期刊
LIMNOLOGY AND OCEANOGRAPHY
卷 62, 期 4, 页码 1426-1435出版社
WILEY
DOI: 10.1002/lno.10508
关键词
-
资金
- Ministry of Oceans and Fisheries, Korea
- Korea Institute of Ocean Science and Technology [PE99432]
- National Research Foundation of Korea [22A20130012692] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Numerous studies have used stable isotope analysis (SIA) of carbon and nitrogen within the bulk tissues of organisms to determine the trophic structure among organisms in a food web. Recently, SIA has evolved to compound-specific stable isotope analysis (CSIA) of nitrogen within amino acids to significantly reduce the uncertainty in the estimated trophic position (TP) of organisms based on the isotopic difference between glutamic acid and phenylalanine within a single organism. However, because the initial offset (beta) between glutamic acid and phenylalanine differs between aquatic algae (ca. +3.4 parts per thousand) and vascular plants (ca. -8.4 parts per thousand) in food webs that rely on both resources, beta should be replaced by a value adapted to the admixture of primary producers for each specimen. In this study, we established a new method involving the beta value (beta(mix)) of each consumer specimen determined based on its bulk tissue delta C-13 value and successfully obtained realistic TPs (TPmix) for organisms in a complex seagrass meadow food web. Remarkable differences between the TPmix and traditional TPalgal values were found in deposit feeders due to the large contribution of seagrass to their basal resources. The estimated TPs of organisms increased by up to 1.5 units (from TPalgal to TPmix), in terms of trophic transfer, when their diets included substantial seagrass-derived contributions. Thus, combinatorial analysis of the amino acid delta N-15 and specimen-specific beta(mix) values provides better understanding of the trophic interactions in food webs, even in complex seagrass meadow ecosystems.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据