多样性(政治)
点(几何)
计数效率
生物
数学
计算机科学
社会学
探测器
电信
人类学
几何学
作者
Hongming Shuai,Xiaoru Liu,Yigui Zhang,Yuqi Sun,Hao Li,Zhongqiu Li
出处
期刊:Avian research
[Springer Science+Business Media]
日期:2025-03-07
卷期号:16 (2): 100236-100236
被引量:4
标识
DOI:10.1016/j.avrs.2025.100236
摘要
Environmental DNA (eDNA) methods have emerged as a promising tool for studying a broad spectrum of biological taxa. However, metabarcoding studies of avian biodiversity using eDNA have received little attention. In this study, we compared waterbird biodiversity derived from eDNA metabarcoding with that obtained from traditional point counting surveys at 23 sites in Tai Lake and evaluated the accuracy of eDNA metabarcoding for waterbird community studies. The point counting method recorded a higher total number of waterbird species (22) compared to the eDNA technique (16). While eDNA achieved a 74.5% detection rate for waterbird species and was able to identify a significantly greater number of species (12.48 ± 1.97) at each sampling site than point counting method (6.13 ± 2.69), particularly highlighting several rare and elusive species, it failed to detect some species commonly observed by the point counting method. The alpha diversity analysis revealed no significant differences in waterbird diversity between the eDNA method and the point counting method, except that the eDNA method exhibited lower Pielou evenness. Waterbird eDNA sequencing abundance correlated significantly with species occurrence, whereas Spearman’s analysis indicated no significant difference between eDNA sequence abundance and species abundance from the point counting method. eDNA method detected no significant difference in waterbird composition between sampling sites, while the point counting method revealed significant differences. Consequently, eDNA is an effective complementary tool for assessing the diversity of wintering waterbirds in lakes, though it is unable to capture the full diversity of waterbird communities. It is crucial to develop sampling strategies that comprehensively monitor species composition and integrate eDNA with traditional survey methods for accurate evaluation of community structure.
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