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Zhou Yuting, Ge Xuezhen, Zou Ya, Guo Siwei, Wang Tao, Tao Jing, Zong Shixiang. Prediction of the potential geographical distribution of Hylurgus ligniperda at the global scale and in China using the Maxent model[J]. Journal of Beijing Forestry University, 2022, 44(11): 90-99. DOI: 10.12171/j.1000-1522.20210345
Citation: Zhou Yuting, Ge Xuezhen, Zou Ya, Guo Siwei, Wang Tao, Tao Jing, Zong Shixiang. Prediction of the potential geographical distribution of Hylurgus ligniperda at the global scale and in China using the Maxent model[J]. Journal of Beijing Forestry University, 2022, 44(11): 90-99. DOI: 10.12171/j.1000-1522.20210345

Prediction of the potential geographical distribution of Hylurgus ligniperda at the global scale and in China using the Maxent model

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  • Received Date: September 04, 2021
  • Revised Date: November 04, 2021
  • Accepted Date: September 06, 2022
  • Available Online: November 04, 2022
  • Published Date: November 24, 2022
  •   Objective  Hylurgus ligniperda is an important quarantine pest of pine species, which has caused severe damages on pines in Chile, New Zealand and many other countries. The pest was recently confirmed to have invaded and established populations in Shandong Province of eastern China through imported wood materials, posing threats to the forestry security of China. Thus, accurate prediction of the climate-suitable regions of H. ligniperda is urgent for relevant institutions to take efficient quarantine and control measures, thus reducing the potential ecological and economic losses.
      Method  Our research used Maxent model to predict the climate-suitable regions of H. ligniperda both at the global scale and in China, following the steps of bioclimatic variable selecting and model parameter optimizing. ArcGIS software was used to visualize the predictive results and make area statistics. The model results were used to analyze the contributing bioclimatic variables affecting the colonization of the pest.
      Result  Compared with the Maxent model with the default parameters, the accuracy of the model with optimized parameters was significantly improved, with the average AUC value of 0.964 6. Meanwhile, the predictive results showed that the climate-suitable regions were mainly distributed in Europe, the east and west coasts of North America, the east of Asia, the southeast of South America, the southernmost tip of Africa and the southeast coast of Oceania, with the very suitable regions, suitable regions and marginal regions accounting for 1.21%, 1.92% and 3.95%, respectively. Within China, the climate-suitable regions of the pest were mainly located in the middle and south zones, which was bounded to Taiwan Province in the South and Dalian of Liaoning Province in the north. The areas of very suitable regions, suitable regions and marginal regions accounted for 0.28%, 5.00% and 13.43%, respectively. The bioclimatic variables having the most significant contribution are the precipitation of the driest quarter (37.9%), the minimum temperature of the coldest month (25.4%), the temperature seasonality (12.7%), the maximum temperature of the warmest month (7%) and the annual precipitation (6.6%).
      Conclusion  Except for the areas where H. ligniperda already existed, the pest has not occurred in the climate-suitable regions in the southeast and northwest of the United States, the east of Argentina, the southern Brazil and most of China, indicating the high risk of H. ligniperda invasion in these regions. The climate-suitable areas of H. ligniperda in China are mainly represented by suitable regions and marginal regions, including almost all provinces in central and southern China, among them the coastal areas and surrounding regions of Shandong Province and Jiangsu Province, Western China, central and southern China have relatively higher suitability. Therefore, it is suggested that the survey and prevention measures should be implemented to control the spread of H. ligniperda, while the quarantine and control on wooden material should be strengthened at entry ports.
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