Zhang Hai Tao, Luo Du, Mu Xi Dong, Xu Meng, Wei Hui, Luo Jian Ren, Zhang Jia En, Hu Yin Chang
Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences/Key Laboratory of Tropical & Subtropical Fishery Resource Application & Cultivation, Ministry of Agriculture, Guangzhou 510380, China.
College of Fisheries and Life Science, Shanghai Ocean University, Shanghai 201306, China.
Ying Yong Sheng Tai Xue Bao. 2016 Apr 22;27(4):1277-1284. doi: 10.13287/j.1001-9332.201604.027.
The high-risk invasive apple snail Pomacea canaliculata has greatly threatened the agriculture, ecosystem integrity and public health. In order to provide scientific evidence for effective prevention and control of P. canaliculata, a most suitable ecological niche model was selected to predict the potential suitable distribution areas of P. canaliculata in China. Based on 377 reported occurrence points and 19 bioclimatic variables, four ecological niche models, MaxEnt, GARP, BIOCLIM, and DOMAIN, the potential geographic suitable distribution areas were predicted for the invasive snail. Then, the results of different models were analyzed and compared with two statistical criteria, the area under the Receiver Operating Characteristic curve (AUC) and Kappa value. The results showed that all of the four ecological niche models could simulate the snail's distributions very well. More specifically, the MaxEnt model outperformed the others in all aspects of predicting the snail's potential distribution (AUC=0.955±0.004, Kappa=0.845±0.017), followed by GARP and DOMAIN. Although BIOCLIM offered the lowest prediction accuracy, its AUC was 0.898±0.017 and its Kappa value was 0.771±0.025. Based on the MaxEnt model, the prediction results showed that the potential suitable distribution areas of P. canaliculata were mainly located in the south of 30° N in China, but there was some regions spreading over the north of 30° N. The potential areas accounted for 13.2% of the national land in area. Notably, Guangdong, Guangxi, Hunan, Chongqing, Zhejiang and the coastal areas of Fujian were potentially high-risk areas. In conclusion, this study would be an important reference for the prevention and control of the invasive apple snail P. canaliculata and it also would be an example of predicting the potential distribution of aquatic alien species on large scale.
高风险入侵物种福寿螺已对农业、生态系统完整性及公众健康构成严重威胁。为给福寿螺的有效防控提供科学依据,选用最合适的生态位模型预测福寿螺在中国的潜在适生区。基于377个已知分布点和19个生物气候变量,运用4种生态位模型(MaxEnt、GARP、BIOCLIM和DOMAIN)预测该入侵螺类的潜在地理适生区。然后,采用两种统计指标(受试者工作特征曲线下面积(AUC)和Kappa值)对不同模型的结果进行分析比较。结果表明,4种生态位模型均能较好地模拟福寿螺的分布。具体而言,MaxEnt模型在预测福寿螺潜在分布的各方面表现最优(AUC=0.955±0.004,Kappa=0.845±0.017),其次是GARP和DOMAIN模型。尽管BIOCLIM模型的预测精度最低,但其AUC为0.898±0.017,Kappa值为0.771±0.025。基于MaxEnt模型的预测结果显示,福寿螺在中国的潜在适生区主要位于北纬30°以南,但也有部分区域分布在北纬30°以北,潜在适生区面积占国土面积的13.2%。值得注意的是,广东、广西、湖南、重庆、浙江及福建沿海地区为潜在高风险区。综上,本研究可为福寿螺的防控提供重要参考,也是大规模预测水生外来物种潜在分布的一个范例。