气候变化对我国黑胸大蠊分布的影响研究

doi:10.11853/j.issn.1003.8280.2023.04.018

中国媒介生物学及控制杂志 ›› 2023, Vol. 34 ›› Issue (4): 542-547.DOI: 10.11853/j.issn.1003.8280.2023.04.018

气候变化对我国黑胸大蠊分布的影响研究

谢梦琪(), 寸得娇, 姚晓燕, 王飞, 李兰花(), 田娜()

潍坊医学院科研处, 山东潍坊 261053

收稿日期:2022-12-13 出版日期:2023-08-20 发布日期:2023-08-17
通讯作者: 李兰花,田娜
作者简介:谢梦琪，女，在读本科，主要从事传染病媒介生物研究，E-mail：xiemengqi95@163.com
基金资助:
国家自然科学基金(81902095);山东省自然科学基金(ZR2019MH093);山东省医药卫生科技发展计划(202112050556);潍坊市科技发展计划（医学类）(2021YX038);潍坊医学院校级大学生创新创业训练计划项目(X2022094)

Effects of climate change on the distribution of Periplaneta fuliginosa in China

Meng-qi XIE(), De-jiao CUN, Xiao-yan YAO, Fei WANG, Lan-hua LI(), Na TIAN()

Scientific Research Department, Weifang Medical University, Weifang, Shandong 261053, China

Received:2022-12-13 Online:2023-08-20 Published:2023-08-17
Contact: Lan-hua LI, Na TIAN
Supported by:
National Natural Science Foundation of China(81902095);Natural Science Foundation of Shandeng Province of China(ZR2019MH093);Medical and Health Science and Technology Development Project of Shandong Province(202112050556);Weifang Science and Technology Development Plan project (Medical science)(2021YX038);Weifang Medical University Innovation and Entrepreneurship Training Program for College Students(X2022094)

摘要/Abstract

摘要：

目的: 分析气候环境因素对我国黑胸大蠊地理分布的影响，预测预估不同气候条件下黑胸大蠊在我国的分布范围。方法: 检索全球生物多样性信息交换平台（GBIF）及公开发表文献，从中获取黑胸大蠊分布相关的地理位置信息，从公开网站获取气候和地理因子等环境因素信息，应用最大熵模型（MaxEnt）分析各因子对我国黑胸大蠊分布的影响，并预估当前和未来2041－2060年黑胸大蠊的潜在地理分布区。结果: 影响黑胸大蠊分布的各环境因素中，最干月降水量贡献率最大（贡献率为37.20%），其次是最湿月降水量（贡献率为15.20%）。当前气候条件下，黑胸大蠊主要分布于我国安徽、湖南、湖北、江苏、江西、四川等省份，高适生区面积达61.31万km²。预估结果表明，在共享社会经济路径（SSP）2-4.5情景下，未来2041－2060年我国黑胸大蠊适生区面积将减少4.29万km²。结论: 降水量可能是影响黑胸大蠊分布的关键因素，未来我国黑胸大蠊适生区面积可能减少。

关键词: 黑胸大蠊, 最大熵模型, 环境因素, 分布, 适生区预测

Abstract:

Objective: To analyze the impact of climatic environmental factors on the geographical distribution of Periplaneta fuliginosa in China, and to predict and project the distribution range of P. fuliginosa in China under different climate conditions. Methods: The Global Biodiversity Information Facility and published literature for the geographical distribution information of P. fuliginosa in China were searched. Information on climatic and geographical factors was acquired from public websites. A maximum entropy model was applied to analyze the impact of the factors on the distribution of P. fuliginosa in China, and project the potential geographical distribution area of P. fuliginosa under current and future (2041-2060) conditions. Results: Among the environmental factors affecting the geographical distribution of P. fuliginosa, the precipitation in the driest month contributed most (contribution rate: 37.20%), followed by the precipitation in the wettest month (contribution rate: 15.20%). Under current climate conditions, P. fuliginosa was mainly distributed in Anhui, Hunan, Hubei, Jiangsu, Jiangxi, and Sichuan provinces, with the area of highly suitable habitats reaching 613 100 km². Under the shared socioeconomic pathway SSP2-4.5 scenario, the suitable habitats of P. fuliginosa in China would decrease by 42 900 km² in 2041-2060. Conclusions: Precipitation may be a key factor influencing the distribution of P. fuliginosa. The suitable habitats of P. fuliginosa in China may decrease in the future.

Key words: Periplaneta fuliginosa, MaxEnt, Environment conditions, Distribution, Suitable habitat projection

中图分类号:

谢梦琪, 寸得娇, 姚晓燕, 王飞, 李兰花, 田娜. 气候变化对我国黑胸大蠊分布的影响研究[J]. 中国媒介生物学及控制杂志, 2023, 34(4): 542-547.

Meng-qi XIE, De-jiao CUN, Xiao-yan YAO, Fei WANG, Lan-hua LI, Na TIAN. Effects of climate change on the distribution of Periplaneta fuliginosa in China[J]. Chinese Journal of Vector Biology and Control, 2023, 34(4): 542-547.

图/表 5

表 1 环境因子对黑胸大蠊分布的影响

Table 1 Effects of environmental factors on the distribution of Periplaneta fuliginosa

图 1 黑胸大蠊出现概率对重要环境因子的响应曲线

Fig. 1 Response curves of Periplaneta fuliginosa occurrence probability to major environmental factors

图 2 当前气候情景下黑胸大蠊的潜在适生区及物种采样点

Fig. 2 Potential suitable areas and sampling sites of Periplaneta fuliginosa under current climate conditions

图 3 当前和2041-2060年共享社会经济路径2-4.5气候情景下黑胸大蠊适生区分布变化

Fig. 3 Changes of suitable areas of Periplaneta fuliginosa under current conditions and the shared socioeconomic pathway SSP2-4.5 scenario in 2041-2060

表 2 当前和2041－2060年共享社会经济路径（SSP）2-4.5气候情景下黑胸大蠊在中国的潜在适生区面积

Table 2 Potential suitable area in China of Periplaneta fuliginosa under current conditions and the shared socioeconomic pathway SSP2-4.5 scenario in 2041-2060

参考文献 25

1	贺盼, 马强. 我国蜚蠊的分布及防制概况[J]. 医学动物防制, 2018, 34 (9):868-872.
	He P, Ma Q. Distribution and control of cockroaches in China[J]. J Med Pest Control, 2018, 34 (9):868-872.
2	侯银续, 林浩飞, 王玮, 等. 安徽省黄山市2017-2018年室内蜚蠊监测结果分析[J]. 中国媒介生物学及控制杂志, 2020, 31 (6):718-721. DOI
	Hou YX, Lin HF, Wang W, et al. An analysis of surveillance results of indoor cockroaches in Huangshan, Anhui province, China, 2017-2018[J]. Chin J Vector Biol Control, 2020, 31 (6):718-721. DOI
3	侯银续, 水岩, 吴磊, 等. 蜚蠊的危害及防制技术研究进展[J]. 安徽预防医学杂志, 2021, 27 (6):487-491, 496. DOI
	Hou YX, Shui Y, Wu L, et al. Research progress on cockroach damage and control technology[J]. Anhui J Prev Med, 2021, 27 (6):487-491, 496. DOI
4	孙耘芹, 李梅, 何凤琴, 等. 五种蜚蠊的生物学特性和综合治理[J]. 昆虫知识, 2004, 41 (3):216-222. DOI
	Sun YQ, Li M, He FQ, et al. Bionomics and integrated management of five species of cockroaches[J]. Entomol Knowl, 2004, 41 (3):216-222. DOI
5	王韶华, 武峥嵘, 董腾飞, 等. 上海市嘉定区2017-2019年蟑螂侵害现状及居家灭蟑效果研究[J]. 上海预防医学, 2020, 32 (12):1001-1005. DOI
	Wang SH, Wu ZR, Dong TF, et al. Surveillance of cockroach population and evaluation of control effects in households from 2017 to 2019 in Jiading district of Shanghai[J]. Shanghai J Prev Med, 2020, 32 (12):1001-1005. DOI
6	刘雪, 葛小伍, 梁丽, 等. 2017―2019年徐州市主城区主要病媒生物监测分析[J]. 中华卫生杀虫药械, 2021, 27 (2):124-128. DOI
	Liu X, Ge XW, Liang L, et al. Monitoring and analysis of the main vectors in main districts of Xuzhou from 2017 to 2019[J]. Chin J Hyg Insect Equip, 2021, 27 (2):124-128. DOI
7	侯银续, 袁华玲, 陈李, 等. 黄山市蟑螂携带肠道菌种多样性初探[J]. 中华卫生杀虫药械, 2021, 27 (2):154-159. DOI
	Hou YX, Yuan HL, Chen L, et al. A preliminary study on the diversity of intestinal bacteria carried by cockroaches in Huangshan city[J]. Chin J Hyg Insect Equip, 2021, 27 (2):154-159. DOI
8	赵泽芳, 卫海燕, 郭彦龙, 等. 人参潜在地理分布以及气候变化对其影响预测[J]. 应用生态学报, 2016, 27 (11):3607-3615. DOI
	Zhao ZF, Wei HY, Guo YL, et al. Potential distribution of Panax ginseng and its predicted responses to climate change[J]. Chin J Appl Ecol, 2016, 27 (11):3607-3615. DOI
9	姜志宽, 吴光华. 蟑螂防治(二): 蟑螂的生态习性与常见种类[J]. 中华卫生杀虫药械, 2009, 15 (2):169-172. DOI
	Jiang ZK, Wu GH. Cockroach control. Ⅱ: Ecological habits and common species of cockroaches[J]. Chin J Hyg Insect Equip, 2009, 15 (2):169-172. DOI
10	Nasirian H. Infestation of cockroaches (Insecta: Blattaria) in the human dwelling environments: A systematic review and meta-analysis[J]. Acta Trop, 2017, 167, 86-98. DOI
11	张路. MaxEnt最大熵模型在预测物种潜在分布范围方面的应用[J]. 生物学通报, 2015, 50 (11):9-12.
	Zhang L. The application of MaxEnt model in predicting the potential range of species[J]. Biol Bull, 2015, 50 (11):9-12.
12	Besprozvannykh VV, Ngo HD, Ha NV, et al. Descriptions of digenean parasites from three snail species, Bithynia fuchsiana (Morelet), Parafossarulus striatulus Benson and Melanoides tuberculata Müller, in North Vietnam[J]. Helminthologia, 2013, 50 (3):190-204. DOI
13	Ren ZP, Wang DQ, Ma AM, et al. Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination[J]. Sci Rep, 2016, 6 (1):20604. DOI
14	王茹琳, 李庆, 封传红, 等. 基于MaxEnt的西藏飞蝗在中国的适生区预测[J]. 生态学报, 2017, 37 (24):8556-8566. DOI
	Wang RL, Li Q, Feng CH, et al. Predicting potential ecological distribution of Locusta migratoria tibetensis in China using MaxEnt ecological niche modeling[J]. Acta Ecol Sin, 2017, 37 (24):8556-8566. DOI
15	周玉婷, 葛雪贞, 邹娅, 等. 基于MaxEnt模型的长林小蠹的全球及中国适生区预测[J]. 北京林业大学学报, 2022, 44 (11):90-99. DOI
	Zhou YT, Ge XZ, Zou Y, et al. Prediction of the potential geographical distribution of Hylurgus ligniperda at the global scale and in China using the MaxEnt model[J]. J Beijing For Univ, 2022, 44 (11):90-99. DOI
16	曾权, 朱雪珍, 周利娟. 基于优化MaxEnt模型的南方三棘果在中国的潜在适生区预测[J]. 华南农业大学学报, 2023, 44 (2):254-262.
	Zeng Q, Zhu XZ, Zhou LJ. Prediction of potential suitable region for Emex australis in China based on the optimized MaxEnt mode[J]. J South China Agric Univ, 2023, 44 (2):254-262.
17	Wouyou HG, Lokonon BE, Idohou R, et al. Predicting the potential impacts of climate change on the endangered Caesalpinia bonduc (L.) Roxb in Benin (West Africa)[J]. Heliyon, 2022, 8 (3):e09022. DOI
18	Liu D, Lei XD, Gao WQ, et al. Mapping the potential distribution suitability of 16 tree species under climate change in northeastern China using MaxEnt modelling[J]. J For Res, 2022, 33 (6):1739-1750. DOI
19	戈斌, 黄涛, 张海兵, 等. 2011-2018年上海市奉贤区蟑螂监测分析[J]. 中华卫生杀虫药械, 2021, 27 (5):425-428. DOI
	Ge B, Huang T, Zhang HB, et al. Investigation on cockroaches in Fengxian district of Shanghai from 2011 to 2018[J]. Chin J Hyg Insect Equip, 2021, 27 (5):425-428. DOI
20	徐绍锐, 汪世平, 吴仕筠, 等. 黑胸大蠊室内繁殖、发育的生物学特性研究[J]. 中国人兽共患病学报, 2006, 22 (10):913-917. DOI
	Xu SR, Wang SP, Wu SJ, et al. Studies on biological characteristics of domestic reproduction and development of Periplaneta fuliginosa[J]. Chin J Zoonoses, 2006, 22 (10):913-917. DOI
21	陈文锦, 袁高林. 宁德市蜚蠊种群密度与季节消长[J]. 海峡预防医学杂志, 2006, 12 (6):28-29. DOI
	Chen WJ, Yuan GL. Population density and seasonal fluctuation of cockroaches in Ningde city[J]. Strait J Prev Med, 2006, 12 (6):28-29. DOI
22	李芮芝, 胡希军, 文亚峰, 等. 基于MaxEnt模型的丹霞梧桐生境预测模拟分析[J]. 中国野生植物资源, 2022, 41 (6):1-7, 30. DOI
	Li RZ, Hu XJ, Wen YF, et al. Habitat prediction simulation analysis of Firmiana danxiaensis based on MaxEnt[J]. Chin Wild Plant Resour, 2022, 41 (6):1-7, 30. DOI
23	沈培谊, 俞松青, 蔡昌曜, 等. 浙江省蜚蠊种群、地理分布特点及防制技术研究[J]. 中国媒介生物学及控制杂志, 2001, 12 (4):275-281. DOI
	Shen PY, Yu SQ, Cai CY, et al. The study on the features of populations and distribution and control technique of the cockroach in Zhejiang province[J]. Chin J Vector Biol Control, 2001, 12 (4):275-281. DOI
24	姜荣升. 基于CWRF研究我国降水变化及其与边界层高度的关系[D]. 南京: 南京信息工程大学, 2021. DOI: 10.27248/d.cnki.gnjqc.2021.000035.
	Jiang RS. Study the interaction between precipitation change and planetary boundary layer height based on CWRF[D]. Nanjing: Nanjing University of Information Science and Technology, 2021. DOI: 10.27248/d.cnki.gnjqc.2021.000035.(in Chinese)
25	刘春蓁, 巢清尘, 王守荣, 等. 水文气象学领域的水文循环研究进展[J]. 气候变化研究进展, 2023, 19 (1):1-10. DOI
	Liu CZ, Chao QC, Wang SR, et al. The research progress of hydrologic cycle in hydrometeorology[J]. Climate Change Res, 2023, 19 (1):1-10. DOI

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气候变化对我国黑胸大蠊分布的影响研究

Effects of climate change on the distribution of Periplaneta fuliginosa in China

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