Identifying the generalizable controls on insect associations of native and non-native trees

Abstract

Trees growing outside their native geographic ranges often exhibit exceptional growth and survival due in part to the lack of co-evolved natural enemies that may limit their spread and suppress population growth. While most non-native trees tend to accumulate natural enemies over time, it remains uncertain which host and insect characteristics affect these novel associations and whether novel associations follow patterns of assembly similar to those of native hosts. Here, we used a dataset of insect-host tree associations in Europe to model which native insect species are paired with which native tree species, and then tested the model on its ability to predict which native insects are paired with which non-native trees. We show that native and non-native tree species closely related to known hosts are more likely to be hosts themselves, but that native host geographic range size, insect feeding guild, and sampling effort similarly affect insect associations. Our model had a strong ability to predict which insect species utilize non-native trees as hosts, but evolutionarily isolated tree species posed the greatest challenge to the model. These results demonstrate that insect-host associations can be reliably predicted, regardless of whether insect and host trees have co-evolved, and provide a framework for predicting future pest threats using a select number of easily attainable tree and insect characteristics.

Keywords: evolutionary isolation; geographic ranges; insect–tree associations; invasive species; native trees; novel interactions; phylogeny.

FIGURE 1

Marginal effects of predictors used in a mixed effect model of host–insect associations. Continuous variables were scaled and centered before inclusion in the model. The y‐axes show the predicted probability of host–insect association, indicated by p(). Note each panel has a unique y‐axis to ensure the shape and directionality of the variables was visible. The large y‐axis range for phylogenetic distance indicates its prominence in the model. Shaded areas in (a)–(e) and whiskers in (f) and (g) represent the 95% confidence interval. Each of the continuous variables was significantly associated with insect–host associations. For insect guilds, galling and sap‐feeding insects were significantly different from the reference guild (folivores), and gymnosperms were significantly different from angiosperms. See also Table 1.

FIGURE 2

True‐positive rate (TPR) and true‐negative rate (TNR) rates for 85 host tree species included in our model. TPR indicates the proportion of insect associations that were accurately predicted by the model, and TNR indicates the proportion of non‐associations that were accurately predicted. For both TPR and TNR, higher values indicate greater predictive accuracy. Native species (n = 68) were used to train the model, while non‐native species (boldface, n = 17) were used to test the model. Visualization was made with ggtree (Yu et al., 2017).

FIGURE 3

True‐positive rate (TPR) and true‐negative rate (TNR) of 1592 insect species used in our model. TPR indicates the proportion of hosts that were accurately predicted by the model, and TNR indicates the proportion of non‐hosts that were accurately predicted. Diamond symbols represent the aggregate TPR and TNR of five feeding guilds. For both TPR and TNR, higher values indicate greater predictive accuracy.