基于MaxEnt模型的新疆地区钝缘蜱适生区分布研究

doi:10.11853/j.issn.1003.8280.2023.05.015

摘要/Abstract

摘要： 目的研究当前及未来气候模式下新疆维吾尔自治区（新疆）钝缘蜱适生区分布情况。方法通过实地采样及文献检索,选取2002－2022年间新疆地区钝缘蜱的分布数据,利用ArcGIS 10.6软件对获取到的钝缘蜱分布数据进行筛选；从WorldClim 2.1数据库中获取新疆地区过去30年及未来80年气候数据,使用最大熵（MaxEnt）模型的折刀法测试结合Spearman相关性分析筛选主要环境变量。根据筛选后的钝缘蜱分布数据及环境变量建立MaxEnt模型,对新疆地区钝缘蜱当下及未来潜在适生区进行预测和预估。通过受试者工作特征曲线（ROC）的曲线下面积（AUC）来评估模型的预测性能；根据 MaxEnt 模型中的折刀法测试检验不同环境变量对钝缘蜱潜在适生区的相对影响；根据MaxEnt模型得出的响应曲线,分析不同环境变量对钝缘蜱潜在出现概率的具体影响；利用ArcGIS 10.6软件对结果进行可视化和重分类,分析当下及未来（ssp245）气候模式下新疆地区钝缘蜱的潜在分布区及适生区面积。结果经过查询比对从82条钝缘蜱分布数据与20个环境变量中,共筛选出65条分布数据与6个环境变量。所构建的MaxEnt模型AUC值为0.892,模型预测精度为“良好”。折刀法测试结果显示,影响钝缘蜱分布的主导气候因子分别为最冷月最低气温和最干季节降水量,贡献率分别为53.32%和15.68%。响应曲线结果显示,适宜的温度及湿度将极大地提高钝缘蜱的出现概率。模型预测图及重分类结果显示,在当前气候条件下,钝缘蜱在新疆地区的适生区主要分布于环塔里木盆地周边地区及吐鲁番盆地,最适生区和高适生区面积分别为8.49和11.99万km²,适生区总面积约占新疆地区总面积的30.01%。在ssp245气候模式下,2021－2040年最适生区将增加至9.37万km²,2081－2100年高适生区将增加至13.42万km²。结论温度是影响钝缘蜱分布的最主要因素,未来气候模式下钝缘蜱最适生区和高适生区面积将有所增加。

关键词: 新疆维吾尔自治区, 钝缘蜱, 最大熵模型, 适生区, 气候因子

Abstract: Objective To study the distribution of suitable habitats of Ornithodoros ticks in Xinjiang Uygur Autonomous Region (Xinjiang),China under current and future climate scenarios.Methods The Ornithodoros distribution data in Xinjiang in 2002-2022 were obtained through field sampling and literature search. The obtained distribution data were sorted and plotted by ArcGIS 10.6 software. The climate data in Xinjiang in the past 30 years and future 80 years were obtained through the WorldClim 2.1 database. The main environmental variables were selected using the maximum entropy (MaxEnt) jackknife test and Spearman correlation analysis. The selected Ornithodoros distribution data and environmental variables were used to construct a MaxEnt model for predicting and projecting the current and future potential suitable habitats of Ornithodoros in Xinjiang. The predictive performance of the model was assessed using the area under the receiver operating characteristic curve (AUC). The relative effects of different environmental variables on the potential distribution of Ornithodoros were assessed using the MaxEnt jackknife test. The specific effects of environmental variables on the potential distribution of Ornithodoros were analyzed using the response curves derived from the MaxEnt model. The results were visualized and reclassified using ArcGIS 10.6 software to analyze the potential distribution of Ornithodoros and the suitable habitat area in Xinjiang under current and future (ssp245) climate scenarios.Results A total of 65 distribution data of Ornithodoros and six environmental variables were selected from 82 pieces of distribution data and 20 environmental variables through query and comparison. The AUC of the constructed MaxEnt model was 0.892,with good prediction accuracy. The jackknife test showed that the dominant climatic factors influencing the distribution of Ornithodoros were the minimum temperature in the coldest month and the precipitation in the driest season, with the contribution rates being 53.32% and 15.68%, respectively. The response curves showed that appropriate temperature and humidity would greatly increase the probability of occurrence of Ornithodoros. According to the model prediction map and reclassification results, under current climatic conditions, the suitable habitats of Ornithodoros in Xinjiang were mainly distributed around the Tarim Basin and the Turpan Basin; the areas of the most suitable habitats and highly suitable habitats were 84 900 km² and 119 900 km², respectively; the total area of the suitable habitats accounted for about 30.01% of the total area of Xinjiang. Under the ssp245 climate scenario, the most suitable area would increase to 93 700 km² in 2021-2040, and the highly suitable area would increase to 134 200 km² in 2081-2100.Conclusions Temperature is the most important factor influencing the distribution of Ornithodoros. The most suitable area and highly suitable area of Ornithodoros would increase under future climate scenarios.

Key words: Xinjiang Uygur Autonomous Region, Ornithodoros, Maximum entropy model, Suitable habitat, Climatic factor

中图分类号:

S852.74⁺6

刘明明, 刘丹丹, 芦星, 王水怡, 刘雨桐, 姜冰冰, 朱慧茹, 杜少磊, 巴音查汗, 张伟. 基于MaxEnt模型的新疆地区钝缘蜱适生区分布研究[J]. 中国媒介生物学及控制杂志, 2023, 34(5): 671-678.

LIU Ming-ming, LIU Dan-dan, LU Xing, WANG Shui-yi, LIU Yu-tong, JIANG Bing-bing, ZHU Hui-ru, DU Shao-lei, Bayinchahan, ZHANG Wei. MaxEnt model-based analysis of distribution of suitable habitats of Ornithodoros ticks in Xinjiang Uygur Autonomous Region,China[J]. Chinese Journal of Vector Biology and Control, 2023, 34(5): 671-678.

参考文献

[1] Wen TH,Chen Z. The world list of ticks. 1. Argasidae and Nuttallielidae （Acari:Ixodida）[J]. Chin J Parasitol Parasit Dis,2016,34（1）:58-69,74. （in Chinese）温廷桓,陈泽. 世界蜱类名录1. 软蜱科与纳蜱科（螨亚纲:蜱目）[J]. 中国寄生虫学与寄生虫病杂志,2016,34（1）:58-69,74.
[2] Wang QL,Jiang YX,Xu JP,et al. Species and pathogens identification of soft ticks in Tarim red deer by PCR[J]. Chin Vet Sci,2022,52（3）:339-343. DOI:10.16656/j.issn.1673-4696.2022.0043.（in Chinese）王奇林,蒋玉曦,徐建平,等. 塔里木马鹿体表寄生的软蜱种类及其携带病原的PCR鉴定[J]. 中国兽医科学,2022,52（3）:339-343. DOI:10.16656/j.issn.1673-4696.2022.0043.
[3] Jiapaer A,He WW,Shi QY,et al. Investigation on the distribution of ticks in spring in Shanshan county,Xinjiang[J]. China Anim Health Insp,2022,39（1）:13-17. DOI:10.3969/j.issn.1005-944X.2022.01.004.（in Chinese）阿力木江·加帕尔,何文文,史倩云,等. 新疆鄯善县春季蜱虫分布调查[J]. 中国动物检疫,2022,39（1）:13-17. DOI:10.3969/j.issn.1005-944X.2022.01.004.
[4] Telmadarraiy Z,Kooshki H,Edalat H,et al. Study on hard and soft ticks of domestic and wild animals in Western Iran[J]. J Arthropod Borne Dis,2022,16（3）:225-232. DOI:10.18502/jad.v16i3.12039.
[5] Zhao L,Wang JL,Ding YL,et al. Theileria ovis （Piroplasmida:Theileriidae） detected in Melophagus ovinus （Diptera:Hippoboscoidea） and Ornithodoros lahorensis （Ixodida:Argasidae） removed from sheep in Xinjiang,China[J]. J Med Entomol,2020,57（2）:631-635. DOI:10.1093/jme/tjz193.
[6] Jori F,Bastos A,Boinas F,et al. An updated review of Ornithodoros ticks as reservoirs of African swine fever in Sub-Saharan Africa and Madagascar[J]. Pathogens,2023,12（3）:469. DOI:10.3390/pathogens12030469.
[7] Hanafi-Bojd AA,Jafari S,Telmadarraiy Z,et al. Spatial distribution of ticks （Arachniada:Argasidae and Ixodidae） and their infection rate to Crimean-Congo hemorrhagic fever virus in Iran[J]. J Arthropod Borne Dis,2021,15（1）:41-59. DOI:10.18502/jad.v15i1.6485.
[8] WeiLT. Identification,biological characteristics analysis and morphological description of different inatars of Ornithodoros lahorensis[D]. Urumqi:Xinjiang Agricultural University,2021. （in Chinese）韦丽婷. 拉合尔钝缘蜱鉴定、生活特性研究及不同龄期形态结构观察[D]. 乌鲁木齐:新疆农业大学,2021.
[9] Robayo-Sánchez LN,López Y,Muñoz-Leal S,et al. Laboratory life cycle of Ornithodoros puertoricensis （Ixodida:Argasidae） collected in the Colombian Caribbean[J]. Exp Appl Acarol,2022,88（3/4）:387-395. DOI:10.1007/s10493-022-00759-y.
[10] Lyu JZ,Zhao L,Zhao YL,et al. Morphological and molecular biology identification of Ornithodoros lahorensis[J]. China Anim Husb Vet Med,2017,44（4）:1149-1158. DOI:10.16431/j.cnki.1671-7236.2017.04.030.（in Chinese）吕继洲,赵丽,赵昱林,等. 拉合尔钝缘蜱的形态学及分子生物学鉴定[J]. 中国畜牧兽医,2017,44（4）:1149-1158. DOI:10.16431/j.cnki.1671-7236.2017.04.030.
[11] Cun DJ,Wang Q,Yao XY,et al. Potential suitable habitats of Haemaphysalis longicornis in China under different climatic patterns[J]. Chin J Schisto Control,2021,33（4）:359-364. DOI:10.16250/j.32.1374.2021023.（in Chinese）寸得娇,王强,姚晓燕,等. 不同气候模式下我国长角血蜱潜在适生区预测[J]. 中国血吸虫病防治杂志,2021,33（4）:359-364. DOI:10.16250/j.32.1374.2021023.
[12] Jiang T,Lyu YR,Huang JL,et al. New scenarios of CMIP6 model （SSP-RCP） and its application in the Huaihe river basin[J]. Adv Met Sci Technol,2020,10（5）:102-109. DOI:10.3969/j.issn.2095-1973.2020.05.016.（in Chinese）姜彤,吕嫣冉,黄金龙,等. CMIP6模式新情景（SSP-RCP）概述及其在淮河流域的应用[J]. 气象科技进展,2020,10（5）:102-109. DOI:10.3969/j.issn.2095-1973.2020.05.016.
[13] Sillero N. What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods[J]. Ecol Model,2011,222（8）:1343-1346. DOI:10.1016/j.ecolmodel.2011.01.018.
[14] Lemke D,Hulme PE,Brown JA,et al. Distribution modelling of Japanese honeysuckle （Lonicera japonica） invasion in the Cumberland Plateau and Mountain Region,USA[J]. For Ecol Manage,2011,262（2）:139-149. DOI:10.1016/j.foreco.2011. 03.014.
[15] Xu YD,Zhu RF,Gao LF,et al. Predicting the current and future distributions of Pennisetum alopecuroides （L.） in China under climate change based on the MaxEnt model[J]. PLoS One,2023,18（4）:e0281254. DOI:10.1371/journal.pone.0281254.
[16] Qin Z,Zhang JE,DiTommaso A,et al. Predicting invasions of Wedelia trilobata （L.） Hitchc. with MaxEnt and GARP models[J]. J Plant Res,2015,128（5）:763-775. DOI:10.1007/s10265-015-0738-3.
[17] Zhu YJ,Wei W,Li H,et al. Modelling the potential distribution and shifts of three varieties of Stipa tianschanica in the eastern Eurasian Steppe under multiple climate change scenarios[J]. Glob Ecol Conserv,2018,16:e00501. DOI:10.1016/j.gecco. 2018.e00501.
[18] Guillera-Arroita G,Lahoz-Monfort JJ,Elith J,et al. Is my species distribution model fit for purpose? Matching data and models to applications[J]. Glob Ecol Biogeogr,2015,24（3）:276-292. DOI:10.1111/geb.12268.
[19] Pramanik M,Paudel U,Mondal B,et al. Predicting climate change impacts on the distribution of the threatened Garcinia indica in the Western Ghats,India[J]. Clim Risk Manag,2018,19:94-105. DOI:10.1016/j.crm.2017.11.002.
[20] Wardhana AH,Cecchi G,Muharsini S,et al. Environmental and phylogeographical determinants of the distribution of the Old World screwworm fly in Indonesia[J]. Acta Trop,2014,138 Suppl:S62-S68. DOI:10.1016/j.actatropica.2014.06.001.
[21] Khali GM,Hoogstraal H. The life cycle of Ornithodoros （Alectorobius） amblus （Acari:Ixodoidea:Argasidae） in the laboratory[J]. J Med Entomol,1981,18（2）:134-139. DOI:10.1093/jmedent/18.2.134.
[22] Lazzari CR,Fauquet A,Lahondère C,et al. Soft ticks perform evaporative cooling during blood-feeding[J]. J Insect Physiol,2021,130:104197. DOI:10.1016/j.jinsphys.2021.104197.
[23] He WW,Wu J,Hulcha,et al. Evaluation of habitat adaptability of Dermacentor niveus and D. marginatus in Xinjiang based on maximum entropy model[J]. Chin J Parasitol Parasit Dis,2022,40（1）:68-75,83. DOI:10.12140/j.issn.1000-7423.2022.01.010.（in Chinese）何文文,伍军,呼尔查,等. 基于最大熵模型的新疆银盾革蜱和边缘革蜱生境适应性评价[J]. 中国寄生虫学与寄生虫病杂志,2022,40（1）:68-75,83. DOI:10.12140/j.issn.1000-7423. 2022.01.010.
[24] Li ZQ,Li LH,Yin HJ,et al. Distribution and suitable habitats of ticks in the Yangtze River Delta urban agglomeration[J]. Chin J Schisto Control,2021,33（4）:365-372. DOI:10.16250/j.32. 1374.2021068.（in Chinese）李中秋,李兰花,殷会军,等. 长三角城市群蜱媒分布及适生区分析[J]. 中国血吸虫病防治杂志,2021,33（4）:365-372. DOI:10.16250/j.32.1374.2021068.