Volume 34, Issue 9
RESEARCH ARTICLE

Nutrient limitation, bioenergetics and stoichiometry: A new model to predict elemental fluxes mediated by fishes

Nina M. D. Schiettekatte

Corresponding Author

E-mail address: nina.schiettekatte@gmail.com

PSL Université Paris: EPHE‐UPVD‐CNRS, USR 3278 CRIOBE, Université de Perpignan, Perpignan, France

Laboratoire d'Excellence “CORAIL”, Perpignan, France

Correspondence

Nina M. D. Schiettekatte

Email: nina.schiettekatte@gmail.com

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Diego R. Barneche

Australian Institute of Marine Science, Crawley, WA, Australia

Oceans Institute, The University of Western Australia, Crawley, WA, Australia

College of Life and Environmental Sciences, University of Exeter, Penryn, UK

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Sébastien Villéger

MARBEC, Université de Montpellier, CNRS, IFREMER, IRD, Montpellier, France

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Jacob E. Allgeier

Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA

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Deron E. Burkepile

Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, CA, USA

Marine Science Institute, University of California, Santa Barbara, CA, USA

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Simon J. Brandl

Department of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada

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Jordan M. Casey

PSL Université Paris: EPHE‐UPVD‐CNRS, USR 3278 CRIOBE, Université de Perpignan, Perpignan, France

Laboratoire d'Excellence “CORAIL”, Perpignan, France

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Alexandre Mercière

PSL Université Paris: EPHE‐UPVD‐CNRS, USR 3278 CRIOBE, Université de Perpignan, Perpignan, France

Laboratoire d'Excellence “CORAIL”, Perpignan, France

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Katrina S. Munsterman

Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA

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Fabien Morat

PSL Université Paris: EPHE‐UPVD‐CNRS, USR 3278 CRIOBE, Université de Perpignan, Perpignan, France

Laboratoire d'Excellence “CORAIL”, Perpignan, France

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Valeriano Parravicini

PSL Université Paris: EPHE‐UPVD‐CNRS, USR 3278 CRIOBE, Université de Perpignan, Perpignan, France

Laboratoire d'Excellence “CORAIL”, Perpignan, France

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First published: 23 June 2020

Abstract

  1. Energy flow and nutrient cycling dictate the functional role of organisms in ecosystems. Fishes are key vectors of carbon (C), nitrogen (N) and phosphorus (P) in aquatic systems, and the quantification of elemental fluxes is often achieved by coupling bioenergetics and stoichiometry. While nutrient limitation has been accounted for in several stoichiometric models, there is no current implementation that permits its incorporation into a bioenergetics approach to predict ingestion rates. This may lead to biased estimates of elemental fluxes.
  2. Here, we introduce a theoretical framework that combines stoichiometry and bioenergetics with explicit consideration of elemental limitations. We examine varying elemental limitations across different trophic groups and life stages through a case study of three trophically distinct reef fishes. Further, we empirically validate our model using an independent database of measured excretion rates.
  3. Our model adequately predicts elemental fluxes in the examined species and reveals species‐ and size‐specific limitations of C, N and P. In line with theoretical predictions, we demonstrate that the herbivore Zebrasoma scopas is limited by N and P, and all three fish species are limited by P in early life stages. Further, we show that failing to account for nutrient limitation can result in a greater than twofold underestimation of ingestion rates, which leads to severely biased excretion rates.
  4. Our model improved predictions of ingestion, excretion and egestion rates across all life stages, especially for fishes with diets low in N and/or P. Due to its broad applicability, its reliance on many parameters that are well‐defined and widely accessible, and its straightforward implementation via the accompanying r‐package fishflux, our model provides a user‐friendly path towards a better understanding of ecosystem‐wide nutrient cycling in the aquatic biome.

A free Plain Language Summary can be found within the Supporting Information of this article.

DATA AVAILABILITY STATEMENT

All data and code to reproduce figures are available online at https://doi.org/10.5281/zenodo.3894509 (Schiettekatte, 2020). The r package fishflux, containing the model can be installed through GitHub: https://github.com/nschiett/fishflux.