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

Area of Science:

• Ecology
• Entomology
• Evolutionary Biology

Background:

• Non-native trees often exhibit enhanced growth due to a lack of co-evolved natural enemies.
• The assembly patterns of insect-host associations for non-native trees are not well understood.
• Predicting which insects will associate with non-native trees is crucial for managing invasive species.

Purpose of the Study:

• To model insect-host tree associations in Europe using native associations.
• To test the model's ability to predict insect associations with non-native trees.
• To identify key host and insect characteristics influencing novel associations.

Main Methods:

• Utilized a dataset of European insect-host tree associations.
• Developed a model based on native insect-tree pairings.
• Validated the model's predictive power on non-native tree species.

Main Results:

• Tree species relatedness to known hosts strongly predicts insect associations.
• Native host geographic range, insect feeding guild, and sampling effort also influence associations.
• The model accurately predicted insect associations for non-native trees, with challenges arising for evolutionarily isolated species.

Conclusions:

• Insect-host associations can be reliably predicted, irrespective of co-evolutionary history.
• The findings provide a framework for anticipating future pest threats.
• Easily obtainable tree and insect characteristics are sufficient for predictive modeling.