投稿中心

审稿中心

编辑中心

期刊出版

网站地图

友情链接

附件
引用本文:
【打印本页】   【HTML】   【下载PDF全文】   查看/发表评论  【EndNote】   【RefMan】   【BibTex】
过刊浏览    高级检索
本文已被:浏览 515次   下载 344  
分享到: 微信 更多
基于环境DNA技术的贵州山区河流鱼类多样性影响因素初步探究
关晓玉1, 严晗璐1, 尹智力2, 陈求稳1,3, 黄天宬1, 刘凌言1, 林育青1,3, 何术锋1
1.南京水利科学研究院生态环境研究所;2.贵州省水利水电勘测设计研究院有限公司;3.长江保护与绿色发展研究院
摘要:
本研究基于环境DNA(eDNA)技术,对贵州省内7个水系的30条典型山区河流开展鱼类多样性调查。结果显示,共调查到鱼类89种,以鲤形目为主,包含5种外来鱼类和4种珍稀濒危鱼类,其中至少74种鱼类(鉴定到种水平物种数的89.2%)在已有研究中有记载。从栖息水层来看,以底层和中下层鱼类为主;从食性来看,以杂食性和肉食性鱼类为主。鲤(Cyprinus carpio)、鲫(Carassius auratus)、鳙(Hypophthalmichthys nobilis)、子陵吻虾虎鱼(Rhinogobius giurinus) 分布较广,均在超过90%的采样点中出现。基于eDNA序列丰度计算鱼类多样性指数(Richness、Shannon-Wiener、Simpson、Pielou),根据多样性指数评价标准,山区河流的鱼类多样性状况总体良好;在空间分布上,鱼类多样性指数未表现出显著的海拔梯度变化特征。基于分段结构方程模型(piecewiseSEM)分析了海拔、景观类型、理化指标、污染指标、生态流量满足程度和人类活动对4种鱼类多样性指数的影响,结果表明水体理化指标和污染指标是影响贵州省山区河流鱼类多样性的关键因子,人类活动和生态流量满足程度是次要影响因子;进一步基于聚合增强树(aggregated boosted tree)评估了不同水质指标对鱼类多样性指数的重要性,发现水温、电导率与氨氮是影响鱼类多样性指数的主要水质因子。此外,研究的环境因子中污染指标、人类活动和生态流量直接作用于鱼类多样性指数,其他因子则通过间接途径产生影响,且不同多样性指数对同一环境因子的响应存在差异。本研究可为山区河流鱼类调查方法的选择提供参考,并为山区河流鱼类多样性保护工作提供数据基础和理论支持。
关键词:  山区河流  环境DNA  鱼类多样性  环境因子  结构方程模型
DOI:
分类号:
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
Preliminary Exploration of Factors Influencing Fish Diversity in Guizhou Mountain Rivers Based on Environmental DNA Technology
Guan Xiaoyu,Yan Hanlu,Yin Zhili,Chen Qiuwen,Huang Tiancheng,Liu Lingyan,Lin Yuqing,He Shufeng
Nanjing Hydraulic Research Institute,Center for Eco-Environmental Research
Abstract:
This study, conducted in Guizhou Province, China, utilized environmental DNA (eDNA) technology to conduct a fish diversity survey in 30 typical mountainous rivers across seven river systems. The results of the study revealed a total of 89 fish species, with 83 of these species being identified to the species level. The majority of the identified species belonged to the order Cypriniformes, including five exotic species and four rare or endangered species. It is noteworthy that at least 74 species (89.2% of those identified to the species level) have been previously documented in existing studies. With respect to their habitat, benthic and demersal fish were predominant, while omnivorous and carnivorous species were more prevalent based on their feeding habits. Cyprinus carpio, Carassius auratus, Hypophthalmichthys nobilis and Rhinogobius giurinu were found to be widely distributed, appearing in over 90% of the sampling sites. Fish diversity indices (Richness, Shannon-Wiener, Simpson, and Pielou) indicated favorable fish diversity conditions in the surveyed rivers, with no significant altitudinal gradient patterns observed in the diversity indices. Utilizing piecewise structural equation modelling (piecewiseSEM), we conducted a comprehensive analysis of the factors influencing the four fish diversity indices. These factors included altitude, landscape type, physicochemical parameters, pollution indicators, ecological flow satisfaction, and human activities. The results of the analysis revealed that physicochemical parameters and pollution indicators emerged as the primary factors affecting fish diversity in the mountainous rivers of Guizhou Province. In contrast, human activities and ecological flow satisfaction were found to be secondary factors. Furthermore, an aggregated boosted tree (ABT) analysis was employed to assess the importance of various water quality parameters on fish diversity indices, revealing that water temperature, conductivity, and ammonia nitrogen were the primary water quality factors affecting fish diversity. Additionally, among the environmental factors examined, pollution indicators, human activities, and ecological flow satisfaction directly influenced fish diversity indices, whereas other factors exerted indirect effects. Notably, different diversity indices exhibited varying responses to the same environmental factors. This study provides methodological insights for fish diversity surveys in mountainous rivers and offers a data-driven foundation and theoretical support for the conservation of fish biodiversity in these ecosystems.
Key words:  Mountainous Rivers  Environmental DNA  Fish Diversity  Environmental Factors  Structural Equation Modeling
分享按钮