward, away from the environmental mean. This results in right-skewed TPCs and suggests an evolutionary bias towards cooler temperature optima under moderate to high environmental noise. Alongside the broadening of TPCs to buffer against thermal fluctuations, the shift towards cooler optima reflects a more conservative thermal strategy in the face of environmental uncertainty.