Biogeosciences (Jun 2016)

Variability in <sup>14</sup>C contents of soil organic matter at the plot and regional scale across climatic and geologic gradients

  • T. S. van der Voort,
  • F. Hagedorn,
  • C. McIntyre,
  • C. Zell,
  • L. Walthert,
  • P. Schleppi,
  • X. Feng,
  • T. I. Eglinton

DOI
https://doi.org/10.5194/bg-13-3427-2016
Journal volume & issue
Vol. 13, no. 11
pp. 3427 – 3439

Abstract

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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 14C studies of soil systems remain relatively rare. In particular, information on the extent of spatial and temporal variability in 14C 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 14C in Swiss forest soils that encompass diverse landscapes and climates. We examine spatial variability in soil organic carbon (SOC) 14C, 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, Δ14C = 130 ± 28.6, 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, Δ14C 126 ± 35.2, n = 8 adjacent plots of 10 × 10 m). Statistical analyses have additionally shown that Δ14C 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.