Microbial growth rate is a stronger predictor of soil organic carbon than carbon use efficiency

nature ecology and evolution

Analysis

Microbial growth rate is a stronger predictor of soil organic carbon than carbon use efficiency

The extent to which microbial processes control soil organic carbon dynamics remains uncertain. Carbon use efficiency, that is, the fraction of assimilated carbon allocated to growth, has been used as a key parameter but its relationship with soil organic carbon reflects carbon partitioning rather than the absolute magnitude of microbial fluxes. The microbial growth rate could provide a more mechanistic link to soil organic carbon accumulation because it quantifies biomass production and reflects necromass formation. Here we combine a global one hundred eighty-H2O dataset paired observations with outputs from four land surface models to test whether growth rate predicts soil organic carbon more strongly than carbon use efficiency. In the incubation experiments, growth rates are more closely associated with soil organic carbon than carbon use efficiency, although soil properties and climate explain equal or greater variance. Models reproduce the stronger role of growth rate over carbon use efficiency but tend to underestimate the abiotic controls. The models also emphasize carbon use efficiency as the main predictor of the soil organic carbon-to-net primary production ratio, in contrast to observations, which indicates the soil's capacity to retain plant carbon inputs. Together, these findings identify the microbial growth rate as a diagnostic that can help bridge models with empirical data and guide a more balanced representation of microbial and mineral controls in soil organic carbon projections.

A key principle in soil carbon research is that carbon fluxes, rather than static pool sizes, are more directly linked to ecosystem function. Microorganisms exemplify this principle, where although microbial biomass typically accounts for less than five percent of total soil organic carbon, microbial residues (necromass) can contribute over fifty percent of soil organic carbon. This reflects their disproportionate and lasting contribution to long-term soil carbon sequestration. This enduring contribution arises from rapid cycling of microbial biomass, which regulates the fluxes of microbial carbon uptake, respiration, growth and death. Therefore, microbial communities act as a biological pump actively shaping soil organic carbon dynamics,

complementing the mineral pump that stabilizes organic matter through mineral interactions.

However, in efforts to quantify microbial control over soil organic carbon dynamics, recent studies have focused on microbial carbon use efficiency, that is, the proportion of assimilated carbon allocated to growth, as a key parameter linking microbial activity to soil organic carbon. Several modeling studies suggest that carbon use efficiency strongly affects soil organic carbon stocks, with Tao et al. reporting that global variations in carbon use efficiency exert a greater influence on soil organic carbon than any other model parameter. However, this claim remains contested. Subsequent work has highlighted methodological concerns such as equifinality in inverse modeling and the omission of key physicochemical stabilization processes, while empirical studies found inconsistent soil organic carbon-carbon use efficiency relationships. More fundamentally, carbon use efficiency is a ratio property; it describes carbon partitioning between growth and respiration but does not capture the absolute magnitude of microbial carbon fluxes. Consequently, a high carbon use efficiency does not necessarily result in greater soil organic carbon accumulation. If microbial biomass turns over rapidly, assimilated carbon may be quickly respired or recycled, limiting its contribution to long-term storage. Conversely, a low carbon use efficiency does not necessarily limit soil organic carbon accumulation. When microbial processing is inefficient and decomposition rates are slow, organic carbon can still progressively accumulate over time depending on stabilization by mineral interactions. These scenarios highlight that carbon use efficiency captures only part of the microbial influence on soil organic carbon and that the variability of soil organic carbon ultimately reflects both microbial process rates and the strength of physicochemical stabilization.

Microbial growth rate, which quantifies the gross rate of biomass production, offers a more mechanistic and process-based metric linking carbon assimilation to microbial biomass cycling and necromass formation. Accumulating evidence suggests that the growth rate may show a stronger association with soil organic carbon dynamics than carbon use efficiency because the microbial growth rate reflects the production and cycling of microbial residues, which are key precursors to stable soil organic carbon. Moreover, while both the microbial growth rate and carbon use efficiency are ecologically meaningful properties, the growth rate is more plastic and responsive to environmental variation, whereas carbon use efficiency is often more constrained across conditions.

In this study, we adopt an integrative framework, which is common in process-based models but less emphasized in experimental studies, in which microbial process rates such as uptake and growth, together with carbon use efficiency, jointly regulate soil organic carbon dynamics. In this framework, microbial process rates act as the engine driving carbon fluxes, with carbon use efficiency serving as the transmission that modulates their efficiency. This highlights the microbial growth rate as the direct mechanistic link to soil organic carbon dynamics, with carbon use efficiency operating as a secondary modulator.

In this study, we combine a global observational dataset derived from the one hundred eighty-H2O labeling method, a robust and widely used approach for quantifying microbial growth rates and carbon use efficiency, with outputs from four land surface models. We ask whether the microbial growth rate is a stronger predictor of observed spatial variation in soil organic carbon than carbon use efficiency or abiotic factors underpinning the mineral pump of soil organic carbon stabilization. In addition, we introduce a diagnostic framework that connects microbial observations with model outputs, offering a clearer way to evaluate model performance and improve predictions of soil carbon change.

Results Observed soil organic carbon is more strongly linked to microbial growth than to carbon use efficiency but even more to abiotic factors

Using two hundred sixty-eight paired observations obtained via the one hundred eighty-H two O labelling method across diverse ecosystems, we examined the relationships between SOC and microbial or ecosystem properties. Bivariate regressions identified significant positive correlations between SOC and the microbial absolute growth rate (that is, microbial biomass production per unit soil mass per unit time; R squared equals zero point three seven one, P is less than zero point zero zero one), microbial respiration rate R squared equals zero point two six nine, P is less than zero point zero zero one, microbial biomass R squared equals zero point two eight five, P is less than zero point zero zero one and, to a much lesser extent, microbial CUE R squared equals zero point zero one five, P equals zero point zero four six). On the other hand, the microbial specific growth rate (that is, the microbial growth rate normalized to the microbial biomass; R squared less than zero point zero zero one, P equals zero point nine nine nine) and net primary production (NPP) (derived from MODIS; R squared less than zero point zero zero one, P equals zero point nine nine nine) showed no significant relationship with SOC. These results indicate that SOC covaries more strongly with microbial absolute growth and biomass than with CUE, specific growth rate or plant productivity.

Random forest regression confirmed these patterns: the microbial growth rate was a stronger predictor of SOC than CUE; however, the soil clay content and the mean annual temperature (MAT) explained comparable or even greater variation. Thus, while the growth rate provides a clearer microbial link to SOC than CUE, abiotic constraints remain equally or even more important.

The positive association between absolute microbial growth rate and SOC mainly reflected microbial biomass regulation by SOC availability: the absolute growth rate correlated with microbial biomass R squared equals zero point two three seven, P is less than zero point zero zero one, respiration R squared equals zero point three eight one, P is less than zero point zero zero one and, to a lesser extent, specific growth rate R squared equals zero point two one nine, P is less than zero point zero zero one; Supplementary Figure two a. On the other hand, soil microbial CUE showed no significant relationship with microbial biomass R squared equals zero point zero one five, P equals zero point zero nine four, a negative relationship with the microbial respiration rate R squared equals zero point two four five, P is less than zero point zero zero one, a modest positive relationship with the specific microbial growth rate R squared equals zero point two zero nine, P is less than zero point zero zero one and a weak positive relationship with the absolute microbial growth rate R squared equals zero point one one nine, P is less than zero point zero zero one; Supplementary Figure two b. Together, these patterns indicate that the absolute microbial growth rate, or the associated respiration rate, captures SOC variation more consistently than microbial CUE, which is largely decoupled from both SOC and microbial biomass.

Because microbial growth rates were measured under controlled laboratory conditions, we examined their sensitivity to incubation temperature. Growth rates exhibited only weak temperature dependence, both in absolute terms R squared equals zero point zero two, P equals zero point zero three four; Supplementary Figure three a and when normalized by SOC to account for pool-size effects R squared equals zero point zero one, P equals zero point one four two; Supplementary Figure three b. These results indicate that the observed variation in microbial growth mainly reflects actual site differences rather than artefacts of incubation temperature.