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苗可儿,钱薇雅,张俊,李鹏,胡超超,常青.2023.功能、谱系多样性在机场鸟类群落研究中的应用——以扬州泰州国际机场为例.动物学杂志,58(2):182-197.
功能、谱系多样性在机场鸟类群落研究中的应用——以扬州泰州国际机场为例
Application of Functional and Phylogenetic Diversity in Airport Bird Communities: A Case Study of Yangzhou Taizhou International Airport
投稿时间:2022-05-18  修订日期:2023-03-16
DOI:10.13859/j.cjz.202302003
中文关键词:  物种多样性  谱系多样性  功能多样性  机场
英文关键词:Species diversity  Phylogenetic diversity  Functional diversity  Airport
基金项目:国家自然科学基金项目(No. 41271057),江苏省农业生物多样性培育与利用研究中心委托研究项目(No. 100605-2022- KY-00210);江苏省林业科学研究院青年基金项目(JAF-2022-01)
作者单位E-mail
苗可儿 南京师范大学生命科学学院 南京 210046 nicolemke@163.com 
钱薇雅 南京师范大学生命科学学院 南京 210046 qianweiya@126.com 
张俊 扬州泰州国际机场 扬州 225831 399199255@qq.com 
李鹏 南京师范大学生命科学学院 南京 210046江苏省农业生物多样性培育与 利用研究中心 南京 210014 lipeng@njnu.edu.cn 
胡超超 南京师范大学生命科学学院 南京 210046
南京师范大学分析测试中心 南京 210046 
huweichen@126.com 
常青 南京师范大学生命科学学院 南京 210046 changq@njnu.edu.cn 
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中文摘要:
      随着航空业的发展,野生动物与飞机之间的冲突愈发密集,机场鸟类群落多样性研究引起了大量关注。研究鸟类群落对生境类型的使用状况,可以掌握生境类型与鸟击风险的潜在关系,为机场环境改造提供理论依据。本研究于2019年7月至2021年11月,采用样点法对扬州泰州机场及周边8 km范围内的农田、湿地、林地和城镇4种生境中30个样点的鸟类群落进行调查。利用鸟类群落多样性指数,包括丰富度、多度、香农威纳多样性指数、辛普森多样性指数以及均匀度指数来表征群落的物种多样性,以及功能和谱系多样性,阐明机场周边4种生境的鸟类群落多样性差异。同时,基于多度加权的平均成对功能距离(MFD)和平均成对谱系距离(MPD)来表征群落的功能和谱系结构,探究群落构建机制,量化各多样性指标间的相关性。研究共记录扬州泰州国际机场鸟类88种,分别隶属于14目36科,目、科中数量最多的为雀形目(Passeriformes)和鹬科(Scolopacidae)。谱系和功能多样性在生境间差异显著,功能分散度在农田最高,城镇最低;谱系多样性指数在城镇最高,湿地最低。标准化效应值分析表明,随机生态过程影响了湿地鸟类群落功能和谱系的构建过程,农田、城镇、林地三种生境群落的聚集主要受到生境过滤作用的影响。研究鸟类群落多样性及生境因子有助于掌握生境类型与机场鸟类群落的关系,为机场及其周边环境整治提供理论帮助。
英文摘要:
      [Objectives] From July 2019 to November 2021, based on the data of bird community diversity surveys conducted at Yangzhou Taizhou International Airport and its surrounding areas, this study analyzed the species, function and phylogenetic diversity of bird communities in different habitats, to explore the function and phylogenetic structure of bird communities and the correlation between each index. This study investigated the construction process of the bird community in the human-disturbed airport environment and provided a theoretical basis for the prevention and control of bird disease in the airport and its surrounding areas. [Methods] The traditional point count method was used to investigate the bird community of 30 sampling sites in 4 habitats (Fig. 1). The statistical analysis included single-group t-test, with a total of 713 samples, which was the cumulative survey number of 30 samples in 2 years. A total of 2 224 individuals were included in the sample, which was the cumulative sum of the number of species observed during the survey of the sample sites. Traditional bird community diversity indices such as richness, abundance, Shannon-Wiener index, Simpson diversity index, and Pielou evenness index were used to characterize the species diversity, functional (FDis) and phylogenetic (Faith’ PD) diversity elucidates the differences in the diversity of bird communities around the airport for each habitat type. Meanwhile, based on the mean pairwise functional distance (MFD) and mean pairwise phylogenetic distance (MPD) weighted by abundance, the function and phylogenetic structures of the community were characterized, and the community assembly mechanisms, as well as correlations between various diversity indicators, were explored. The calculation and statistical analysis of this study were completed in R 4.0.0. A total of 30 survey samples were designed in this study, with a total of 713 survey samples and 2 224 observational data. [Results] Our results showed that (1) The species accumulation curves of the four habitats were close to asymptotes, indicating that the survey data of bird species were relatively complete and fully met the requirements of the analysis (Fig. 2). (2) A total of 88 bird species were recorded, belonging to 14 orders and 36 families, respectively. The largest number of orders and families were Passeriformes and Scolopacidae (Fig. 3). (3) FDis was highest in farmland and lowest in urban areas, and PD was highest in urban areas and lowest in wetlands (Fig. 4). (4) Standardized effect size analysis showed that random processes affected the function and phylogenetic construction of wetland bird communities, and the clustering of communities in the other three habitats was mainly affected by habitat filtering (Fig. 5). [Conclusion] The analysis of bird community diversity and related indicators in this study can grasp the relationship between habitat types and airport bird communities, and provide theoretical guidance for airport managers.
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