RDA-PSO: A computational method to quantify the diffusive dispersal of insects

TL;DR

This paper presents RDA-PSO, a new computational method for accurately estimating insect dispersal parameters from mark-release-recapture data, even with low recapture rates and uneven sampling.

Contribution

The paper introduces RDA-PSO, a novel, robust computational approach that outperforms existing methods in estimating insect diffusion coefficients from field data.

Findings

RDA-PSO reliably estimates diffusion coefficients with low recapture rates.

The method outperforms three existing diffusion equation-based techniques.

Application to real mosquito data demonstrates practical utility.

Abstract

This article introduces a computational method, called "Recapture of Diffusive Agents & Particle Swarm Optimization" (RDA-PSO), designed to estimate the dispersal parameter of diffusive insects in mark-release-recapture (MRR) field experiments. In addition to describing the method, its properties are discussed, with particular focus on robustness in estimating the observed diffusion coefficient in the presence of uncertainty. It is shown that RDA-PSO provides a simple and reliable approach to quantify insect dispersal that can handle low recapture rates and uneven capture site distributions without the need for area corrections. Tests on synthetic data, for which the actual diffusion coefficient is known, show the method outperforms three techniques based on the solution of the diffusion equation, which are also introduced in this work. Examples of application to real field data for the yellow fever mosquito are provided.