Estimation of Spatial Distribution of <i>Dendrolimus punctatus</i> Disaster Risk in Shizhu County Based on MaxEnt Model

Xinyuan Yang; Shuisheng Huang; Xinyu Hu; Feng Jiang; Fangxin Meng; Linfeng Yu; Xianlin Qin

doi:10.12356/j.2096-8884.2024-0001

Volume 4 Issue 1

Feb. 2024

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Article Navigation > Terrestrial Ecosystem and Conservation > 2024 > 4(1): 48-58

Xinyuan Yang, Shuisheng Huang, Xinyu Hu, Feng Jiang, Fangxin Meng, Linfeng Yu, Xianlin Qin. Estimation of Spatial Distribution of Dendrolimus punctatus Disaster Risk in Shizhu County Based on MaxEnt Model[J]. Terrestrial Ecosystem and Conservation, 2024, 4(1): 48-58. doi: 10.12356/j.2096-8884.2024-0001

Citation:

Xinyuan Yang, Shuisheng Huang, Xinyu Hu, Feng Jiang, Fangxin Meng, Linfeng Yu, Xianlin Qin. Estimation of Spatial Distribution of Dendrolimus punctatus Disaster Risk in Shizhu County Based on MaxEnt Model[J]. Terrestrial Ecosystem and Conservation, 2024, 4(1): 48-58. doi: 10.12356/j.2096-8884.2024-0001

Citation:

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Estimation of Spatial Distribution of Dendrolimus punctatus Disaster Risk in Shizhu County Based on MaxEnt Model

doi: 10.12356/j.2096-8884.2024-0001

Xinyuan Yang^{1, 2
,},
Shuisheng Huang^{1, 2},
Xinyu Hu^{1, 2},
Feng Jiang^{1, 2},
Fangxin Meng^{1, 2},
Linfeng Yu^{1, 2},
Xianlin Qin^{1, 2
,
,}

1.
Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China
2.
Key Laboratory of Forestry Remote Sensing and Information System, Chinese Academy of Forestry, Beijing 100091, China

Received Date: 2024-01-08
Accepted Date: 2024-02-26

Available Online: 2024-04-19

Publish Date: 2024-02-29

Abstract

Abstract

Objective Accurately grasp the risk range of Dendrolimus punctatus in Shizhu Tujia Autonomous County, Chongqing, and provide a strong basis for timely and effective pest control. Method In this paper, the MaxEnt model has been used to estimate the risk of D. punctatus in the county using the data from 60 selected distribution points of D. punctatus. These points were combined with the topographic, climatic, and human factors in the growing area of Pinus massoniana. By analyzing the contribution rate and permutation importance of environmental indicators, as well as the response curve of environmental indicators, the suitable habitat conditions of D. punctatus in this county were analyzed. The risk areas were classified using the threshold of 'balance training omission, predicted area and threshold value logistic threshold' and the threshold of 'equate entropy of thresholded and original distributions logistic threshold' of the model. The risk level of D. punctatus disaster in this area was divided into low risk, medium risk, and high risk, and the area of each risk level was calculated using geographic information system software. The accuracy of the estimation was confirmed through the mean AUC value of the model, and the efficacy of risk classification was verified by comparing the proportional areas of each risk level to the area of D. punctatus aerial control in this county in 2022. Result 1) The main environmental factors affecting the survival of D. punctatus in this county were annual mean precipitation, monthly average potential evapotranspiration, distance to settlement, and altitude. 2) The mean AUC values of training and testing of the MaxEnt model were 0.92 and 0.87, respectively, and the standard deviation was 0.013, which was less than 0.05, indicating that the results of the model were excellent and the prediction results were reliable. It can be used to estimate the risk of D. punctatus disaster in this county. By comparing the area of D. punctatus aerial control in spring of Shizhu County in 2022, the area accounted for as high as 99.05%, indicating that the distribution of high-risk areas was highly unified with its actual distribution, and the classification effect was good. 3) The high-risk areas of D. punctatus disaster in this county were mainly concentrated in Linxi Town, Yuelai Town, Yuchi Town, Hezui Town, Wanchao Town and so on. The high-risk areas of Wangchang Town, Longsha Town, Wangjia Township, Xituo Town, Lichang Township, Yanxi Town, and Wanchao Town accounted for more than 90% of the P. massoniana area in each town. Conclusion The findings indicated that the high-risk areas for D. punctatus disaster in this county were predominantly located in the western and northern towns. By conducting statistical analyses on the distribution of high-risk areas both inter- and intra-town, a more comprehensive understanding of the distribution of D. punctatus disaster in Shizhu County was achieved, offering a scientific basis for targeted prevention and management of D. punctatus disaster.
- Dendrolimus punctatus,
- maximum entropy model,
- geographic information system,
- risk distribution

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References(25)

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