# A Bayesian model for assessing organic matter supply in complex marine food webs using amino acid stable isotope analysis

**Authors:** Connor H.H. Shea, Jeffrey C. Drazen, Brian N. Popp

PMC · DOI: 10.7717/peerj.20220 · PeerJ · 2025-11-19

## TL;DR

This paper introduces a new Bayesian model to trace organic matter flow in marine food webs using amino acid isotope data, improving understanding of nutrient transfer in complex ecosystems.

## Contribution

A novel Bayesian mixing model for amino acid stable isotope analysis to assess organic matter supply in marine food webs.

## Key findings

- The model successfully estimates trophic relationships and organic matter contributions in simulated zooplankton data.
- Certain amino acids like glutamic acid and proline are effective markers for trophic ecology, while phenylalanine, lysine, and threonine trace basal organic matter sources.
- Amino acids with inconsistent isotope fractionation (e.g., isoleucine, valine) should be excluded to improve model reliability.

## Abstract

While several software packages have been developed to solve stable isotope mixing models, none are currently equipped to trace the flow of organic matter through the lower trophic levels of planktonic food webs. To address this gap, we have developed a new Bayesian mixing model tailored for use with δ15N values of individual amino acids. This model simultaneously estimates trophic relationships between consumers and organic matter sources at the base of the food web, determines the relative contributions of these basal organic matter sources to consumers, and accounts for trophic discrimination affecting amino acid δ15N values during protozoan and metazoan trophic steps. This “Organic Matter Supply Model” is uniquely suited for applications where food web structure is unknown and trophic intermediaries, such as protozoan and metazoan grazers with distinct amino acid trophic discrimination factors, play a critical role in nutrient transfer. In this paper, we describe the model’s basic structure, outline key considerations for adapting it to specific applications, evaluate its performance using simulated zooplankton data, discuss its strengths and limitations, and offer recommendations for its further development. By testing the model on simulated zooplankton amino acid δ15N data, we demonstrate that the Organic Matter Supply Model can enhance our understanding of the roles of small particles and diel vertical migration in deep-sea organic matter supply pathways. Furthermore, it provides a new framework for exploring the foundational role of heterotrophic protists in marine ecosystems. We find specific subsets of amino acids to be most useful as markers of trophic ecology (in this case including glutamic acid and proline) and to identify supply from basal organic matter sources (phenylalanine, lysine, and threonine). Other amino acids may be more ideal source tracers in other settings, although amino acids with inconsistent or poorly constrained isotope fractionation behavior (e.g., isoleucine, valine) should be excluded to optimize model reliability.

## Linked entities

- **Chemicals:** glutamic acid (PubChem CID 611), proline (PubChem CID 614), phenylalanine (PubChem CID 994), lysine (PubChem CID 866), threonine (PubChem CID 205), isoleucine (PubChem CID 791), valine (PubChem CID 1182)

## Full-text entities

- **Chemicals:** threonine (MESH:D013912), proline (MESH:D011392), glutamic acid (MESH:D018698), lysine (MESH:D008239), phenylalanine (MESH:D010649), Organic Matter (-), valine (MESH:D014633), isoleucine (MESH:D007532), amino acid (MESH:D000596)

## Full text

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## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12640130/full.md

## References

43 references — full list in the complete paper: https://tomesphere.com/paper/PMC12640130/full.md

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Source: https://tomesphere.com/paper/PMC12640130