Potential Global Invasion Risk of Scale Insect Pests Based on a Self-Organizing Map
2023
Jun Deng | Junjie Li | Xinrui Zhang | Lingda Zeng | Yanqing Guo | Xu Wang | Zijing Chen | Jiali Zhou | Xiaolei Huang
In the present study, a global presence/absence dataset including 2486 scale insect species in 157 countries was extracted to assess the establishment risk of potential invasive species based on a self-organizing map (SOM). According to the similarities in species assemblages, a risk list of scale insects for each country was generated. Meanwhile, all countries in the dataset were divided into five clusters, each of which has high similarities of species assemblages. For those countries in the same neuron of the SOM output, they may pose the greatest threats to each other as the sources of potential invasive scale insect species, and therefore, require more attention from quarantine departments. In addition, normalized &zeta:i values were used to measure the uncertainty of the SOM output. In total, 9 out of 63 neurons obtained high uncertainty with very low species counts, indicating that more investigation of scale insects should be undertaken in some parts of Africa, Asia and Northern Europe.
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