Kristine L. Grayson

Aim Metabolic rate is a widely studied physiological species trait related to energetics, climate, and geographical distributions. Hypotheses have been proposed to explain variation in metabolic rate, but evidence has been mixed due to the limited sampling scope of intraspecific studies. Successful biological invasions offer a unique opportunity to examine the development of intraspecific physiological variation and how it relates to climate, invasive spread and species range limits. The aim of this study was to determine if metabolic rate variation across the spongy moth invasive range was consistent with a pattern of adaptation to local climate. Location Northeastern United States of America. Taxon Lymantria dispar dispar L. (Lepidoptera: Erebidae). Methods Larvae were sourced from 14 populations across the invasion front and interior of the current L. d. dispar invasive range and were reared at a constant temperature. Routine metabolic rates (RMR) of larvae were assayed at three ecologically relevant temperatures. These data were analysed to determine if there were differences in RMR and temperature sensitivity of RMR among populations. Population‐level variation in RMR was then analysed as a function of local climate and geographical position to test for patterns consistent with local adaptation. Results Larval RMR showed significant variation among populations across all assay temperatures, but there was no difference in temperature sensitivity (i.e. slope). This variation followed a positive latitudinal cline with RMR increasing from the southern range to the north. This cline also showed a significant relationship with local climate variables. Main Conclusions Larval metabolic rate variation was consistent with a pattern of adaptation by L. d. dispar to divergent climates across its invasive range. These results indicated that thermal adaptation of whole‐organism physiology may play a key role in promoting species spread and expansion for biological invasions like L. d. dispar .

Aim Biological invasions are an escalating environmental challenge due to their substantial ecological and socio‐economic consequences. Accurate near‐term forecasts of future areas occupied by an invasive species could enhance the efficiency and efficacy of invasion monitoring and management but spread forecasting models have been developed and tested for few invasive species thus far. Location Northeastern USA. Methods We developed a quantitative model to forecast 1‐year‐ahead occupancy of Lymantria dispar dispar , an expanding invasive forest insect introduced into the eastern United States in 1869 that causes large‐scale defoliation of forests. We validated and tested the model using historical distribution and density data from a large‐scale network of pheromone‐baited traps. We first assessed how forecast accuracy depended on trap catch density thresholds for determining occupancy and on the spatial scale of local connectivity measures. Next, we tested how increasing the computational complexity and biological detail encoded in the models affected prediction accuracy. Results Models using lower occupancy thresholds and measuring connectivity over shorter distances tended to perform best. A simple model using only coarse and generic representations of habitat suitability and local diffusive spread potential performed at least as well as more complex models. Our best models achieved total accuracy and true‐positive rates exceeding 95%. Conclusions Our baseline model illustrates the utility of a mechanistic model to forecast year‐to‐year occupancy dynamics of L. dispar. Near‐term spread forecasting can be a valuable tool for invasion management, even for species without detailed a priori ecological knowledge.