Clarifying the trophic state concept to advance macroscale freshwater science and management

Michael F. Meyer, Benjamin M. Kraemer, Carolina C. Barbosa, Davi G.F. Cunha, Walter K. Dodds, Stephanie E. Hampton, César Ordóñez, Rachel M. Pilla, Amina I. Pollard, Joshua A. Culpepper, Alexander K. Fremier, Tyler V. King, Robert Ladwig, Dina M. Leech, Shin Ichiro S. Matsuzaki, Isabella A. Oleksy, Simon N. Topp, R. Iestyn Woolway, Ludmila S. Brighenti, Kate C. FickasBrian P. Lanouette, Jianning Ren, Mortimer Werther, Xiao Yang

Research output: Contribution to journalArticlepeer-review

Abstract

For over a century, ecologists have used the concept of trophic state (TS) to characterize an aquatic ecosystem's biological productivity. However, multiple TS classification schemes, each relying on a variety of measurable parameters as proxies for productivity, have emerged to meet use-specific needs. Frequently, chlorophyll a, phosphorus, and Secchi depth are used to classify TS based on autotrophic production, whereas phosphorus, dissolved organic carbon, and true color are used to classify TS based on both autotrophic and heterotrophic production. Both classification approaches aim to characterize an ecosystem's function broadly, but with varying degrees of autotrophic and heterotrophic processes considered in those characterizations. Moreover, differing classification schemes can create inconsistent interpretations of ecosystem integrity. For example, the US Clean Water Act focuses exclusively on algal threats to water quality, framed in terms of eutrophication in response to nutrient loading. This usage lacks information about non-algal threats to water quality, such as dystrophication in response to dissolved organic carbon loading. Consequently, the TS classification schemes used to identify eutrophication and dystrophication may refer to ecosystems similarly (e.g., oligotrophic and eutrophic), yet these categories are derived from different proxies. These inconsistencies in TS classification schemes may be compounded when interdisciplinary projects employ varied TS frameworks. Even with these shortcomings, TS can still be used to distill information on complex aquatic ecosystem function into a set of generalizable expectations. The usefulness of distilling complex information into a TS index is substantial such that usage inconsistencies should be explicitly addressed and resolved. To emphasize the consequences of diverging TS classification schemes, we present three case studies for which an improved understanding of the TS concept advances freshwater research, management efforts, and interdisciplinary collaboration. To increase clarity in TS, the aquatic sciences could benefit from including information about the proxy variables, ecosystem type, as well as the spatiotemporal domains used to classify TS. As the field of aquatic sciences expands and climatic irregularity increases, we highlight the importance of re-evaluating fundamental concepts, such as TS, to ensure their compatibility with evolving science.

Original languageEnglish
Article numbere70392
JournalEcosphere
Volume16
Issue number9
DOIs
StatePublished - Sep 2025

Funding

We thank Matthew R. Brousil, Jack R. Eggleston, Matthew R.V. Ross, Dustin W. Kincaid, and Jacob A. Zwart for diverse creative support during the formation of this manuscript. We are very grateful to Craig E. Williamson, Linnea A. Rock, Bryan M. Maitland, and Paul C. Hanson for commenting on a previous version of this manuscript. Michael F. Meyer, Simon N. Topp, and Kate C. Fickas were supported by a Mendenhall Fellowship from the US Geological Survey Water Mission Area. Rachel M. Pilla was supported by the US Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Water Power Technologies Office, and Environmental Sciences Division at Oak Ridge National Laboratory (ORNL). ORNL is managed by UT‐Battelle, LLC, for the US DOE under contract DE‐AC05‐00OR22725. IAO was supported by awards EPS‐2019528 and DEB‐2306895. DGFC thanks Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for the research productivity grant (number 310844/2020‐7). LSB thanks the Programa de Apoio Institucional a Pesquisa from the Universidade do Estado de Minas Gerais for the research productivity grant (PAPq‐UEMG 11/2022). RIW was supported by a UKRI Natural Environment Research Council (NERC) Independent Research Fellowship (grant number NE/T011246/1). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government. We thank Matthew R. Brousil, Jack R. Eggleston, Matthew R.V. Ross, Dustin W. Kincaid, and Jacob A. Zwart for diverse creative support during the formation of this manuscript. We are very grateful to Craig E. Williamson, Linnea A. Rock, Bryan M. Maitland, and Paul C. Hanson for commenting on a previous version of this manuscript. Michael F. Meyer, Simon N. Topp, and Kate C. Fickas were supported by a Mendenhall Fellowship from the US Geological Survey Water Mission Area. Rachel M. Pilla was supported by the US Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Water Power Technologies Office, and Environmental Sciences Division at Oak Ridge National Laboratory (ORNL). ORNL is managed by UT-Battelle, LLC, for the US DOE under contract DE-AC05-00OR22725. IAO was supported by awards EPS-2019528 and DEB-2306895. DGFC thanks Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for the research productivity grant (number 310844/2020-7). LSB thanks the Programa de Apoio Institucional a Pesquisa from the Universidade do Estado de Minas Gerais for the research productivity grant (PAPq-UEMG 11/2022). RIW was supported by a UKRI Natural Environment Research Council (NERC) Independent Research Fellowship (grant number NE/T011246/1). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.

Keywords

  • classificaiton
  • ecosystem function
  • limnology
  • metabolism
  • water quality

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