Path-finding algorithm as a dispersal assessment method for invasive species with human-vectored long-distance dispersal event

Aim: An assessment method that can precisely represent human-vectored long-distance dispersals (HVLDD) is currently in need for effective management of invasive species. Here, we focused on HVLDD happening along roads and proposed a path-finding algorithm as a more precise dispersal assessment tool than the most widely used Euclidean distance method by using pine wilt disease (PWD) as a case study.
Location: Busan Metropolitan City, Republic of Korea
Methods: A path-finding algorithm, which calculates distances by considering spatial distribution of road networks, was tested for its effectiveness in estimating dispersal distances of HVLDD events. To this end, annual HVLDD cases were classified from entire PWD occurrence data from 2016 to 2019 and their dispersal distances were calculated using the path-finding algorithm and the Euclidean distance method. We constructed potential dispersal ranges based on the occurrence points in 2016, 2017, and 2018 using the respective year's mean disp...