Maximum entropy model-based projection of potential distribution areas of Parafossarulus striatulus in China

doi:10.11853/j.issn.1003.8280.2022.04.021

Abstract

Abstract: Objective To analyze the distribution of suitable habitats of Parafossarulus striatulus in China based on environmental factors, and to project the impact of climate changes on the distribution of P. striatulus in China. Methods The Chinese and English literatures related to the geographical distribution of P. striatulus in China were searched in the Chinese National Knowledge Infrastructure, VIP, Wanfang Data Knowledge Service Platform, PubMed, and Web of Science, from which, the coordinate information of distribution points of P. striatulus was extracted, and the information of other distribution points of P. striatulus was obtained from the Global Biodiversity Information Facility (GBIF) combined with the required climate and geographical factors. The MaxEnt was used to project the suitable habitats of P. striatulus in China in the future under different scenarios. Results Among the environmental factors affecting the distribution of suitable habitats of P. striatulus in China, the top four contributing factors were elevation (contribution rate, 51.42%), water index (contribution rate, 11.23%), precipitation in the wettest month (contribution rate, 8.71%), and precipitation in the driest month (contribution rate, 6.82%). Under the current climate conditions, P. striatulus was mainly distributed in the southeastern and northern regions of China, and the areas of highly and moderately suitable habitats were 373 700 km² and 616 000 km², respectively. Under the shared socioeconomic pathway (SSP) 126 scenario, the highly suitable habitats increased by 910 000 km² and 938 200 km² during 2041 to 2060 and 2061 to 2080, respectively. Under the SSP245 scenario, the highly suitable habitats increased by 412 200 km² and 494 400 km² during 2041 to 2060 and 2061 to 2080, respectively. Conclusion Elevation is the most important environmental factor affecting the distribution of P. striatulus. Under the SSP126 and SSP245 scenarios, future climate changes are expected to expand the suitable habitats of P. striatulus to varying degrees.

Key words: Parafossarulus striatulus, Maximum entropy model, Projection of suitable habitat, Environmental factor

摘要： 目的结合环境因子分析纹沼螺在我国的适生区分布，并预估气候变化对我国纹沼螺分布情况的影响。方法在中英文数据库（中国知网、维普、万方数据知识服务平台、PubMed、Web of Science）中检索我国纹沼螺地理分布相关中英文文献，从中提取纹沼螺分布点的坐标信息，同时从世界生物多样性信息交换平台（GBIF）中获取纹沼螺其他分布点信息。结合所需气候和地理因子，建立最大熵模型（MaxEnt）对不同情景模式下未来我国纹沼螺适生区进行预估。结果影响我国纹沼螺适生区分布的环境因子中，贡献率前4位的因子为海拔（贡献率51.42%）、水体指数（贡献率11.23%）、最湿月降水量（贡献率8.71%）和最干月降水量（贡献率6.82%）；当前气候条件下，纹沼螺主要分布于我国东南地区和华北地区，高适生区和中适生区面积分别为37.37和61.60万km²；在共享社会经济路径（SSP）126情景模式下，高适生区在2041－2060年和2061－2080年2个周期内将分别增加91.00和93.82万km²；在SSP245情景模式下，高适生区在2041－2060年和2061－2080年2个周期内将分别增加41.22和49.44万km²。结论海拔是影响纹沼螺分布的最主要环境因素，在SSP126和SSP245情景模式下，未来气候变化均使纹沼螺的适生区不同程度扩大。

关键词: 纹沼螺, 最大熵模型, 适生区预估, 环境因子

CLC Number:

R184.39

SUN Yuan-chao, LIU Kai, YAO Xiao-yan, CUN De-jiao, TIAN Na, ZHANG Yi, WANG Fei, LI Lan-hua. Maximum entropy model-based projection of potential distribution areas of Parafossarulus striatulus in China[J]. Chinese Journal of Vector Biology and Control, 2022, 33(4): 555-561.

孙元超, 刘凯, 姚晓燕, 寸得娇, 田娜, 张仪, 王飞, 李兰花. 基于MaxEnt模型对我国纹沼螺潜在分布区的预估研究[J]. 中国媒介生物学及控制杂志, 2022, 33(4): 555-561.

References

[1] 江颖. 我国华支睾吸虫中间宿主螺类分子系统发育研究[D]. 北京:中国疾病预防控制中心, 2016. Jiang Y. Molecular phylogeny on intermediate host snails of Clonorchis sinensis in China[D]. Beijing:Chinese Center for Disease Control and Prevention, 2016. (in Chinese)
[2] 姜彤, 吕嫣冉, 黄金龙. 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. Jiang T, Lyu YR, Huang JL. New scenarios of CMIP6 model (SSP-RCP) and its application in the Huaihe River basin[J] Adv Meteor Sci Technol, 2020, 10(5):102-109. DOI:10.3969/j.issn.2095-1973.2020.05.016.(in Chinese)
[3] 叶永昌, 周广胜, 殷晓洁. 1961-2010年内蒙古草原植被分布和生产力变化:基于MaxEnt模型和综合模型的模拟分析[J]. 生态学报, 2016, 36(15):4718-4728. DOI:10.5846/stxb201412302599. Ye YC, Zhou GS, Yin XJ. Changes in distribution and productivity of steppe vegetation in Inner Mongolia during 1961 to 2010:Analysis based on MaxEnt model and synthetic model[J]. Acta Ecol Sin, 2016, 36(15):4718-4728. DOI:10.5846/stxb201412302599.(in Chinese)
[4] 王雨生, 王召海, 邢汉发, 等. 基于MaxEnt模型的珙桐在中国潜在适生区预测[J]. 生态学杂志, 2019, 38(4):1230-1237. DOI:10.13292/j.1000-4890.201904.024. Wang YS, Wang ZH, Xing HF, et al. Prediction of potential suitable distribution of Davidia involucrata baill in China based on MaxEnt[J]. Chin J Ecol, 2019, 38(4):1230-1237. DOI:10.13292/j.1000-4890.201904.024.(in Chinese)
[5] 王茹琳, 王闫利, 陈东东, 等. 基于MaxEnt模型的柑橘木虱在西南地区潜在分布模拟[J]. 植物保护, 2021, 47(1):84-90, 96. DOI:10.16688/j.zwbh.2019592. Wang RL, Wang YL, Chen DD, et al. Analysis of the potential distribution of the Asian citrus psyllid, Diaphorina citri Kuwayama in Southwest China using the MaxEnt model[J]. Plant Prot, 2021, 47(1):84-90, 96. DOI:10.16688/j.zwbh.2019592.(in Chinese)
[6] 何文文, 伍军, 温丽翠, 等. MaxEnt模型对新疆盾糙璃眼蜱生境适应性预测[J]. 中国动物检疫, 2022, 39(2):45-51. DOI:10.3969/j.issn.1005-944X.2022.02.009. He WW, Wu J, Wen LC, et al, Prediction to the habitat adaptability of Hyalomma scupense in Xinjiang by MaxEnt model[J]. China Anim Health Insp, 2022, 39(2):45-51. DOI:10.3969/j.issn.1005-944X.2022.02.009.(in Chinese)
[7] 杨绚, 李栋梁, 汤绪. 基于CMIP5多模式集合资料的中国气温和降水预估及概率分析[J]. 中国沙漠, 2014, 34(3):795-804. DOI:10.7522/j.issn.1000-694X.2013.00381. Yang X, Li DL, Tang X. Probability assessment of temperature and precipitation over China by CMIP5 multi-model Ensemble[J]. J Desert Res, 2014, 34(3):795-804. DOI:10.7522/j.issn. 1000-694X.2013.00381.(in Chinese)
[8] 张蕾, 黄大鹏, 杨冰韵. RCP4.5情景下中国人口对高温暴露度预估研究[J]. 地理研究, 2016, 35(12):2238-2248. DOI:10.11821/dlyj201612004. Zhang L, Huang DP, Yang BY. Future population exposure to high temperature in China under RCP4.5 scenario[J]. Geogr Res, 2016, 35(12):2238-2248. DOI:10.11821/dlyj201612004.(in Chinese)
[9] 贾翔, 王超, 金慧, 等. 基于优化的MaxEnt模型评价红松适宜分布区[J]. 生态学杂志, 2019, 38(8):2570-2576. DOI:10. 13292/j.1000-4890.201908.017. Jia X, Wang C, Jin H, et al. Assessing the suitable distribution area of Pinus koraiensis based on an optimized MaxEnt model[J] Chin J Ecol, 2019, 38(8):2570-2576. DOI:10.13292/j.1000-4890.201908.017.(in Chinese)
[10] 管强, 刘吉平, 武海涛, 等. 中国自然湿地螺类生态学研究进展[J]. 生态学报, 2016, 36(9):2471-2481. DOI:10.5846/stxb 201411162267. Guan Q, Liu JP, Wu HT, et al. Research progress on the ecology of natural wetland snails (Mollusca:Gastropoda) in China[J]. Acta Ecol Sin, 2016, 36(9):2471-2481. DOI:10.5846/stxb 201411162267.(in Chinese)
[11] 曹正光, 蒋忻坡. 几种环境因子对梨形环棱螺的影响[J]. 上海水产大学学报, 1998, 7(3):200-205. Cao ZG, Jiang XP. The influence of environmental factors on Bellamya purificate[J]. J Shanghai Fish Univ, 1998, 7(3):200-205. (in Chinese)
[12] 李宽意, 刘正文, 杨宏伟, 等. 牧食损害对伊乐藻(Elodea nuttallii)生长的影响[J]. 生态学报, 2007, 27(10):4209-4213. DOI:10.3321/j.issn:1000-0933.2007.10.031. Li KY, Liu ZW, Yang HW, et al. Effects of mechanical damage on the growth of Elodea nuttallii[J]. Acta Ecol Sin, 2007, 27(10):4209-4213. DOI:10.3321/j.issn:1000-0933.2007.10.031.(in Chinese)
[13] 池秀莲, 唐志尧. 面积、温度及分布区限制对物种丰富度海拔格局的影响:以秦岭太白山为例[J]. 植物生态学报, 2011, 35(4):362-370. DOI:10.3724/SP.J.1258.2011.00362. Chi XL, Tang ZY. Effects of area, temperature and geometric constraints on elevational patterns of species richness:A case study in the Mountain Taibai, Qinling Mountains, China[J]. Chin J Plant Ecol, 2011, 35(4):362-370. DOI:10.3724/SP.J.1258. 2011.00362.(in Chinese)
[14] 刘意立. 我国亚热带季风气候区湿地土壤CO₂、CH₄排放规律研究[D]. 杭州:浙江大学, 2014. Liu YL. Laboratory study on the carbon dioxide and methane emission from wetland soil in subtropical monsoon climate zone[D]. Hangzhou:Zhejiang University, 2014. (in Chinese)
[15] 刘帅磊, 王赛, 崔永德, 等. 亚热带城市河流底栖动物完整性评价:以流溪河为例[J]. 生态学报, 2018, 38(1):342-357. DOI:10.5846/stxb201612242660. Liu SL, Wang S, Cui YD, et al. Ecological assessment of a subtropical urban river based on the Benthic-Index of Biotic Integrity-Liuxi River[J]. Acta Ecol Sin, 2018, 38(1):342-357. DOI:10.5846/stxb201612242660.(in Chinese)
[16] 刘艳斌, 韩微, 贤振华. 温度对福寿螺生长发育及摄食的影响[J]. 南方农业学报, 2011, 42(8):901-905. DOI:10.3969/J.issn.2095-1191.2011.08.018. Liu YB, Han W, Xian ZH. Effect of different temperatures on growth, development and feeding of Pomacea canaliculata[J]. J South Agric, 2011, 42(8):901-905. DOI:10.3969/J.issn.2095-1191.2011.08.018.(in Chinese)
[17] 杨海艳. 我国人居适宜性的海拔高度分级研究[D]. 南京:南京师范大学, 2013. Yang HY. Study on altitude classification of human settlement suitability in China[D]. Nanjing:Nanjing Normal University, 2013. (in Chinese)
[18] 曹福祥, 徐庆军, 曹受金, 等. 全球变暖对物种分布的影响研究进展[J]. 中南林业科技大学学报, 2008, 28(6):86-89. DOI:10.3969/j.issn.1673-923X.2008.06.019. Cao FX, Xu QJ, Cao SJ, et al. Advances of global warming impact on species distribution[J]. J Cent South Univ For Technol, 2008, 28(6):86-89. DOI:10.3969/j.issn.1673-923X.2008.06.019.(in Chinese)
[19] 姜江, 姜大膀, 林一骅. RCP4.5情景下中国季风区及降水变化预估[J]. 大气科学, 2015, 39(5):901-910. DOI:10.3878/j.issn.1006-9895.1411.14216. Jiang J, Jiang DB, Lin YH. Projection of monsoon area and precipitation in China under the RCP4.5 scenario[J]. Chin J Atmos Sci, 2015, 39(5):901-910. DOI:10.3878/j.issn.1006-9895.1411.14216.(in Chinese)
[20] 刘燕. 湖北钉螺生存环境主要影响因素探析[J]. 九江学院学报(自然科学版), 2013, 28(3):1-4. DOI:10.19717/j.cnki.jjun. 2013.03.001. Liu Y. Main environmental factors affecting Oncomelania snail ecology[J]. J Jiujiang Univ(Nat Sci), 2013, 28(3):1-4. DOI:10.19717/j.cnki.jjun.2013.03.001.(in Chinese)
[21] 赵国平. 中国蜱类空间分布及其危害预测[D]. 北京:军事科学院, 2018. Zhao GP. Spatial distribution of ticks and their hazard prediction in China[D]. Beijing:Academy of Military Sciences, 2018. (in Chinese)
[22] 李博, 周天军. 基于IPCC A1B情景的中国未来气候变化预估:多模式集合结果及其不确定性[J]. 气候变化研究进展, 2010, 6(4):270-276. Li B, Zhou TJ. Projected climate change over China under SRES A1B scenario:Multi-model ensemble and uncertainties[J]. Adv Climate Change Res, 2010, 6(4):270-276. (in Chinese)