Locusts are serious agricultural pests that exhibit social behavior and collective movement. In a precursor to devastating flying swarms, flightless nymphs form hopper bands that march along the ground in a common direction, often through agricultural regions, causing significant damage to crops. Hopper bands take on a variety of morphologies that range from streaming columns to planar fronts. Hopper band morphology appears to serve ecological functions for the collective group, namely foraging and migration, but the mechanisms that give rise to these collective behaviors are not well understood. The hope is that if we can understand how an individual’s behavioral response to social and environment cues (that is the microscopic description) leads to these morphologies (that is the macroscopic observables) then we can inform development of more efficient and effective strategies for controlling and disrupting harmful swarms. Moreover, these ideas may contribute more broadly to understanding collective behavior in other ecological (livestock herds, fish schools) and human (crowd control, traffic) contexts.
This team has significant and varied expertise in mathematical modeling, statistics, and data analysis that they have brought to analyzing field observations of locusts. One of the outstanding challenges in mathematical biology today is developing techniques for robustly selecting models for observed behaviors and estimating the parameter values (and their uncertainties) for these models. They used published field data to identify a parameter set consistent with field observation in their ten parameter agent-based model. This study primarily used macroscopic observables in the field data. They are now planning to use microscopic data to determine a model for locust alignment.
The researchers have developed a conceptual and technical framework for this purpose. They initiated a new collaboration with Dr. John Maclean, who is an expert on data assimilation methods for model and parameter identification from time series data. Using a small subset of the available data they have so far demonstrated that locusts orient themselves to be parallel to their neighbors. They are ready to scale up their data and simulation pipeline and are using the computational resources of MSI to do so.