Social aggregation in pea aphids: experiment and random walk modeling.

Area of Science:

• Mathematical Biology
• Animal Behavior
• Collective Motion

Background:

• Social biological aggregations, such as flocks, schools, and swarms, are prevalent in nature.
• A key challenge in modeling these aggregations is linking mathematical models to empirical data by quantifying individual-level rules.
• Understanding individual behavior is crucial for explaining emergent group patterns.

Purpose of the Study:

• To model the aggregation behavior of the pea aphid (Acyrthosiphon pisum).
• To deduce individual-level movement rules from experimental data.
• To assess if a nearest-neighbor interaction model can reproduce observed macroscopic aggregation patterns.

Main Methods:

• Conducted experiments tracking pea aphid motion in a featureless circular arena.
• Observed stochastic transitions between moving and stationary states, with moving aphids exhibiting correlated random walks.
• Estimated state transition probabilities and random walk parameters as functions of nearest neighbor distance.

Main Results:

• Aphid movement rules are strongly dependent on the distance to the nearest neighbor.
• Isolated aphids exhibit ballistic motion (faster, less turning, less likely to stop).
• Aphids in close proximity exhibit slower movement, more turning, and increased likelihood of becoming stationary, facilitating aggregation.

Conclusions:

• A stochastic, social nearest neighbor model accurately reproduces key experimental data on aphid aggregation.
• The model captures macroscopic movement patterns (nearest neighbor distance, angle, population movement percentage) better than a non-social control model.
• Nearest neighbor interactions are a primary driver of pea aphid aggregation behavior.