The study of biological invasions is not only essential to regulate their vast potential for ecological and economical harm, they offer a unique opportunity to study adaptive evolution in the context of recent range expansions into novel environments. The North American invasion of the gypsy moth, Lymantria dispar L., since its introduction in 1869 to Massachusetts, has expanded westward to Minnesota, northward to Canada, and southward to North Carolina. Fluctuating range dynamics at the southern invasive edge are heavily influenced by heat exposure over their optimal (supraoptimal) during the larval stage of development. We coupled genomic sequencing with reciprocal transplant and laboratory-rearing experiments to examine the interactions of phenotypic, genetic, and environmental variation under selective supraoptimal regimes. We demonstrate that while there is no evidence to support local adaptation in the fitness-related physiological traits we measured, there are clear genomic patterns of adaptation due to differential survival in higher temperatures. Mapping of loci identified as contributing to local adaptation in a selective environment and those associated with phenotypic variation highlighted that variation in larval development time is partly driven by pleiotropic loci also affecting survival. Overall, I highlight the necessity and inferential power gained through replicating environmental conditions using both phenotypic and genome-wide analyses.

Biological invasions are major threats to any nation’s economy and biodiversity. To detect new biological incursions of some species biosecurity agencies deploy pheromone sentinel traps for targeted species at high risk sites such as airports, seaports and transitional facilities. A good example is the gypsy moth surveillance program in New Zealand. Following the detection of an incursion by an unwanted organism, ground-based searches to locate the source can be very expensive, but are essential to identify the introduction pathway and to increase the chances of success eradicating the unwanted organism. In such circumstances, the possibility of better targeting the search for the source of the incursion using a modelling approach is worthy of investigation A stochastic mechanistic model to hindcast moth flight from a recapture location to the release location was developed based on insect behaviour in response to wind and pheromones. The model was composed of two main processes, 1) downwind dispersal, assumed to result from an appetitive behaviour, indicated by an analysis of a previous mark-release-recapture experiment on painted apple moth (Teia anartoides, Walker) and, 2) anemotaxic dispersal inspired by pheromone anemotaxis theory but up-scaled from a fine-scaled behaviour model to a 2 m scale. A genetic algorithm was used to fit some model parameters. A specialised fitness function was developed to allow the genetic algorithm to identify parameters that resulted in models that reflected both the spread and density patterns in the trapping data. The resulting function allowed the stochastic model results to be compared with the inherently stochastic trapping data. The resulting individual based model simulates the spatio-temporal dispersal pattern of painted apple moth recorded during a previous mark-release-recapture experiment. While the proposed model is shown to have limitations with respect to accuracy and precision it is also demonstrated to greatly improve biosecurity incursion response capability, by more efficient targeting of search effort for the proximal source of an incursion.