Movement-surface interactions of flying insects in three-dimensional space
Year: 2026
Type: preprint
Abstract: Three-dimensional movement is increasingly measurable for flying insects. However, modelling approaches have lagged behind, limiting mechanistic understanding of how flight behaviour influences interception by planar trapping surfaces. We simulate insect movement in three-dimensional space using biased and correlated random walks, distinguishing panel contact from edge leakage and accounting for repeated encounters and probabilistic retention upon contact. Using biologically plausible parameters for short-range flight by insects (such as whiteflies, thrips and mosquitoes), we examined how movement behaviour, panel size and retention jointly influence trapping outcomes. Encounter and capture probabilities increased with panel size relative to movement persistence length (the characteristic distance over which successive flight directions remain correlated), but remained low without directional bias, showing that larger panels cannot compensate for weak attraction. Stronger directional bias towards the panel increased encounters, repeated contacts and capture, whereas greater persistence generally reduced capture by producing straighter trajectories less readily redirected towards the panel, despite shortening time to first encounter among successful trajectories. Increasing retention enhanced capture but could not compensate for low encounter rates, while also truncating repeated-contact sequences. Interception failure due to edge leakage peaked at intermediate directional bias and greater persistence, and declined with stronger bias or larger panels. These results show that planar trap performance in flying insects depends jointly on movement behaviour, finite trap geometry and retention. The framework provides a mechanistic basis for interpreting trap catches, generating experimentally testable predictions, and exploring how context-specific differences in movement behaviour may influence planar trap performance across monitoring and control initiatives.
DOI: 10.32942/x2597x
Language: English
Subfield: Insect Science
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7225642774
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