Bioinvasion risk analysis based on automatic identification system and marine ecoregion data

被引:0
|
作者
Shi, Hongwei [1 ]
Wang, Chenyu [1 ,2 ]
Zhao, Hang [1 ]
Wang, Shengling [1 ]
Chen, Yixian [2 ]
机构
[1] Beijing Normal Univ, Sch Artificial Intelligence, Beijing 100875, Peoples R China
[2] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30302 USA
来源
HIGH-CONFIDENCE COMPUTING | 2024年 / 4卷 / 04期
关键词
Biological invasion; Species invasion network; Global shipping network; PROPAGULE PRESSURE; INVASION; PATHWAY;
D O I
10.1016/j.hcc.2024.100210
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The global maritime trade plays a key role in propagating alien aquatic invasive species, which incurs side effects in terms of environment, human health and economy. The existing biosecurity methods did not take into account the invaded risk as well as the diffusion of invasive species at the same time, which may lead to inadequate bioinvasion control. In addition, the lack of considering the impact of bioinvasion control on shipping also makes their methods cost-ineffective. To solve the problems of the existing methods, we employ the automatic identification system (AIS) data, the ballast water data and the water temperature & salinity data to construct two networks: the species invasion network (SIN) and the global shipping network (GSN). The former is used to analyze the potential of a port in propagating marine invasive species while the latter is employed to evaluate the shipping importance of ports. Based on the analysis of SIN and GSN, two categories of biosecurity triggering mechanisms are proposed. The first category takes into consideration both being bioinvaded and spreading invasive species and the second one concerns the shipping value of each port besides its invasion risk. A lot of case studies have been done to discover the key ports needed to be controlled preferentially under the guide of the proposed biosecurity triggering mechanisms. Finally, our correlation analysis shows that closeness is most highly correlated to the invasion risk. (c) 2024 The Author(s). Published by Elsevier B.V. on behalf of Shandong University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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页数:8
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