A numerical evaluation of chamber methodologies used in measuring the δ¹³C of soil respiration

Abstract

Measurement of the delta(13)C value of soil-respired CO(2) (delta(r)) has become a commonplace method through which ecosystem function and C dynamics can be better understood. Despite its proven utility there is currently no consensus on the most robust method with which to measure delta(r). Static and dynamic chamber systems are both commonly used for this purpose; however, the literature on these methods provides evidence suggesting that measurements of delta(r) made with these chamber systems are neither repeatable (self-consistent) nor comparable across methodologies. Here we use a three-dimensional (3-D) numerical soil-atmosphere-chamber model to test these chamber systems in a 'surrogate reality'. Our simulations show that each chamber methodology is inherently biased and that no chamber methodology can accurately predict the true delta(r) signature under field conditions. If researchers intend to use delta(r) to study in situ ecosystem processes, the issues with these chamber systems need to be corrected either by using diffusive theory or by designing a new, unbiased delta(r) measurement system.

Effects of soil type and composition of rhizodeposits on rhizosphere priming phenomena

“…8 ‰ more positive than those in Experiment A. We suppose this is due to isotopic fractionation in the transient-state diffusion of respired CO 2 through the soil to the microcosm chambers, as discussed by Nickerson andRisk (2009) andOhlsson (2010). In systems using purged chambers, such as ours, this can produce a positive δ 13 C bias of up to 15 ‰ (Nickerson and Risk, 2009).…”

“…The values measured in the control soils in Experiment B were significantly less negative than those in the control soils in Experiment A. Following Nickerson and Risk (2009) and Ohlsson (2010), we suppose this is due to isotopic fractionation in transient-state diffusion of respired CO 2 through the soil to the purged microcosm chambers, which is expected to be greater in Experiment B for reasons discussed in Appendix A. In calculations given in Appendix A, we show that the apparent error in δ 13 C values will cause the size of the priming effect to be under-estimated, but the trends across the treatments and over time are unchanged.…”

“…We suppose this is due to isotopic fractionation in the transient-state diffusion of respired CO 2 through the soil to the microcosm chambers, as discussed by Nickerson andRisk (2009) andOhlsson (2010). In systems using purged chambers, such as ours, this can produce a positive δ 13 C bias of up to 15 ‰ (Nickerson and Risk, 2009). Following reasoning given below, the effect is expected to be greater in Experiment B because of the larger ratio of chamber volume to soil surface area (18 versus 8 cm) and smaller soil depth (≤ 4.6 versus 30 cm) and resulting smaller CO 2 flux (approx.…”

“…This 'chamber feedback' happens more rapidly for 12 CO 2 because of its greater diffusion coefficient. Hence, the chamber C C 12 13 ratio falls less rapidly, also resulting in a positive bias in δ 13 C S estimates (Nickerson and Risk, 2009). The bias increases with the time required for the CO 2 concentration gradient through the soil to reach zero as CO 2 accumulates in the chamber, i.e.…”

Challenges in measuring the δ13C of the soil surface CO2 efflux

“…Nickerson and Risk, [66] using a 3D soil-atmosphere-chamber model, recently confirmed these observations, and suggested that this approach is inherently biased due to chamber-to-soil feedbacks. These feedbacks arise from non-steady-state conditions, with the build up of CO 2 in the chamber influencing the diffusion of soil CO 2 and its isotopologues, which would be an issue for all chamber systems, to a greater or lesser extent, [66] with dynamic chambers (see later) offering possibly the least disturbance.…”