Modeling the Evolution of Insect Phenology

Abstract

Climate change is likely to disrupt the timing of developmental events (phenology) in insect populations in which development time is largely determined by temperature. Shifting phenology puts insects at risk of being exposed to seasonal weather extremes during sensitive life stages and losing synchrony with biotic resources. Additionally, warming may result in loss of developmental synchronization within a population making it difficult to find mates or mount mass attacks against well-defended resources at low population densities. It is unknown whether genetic evolution of development time can occur rapidly enough to moderate these effects. We present a novel approach to modeling the evolution of phenology by allowing the parameters of a phenology model to evolve in response to selection on emergence time and density. We use the Laplace method to find asymptotic approximations for the temporal variation in mean phenotype and phenotypic variance arising in the evolution model that are used to characterize invariant distributions of the model under periodic temperatures at leading order. At these steady distributions the mean phenotype allows for parents and offspring to be oviposited at the same time of year in consecutive years. Numerical simulations show that populations evolve to these steady distributions under periodic temperatures. We consider an example of how the evolution model predicts populations will evolve in response to warming temperatures and shifting resource phenology.

Modeling the Effects of Developmental Variation on Insect Phenology

“…If τ i (T ) is the base development time curve for stage i, then an individual with phenotype α has development time ατ i (T ). This is consistent with the model of developmental variation presented in Yurk and Powell (2009). We assume each individual maintains its phenotype throughout the life stage, which is consistent with our definition of persistent variation.…”

“…In particular, it is important to account for persistent variation (which includes the effects of genetic variation) if we are to understand how populations might evolve to cope with climate change (Yurk and Powell, 2009). In this paper, we present three phenology models incorporating increasing amounts of developmental variation, while explicitly separating persistent and random variation.…”

“…For example, neither model accounts for the fact that individuals that develop slowly due to their genotypes will emerge later than individuals that develop quickly. The ability to predict such patterns is important in modeling the evolution of development time because individuals that emerge at different times will be exposed to different selective pressures and individuals that emerge at the same time are more likely to mate (Yurk and Powell, 2009).…”

“…This is achieved by introducing a developmental phenotype that scales some base temperature-dependent development time curve (Yurk and Powell, 2009). This phenotype is assumed to vary within a population, and development is simulated separately for insects with different phenotypes.…”

How do plant communities and flower visitors relate? A case study of semi-natural xerothermic grasslands

“…The period of imago activity for the majority of insects in the Northern Hemisphere is between May and August [46]. This is the result of the coincidence of the two main optimal temperatures for heat-labile animals and the availability of plant resources [47]. This means that on a plot with a dominance of early-flowering plants the abundance of possible pollinators should be lower.…”