Factors affecting Pomacea distribution and prediction of suitable distribution areas of Pomacea in Dali Bai Autonomous Prefecture of Yunnan Province
10.16250/j.32.1915.2024201
- VernacularTitle:云南省大理白族自治州福寿螺分布影响因素及适生区扩散预测
- Author:
Zhongqiu LI
1
,
2
,
3
;
Yuhua LIU
3
,
4
;
Yunhai GUO
1
;
Zixin WEI
5
;
Junhu CHEN
1
;
Qiang WANG
1
;
Tianmei LI
4
;
Shizhu LI
1
Author Information
1. National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, School of Global Health, Shanghai Jiao Tong University School of Medicine and Chinese Center for Tropical Diseases Research, Shanghai 200025, China
2. Dali Bai Autonomous Prefecture Institute of Schistosomiasis Control, Dali, Yunnan 671099, China
3. Co-first authors
4. Dali Bai Autonomous Prefecture Institute of Schistosomiasis Control, Dali, Yunnan 671099, China
5. Shanghai Center for Disease Control and Prevention, China
- Publication Type:Journal Article
- Keywords:
Pomacea;
Distribution;
Spread;
Maximum entropy model;
Suitable distribution area;
Prediction;
Dali Bai Autonomous Prefecture
- From:
Chinese Journal of Schistosomiasis Control
2025;37(1):69-75
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the factors affecting the distribution of Pomacea and project the trends in the spread of suitable distribution areas of Pomacea in 2050 and 2070 in Dali Bai Autonomous Prefecture, so as to provide insights into Pomacea control in the prefecture. Methods The longitudes and latitudes of Pomacea sampling sites were captured based on Pomacea field survey data in 12 cities (counties) of Dali Bai Autonomous Prefecture from 2023 to 2024. A total of 19 climatic factors (annual mean temperature, mean diurnal range, isothermality, temperature seasonality, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature annual range, mean temperature of the wettest quarter, mean temperature of the driest quarter, mean temperature of the warmest month, mean temperature of the coldest month, annual precipitation, precipitation of the wettest month, precipitation of the driest month, precipitation seasonality, precipitation of the wettest quarter, precipitation of the driest quarter, mean temperature of the warmest quarter, and mean temperature of the coldest quarter) and representative concentration pathways (RCPs) were retrieved from the world climate database (www.worldclim.org). All climatic variables were employed to create a maximum entropy (MaxEnt) model. The predictive accuracy of the model was assessed with the area under the receiver operating characteristic (ROC) curve (AUC), and the contributions of these 19 climatic factors to the distribution of Pomacea were analyzed in Dali Bai Autonomous Prefecture using Jackknife test. In addition, the suitable distribution areas of Pomacea were predicted with the MaxEnt model in Dali Bai Autonomous Prefecture in 2024 and in 2050 and 2070 under RCP4.5. Results Data pertaining to 91 Pomacea sampling sites were captured. ROC analysis revealed the MaxEnt model had an AUC value of 0.885 ± 0.088 for predicting the suitable distribution areas of Pomacea in Dali Bai Autonomous Prefecture. Of the 19 climatic factors, the maximum temperature of the warmest month had the highest contribution to the distribution of Pomacea in Dali Bai Autonomous Prefecture, followed by mean temperature of the driest quarter, mean temperature of the wettest quarter and minimum temperature of the coldest month. The suitable distribution area of Pomacea was predicted to be 14 555.69 km2 in Dali Bai Autonomous Prefecture in 2024, and would expand gradually to the southeastern part of the prefecture in the future due to climatic factors. The suitable distribution areas of Pomacea were projected to expand to 21 475.61 km2 in 2050 and 25 782.52 km2 in 2070 in Dali Bai Autonomous Prefecture, respectively. Conclusions Temperature is an important contributor to the distribution of Pomacea in Dali Bai Autonomous Prefecture, and the suitable distribution area of Pomacea will gradually expand to the southeastern part of the prefecture in 2050 and 2070.
