C in cropland soil of a long-term field trial – infield variability and implications for estimating carbon turnover

14C in cropland soil of a long-term field trial – in-field variability and implications for estimating carbon turnover J. Leifeld and J. Mayer Climate/Air Pollution Group, Institute for Sustainability Sciences, Agroscope, Reckenholzstrasse 191, 8046 Zurich, Switzerland Water Protection/Substance Flows Group, Institute for Sustainability Sciences, Agroscope, Reckenholzstrasse 191, 8046 Zurich, Switzerland

across three different treatments and for three different soil layers between surface and 90 cm depths. On average, in-field variability in 14 C content was 12 times the analytical error but still, on a relative basis, smaller than that of in-field soil carbon concentration variability. Despite a relative homogeneous variability across the field and along the soil profile, the curved nature of the relationship between radiocarbon content and modelled 15 carbon mean residence time suggests that the absolute error, without consideration of in-field variability, introduced to soil carbon turnover time calculations increases with soil depth. In our field experiment findings on topsoil carbon turnover variability would, if applied to subsoil, tend to underweight turnover variability even if in-field variability of the subsoil isotope concentration is not higher. Together, in-field variability in radio-20 carbon is an important component in an overall uncertainty assessment of soil carbon turnover.

Introduction
Long-term agricultural field trials have long been recognized as important sources for understanding long-term management effects on soil parameters such as soil organic 25 carbon content and turnover (Jenkinson, 1991). Their special value lays in their con-218 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | trolled nature, the long-term record of management activities, reliable soil and crop parameter records as well as site climate data. Many experiments have indicated that soil carbon responds sensitively to agricultural management and have allowed to identify sustainable management practices. Hence, these data sets are valuable sources of information also for developing or testing soil and ecosystem carbon models (Smith 5 et al., 1997;Franko et al., 2011).
Soil carbon feedback to management is controlled by organic matter input as well as turnover and hence loss. Isotopes play an important role for unraveling soil carbon turnover rates. In complementation to records on carbon storage change over time, they deliver information on how fast new carbon replaces old carbon. Besides stable 10 12 C / 13 C, the radioactive isotope 14 C has a long history of application in soil carbon studies (Harkness et al., 1986;Jenkinson et al., 1992;Trumbore, 1993). The introduction of extra 14 C to the atmosphere via nuclear bomb testing in the 50s and 60s of the last century and the subsequent diffusion of that label into terrestrial ecosystems has triggered a vast amount of research that makes use of the 14 C signature of soil carbon. 15 The beauty of 14 C is given by its ubiquity and its potential to cover the whole relevant time frame of soil carbon turnover, ranging from years to millennia. Information from both, controlled long-term field experiments and the soil's radiocarbon signature have been combined previously with the aim to get better insight into soil carbon dynamics (Table 1). These data are particularly useful for model develop-20 ment as the isotope reduces the degrees of freedom in the modeling approach, i.e., it constraints the carbon turnover dynamics and reduces the risk of giving right answers for the wrong reasons. For example Jenkinson and Coleman (2008) used 14 C from the famous Rothamsted field trials to extent the existing Rothamsted Carbon Model RothC by a subsoil module. Hsieh (1993) took advantage of the oldest cropland experiments 25 from the US, Morrow plot and Sanborn field, to get insight into labile carbon turnover. These and other applications as listed in Table 1 have not yet, though, considered the variability of radiocarbon in the field. In-field variability, both across the field and within the soil profile, adds an important component of uncertainty to any modeling of ter- restrial carbon which needs to be known for reliable estimates of management-carbon storage feedbacks. For radiocarbon, the relatively high costs of the nowadays mostly used measurement by accelerator mass spectrometry (AMS) is a major obstacle to addressing in-field variability questions. To our knowledge, in-field variability of soil 14 C using independent treatment repli-5 cates has not yet been addressed in any of the world's long-term cropland experiments listed in Table 1. Here, we aim to fill that gap by using recent 14 C measurements of mineral soil from a 60 years temperate long-term cropland trial in Zurich, Switzerland. Two questions are studied: (i) what is the variability in soil radiocarbon content in independent replicates of a long-term field trial both in top-and subsoil, and (ii) what are 10 possible implications of in-field variability for the interpretation of soil carbon turnover estimates?

Material and methods
The Zurich Organic Fertilization Experiment ZOFE was commenced in 1949 at the Swiss federal research institute for agriculture, Agroscope in Zurich. It is located at Here we present data from three treatments ( Fig. 1) that were analyzed for their radiocarbon content. Treatment "Null" received no fertilizer since 1949, treatment "FYM + PK" receives 2.5 t farmyard manure (dry organic matter) every second year plus annually 235 kg K and 35 kg P as mineral fertilizer. Treatment "N2P2K2Mg" re-Introduction Soil samples were taken in April 2012 from the center of each plot using a powered rotating soil auger (Humax, Burch AG, Rothenburg, Switzerland) down to depth 5 of 90 cm. The auger is equipped with an outer shaft hosting a PVC inlet that gets filled with a volumetric soil sample of diameter 5.0 cm during drilling. Samples were pooled into segments 0-20, 20-30, 30-60, and 60-90 cm. For the present study, samples from the plough pan 20-30 cm were not analyzed. After extraction, samples were sieved < 2 mm, dried at 105 • C, roots were removed by hand, and an aliquot was finely 10 ground. Prior to radiocarbon analysis, samples were pretreated using acid fumigation with 0.5 M HCl to remove possible remnants from liming or traces of pedogenic carbonate. Soil radiocarbon content was measured by accelerator mass spectrometry at two different facilities, the radiocarbon laboratory of ETH Zurich, and the radiocarbon laboratory of the University of Bern, Switzerland. Both systems operate following the 15 protocol of Synal et al. (2007). Radiocarbon concentrations are given as percent Modern Carbon (pMC) as defined by Stuiver and Polach (1977).
To study effects of in-field 14 C variability on soil carbon dynamics, we applied a common, time-dependent steady-state soil carbon turnover model that has been first described by Harkness et al. (1986) and later been used as single or multiple pool version 20 in various studies (e.g. Baisden et al., 2013;Gaudinski et al., 2000;Harrison, 1996;Trumbore et al., 1996). The model gives mean residence times (MRT's) of soil carbon. Because we have no 14 C time-series available the most simple version of that model is applied representing a single-pool assumption as described in Leifeld et al. (2013). Although soil carbon time-series are better described by multiple pool approaches (Bais-25 den et al., 2013), the assumption followed here is sufficient to discuss possible consequences of in-field variability for the interpretation of soil carbon dynamics. Because our data represent a single point in time, they do not allow adequate parameterization of a more complex model. Hence, we do not claim the presented turnover estimates to 221 represent the most realistic in situ situation but rather to allow discussion of variability effects. The effect of depth on pMC and carbon mean residence time was tested by univariate ANOVA separately for each treatment and for the aggregated sample across treatments.

3 Results and discussion
Radiocarbon contents in the ZOFE plots average 100.2 (±1.8 (1 SD)), 88.0 (±3.00), and 76.5 (±4.2) pMC for 0-20, 30-60, and 60-90 cm, respectively (Table 2). Across all 15 plots as well as when grouped by treatment, the depth effect was highly significant (p < 0.001). Declining pMC values with soil depth are indicative for longer carbon 10 mean residence times in the deeper layer of soil and have been reported frequently for soils that were not prone to substantial inputs from fossil carbon (Budge et al., 2011;Gaudinski et al., 2000;Jenkinson et al., 2008;Toyota et al., 2010).
Table 2 also indicates that the coefficient of variation (CV) of pMC for five independent plots, representing mostly in-field variability, lays between 1-7 % (mean of all 15 treatments and layers: 3.1 %). This is, for the present data set, 3-23 times the CV of the analytical precision of the AMS measurement. Notably, the CV for soil organic carbon concentration is, per treatment and layer, on average 9.5 % (data not shown), thus three times that of the radiocarbon content. There was no depth effect on the coefficient of variation (p = 0.16), hence, 14 C variability does neither increase nor decrease with 20 depth. At the same time, the CV grouped by treatment was statistically not different between "Null", "FYM + PK", and "N2P2K2Mg" (p = 0.64). The latter implies that 14 C field variability as measured in ZOFE is related to site -or soil inherent properties rather than to agricultural management Although 14 C variability did not change with depth, it influences the variability of the 25 derived soil carbon MRT's differently in the three layers. This can be studied by calculating turnover for the range of data expressed by their average confidence interval (CI). Owing to the combination of (i) a non-constant atmospheric radiocarbon concentration as a result from long-term and short-term 14 CO 2 fluctuations and (ii) exponential radioactive decay in the soil, the relationship between pMC and MRT is non-linear. This is illustrated for a series of homogeneous soil pools of different age. Radiocarbon signatures of such a pool series with range from 70-105 pMC (resembling the span found 5 in the soil data, Table 2), convert to MRT's of between 3891 and 156 years (Fig. 2). The pMC-age curve becomes steeper at smaller radiocarbon concentrations. Whereas the central curve in Fig. 2 gives results for the mean pMC, the inner and outer bands represent the 95 % CI of (i) the average variability owing to measurement error only (inner band) and (ii) the average in-field variability in the soil (outer band, 3.6 % of the measured pMC. This CI represents the 3.1 % CV above). These bands give upper and lower probability limits for the calculated MRT and they deviate the further from their mean the older the carbon is. For example, a MRT of 3891 (CI 3392-4453) years is assigned to a soil carbon pool with signature pMC = 70 (CI 67.50-72.50 pMC), whereas the same relative uncertainty for a mean pMC of 105 (Cl 101.26-108.74 pMC) converts to a MRT of 156 (CI 92-268) years. Figure 3 further illustrates the principle. Soil carbon from 60-90 cm, carrying a signature of e.g. 75 pMC, has a calculated MRT of 2947 years with deviations of +477 and −428 years, referring to the variability among five independent field replicates. The uncertainty range is reduced to +193 and −129 years (mean MRT 321 years) for a pMC of 20 100, roughly representing the current topsoil. While the absolute uncertainty declines the younger the soil becomes, the relative uncertainty increases in the opposite direction (Fig. 3, right panel). Figure 3 also exemplifies the wider uncertainty band, over the calculated pMC range, when in-field variability and not only measurement error is accounted for. At pMC 70, the uncertainty range of MRT's considering in-field variability 25 is 4.2 times that of measurement error only. This factor increases to 6.5 at pMC 105, indicating that for younger soil carbon the omission of in-field variability introduces a larger relative uncertainty than for older soil carbon.

Conclusions
Soil radiocarbon dating from a long-term agricultural experiment indicates that in-field variability of this parameter is many times the analytical error. In-field variability seems neither controlled by management nor by soil depth. Conversion of relative uncertainty in radiocarbon content to relative uncertainty in carbon turnover reveals a higher sensi-5 tivity of carbon turnover to 14 C variability in deeper soil layers that contain older carbon.
Consequently, when soil samples from a long-term field trial are pooled per depth and treatment for 14 C analysis, the underestimation of the actual in-field variability of soil carbon turnover is larger for subsoil samples where long-lived C pools are more abundant.