<p><strong>Abstract.</strong> Soil organic matter (SOM) forms the largest terrestrial pool of carbon outside of sedimentary rocks. Radiocarbon is a powerful tool for assessing soil organic matter dynamics. However, due to the nature of the measurement, extensive <sup>14</sup>C studies of soils systems remain relatively rare. In particular, information on the extent of spatial and temporal variability in <sup>14</sup>C contents of soils is limited, yet this information is crucial for establishing the range of baseline properties and for detecting potential modifications to the SOM pool. This study describes a comprehensive approach to explore heterogeneity in bulk SOM <sup>14</sup>C in Swiss forest soils that encompass diverse landscapes and climates. We examine spatial variability in soil organic carbon (SOC) <sup>14</sup>C, SOC content and C:N ratios over both regional climatic and geologic gradients, on the watershed- and plot-scale and within soil profiles. Results reveal (1) a relatively uniform radiocarbon signal across climatic and geologic gradients in Swiss forest topsoils (0-5 cm, Δ<sup>14</sup>C=159±36.4, n=12 sites), (2) similar radiocarbon trends with soil depth despite dissimilar environmental conditions, and (3) micro-topography dependent, plot-scale variability that is similar in magnitude to regional-scale variability (e.g., Gleysol, 0-5 cm, Δ<sup>14</sup>C 126±35.2, n=8 adjacent plots of 10x10m). Statistical analyses have additionally shown that Δ<sup>14</sup>C signature in the topsoil is not significantly correlated to climatic parameters (precipitation, elevation, primary production) except mean annual temperature at 0-5 cm. These observations have important consequences for SOM carbon stability modelling assumptions, as well as for the understanding of controls on past and current soil carbon dynamics.</p>

<p><strong>Abstract.</strong> Quantitative constraints on soil organic matter (SOM) dynamics are essential for comprehensive understanding of the terrestrial carbon cycle. Deep soil carbon is of particular interest, as it represents large stocks and its turnover rates remain highly uncertain. In this study, SOM dynamics in both the top and deep soil across a climatic (average temperature ~ 1–9 °C) gradient are determined using time-series (~ 20 years) <sup>14</sup>C data from bulk soil and water-extractable organic carbon (WEOC). Analytical measurements reveal enrichment of bomb-derived radiocarbon in the deep soil layers on the bulk level during the last two decades. The WEOC pool is strongly enriched in bomb-derived carbon, indicating that it is a dynamic pool. We used a numerical model to determine turnover time of the bulk, slow and dynamic pool as well as the size of the dynamic pool. The presence of bomb-derived carbon in the deep soil, as well as the rapidly turning over WEOC pool and sizeable dynamic fraction at depth across the climatic gradient implies that there likely is a dynamic component of carbon in the deep soil. Precipitation appears to exert a stronger influence on soil C dynamics than temperature. Overall, geology seems to impact the carbon cycling in three key ways: (1) bedrock-derived (petrogenic) carbon can comprise an important component of the soil carbon pool even at relatively shallow depths (< 1 m). (2) Bedrock type influences water logging either by its porosity or by determining texture, and (3) rock and soil mineralogy controls C stabilization.</p>

<p><span xml:lang="EN-GB" data-contrast="auto"><span>I</span></span><span><span>mproved</span><span> soil and cropland management </span></span><span xml:lang="EN-GB" data-contrast="auto"><span>changes the</span></span><span><span> soil carbon stocks and thereby mitigate climate change. However, spatially explicit insights on management impacts as well as critical thresholds for optimum SOC levels are lacking, which is crucial for actionable changes in farming practices. In this study we </span></span><span xml:lang="EN-GB" data-contrast="auto"><span>unravelled the contribution of </span></span><span><span>soil texture, geohydrology and soil quality </span></span><span xml:lang="EN-GB" data-contrast="auto"><span>to changes in SOC </span><span>in the Netherlands </span><span>using a data-driven approach (using </span><span>XGBoost</span><span>) using </span><span>21.123</span><span> soil analyses done by agricultural laboratories.</span></span><span><span> The current C stock of the 0-30cm soil layer is 119 ton C ha</span></span><span><span>-1</span></span><span><span> and could be increased by 21 to 59 ton C ha</span></span><span><span>-1</span></span><span><span> depending on soil type, land use and the agronomic measures taken. The SOC saturation capacity, expressed as the ratio between the actual and potential SOC stock varied from 85 to 93% in grassland soils, from 55 to 83% in arable soils and from 69 to 91% in other land uses. On average, the actual C saturation degree was 75%. The key factors </span></span><span xml:lang="EN-GB" data-contrast="auto"><span>controlling the potential of soils to sequester additional carbon within environmental limits for N and P included</span></span><span><span> the</span></span><span xml:lang="EN-GB" data-contrast="auto"><span> crop sequence in the last decade,</span></span><span><span> soil texture (</span></span><span xml:lang="EN-GB" data-contrast="auto"><span>i.e.</span><span> oxide extractable aluminium, iron and phosphorus</span></span><span><span>), </span></span><span xml:lang="EN-GB" data-contrast="auto"><span>the acidity</span></span><span><span>, and groundwater depth. The data driven approach shows that spatially explicit recommendations for carbon farming are possible up to the farm and field scale, facilitating the implementation of carbon farming and the mitigation of climate change. When all agricultural fields are saturated with C</span><span>,</span><span> an equivalent of 257 </span><span>Mton</span><span> of CO</span></span><span><span>2</span></span><span><span> can be stored. </span></span><span> </span></p>

Interactive comment on "Dynamics of deep soil carbon -insights from 14 C time-series across a climatic gradient" by Tessa Sophia van der Voort et al. Tessa Sophia van der Voort et al.

The main hurdle in instrumentalizing agricultural soils to sequester atmospheric carbon is the development of methods to measure soil carbon stocks which are robust, scalable, and widely applicable. Our objective is to develop an approach that can help overcome these hurdles. In this paper, we present the Wageningen Soil Carbon STOck pRotocol (SoilCASTOR). SoilCASTOR uses a novel approach fusing satellite data, direct proximal sensing-based soil measurements, and machine learning to yield soil carbon stock estimates. The method has been tested and applied in the USA on fields with agricultural land use. Results show that the estimates are precise and repeatable and that the approach could be rapidly scalable. The precision of farm C stocks is below 5% enabling detection of soil organic carbon changes desired for the 4 per 1000 initiative. The assessment can be done robustly with as few as 0.5 sample per hectare for farms varying from 20 to 150 hectares. These findings could enable the structural implementation of carbon farming.