Ma Rui, Li Chunfu, Gao Ai, Jiang Na, Li Jian, Hu Wei, Feng Xinyu
College of Life Sciences, Inner Mongolia University, Hohhot, China.
Basic Medical College, Guangxi University of Chinese Medicine, Nanning, Guangxi, China.
PLoS Negl Trop Dis. 2024 Apr 29;18(4):e0012108. doi: 10.1371/journal.pntd.0012108. eCollection 2024 Apr.
Ticks are a hematophagous parasite and a vector of pathogens for numerous human and animal diseases of significant importance. The expansion of tick distribution and the increased risk of tick-borne diseases due to global climate change necessitates further study of the spatial distribution trend of ticks and their potential influencing factors. This study constructed a dataset of tick species distribution in Xinjiang for 60 years based on literature database retrieval and historical data collection (January 1963-January 2023). The distribution data were extracted, corrected, and deduplicated. The dominant tick species were selected for analysis using the MaxEnt model to assess their potential distribution in different periods under the current and BCC-CSM2.MR mode scenarios. The results indicated that there are eight genera and 48 species of ticks in 108 cities and counties of Xinjiang, with Hyalomma asiaticum, Rhipicephalus turanicus, Dermacentor marginatus, and Haemaphysalis punctatus being the top four dominant species. The MaxEnt model analysis revealed that the suitability areas of the four dominant ticks were mainly distributed in the north of Xinjiang, in areas such as Altay and Tacheng Prefecture. Over the next four periods, the medium and high suitable areas within the potential distribution range of the four tick species will expand towards the northwest. Additionally, new suitability areas will emerge in Altay, Changji Hui Autonomous Prefecture, and other local areas. The 60-year tick dataset in this study provides a map of preliminary tick distribution in Xinjiang, with a diverse array of tick species and distribution patterns throughout the area. In addition, the MaxEnt model revealed the spatial change characteristics and future distribution trend of ticks in Xinjiang, which can provide an instrumental data reference for tick monitoring and tick-borne disease risk prediction not only in the region but also in other countries participating in the Belt and Road Initiative.
蜱是一种吸血寄生虫,也是许多对人类和动物具有重大意义的疾病的病原体传播媒介。由于全球气候变化,蜱的分布范围不断扩大,蜱传疾病的风险增加,因此有必要进一步研究蜱的空间分布趋势及其潜在影响因素。本研究基于文献数据库检索和历史数据收集(1963年1月至2023年1月),构建了一个60年来新疆蜱种分布数据集。对分布数据进行提取、校正和去重。选取优势蜱种,采用MaxEnt模型进行分析,以评估其在当前和BCC-CSM2.MR模式情景下不同时期的潜在分布。结果表明,新疆108个市县共有蜱8属48种,其中亚洲璃眼蜱、图兰扇头蜱、边缘革蜱和微小牛蜱为前四大优势种。MaxEnt模型分析显示,这四种优势蜱的适宜区域主要分布在新疆北部,如阿勒泰地区和塔城地区。在接下来的四个时期,这四种蜱潜在分布范围内的中高适宜区域将向西北方向扩展。此外,阿勒泰、昌吉回族自治州等局部地区将出现新的适宜区域。本研究中的60年蜱数据集提供了新疆蜱初步分布图谱,该地区蜱种和分布模式多样。此外,MaxEnt模型揭示了新疆蜱的空间变化特征和未来分布趋势,可为该地区乃至其他参与“一带一路”倡议国家的蜱监测和蜱传疾病风险预测提供有用的数据参考。