Risk assessment of Anopheles barbirostris invasion responding to future climate change in China

doi:10.11853/j.issn.1003.8280.2023.02.003

Abstract

Abstract: Objective To assess the risk of Anopheles barbirostris invading China under future climate change scenarios, and to provide a basis for monitoring and early warning. Methods The maximum entropy model was used to predict the recent global potential distribution and project the future potential distribution of An. barbirostris in China. The main environmental factors affecting the distribution of An. barbirostris were analyzed based on the contribution rate of environmental factors. The vector risk assessment index system was established to calculate the comprehensive risk value of invasive species. Results A total of 99 effective distribution points of An. barbirostris were identified. The rainfall in September played a leading role in affecting the distribution of potential suitable areas of An. barbirostris. The omission rate of model training was roughly the same as the theoretical omission rate, and the area under the receiver operating characteristic curve was 0.988. Under the current climate scenario, the potential suitable areas of An. barbirostris in China were mainly in Guangdong province, Guangxi Zhuang Autonomous Region, and Hainan province as well as the eastern Sichuan Basin. In 2081-2100, China has the largest potential suitable area (207.51×10⁴ km²) under the shared socioeconomic pathway 585 climate scenario, and the area of suitable area will show an increasing trend under various climate scenarios. Through the risk assessment index system, it was calculated that the comprehensive risk value of An. barbirostris was 0.57, so An. barbirostris belonged to the medium-risk invasive species. Conclusions An. barbirostris is a species with a medium invasion risk. In the future, the mosquito vector surveillance system should be improved according to the distribution of its suitable areas, and scientific prevention and control strategies should be formulated.

Key words: MaxEnt, Climate change, Potential suitable area, Invasion risk assessment, Anopheles barbirostris

摘要： 目的评估未来气候变化情景下须喙按蚊入侵中国的风险，为监测预警提供依据。方法使用最大熵模型预测须喙按蚊近期在全球的潜在分布状况和预估未来在中国的潜在分布区变化趋势。基于环境因子的贡献率，分析影响须喙按蚊分布的主要环境因子；构建病媒生物风险评估指标体系用于计算入侵物种的综合风险值。结果共筛选出须喙按蚊有效分布点99个；9月降雨量在影响须喙按蚊潜在适生区分布中占有主导作用；模型训练遗漏率与理论遗漏率大体一致，受试者工作特征曲线下面积（AUC）值为0.988；当前气候情景下，须喙按蚊在中国的潜在适生区主要集中在广东、广西、海南省（自治区）以及四川盆地东部等；须喙按蚊在未来2081－2100年共享社会经济路径（SSP）585气候情景下中国的潜在适生区范围最广（207.51×10⁴ km²），未来各气候情景下适生区面积呈增加趋势；通过风险评估指标体系，计算得出须喙按蚊的综合风险值为0.57，属于中等入侵风险物种。结论须喙按蚊在中国属于中等入侵风险物种，未来应根据其适生区分布情况完善蚊媒监测系统，制定科学的防控策略。

关键词: 最大熵模型, 气候变化, 潜在适生区, 入侵风险评估, 须喙按蚊

CLC Number:

R384.1

LI Chao, YANG Hai-bo, LIANG Ying, WANG Guo-zheng, LI Yang, WANG Bin, LI Hong-yun, WANG Jun, LIU Qi-yong. Risk assessment of Anopheles barbirostris invasion responding to future climate change in China[J]. Chinese Journal of Vector Biology and Control, 2023, 34(2): 145-153.

李超, 杨海波, 梁莹, 王国政, 李阳, 王彬, 李泓运, 王君, 刘起勇. 须喙按蚊入侵中国对未来气候变化的响应及风险评估[J]. 中国媒介生物学及控制杂志, 2023, 34(2): 145-153.

References

[1] Woolway RI,Jennings E,Shatwell T,et al. Lake heatwaves under climate change[J]. Nature,2021,589(7842):402-407. DOI:10.1038/s41586-020-03119-1.
[2] Willis KJ,Bhagwat SA. Biodiversity and climate change[J]. Science,2009,326(5954):806-807. DOI:10.1126/science. 1178838.
[3] 刘起勇. 气候变化对中国媒介生物传染病的影响及应对:重大研究发现及未来研究建议[J]. 中国媒介生物学及控制杂志,2021,32(1):1-11. DOI:10.11853/j.issn.1003.8280.2021. 01.001.Liu QY. Impact of climate change on vector-borne diseases and related response strategies in China:Major research findings and recommendations for future research[J]. Chin J Vector Biol Control,2021,32(1):1-11. DOI:10.11853/j.issn.1003.8280. 2021.01.001.(in Chinese)
[4] 刘起勇. 气候变化对媒介生物性传染病的影响[J]. 中华卫生杀虫药械,2013,19(1):1-7,12. DOI:10.19821/j.1671-2781. 2013.01.001.Liu QY. The impacts of climate change on vector-borne diseases[J]. Chin J Hyg Insect Equip,2013,19(1):1-7,12. DOI:10.19821/j.1671-2781.2013.01.001.(in Chinese)
[5] Alam MS,Chakma S,Khan WA,et al. Diversity of anopheline species and their Plasmodium infection status in rural Bandarban,Bangladesh[J]. Parasit Vectors,2012,5:150. DOI:10.1186/1756-3305-5-150.
[6] Greenwood BM,Bojang K,Whitty CJ,et al. Malaria[J]. Lancet,2005,365(9469):1487-1498. DOI:10.1016/S0140-6736(05)66420-3.
[7] Ippolito MM,Denny JE,Langelier C,et al. Malaria and the microbiome:A systematic review[J]. Clin Infect Dis,2018,67(12):1831-1839. DOI:10.1093/cid/ciy374.
[8] Bashar K,Tuno N,Ahmed TU,et al. Blood-feeding patterns of Anopheles mosquitoes in a malaria-endemic area of Bangladesh[J]. Parasit Vectors,2012,5:39. DOI:10.1186/1756-3305-5-39.
[9] Harbach RE. The classification of genus Anopheles (Diptera:Culicidae):A working hypothesis of phylogenetic relationships[J]. Bull Entomol Res,2004,94(6):537-553. DOI:10.1079/ber2004321.
[10] Sinka ME,Bangs MJ,Manguin S,et al. The dominant Anopheles vectors of human malaria in the Asia-Pacific region:Occurrence data,distribution maps and bionomic précis[J]. Parasit Vectors,2011,4:89. DOI:10.1186/1756-3305-4-89.
[11] Elias M. Larval habitat of Anopheles philippinensis:A vector of malaria in Bangladesh[J]. Bull World Health Organ,1996,74(4):447-450.
[12] Iryani K. Hubungan Anopheles barbirostris dengan malaria[J]. J Mat Sains Teknol,2013,12(1):18-29.
[13] Paredes-Esquivel C,Donnelly MJ,Harbach RE,et al. A molecular phylogeny of mosquitoes in the Anopheles barbirostris subgroup reveals cryptic species:Implications for identification of disease vectors[J]. Mol Phylogenet Evol,2009,50(1):141-151. DOI:10.1016/j.ympev.2008.10.011.
[14] Chakravarty SK,Sarkar JK,Chakravarty MS,et al. The first epidemic of Japanese encephalitis studied in India:Virological studies[J]. Indian J Med Res,1975,63(1):77-82.
[15] Root TL,Price JT,Hall KR,et al. Fingerprints of global warming on wild animals and plants[J]. Nature,2003,421(6918):57-60. DOI:10.1038/nature01333.
[16] Ricciardi A,Hoopes MF,Marchetti MP,et al. Progress toward understanding the ecological impacts of nonnative species[J]. Ecol Monogr,2013,83(3):263-282. DOI:10.1890/13-0183.1.
[17] Gao XX,Liu J,Huang ZH. The impact of climate change on the distribution of rare and endangered tree Firmiana kwangsiensis using the MaxEnt modeling[J]. Ecol Evol,2022,12(8). DOI:10.1002/ECE3.9165.
[18] Papeş M,Gaubert P. Modelling ecological niches from low numbers of occurrences:Assessment of the conservation status of poorly known viverrids (Mammalia,Carnivora) across two continents[J]. Divers Distrib,2007,13(6):890-902. DOI:10.1111/j.1472-4642.2007.00392.x.
[19] Moreno R,Zamora R,Molina JR,et al. Predictive modeling of microhabitats for endemic birds in south Chilean temperate forests using maximum entropy (MaxEnt)[J]. Ecol Inform,2011,6(6):364-370. DOI:10.1016/j.ecoinf.2011.07.003.
[20] 马松梅,张明理,张宏祥,等. 利用最大熵模型和规则集遗传算法模型预测孑遗植物裸果木的潜在地理分布及格局[J]. 植物生态学报,2010,34(11):1327-1335. DOI:10.3773/j.issn. 1005-264x.2010.11.010.Ma SM,Zhang ML,Zhang HX,et al. Predicting potential geographical distributions and patterns of the relic plant Gymnocarpos przewalskii using maximum entropy and genetic algorithm for rule-set prediction[J]. Chin J Plant Ecol,2010,34(11):1327-1335. DOI:10.3773/j.issn.1005-264x.2010.11.010.(in Chinese)
[21] 车乐,曹博,白成科,等. 基于MaxEnt和ArcGIS对太白米的潜在分布预测及适宜性评价[J]. 生态学杂志,2014,33(6):1623-1628. DOI:10.13292/j.1000-4890.20140327.001.Che L,Cao B,Bai CK,et al. Predictive distribution and habitat suitability assessment of Notholirion bulbuliferum based on MaxEnt and ArcGIS[J]. Chin J Ecol,2014,33(6):1623-1628. DOI:10.13292/j.1000-4890.20140327.001.(in Chinese)
[22] 徐卫华,罗翀. MaxEnt模型在秦岭川金丝猴生境评价中的应用[J]. 森林工程,2010,26(2):1-3,26. DOI:10.16270/j.cnki.slgc.2010.02.020.Xu WH,Luo C. Application of MaxEnt model in Rhinopithecus roxllanae habitat assessment in Qinling mountain[J]. For Eng,2010,26(2):1-3,26. DOI:10.16270/j.cnki.slgc.2010.02.020.(in Chinese)
[23] 齐国君,高燕,黄德超,等. 基于MaxEnt的稻水象甲在中国的入侵扩散动态及适生性分析[J]. 植物保护学报,2012,39(2):129-136. DOI:10.13802/j.cnki.zwbhxb.2012.02.006.Qi GJ,Gao Y,Huang DC,et al. Historical invasion,expansion process and the potential geographic distributions for the rice water weevil,Lissorhoptrus oryzophilus in China based on MaxEnt[J]. Acta Phytophy Sin,2012,39(2):129-136. DOI:10.13802/j.cnki.zwbhxb.2012.02.006.(in Chinese)
[24] Sarma RR,Munsi M,Ananthram AN,et al. Effect of climate change on invasion risk of giant African snail (Achatina fulica Férussac,1821:Achatinidae) in India[J]. PLoS One,2015,10(11):e0143724. DOI:10.1371/journal.pone.0143724.
[25] Galvis-Martinez CA,Moo-Llanes DA,Altamiranda-Saavedra M. Similarity but not equivalence:Ecological niche comparison between sandflies from the Pleistocene and future scenarios in central and South America[J]. Med Vet Entomol,2023,37(1):111-123. DOI:10.1111/mve.12615.
[26] 王瑞,黄蓬英,傅建炜,等. 进境台湾果蔬主要病虫风险评估与早期监测预警[J]. 生物安全学报,2019,28(4):269-279. DOI:10.3969/j.issn.2095-1787.2019.04.006.Wang R,Huang PY,Fu JW,et al. Invasion risk assessment,early warning and monitoring of major invasive pests introduced with fruit and vegetables from Taiwan to mainland China[J]. J Biosaf,2019,28(4):269-279. DOI:10.3969/j.issn.2095-1787.2019. 04.006.(in Chinese)
[27] 鞠瑞亭,李博. 城市绿地外来物种风险分析体系构建及其在上海世博会管理中的应用[J]. 生物多样性,2012,20(1):12-23. DOI:10.3724/SP.J.1003.2012.12139.Ju RT,Li B. A risk analysis system for alien species in urban green spaces and application to the 2010 Expo,Shanghai[J]. Biodiv Sci,2012,20(1):12-23. DOI:10.3724/SP.J.1003.2012. 12139.(in Chinese)
[28] 龚正达, 周红宁, 岳仁苹, 等. 云南澜沧江流域居民区蚊类大尺度空间生态位特征[J]. 寄生虫与医学昆虫学报, 2020, 27(2):86-100. DOI:10.3969/j.issn.1005-0507.2020.02.005.Gong ZD, Zhou HN, Yue RP, et al. Large-scale spatial niche characteristics of mosquitoes in residential areas of Lancang river basin, Yunnan province[J]. Acta Parasitol Med Entomol Sin, 2020,27(2):86-100. DOI:10.3969/j.issn.1005-0507.2020. 02.005.(in Chinese)
[29] 赵宣, 侯乃旭, 陈晨, 等. 海南省传播病毒蚊媒种类及蚊媒病毒流行情况分析[J]. 海南医学, 2017, 28(7):1174-1179. DOI:10.3969/j.issn.1003-6350.2017.07.052.Zhao X, Hou NX, Chen C, et al. Analysis of mosquito vector species and epidemic situation of mosquito-borne viruses in Hainan province[J]. Hainan Med J, 2017, 28(7):1174-1179. DOI:10.3969/j.issn.1003-6350.2017.07.052.(in Chinese)