Stoichiometry of microbial carbon use efficiency in soils

Abstract

Abstract. The carbon use efficiency (CUE) of microbial communities partitions the flow of C from primary producers to the atmosphere, decomposer food webs and soil C stores. CUE, usually defined as the ratio of growth to assimilation, is a critical parameter in ecosystem models, but is seldom measured directly in soils because of the methodological difficulty of measuring in situ rates of microbial growth and respiration. Alternatively, CUE can be estimated indirectly from the elemental stoichiometry of organic matter and microbial biomass, and the ratios of C to nutrient-acquiring ecoenzymatic activities. We used this approach to estimate and compare microbial CUE in >2000 soils from a broad range of ecosystems. Mean CUE based on C:N stoichiometry was 0.269 ± 0.110 (SD). A parallel calculation based on C:P stoichiometry yielded a mean CUE estimate of 0.252 ± 0.125 (SD). The mean values and frequency distributions were similar to those from aquatic ecosystems, also calculated from stoichiometric models, and to those calculated from direct measurements of bacterial and fungal growth and respiration. CUE was directly related to microbial biomass C with a scaling exponent of 0.304 ± 0.067 (95% CI) and inversely related to microbial biomass P with a scaling exponent of -0.234 ± 0.055 (95% CI). Relative to CUE, biomass specific turnover time increased with a scaling Accepted ArticleThis article is protected by copyright. All rights reserved. exponent of 0.509 ± 0.042. CUE increased weakly with mean annual temperature. CUE declined with increasing soil pH reaching a minimum at pH 7.0, then increased again as soil pH approached 9.0, a pattern consistent with pH trends in the ratio of fungal:bacteria abundance and growth. Structural equation models that related geographic variables to CUE component variables showed the strongest connections for paths linking latitude and pH to ß-glucosidase activity and soil C:N:P ratios. The integration of stoichiometric and metabolic models provides a quantitative description of the functional organization of soil microbial communities that can improve the representation of CUE in microbial process and ecosystem simulation models.

Minerals in the rhizosphere: overlooked mediators of soil nitrogen availability to plants and microbes

“…In contrast to scenarios where CUE is high, microbes that use C inefficiently will require less N, and will consequently show a depressed N mining response to root exudation (Mooshammer et al 2014). Further, microbial CUE and NUE also constrain microbial biomass, turnover, and activity, which will have feedbacks to the cycling and bioavailability of MAOM-N (Sinsabaugh et al 2016).…”

ORCHIDEE-SOM: modeling soil organic carbon (SOC) and dissolved organic carbon (DOC) dynamics along vertical soil profiles in Europe

“…The lower CUE in Hainich may be partly explained by the higher soil pH compared to Brasschaat coniferous forest (Table 2). Less acidic soils may contribute to lowering not only DOC concentrations in the soil solution of the Hainich forest (CaminoSerrano et al, 2014;Löfgren and Zetterberg, 2011), but also the microbial CUE that tends to decrease with increasing soil pH, reaching a minimum at pH 7.0 (Sinsabaugh et al, 2016).…”

“…15) as a first step towards linking the physicochemical soil properties to our model parameters, although the correlation was weak and some important parameters (Al or Fe in soils) are still missing. A similar exercise should be done for biological model parameters like CUE DOC , which for the moment do not reflect their known changes with vegetation or soil properties (Manzoni et al, 2017;Sinsabaugh et al, 2016). Also, the SOC diffusion coefficient was kept constant along the soil profile, although it is known that diffusion is higher in the upper soil layers and that biotic activity is controlled by the pH, among other factors (Jagercikova et al, 2014).…”

ORCHIDEE-SOM: Modeling soil organic carbon (SOC) and dissolved organic carbon (DOC) dynamics along vertical soil profiles in Europe

“…In this case, the CUE DOC parameter was decreased from 0.5 to 0.35, value that is in agreement with 10 observed bacterial growth efficiency in soil water matrix in a beech forest (Andreasson et al, 2009), to better capture the relatively low DOC concentrations observed in Hainich forest (median= 9.53 mg L -1 , range=1.5-50.7 mg L -1 ). The higher soil pH compared to Brasschaat coniferous forest may have contributed to lowering DOC concentrations in the soil solution of the Hainich forest, and microbial CUE tends to decrease with soil pH, reaching a minimum at pH 7.0 (Sinsabaugh et al, 2016). 15…”

“…15), as a first step 35 towards linking the physico-chemical soil properties to our model parameters, although the correlation was weak and some important parameters (Al or Fe in soils) are still missing. A similar exercise should be done for the biological model parameters like CUE DOC , which for the moment do not reflect their known changes with vegetation or soil properties (Manzoni et al, 2017;Sinsabaugh et al, 2016). Also, the SOC diffusion coefficient Geosci.…”