# Infestation Patterns and Climate-Based Projections for European Spongy Moth (Lymantria dispar) in Whirlpool Forest, Ontario, Canada

## TL;DR

This study examines how spongy moths infest trees in Ontario and predicts future outbreaks due to climate change.

## Contribution

The study provides region-specific insights into spongy moth infestation patterns and climate-based projections for Ontario.

## Key findings

- Spongy moths prefer red oak trees, especially larger ones, and lay eggs above one meter on trunks.
- Climate projections suggest a potential expansion of outbreak areas to nearly 10 million hectares by 2100.
- A 1 °C temperature increase could expand outbreak areas by 814,100 hectares.

## Abstract

The spongy moth is an invasive insect that damages forests across North America by eating tree leaves. We studied how these moths choose which trees to lay their eggs on in Whirlpool Forest near Niagara Falls, Ontario. We counted moth egg clusters on different tree species and measured tree sizes and health conditions. Our results showed that spongy moths strongly prefer oak trees, especially larger ones, and tend to place their eggs higher up on tree trunks. We found over 2000 egg clusters per hectare, which suggests moderate tree damage is likely in the coming growing season. Using climate data from the past eight years, we created a computer model to predict future moth outbreaks. The model shows that warmer temperatures and changing rainfall patterns could dramatically increase outbreak area across Ontario by the year 2100. In the worst climate scenario, the area at risk could expand from current levels to nearly 10 million hectares. These findings help forest managers understand which trees are most vulnerable and prepare for larger outbreaks as climate continues to change.

This study investigates spongy moth (Lymantria dispar) infestation patterns in Whirlpool Forest, Ontario, offering a region-specific perspective while largely corroborating existing findings. We analyzed egg mass distribution across 43 sampling plots, relating it to tree characteristics. Results revealed a preference for red oak species, with significant egg-laying above one meter. Positive correlations were found between tree diameter and egg mass quantity (ρ = 0.458, p < 0.001 above 1 m; ρ = 0.218, p = 0.006 below 1 m). Tree health was significantly associated with egg mass presence (χ2 = 6.08, p = 0.014). A climate-based regression model (R2 = 0.714, p < 0.05) projected substantial increases in outbreak area by 2100, with the most severe scenario predicting 9,927,378.49 hectares at risk. Sensitivity analysis showed a 1 °C temperature increase could expand the outbreak area by 814,100 hectares. These findings underscore complex infestation dynamics, challenging simplified models and emphasizing the need for tailored, adaptive forest management strategies in response to changing environmental conditions and pest behaviors.