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Finding Liebig’s law of the minimum
Liebig’s law of the minimum (LLM) is often used to interpret empirical biological growth data and model multiple substrates co‐limited growth. However, its mechanistic foundation is rarely discussed, even though its validity has been questioned since its introduction in the 1820s. Here we first show...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9285345/ https://www.ncbi.nlm.nih.gov/pubmed/34529311 http://dx.doi.org/10.1002/eap.2458 |
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author | Tang, Jinyun Riley, William J. |
author_facet | Tang, Jinyun Riley, William J. |
author_sort | Tang, Jinyun |
collection | PubMed |
description | Liebig’s law of the minimum (LLM) is often used to interpret empirical biological growth data and model multiple substrates co‐limited growth. However, its mechanistic foundation is rarely discussed, even though its validity has been questioned since its introduction in the 1820s. Here we first show that LLM is a crude approximation of the law of mass action, the state of art theory of biochemical reactions, and the LLM model is less accurate than two other approximations of the law of mass action: the synthesizing unit model and the additive model. We corroborate this conclusion using empirical data sets of algae and plants grown under two co‐limiting substrates. Based on our analysis, we show that when growth is modeled directly as a function of substrate uptake, the LLM model improperly restricts the organism to be of fixed elemental stoichiometry, making it incapable of consistently resolving biological adaptation, ecological evolution, and community assembly. When growth is modeled as a function of the cellular nutrient quota, the LLM model may obtain good results at the risk of incorrect model parameters as compared to those inferred from the more accurate synthesizing unit model. However, biogeochemical models that implement these three formulations are needed to evaluate which formulation is acceptably accurate and their impacts on predicted long‐term ecosystem dynamics. In particular, studies are needed that explore the extent to which parameter calibration can rescue model performance when the mechanistic representation of a biogeochemical process is known to be deficient. |
format | Online Article Text |
id | pubmed-9285345 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92853452022-07-15 Finding Liebig’s law of the minimum Tang, Jinyun Riley, William J. Ecol Appl Articles Liebig’s law of the minimum (LLM) is often used to interpret empirical biological growth data and model multiple substrates co‐limited growth. However, its mechanistic foundation is rarely discussed, even though its validity has been questioned since its introduction in the 1820s. Here we first show that LLM is a crude approximation of the law of mass action, the state of art theory of biochemical reactions, and the LLM model is less accurate than two other approximations of the law of mass action: the synthesizing unit model and the additive model. We corroborate this conclusion using empirical data sets of algae and plants grown under two co‐limiting substrates. Based on our analysis, we show that when growth is modeled directly as a function of substrate uptake, the LLM model improperly restricts the organism to be of fixed elemental stoichiometry, making it incapable of consistently resolving biological adaptation, ecological evolution, and community assembly. When growth is modeled as a function of the cellular nutrient quota, the LLM model may obtain good results at the risk of incorrect model parameters as compared to those inferred from the more accurate synthesizing unit model. However, biogeochemical models that implement these three formulations are needed to evaluate which formulation is acceptably accurate and their impacts on predicted long‐term ecosystem dynamics. In particular, studies are needed that explore the extent to which parameter calibration can rescue model performance when the mechanistic representation of a biogeochemical process is known to be deficient. John Wiley and Sons Inc. 2021-10-20 2021-12 /pmc/articles/PMC9285345/ /pubmed/34529311 http://dx.doi.org/10.1002/eap.2458 Text en © 2021 The Authors. Ecological Applications published by Wiley Periodicals LLC on behalf of The Ecological Society of America. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Tang, Jinyun Riley, William J. Finding Liebig’s law of the minimum |
title | Finding Liebig’s law of the minimum |
title_full | Finding Liebig’s law of the minimum |
title_fullStr | Finding Liebig’s law of the minimum |
title_full_unstemmed | Finding Liebig’s law of the minimum |
title_short | Finding Liebig’s law of the minimum |
title_sort | finding liebig’s law of the minimum |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9285345/ https://www.ncbi.nlm.nih.gov/pubmed/34529311 http://dx.doi.org/10.1002/eap.2458 |
work_keys_str_mv | AT tangjinyun findingliebigslawoftheminimum AT rileywilliamj findingliebigslawoftheminimum |