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Mineral protection regulates long-term global preservation of natural organic carbon

Abstract

The balance between photosynthetic organic carbon production and respiration controls atmospheric composition and climate1,2. The majority of organic carbon is respired back to carbon dioxide in the biosphere, but a small fraction escapes remineralization and is preserved over geological timescales3. By removing reduced carbon from Earth’s surface, this sequestration process promotes atmospheric oxygen accumulation2 and carbon dioxide removal1. Two major mechanisms have been proposed to explain organic carbon preservation: selective preservation of biochemically unreactive compounds4,5 and protection resulting from interactions with a mineral matrix6,7. Although both mechanisms can operate across a range of environments and timescales, their global relative importance on 1,000-year to 100,000-year timescales remains uncertain4. Here we present a global dataset of the distributions of organic carbon activation energy and corresponding radiocarbon ages in soils, sediments and dissolved organic carbon. We find that activation energy distributions broaden over time in all mineral-containing samples. This result requires increasing bond-strength diversity, consistent with the formation of organo-mineral bonds8 but inconsistent with selective preservation. Radiocarbon ages further reveal that high-energy, mineral-bound organic carbon persists for millennia relative to low-energy, unbound organic carbon. Our results provide globally coherent evidence for the proposed7 importance of mineral protection in promoting organic carbon preservation. We suggest that similar studies of bond-strength diversity in ancient sediments may reveal how and why organic carbon preservation—and thus atmospheric composition and climate—has varied over geological time.

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Data availability

All data that support the findings of this study are available on the RPO Compilation Online Database (https://github.com/FluvialSeds/RPO_Database) with the identifier https://doi.org/10.5281/zenodo.1158742.

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Acknowledgements

This work is dedicated to John Hayes, who developed the instrument and the techniques used herein, and whose knowledge, support and inspiration was always invaluable. We thank the National Ocean Sciences Accelerator Mass Spectrometer staff, especially A. McNichol, A. Gagnon and M. Lardie-Gaylord for RPO assistance; P. Raymond, E. Kyzivat, R. Spencer and A. Stubbins for supplying sample material; B. Rosenheim, C. Schafer and X. Zhang for providing access to raw data from published manuscripts; and A. Pearson, D. Johnston and A. Piasecki for comments and discussions. This research was supported by the NSF Graduate Research Fellowship Program (grant number 2012126152 to J.D.H.); by the NASA Astrobiology Institute (grant number NNA13AA90A to D.H.R.), by the NSF (grant number EAR-1338810 to D.H.R.); by the NSF-IGERT in Cross Scale Biogeochemistry and Climate at Cornell University (K.E.G.); and by the WHOI Independent Study Award (V.V.G.).

Reviewer information

Nature thanks David Butman, Jason James, Lawrence Mayer and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

J.D.H., D.H.R. and V.V.G. conceived the study. J.D.H. compiled data. J.D.H., K.E.G. and S.Z.R. performed laboratory measurements. J.D.H. and D.H.R. developed theoretical models and analysed data. J.D.H., K.E.G., L.A.D. and V.V.G. provided samples. T.I.E. and L.A.D. contributed analytical tools and discussions. J.D.H., D.H.R. and V.V.G. wrote the manuscript with input from all authors.

Competing interests

The authors declare no competing interests.

Correspondence to Jordon D. Hemingway.

Extended data figures and tables

  1. Extended Data Fig. 1 Sample locations.

    Marine/riverine DOC (black circles), soil OC (white squares), riverine POC (red triangles), and marine sediment OC (blue diamonds). See Extended Data Table 1 for GPS coordinates, sample collection information, and original publication references. (This figure was generated using the Geographic Resources Analysis Support System (GRASS) GIS software (https://grass.osgeo.org/) and the latitude/longitude sample locations that are provided in Extended Data Table 1.).

  2. Extended Data Fig. 2 Intra-sample 14C age variances.

    All individual mineral-containing samples (soil, white squares; river POC, red triangles; marine sediment OC, blue diamonds) plotted against %OC reveal a globally coherent power-law relationship (black solid line). r is the reduced major axis correlation coefficient. Age variance is calculated as the sample variance of 14C ages for all RPO fractions within a given sample (equation (4)). Age variance and %OC are presented on logarithmic scales. Uncertainty (±1σ) is smaller than the marker for all data points. The %OC axis is reversed to emphasize that OC content generally decreases with time. Source Data

  3. Extended Data Table 1 Sample details
  4. Extended Data Table 2 μE and σE values for samples used to determine methodological uncertainty

Source data

  1. Source Data Fig. 2

  2. Source Data Fig. 3

  3. Source Data Fig. 4

  4. Source Data Extended Data Fig. 2

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Fig. 1: Schematic representation of two potential preservation mechanisms.
Fig. 2: E and 14C age distributions.
Fig. 3: Predicted and observed p(E) evolution.
Fig. 4: Predicted and observed μE and σE evolution.
Extended Data Fig. 1: Sample locations.
Extended Data Fig. 2: Intra-sample 14C age variances.

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