Radiocarbon measurements as a realiable tool to determine soil heterotrophic respiration
Tommaso Chiti1, Riccardo Valentini2
1Department for Innovation in Biological, Agro-food and Forest systems (DIBAF), University of Tuscia, 01100 Viterbo, Italy 2Far Eastern Federal University, Vladivostok, Russia
The amount of soil organic carbon (SOC) released into the atmosphere as carbon dioxide (CO2), which is referred to as heterotrophic respiration (Rh), is technically difficult to measure despite its necessity to the understanding of how to protect and increase SOC stocks. In recent decades, new techniques have been developed to better investigate the nature and turnover time (TT) of SOC. In particular, tracing radiocarbon (14C) throughout terrestrial ecosystems has emerged as a viable tool for discriminating the Rh component of soil respiration (SR).
In this work, two approaches were used to estimate the contribution of different C pools to SR. In the first approach, the variations in 14C content of SR were monitored during one year and compared to the atmospheric and SOC 14C signatures to determine the contribution of “fast” (root respiration and fast decomposing SOC) and “slow” cycling C pools to total SR. In the second approach an estimate of the total Rh, comprising the slow cycling C and the heterotrophic part of the fast-cycling C pools, was derived applying a box model based on the amount of the SOC pool and its 14C-derived TT.
Following the 14C variation in SR from the former approach, allowed to determine that on an annual basis the fast-cycling C was the main contributor to SR, about 85%, while the contribution of the slow-cycling C (with TT >1 yr) to total SR was 15%.
The second approach indicated that there were non significant differences between the Rh we determined and the Rh derived using independent measurements, suggesting the suitability of our methodology to infer Rh.
In conclusion, radiocarbon analysis of SOC and its fractions provided a reliable estimate of the average annual amount of SOC released into the atmosphere; hence, its application is convenient for calculating Rh because it utilizes only a minimum amount of samples and no time-consuming monitoring activities.