Pest host expansion as a scale-free stepwise process across the host phylogeny

Area of Science:

• Ecology
• Evolutionary Biology
• Computational Biology

Background:

• Pest host range is critical for ecology, economics, and health.
• While many pests maintain symbiotic relationships with related hosts, jumps to distant hosts are frequent and impactful.
• Understanding host-jump dynamics is key to predicting pest spread.

Purpose of the Study:

• To develop and validate a model predicting pest host range expansion based on host phylogeny.
• To investigate differences in host-jump behavior between native and non-native insect pests and pathogens.
• To estimate the risk of future host expansion for North American tree pests.

Main Methods:

• A novel model was created representing host distributions as random jumps across a host phylogeny.
• Jump probabilities were modeled as a power function of phylogenetic distance, akin to Lévy flights.
• Machine learning was employed to fit the model to empirical data of insect and pathogen pests affecting North American trees.

Main Results:

• The model successfully estimated parameters governing host jump distances.
• Non-native insect pests demonstrated a higher propensity for jumping to phylogenetically distant hosts compared to native insects.
• No significant difference in host-jump behavior was observed between non-native and native pathogens.

Conclusions:

• The developed model provides insights into the mechanisms driving pest host range expansion.
• Phylogenetic distance plays a crucial role in host-jump probabilities, particularly for insect pests.
• Findings inform predictions of future pest spread and host expansion risks across North American trees.