城市森林不同林分类型的昆虫多样性: 以南京紫金山南麓为例
收稿日期: 2022-06-29
录用日期: 2022-10-13
网络出版日期: 2022-12-31
基金资助
江苏省自然科学基金青年基金(BK20210159);江苏省农业科技自主创新资金(CX(20)3184);江苏省农业科学院探索性颠覆性项目(ZX(21)1227);江苏农林职业技术学院院级课题(2021KJ45)
Insect diversity in different stand types of urban forest: A case study at the southern foot of Zijin Mountain, Nanjing
Received date: 2022-06-29
Accepted date: 2022-10-13
Online published: 2022-12-31
为阐明影响城市森林昆虫多样性的关键因素, 本研究采用扫网法与马氏网法, 于2020年7月下旬至2021年7月上旬对江苏南京紫金山南麓阔叶混交林、针阔混交林、针阔混交沼泽地、针阔混交绿道、人工阔叶绿道和人工针叶林6类生境开展昆虫多样性调查。累计采集昆虫9目78科145种59,648头, 其中鳞翅目、半翅目、膜翅目与双翅目的物种数和个体数相对较高。α-多样性分析结果显示, 阔叶混交林昆虫多样性最高, 人工针叶林最低。仅针阔混交沼泽地与阔叶混交林的昆虫群落中等相似, 其他生境昆虫群落均互相中等不相似或极不相似。冗余分析与Pearson相关性分析结果表明, 虽然各主要昆虫类群α-多样性与环境因素的相关性存在差异, 但总体而言, 影响紫金山南麓昆虫多样性的环境因素主要为人为干扰程度、人流量、气温、日照时长、降水和海拔, 其中植被人为干扰程度影响最为显著, 干扰程度越强, 昆虫多样性越低。科学地规划和管理植被结构是保护城市森林昆虫多样性的关键。
唐楚飞, 葛成, 曹烨, 曹弘毅, 宋晓晓, 廖怀建 . 城市森林不同林分类型的昆虫多样性: 以南京紫金山南麓为例[J]. 生物多样性, 2023 , 31(2) : 22357 . DOI: 10.17520/biods.2022357
Aims: This research aimed to clarify the correlation between various environmental factors, such as anthropogenic impacts, and the insect diversity in urban forests, which can lead to the elucidation of key factors that can affect insect diversity in urban forests. Furthermore, this could result in the development and implementation of more efficient conservation guidelines and conservation strategies for the protection of urban species diversity.
Methods: From late July 2020 to early July 2021, with the use of sweeping method and Malaise traps, we collected insects from six habitats with different stand types from Zijin Mountain, Nanjing, including greenway in artificial broadleaf forest, greenway in broadleaf-conifer mixed forest, wetland in broadleaf-conifer mixed forest, as well as woodlands in artificial coniferous forest, broadleaf-conifer mixed forest, and broadleaf mixed forest. Insects were identified using morphological guides from taxonomic monographs. Shannon-Wiener diversity index, Pielou evenness index, Margalef richness index, and Simpson diversity index were used to evaluate α-diversity. Differences between insect diversity in different habitats and taxonomic orders were evaluated by Kruskal-Wallis analyses. Insect diversity in different habitats was estimated by rarefaction and extrapolation analyses. Bray-Curtis distance was calculated to evaluate the similarity of insect diversity and richness between different habitats. The influence of different environmental variables, both abiotic and biotic, on insect diversity was evaluated by redundancy analysis and Pearson correlation. Both samplings of the whole year and a part of summer were used.
Results: A total of 59,648 insects belonging to 145 species in 78 families and 9 orders were collected. Among these, the orders Lepidoptera, Hemiptera, Hymenoptera, and Diptera had the highest number of species and relative abundance. Most species were captured between July and September. Rarefaction and extrapolation analyses showed that the collections of specimens can represent the insect communities of each habitat. The α-diversity analyses indicated that woodland in broadleaf mixed forest had the highest insect diversity among sampled habitats, while woodland in artificial coniferous forest had the lowest. Although most habitats do not differ significantly in α-diversity, in terms of species composition, only the wetland in broadleaf-conifer mixed forest was moderately similar to the woodland in broadleaf mixed forest. Other habitats were all moderately dissimilar or very dissimilar to each other. The redundancy analyses showed that artificial interference of vegetation, pedestrian volume, altitude, temperature, sunshine duration, and precipitation were the major variables that significantly impacted insect diversity at the southern foot of Zijin Mountain. In addition, Pearson analyses indicated that most variables are correlated to insect diversity. Despite the different effects environmental variables have on the α-diversity of major insect orders, artificial interference of vegetation had the most significant effect, as our results showed that insect diversity significantly decreased with the increase of artificial interference of vegetation. Considering the correlations between insect diversity and other variables that can be attributed to artificial interferences, we determined that vegetation structure was the variable that has the highest degree of influence on insect diversity in urban forests.
Conclusion: This study clarifies key factors affecting insect diversity in urban forests. This could potentially provide theoretical guidance in urban species diversity conservation. Scientific planning and management of vegetation structure may be the key to preserving insect diversity in urban forests. It is thus suggested that more research on the dominant factors affecting the diversity of the major insect groups be carried out. This, even at a smaller scale according to local conditions, could greatly benefit the dynamic management of urban forests.
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