Non-native organisms have invaded novel ecosystems for centuries, yet we have only a limited understanding of why their impacts vary widely from minor to severe. Predicting the impact of non-established or newly detected species could help focus biosecurity measures on species with the highest potential to cause widespread damage. However, predictive models require an understanding of potential drivers of impact and the appropriate level at which these drivers should be evaluated. Here, we used non-native, specialist herbivorous insects of forest ecosystems to test which factors drive impact and if there were differences based on whether they used woody angiosperms or conifers as hosts. We identified convergent and divergent patterns between the two host types indicating fundamental similarities and differences in their interactions with non-native insects. Evolutionary divergence time between native and novel hosts was a significant driver of insect impact for both host types but was modulated by different factors in the two systems. Beetles in the subfamily Scolytinae posed the highest risk to woody angiosperms, and different host traits influenced impact of specialists on conifers and woody angiosperms. Tree wood density was a significant predictor of host impact for woody angiosperms with intermediate densities (0.5–0.6 mg/mm3
) associated with highest risk, whereas risk of impact was highest for conifers that coupled shade tolerance with drought intolerance. These results underscore the importance of identifying the relevant levels of biological organization and ecological interactions needed to develop accurate risk models for species that may arrive in novel ecosystems.
Schulz, Ashley N.; Mech, Angela M.; Ayres, Matthew P.; Gandhi, Kamal J. K.; Havill, Nathan P.; Herms, Daniel A.; Hoover, Angela M.; Hufbauer, Ruth A.; Liebhold, Andrew M.; Marsico, Travis D.; Raffa, Kenneth F.; Tobin, Patrick C.; Uden, Daniel R.; Thomas, Kathryn A. 2021. Predicting non-native insect impact: focusing on the trees to see the forest. Biological Invasions. 23: 3921-3936. https://doi.org/10.1007/s10530-021-02621-5.