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利用空间风险分析和媒介库蠓的生境连通性预测非洲马瘟传入中国的可能性。

Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides.

机构信息

College of Wildlife & Protected Area, Ministry of Education, Northeast Forestry University, 26 Hexing Road, Xiangfang District, Harbin, 150040, Heilongjiang Province, People's Republic of China.

Key Laboratory of Wildlife Diseases and Biosecurity Management of Heilongjiang Province, 26 Hexing Road, Xiangfang District, Harbin, 150040, Heilongjiang Province, People's Republic of China.

出版信息

Sci Rep. 2022 Mar 10;12(1):3910. doi: 10.1038/s41598-022-07512-w.

Abstract

African horse sickness (AHS) is a devastating equine infectious disease. On 17 March 2020, it first appeared in Thailand and threatened all the South-East Asia equine industry security. Therefore, it is imperative to carry out risk warnings of the AHS in China. The maximum entropy algorithm was used to model AHS and Culicoides separately by using climate and non-climate variables. The least cost path (LCP) method was used to analyze the habitat connectivity of Culicoides with the reclassified land cover and altitude as cost factors. The models showed the mean area under the curve as 0.918 and 0.964 for AHS and Culicoides. The prediction result map shows that there is a high risk area in the southern part of China while the habitats of the Culicoides are connected to each other. Therefore, the risk of introducing AHS into China is high and control of the border area should be strengthened immediately.

摘要

非洲马瘟(AHS)是一种毁灭性的马属动物传染病。2020 年 3 月 17 日,它首次出现在泰国,威胁到整个东南亚马业的安全。因此,在中国开展 AHS 风险预警迫在眉睫。本研究采用最大熵算法,分别利用气候和非气候变量对 AHS 和库蠓进行建模。采用最小成本路径(LCP)方法,以重新分类的土地覆盖和海拔为成本因素,分析库蠓的生境连通性。模型的曲线下平均面积(AUC)分别为 AHS 和库蠓的 0.918 和 0.964。预测结果图显示,中国南部存在高风险区域,而库蠓的栖息地相互连接。因此,AHS 传入中国的风险很高,应立即加强边境地区的管控。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3894/8913660/f5cccfd5d20c/41598_2022_7512_Fig1_HTML.jpg

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