Elucidating food web structure of the Poyang Lake ecosystem using amino acid nitrogen isotopes and Bayesian mixing model

Abstract

Compound‐specific isotope analysis of amino acids (CSIA‐AA) is regarded as a more advanced method of unraveling food web connections than the traditional bulk isotope approach. One of the most important assumptions of the CSIA‐AA approach is that the initial offset (β) between glutamate and phenylalanine in primary producers should remain unchanged. However, the considerable difference in β values between algae (+3.4‰) and vascular plants (−8.0‰) raises concern regarding the application of the CSIA‐AA approach for complex ecosystems that depend on both resources. In the present study, a Bayesian mixing model was used to estimate the individual contribution of basal dietary resources to each consumer of Poyang Lake, and then, the β was reevaluated to adapt to the assimilation of the individual primary producer for each consumer specimen. In general, the contributions of vascular plant‐derived resources to most consumers are consistent with their feeding behaviors. The smaller contribution of vascular plants to planktivorous fish (usually less than 20%) is biologically expected because of their feeding ecology. Using this strategy, we successfully obtained realistic trophic positions (TP) of consumers in Poyang Lake, which are significantly different from traditional TPalgae or TPvascular. For instance, the TP value of grass carp (2.04) was consistent with the feeding behavior of this fish, i.e., they primarily feed on vascular hydrophytes. Therefore, the combination of the CSIA‐AA and Bayesian mixing model provides a better understanding of food web structures, even in a complex freshwater ecosystem.

Amino acid nitrogen and carbon isotope data: Potential and implications for ecological studies

“…Moreover, obtaining the correct TP AA helps to infer the δ 15 N baseline of local habitats across geographic scales, and ultimately to construct isotope maps to trace migration routes of consumer animals over regions and time periods (Le‐Alvarado et al, 2021 ; Matsubayashi et al, 2020 ). Overall, an accurate TP AA estimate enables connecting trophic relations reliably between individual species and, consequently, delineating food web complexity and construction in detail (Bode et al, 2021 ; Decima & Landry, 2020 ; Zhang, Tian, et al, 2019 ).…”

“…Moreover, obtaining the correct TP AA helps to infer the δ 15 N baseline of local habitats across geographic scales, and ultimately to construct isotope maps to trace migration routes of consumer animals over regions and time periods(Le-Alvarado et al, 2021;Matsubayashi et al, 2020). Overall, an accurate TP AA estimate enables connecting trophic relations reliably between individual species and, consequently, delineating food web complexity and construction in detail(Bode et al, 2021;Decima & Landry, 2020;Zhang, Tian, et al, 2019).Determining the TP AA of consumer is frequently generated byGlx and Phe pair, trophic AA and source AA, respectively, and recent studies examined Ala or Pro relative to Phe, and the mean of multiple trophic AA δ 15 N variables relative to the mean of multiple source AA δ 15 N variables. It is very important to obtain proper TDF…”

Meta‐analysis of primary producer amino acid δ15N values and their influence on trophic position estimation

“…Freshwater non‐vascular primary producers are woefully understudied within the CSIA‐AA literature (3.8% of analysed taxa; Table 1), with only four studies reporting AA δ 15 N data (Fogel & Tuross, 1999; Ishikawa et al., 2014; Ohkouchi et al, 2015; Zhang et al, 2019, 2021). Freshwater eukaryotic microalgae β Glx‐Phe values (+4.2 ± 0.7‰, n = 5) were similar to those of their marine counterparts (+3.9 ± 1.6‰, n = 22, p > 0.05; Figure 3).…”

“…Multiple molecular tools are available for use in tandem with mixing models to estimate the relative contribution of vascular and non‐vascular primary producers to consumer food webs, such as bulk tissue δ 13 C and δ 15 N values (e.g. Choi et al., 2017; Zhang et al., 2019, 2021), AA δ 13 C ‘fingerprinting’ (e.g. Bowes et al., 2020; Chua et al., 2020), fatty acid analysis (Hebert et al., 2016) and Δ Met‐Phe (δ 15 N Met – δ 15 N Phe ; Ishikawa et al, 2018).…”

Trophic Transfer of Halogenated Organic Pollutants in a Wetland Food Web: Insights from Compound-Specific Nitrogen Isotope of Amino Acids and Food Source Analysis

“…Quantification of the relative contribution of primary producers within consumers based on stable isotope analysis and the relative contribution of food sources in each consumer species was quantized by the quantitative fatty acid signature analysis (the QFASA model). We ran the Bayesian mixing model of SIMMR (the simmr model) (Package SIMMR version 0.4.5) with four isotope indexes of δ 13 C, δ 15 N, δ 15 N Phe , and δ 15 N Glu − and ran the QFASA model (Package qfasar version 1.2.1) with 14 fatty acids (more than 1% of all samples) in RStudio Version 1.3.1093. The parameter settings of the model and the method for trophic position correction are described in Text S1.…”