Abstract

Simple SummaryLeptocybe invasa is a global eucalyptus plantation invasive pest and the second alien invasive species in China. In this study, based on the current distribution data of L. invasa in China, combined with a geographic detector model and MaxEnt model, the main environmental variables were selected, and potential suitable growth areas of L. invasa in China in 2030 and 2050 were predicted. The results show that under the future climate change scenario, the potential distribution core areas of L. invasa in China will be located in Yunnan, Guangxi, Guangdong, and Hainan, and tend to spread to high latitudes (Hubei, Anhui, Zhejiang, Jiangsu, and other regions). Combined with the results of predicting the potential suitable zone in this study, we can clearly identify its diffusion trend, which has important theoretical significance for curbing the growth and development of L. invasa and formulating effective control measures.Leptocybe invasa is a globally invasive pest of eucalyptus plantations, and is steadily spread throughout China. Predicting the growth area of L. invasa in China is beneficial to the establishment of early monitoring, forecasting, and prevention of this pest. Based on 194 valid data points and 21 environmental factors of L. invasa in China, this study simulated the potential distribution area of L. invasa in China under three current and future climate scenarios (SSPs1–2.5, SSPs2–3.5, and SSPs5–8.5) via the MaxEnt model. The study used the species distribution model (SDM) toolbox in ArcGIS software to analyze the potential distribution range and change of L. invasa. The importance of crucial climate factors was evaluated by total contribution rate, knife-cut method, and environmental variable response curve, and the area under the receiver operating characteristic (ROC) curve was used to test and evaluate the accuracy of the model. The results showed that the simulation effect of the MaxEnt model is excellent (area under the ROC curve (AUC) = 0.982). The prediction showed that L. invasa is mainly distributed in Guangxi, Guangdong, Hainan, and surrounding provinces, which is consistent with the current actual distribution range. The distribution area of the potential high fitness zone of L. invasa in the next three scenarios increases by between 37.37% and 95.20% compared with the current distribution. Climate change affects the distribution of L. invasa, with the annual average temperature, the lowest temperature of the coldest month, the average temperature of the driest season, the average temperature of the coldest month, and the precipitation in the wettest season the most important. In the future, the core areas of the potential distribution of L. invasa in China will be located in Yunnan, Guangxi, Guangdong, and Hainan. They tend to spread to high latitudes (Hubei, Anhui, Zhejiang, Jiangsu, and other regions).

Highlights

  • Alien invasive species refer to non-native species that migrate from their place of origin to a new ecological environment via natural or human-made means

  • The area under the curve (AUC) value tested by the MaxEnt model was 0.982, which shows that the prediction result of the model has high accuracy and credibility [36], and that the prediction result is consistent with the actual distribution of L. invasa in China

  • This is consistent with a study by Huang Rui, which found that the growth, development, reproduction, and distribution of L. invasa are mainly affected by temperature [42]

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Summary

Introduction

Alien invasive species refer to non-native species that migrate from their place of origin to a new ecological environment via natural or human-made means. They can reproduce in nature, resulting in damage to local biodiversity and impacts on the local ecological environment [1]. To effectively prevent the harm caused by invasive species, it is essential to study their geographical distribution. Studying the potential geographical distribution pattern of invasive species in the context of future climate change has important theoretical and practical significance for putting forward reasonable and effective biodiversity conservation measures

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