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Soils of temperate forests store significant amounts of organic matter and are considered to be net sinks of atmospheric CO2. Soil organic carbon (SOC) turnover has been studied using the Δ14C values of bulk SOC or different SOC fractions as observational constraints in SOC models. Further, the Δ14C values of CO2 that evolved during the incubation of soil and roots have been widely used together with Δ14C of total soil respiration to partition soil respiration into heterotrophic respiration (HR) and rhizosphere respiration. However, these data have not been used as joint observational constraints to determine SOC turnover times. Thus, we focus on (1) how different combinations of observational constraints help to narrow estimates of turnover times and other parameters of a simple two-pool model, the Introductory Carbon Balance Model (ICBM); (2) whether relaxing the steady-state assumption in a multiple constraints approach allows the source/sink strength of the soil to be determined while estimating turnover times at the same time. To this end ICBM was adapted to model SOC and SO14C in parallel with litterfall and the Δ14C of litterfall as driving variables. The Δ14C of the atmosphere with its prominent bomb peak was used as a proxy for the Δ14C of litterfall. Data from three spruce-dominated temperate forests in Germany and the USA (Coulissenhieb II, Solling D0 and Howland Tower site) were used to estimate the parameters of ICBM via Bayesian calibration. Key findings are as follows: (1) the joint use of all four observational constraints (SOC stock and its Δ14C, HR flux and its Δ14C) helped to considerably narrow turnover times of the young pool (primarily by Δ14C of HR) and the old pool (primarily by Δ14C of SOC). Furthermore, the joint use of all observational constraints made it possible to constrain the humification factor in ICBM, which describes the fraction of the annual outflux from the young pool that enters the old pool. The Bayesian parameter estimation yielded the following turnover times (mean ± standard deviation) for SOC in the young pool: Coulissenhieb II 1.1 ± 0.5 years, Solling D0 5.7 ± 0.8 years and Howland Tower 0.8 ± 0.4 years. Turnover times for the old pool were 377 ± 61 years (Coulissenhieb II), 313 ± 66 years (Solling D0) and 184 ± 42 years (Howland Tower), respectively. (2) At all three sites the multiple constraints approach was not able to determine if the soil has been losing or storing carbon. Nevertheless, the relaxed steady-state assumption hardly introduced any additional uncertainty for the other parameter estimates. Overall the results suggest that using Δ14C data from more than one carbon pool or flux helps to better constrain SOC models.

Soil respiration (SR) constitutes the largest flux of CO2 from terrestrial ecosystems to the atmosphere. However, there still exist considerable uncertainties as to its actual magnitude, as well as its spatial and interannual variability. Based on a reanalysis and synthesis of 80 site-years for 57 forests, plantations, savannas, shrublands and grasslands from boreal to tropical climates we present evidence that total annual SR is closely related to SR at mean annual soil temperature (SRMAT), irrespective of the type of ecosystem and biome. This is theoretically expected for non water-limited ecosystems within most of the globally occurring range of annual temperature variability and sensitivity (Q10). We further show that for seasonally dry sites where annual precipitation (P) is lower than potential evapotranspiration (PET), annual SR can be predicted from wet season SRMAT corrected for a factor related to P/PET. Our finding indicates that it can be sufficient to measure SRMAT for obtaining a well constrained estimate of its annual total. This should substantially increase our capacity for assessing the spatial distribution of soil CO2emissions across ecosystems, landscapes and regions, and thereby contribute to improving the spatial resolution of a major component of the global carbon cycle.

The flux of carbon dioxide from the soil to the atmosphere (soil respiration) is one of the major fluxes in the global carbon cycle. At present, the accumulated field observation data cover a wide range of geographical locations and climate conditions. However, there are still large uncertainties in the magnitude and spatiotemporal variation of global soil respiration. Using a global soil respiration data set, we developed a climate-driven model of soil respiration by modifying and updating Raich's model, and the global spatiotemporal distribution of soil respiration was examined using this model. The model was applied at a spatial resolution of 0.5° and a monthly time step. Soil respiration was divided into the heterotrophic and autotrophic components of respiration using an empirical model. The estimated mean annual global soil respiration was 91 PgCyr-1 (between 1965 and 2012; Monte Carlo 95 % confidence interval: 8795 Pg C yr-1) and increased at the rate of 0.09 Pg Cyr-2. The contribution of soil respiration from boreal regions to the total increase in global soil respiration was on the same order of magnitude as that of tropical and temperate regions, despite a lower absolute magnitude of soil respiration in boreal regions. The estimated annual global heterotrophic respiration and global autotrophic respiration were 51 and 40 Pg Cyr-1, respectively. The global soil respiration responded to the increase in air temperature at the rate of 3.3PgCyr-1 °C-1, and Q10 = 1.4. Our study scaled up observed soil respiration values from field measurements to estimate global soil respiration and provide a data-oriented estimate of global soil respiration. The estimates are based on a semi-empirical model parameterized with over one thousand data points. Our analysis indicates that the climate controls on soil respiration may translate into an increasing trend in global soil respiration and our analysis emphasizes the relevance of the soil carbon flux from soil to the atmosphere in response to climate change. Further approaches should additionally focus on climate controls in soil respiration in combination with changes in vegetation dynamics and soil carbon stocks, along with their effects on the long temporal dynamics of soil respiration. We expect that these spatiotemporal estimates will provide a benchmark for future studies and also help to constrain process-oriented models. [ABSTRACT FROM AUTHOR]

Soil respiration (SR) constitutes the largest flux of CO2 from terrestrial ecosystems to the atmosphere. There still exist considerable uncertainties as to its actual magnitude, as well as its spatial and interannual variability. Based on a reanalysis and synthesis of 72 site-years for 58 forests, plantations, savannas, shrublands and grasslands from boreal to tropical climates we present evidence that total annual SR is closely related to SR at mean annual soil temperature (SRMAT), irrespective of the type of ecosystem and biome. This convergence is to be theoretically expected for non water-limited ecosystems within most of the globally occurring range of annual temperature variability and sensitivity (Q10). We further show that for seasonally dry sites where annual precipitation (P ) is lower than potential evapotranspiration (PET), annual SR can be predicted from wet season SRMAT corrected for a factor related to P/PET. Our finding indicates that it is sufficient to measure SRMAT for obtaining a highly constrained estimate of its annual total. This should substantially increase our capacity for assessing the spatial distribution and interannual variation of soil CO2 emissions across ecosystems, land- scapes and regions, and thereby contribute to improving the spatio-temporal resolution of a major component of the global carbon cycle. [ABSTRACT FROM AUTHOR]