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Carbon use efficiency of microbial communities: stoichiometry, methodology and modelling
Author(s) -
Sinsabaugh Robert L.,
Manzoni Stefano,
Moorhead Daryl L.,
Richter Andreas
Publication year - 2013
Publication title -
ecology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.852
H-Index - 265
eISSN - 1461-0248
pISSN - 1461-023X
DOI - 10.1111/ele.12113
Subject(s) - biomass (ecology) , ecosystem , trophic level , ecological stoichiometry , environmental science , ecology , aquatic ecosystem , resource (disambiguation) , nutrient , terrestrial ecosystem , microbial population biology , biochemical engineering , biology , computer science , computer network , engineering , genetics , bacteria
Carbon use efficiency ( CUE ) is a fundamental parameter for ecological models based on the physiology of microorganisms. CUE determines energy and material flows to higher trophic levels, conversion of plant‐produced carbon into microbial products and rates of ecosystem carbon storage. Thermodynamic calculations support a maximum CUE value of ~ 0.60 ( CUE max ). Kinetic and stoichiometric constraints on microbial growth suggest that CUE in multi‐resource limited natural systems should approach ~ 0.3 ( CUE max /2). However, the mean CUE values reported for aquatic and terrestrial ecosystems differ by twofold (~ 0.26 vs. ~ 0.55) because the methods used to estimate CUE in aquatic and terrestrial systems generally differ and soil estimates are less likely to capture the full maintenance costs of community metabolism given the difficulty of measurements in water‐limited environments. Moreover, many simulation models lack adequate representation of energy spilling pathways and stoichiometric constraints on metabolism, which can also lead to overestimates of CUE . We recommend that broad‐scale models use a CUE value of 0.30, unless there is evidence for lower values as a result of pervasive nutrient limitations. Ecosystem models operating at finer scales should consider resource composition, stoichiometric constraints and biomass composition, as well as environmental drivers, to predict the CUE of microbial communities.

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