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 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