ABSTRACT:

This Data Resource includes the Mathematica notebook developed to generate the Figures for the manuscript titled "Fluxes vs. Pools: Connecting Temperature Dependence and Sensitivity of Soil Carbon Dynamics Across Timescales". The Notebook can be run using Mathematica or through a Wolfram Engine. The abstract of the manuscript:

As global temperature (T) regimes shift, there is growing interest in understanding the biotic and abiotic mechanisms driving short- and long-term changes in soil organic carbon (SOC) dynamics. Inconsistent terminology—particularly the use of T sensitivity and dependence—and varying methodological emphases on SOC pools versus fluxes can hinder the integration of experimental results with process-based models aimed at mechanistic insights into SOC-T responses. Here, we clarify the distinction between T dependence (e.g., Q10 formulations of fluxes) and T sensitivity (i.e., T the derivative of SOC fluxes or pools), and demonstrate how T responses of SOC fluxes are related to that of SOC pools. We apply this framework to analyze SOC dynamics using experimental data and a SOC model, examining both steady-state (quasi-static) and transient responses, including the change in heterotrophic respiration following a step-change in T. Our analysis reveals that the T dependence of SOC pools emerges from the T dependence of individual fluxes and is determined, at steady state, by ratios of Q10 values. This underscores the need to measure multiple SOC pools and fluxes, and to use process-based models, in order to estimate the Q10s accurately. Recognizing heterotrophic respiration as an emergent process, we showed that its short-term T response is influenced by the Q10 ratio of microbial uptake and maintenance processes, while the long-term decline arises from mass-balance constraints. Our results offer a mechanistic basis for integrating flux- and pool-based studies and emphasize the importance of combining data and models to quantify SOC-T responses across temporal scales.

ABSTRACT:

Soil carbon cycling and ecosystem functioning can strongly depend on how microbial communities regulate their metabolism and adapt to changing environmental conditions to improve their fitness. Investing in extracellular enzymes is an important strategy for the acquisition of resources, but the principle behind the trade-offs between enzyme production and growth is not entirely clear. In the paper associated to this resource, we show that the enzyme production rate per unit biomass may be regulated in order to maximize the biomass specific growth rate. Here we provide the Mathematica code, with data embedded, used to draw the Figures.

ABSTRACT:

Microbial growth is a clear example of organization and structure arising in non-equilibrium conditions. Due to the complexity of the microbial metabolic network, elucidating the fundamental principles governing microbial growth remains a challenge. Here leveraging decades of experimental data on growth of microbial isolates, we study in depth the non-equilibrium thermodynamics of microbial growth to shed light on the relation between mass and energy constraints on growth. Our results show that there exist universal scaling laws relating the thermodynamic efficiency of microbial growth to the electron donor uptake rate and to the growth yield, which tightly couple mass and energy conversion in microbial growth. This resource contains an excel file with original data from Smeaton and Van Cappellen (2018) and the thermodynamic calculations for the article associated to this resource, and a Mathematica code used for drawing the Figures.

ABSTRACT:

Global methane (CH4) emissions have reached approximately 600 Tg per year, 20-40% of which are from wetlands. Of the primary factors affecting these emissions, the water table level is among the most uncertain. Here, a global meta-analysis of chamber and flux-tower observations of CH4 emissions shows that wetlands have maximum emissions at a critical level of inundation.

ABSTRACT:

This dataset contains measurements of chemical depletion fraction (CDF), from three published articles, and estimates for each location of the dryness index (PET/P). To estimate the dryness index, long-term potential evapotranspiration (PET) was retrieved from climate data, while precipitation was provided by the three publication alongside the CDF measurements. The data reveal the strong nonlinear relation between CDF and wetness at the global scale.