Data to support publication figures and animation scripts at GitHub: Modeling weather-driven long-distance dispersal of spruce budworm moths (Choristoneura fumiferana)

Long-term studies of insect populations in the North American boreal
forest have shown the vital importance of long-distance dispersal to the
maintenance and expansion of insect outbreaks. In this work, we extend
several concepts established previously in an empirically-based dispersal
flight model with recent work on the physiology and behavior of the adult
eastern spruce budworm (SBW) moth, Choristoneura fumiferana (Clem.). An
outbreak of defoliating SBW in Quebec, ongoing since the mid-2000s,
already covers millions of hectares of forests in eastern Canada and
threatens to spread into neighboring areas through annual summertime
episodes of long-distance dispersal. Such flight events in favorable
conditions frequently include billions of SBW moths dispersing in the warm
atmospheric boundary layer, typically starting around sunset and often
lasting through several hours of wind-driven transport over hundreds of
kilometers. Successful SBW dispersal to possibly distant host forest areas
depends acutely on the weather. Here we describe the components and
results of SBW–pyATM, an open-source individual-based modeling framework
developed in Python for the simulation of these weather-driven SBW
dispersal events. Using seasonal SBW phenology results from BioSIM at
known outbreak locations and high-resolution Weather Research and
Forecasting (WRF) model output, we focus on modeling dispersal flights
over two successive nights in July 2013 in southern Quebec. Our flight
model closely reproduces the SBW spatial patterns and motions observed by
weather surveillance radar over the St. Lawrence estuary. With SBW–pyATM
we can estimate landing locations for both male and female SBW and the
resulting spatial patterns of egg distribution, allowing us eventually to
forecast future larval defoliation activity in new locations where
immigration could help overcome local limitations on SBW populations. This
information could then support forest management decisions where SBW
outbreaks threaten valuable resources.