Skip to main content
Dryad logo

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

Citation

Lee, Sung-Joo et al. (2022), Path-finding algorithm as a dispersal assessment method for invasive species with human-vectored long-distance dispersal event, Dryad, Dataset, https://doi.org/10.5061/dryad.k98sf7m6w

Abstract

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 dispersal distance for both methods, and their performances in accounting for each subsequent year's HVLDD cases were compared to determine which method calculated more precise distances. The information on which road class contributed more to dispersal occurrences and distances was analysed as well using the proposed algorithm.

Results: The potential dispersal ranges of the path-finding algorithm accounted for more future anthropogenic infection cases than the ones that used the Euclidean distance method, validating its higher functionality. It also revealed that most HVLDDs started and ended on small roads, and large roads constituted the majority of the total dispersal length.

Main Conclusions: The path-finding algorithm has proven to be a more effective dispersal assessment method for HVLDD events. It can help design effective control strategies. Thus, we encourage using the path-finding algorithm for dispersal assessment of invasive species that move along road networks, as well as for the development of more powerful HVLDD prediction models.a

Funding

Korea Ministry of Environment, Award: 2020002990009

Korea University