# Modeling stratified dispersal in forest pests: A case study of the mountain pine beetle in Alberta

## TL;DR

The paper studies how mountain pine beetles spread in Alberta, finding that most travel short distances but a few rare beetles cause long-distance spread.

## Contribution

The study introduces a fat-tailed dispersal model for mountain pine beetles using aerial survey data.

## Key findings

- A Student's t-distribution model best fits dispersal data with a median of 60 m and 95th percentile near 5 km.
- Long-distance dispersal is driven by rare beetles, consistent with biological factors like beetle size and emergence timing.
- Aerial surveys can detect dispersal patterns via foliage damage and host preferences visible from above.

## Abstract

Forest pests pose critical threats to forest ecosystems worldwide, yet accurately predicting their spatial spread remains challenging due to complex dispersal behaviors, weather effects, and the inherent difficulty of tracking small organisms across large landscapes. These challenges have resulted in divergent estimates of typical dispersal distances across studies. Here, we use high‐quality data from helicopter and field‐crew surveys to parameterize dispersal kernels for the mountain pine beetle, a destructive pest that has recently expanded its range into Alberta, Canada. We find that fat‐tailed kernels—those which allow for a small number of long‐distance dispersal events—consistently provide the best fit to these data. Specifically, the radially symmetric Student's t‐distribution with parameters ρ=0.012 km and ν=1.45 stands out as parsimonious and user‐friendly; this model predicts a median dispersal distance of 60 m, with the 95th percentile of dispersers traveling nearly 5 km. The best‐fitting mathematical models have biological interpretations. The Student's t‐distribution, derivable as a mixture of diffusive processes with varying settling times, is consistent with observations that mountain pine beetle adults fly short distances while few travel far; early‐emerging beetles fly farther; and larger beetles from larger trees exhibit greater variance in flight distance. This phenotypic variability is mirrored in other forest pests, resulting in a stratified dispersal pattern where most individuals disperse locally while rare long‐distance “jumpers” drive range expansion. Our approach demonstrates how aerial survey data can be used to characterize dispersal patterns, as many insects create diagnostic signatures—combining foliage damage patterns and host‐tree preferences—that are visible from above. Since aerial surveys of North American forests are widely available, our methodology can be broadly used to create parsimonious dispersal models for many forest insects.