Bioinvasion risk analysis based on automatic identification system and marine ecoregion data
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...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | High-Confidence Computing |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667295224000138 |
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| author | Hongwei Shi Chenyu Wang Hang Zhao Shengling Wang Yixian Chen |
| author_facet | Hongwei Shi Chenyu Wang Hang Zhao Shengling Wang Yixian Chen |
| author_sort | Hongwei Shi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-7363ac30687847a98d2b4e31befc2e6b |
| institution | OA Journals |
| issn | 2667-2952 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | High-Confidence Computing |
| spelling | doaj-art-7363ac30687847a98d2b4e31befc2e6b2025-08-20T01:59:48ZengElsevierHigh-Confidence Computing2667-29522024-12-014410021010.1016/j.hcc.2024.100210Bioinvasion risk analysis based on automatic identification system and marine ecoregion dataHongwei Shi0Chenyu Wang1Hang Zhao2Shengling Wang3Yixian Chen4School of Artificial Intelligence, Beijing Normal University, Beijing 100875, ChinaSchool of Artificial Intelligence, Beijing Normal University, Beijing 100875, China; Department of Computer Science, Georgia State University, Atlanta 30302, USASchool of Artificial Intelligence, Beijing Normal University, Beijing 100875, China; Corresponding author.School of Artificial Intelligence, Beijing Normal University, Beijing 100875, ChinaDepartment of Computer Science, Georgia State University, Atlanta 30302, USAThe 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.http://www.sciencedirect.com/science/article/pii/S2667295224000138Biological invasionSpecies invasion networkGlobal shipping network |
| spellingShingle | Hongwei Shi Chenyu Wang Hang Zhao Shengling Wang Yixian Chen Bioinvasion risk analysis based on automatic identification system and marine ecoregion data High-Confidence Computing Biological invasion Species invasion network Global shipping network |
| title | Bioinvasion risk analysis based on automatic identification system and marine ecoregion data |
| title_full | Bioinvasion risk analysis based on automatic identification system and marine ecoregion data |
| title_fullStr | Bioinvasion risk analysis based on automatic identification system and marine ecoregion data |
| title_full_unstemmed | Bioinvasion risk analysis based on automatic identification system and marine ecoregion data |
| title_short | Bioinvasion risk analysis based on automatic identification system and marine ecoregion data |
| title_sort | bioinvasion risk analysis based on automatic identification system and marine ecoregion data |
| topic | Biological invasion Species invasion network Global shipping network |
| url | http://www.sciencedirect.com/science/article/pii/S2667295224000138 |
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