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. 2021 Jan 21;12(2):92.
doi: 10.3390/insects12020092.

Predicting the Distribution of the Invasive Species Leptocybe invasa: Combining MaxEnt and Geodetector Models

Hua Zhang  1 , Jinyue Song  1 , Haoxiang Zhao  1 , Ming Li  1 , Wuhong Han  1
Affiliations

Predicting the Distribution of the Invasive Species Leptocybe invasa: Combining MaxEnt and Geodetector Models

Hua Zhang et al. Insects. .

Abstract

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).

Keywords: L. invasa; MaxEnt; climate change; suitable growth area.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Distribution data of L. invasa in China.
Figure 2
Figure 2
Reliability test of the distribution model created for L. invasa.
Figure 3
Figure 3
Permutation importance of variables for modeling.
Figure 4
Figure 4
The jackknife test result of environmental factor for L. invasa.
Figure 5
Figure 5
Response curves of probability of presence for L. invasa.
Figure 6
Figure 6
Potential current and suitable habitat for L. invasa in China.
Figure 7
Figure 7
Potentially suitable climatic distribution of L. invasa under different climate change scenarios in China.
Figure 8
Figure 8
Changes in the potential geographical distribution of L. invasa under climate change scenarios.
Figure 9
Figure 9
Highly suitable area centroid distributional shifts under climate change for L. invasa.
Figure 10
Figure 10
Analysis of the multivariate environmental similarity surface (MESS) of the potential area of distribution for L. invasa under future climate change.
See this image and copyright information in PMC

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