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Geomorphic controls on the abundance and persistence of soil organic carbon pools in erosional landscapes

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Soils play a central role in the global carbon cycle and constitute a key component of natural climate solutions that require quantitative predictions of soil organic carbon (SOC) dynamics at local to regional scales. In hilly and mountainous terrain, variations in uplift and stream incision generate gradients in erosion and hillslope morphology that control soil properties that impact the abundance and persistence of SOC. Here we use topographic and soil biogeochemical analyses to show that across 16 sites in our study region, total SOC stocks and the typically slower-cycling mineral-associated fraction of SOC decrease exponentially with modelled erosion rate from 21.0 to 0.2 kg m–2 and 12.0 to 0.1 kg m–2, respectively. Along the greater than order-of-magnitude erosional gradient, radiocarbon (Δ14C), soil thickness and texture data trend younger, thinner and coarser, respectively, such that fast-eroding sites have much less SOC than slow-eroding sites and are dominated by faster-cycling SOC pools. By coupling these erosion-driven soil and SOC trends with high-resolution topographic data, hilltop convexity and other erosion rate metrics can be readily applied to estimate SOC abundance and persistence in diverse landscape settings, facilitating our ability to predict carbon dynamics across a range of spatiotemporal scales.

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Fig. 1: Study area.
Fig. 2: Total SOC, percentage MaOC and POC stock, fraction modern, soil thickness and coarse fraction as functions of Cht and modelled E.
Fig. 3: SOC profiles.

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Data availability

Soil sample data for figure reconstruction are available within the paper and its Supplementary Information as well as via Figshare53 ( LiDAR data for the Rabbit Mountain region in southwestern Oregon for this project are available via the Oregon Department of Geology and Mineral Industries (DOGAMI) online ( or through OpenTopography (

Code availability

We suggest parties interested in the source code for calculating curvature contact the corresponding author from ref. 37.


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Land access to Rabbit Mountain and the Cow Creek recreation area was facilitated through S. Post and K. Knox at the Bureau of Land Management in Roseburg, OR. Soil sample collection sites were approved to avoid culturally sensitive locations. Access to large LiDAR data from DOGAMI was facilitated by J. Edwards. We thank W. Struble for access to curvature code and discussion as well as P. Almond and lab members in the Soil Plant Atmosphere lab group at the University of Oregon for discussions. Thank you to undergraduate students B. Quinn, N. Cleland, D. Kleiner and J. Odenthal, who assisted in soil sample preparation. Funding for this work was provided by NSF Division of Earth Sciences (EAR) Climate grant #2136934 (J.J.R. and L.C.R.S.) and NSF grant #2319597 (L.C.R.S.). Digital elevation model (DEM) data were collected by the National Center for Airborne Laser Mapping (NCALM) as a Seed grant (B.D.H.).

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Authors and Affiliations



B.D.H. and J.J.R. designed the study and collected samples. L.C.R.S provided access to laboratory equipment and discussion. K.C.M. advised radiocarbon sample preparation and provided discussion. All authors contributed to the interpretation of the results. B.D.H. wrote the paper and produced the figures. J.J.R., L.C.R.S. and K.C.M. provided comments and additions to the text.

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Correspondence to Brooke D. Hunter.

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Nature Geoscience thanks Christopher Feeney and Nicholas Patton for their contribution to the peer review of this work. Primary Handling Editor: Xujia Jiang, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Field map of Rabbit Mountain with insets.

(A), and insets for Ridgeline 1 (RL1) (B), and Ridgeline 6 (RL6) (C). Black dots show locations where we measured soil thickness and collected samples along ridgelines for laboratory analysis. Black lines along ridgelines in (B) and (C) show ridgelines and where we extracted hilltop curvature (Cht) values from full curvature maps.

Extended Data Fig. 2 Total SOC stock with hilltop curvature (Cht) and erosion rate (E) relationships for single wavelet scale across sites.

Total SOC (black circles) vs Cht using one single wavelet scale for all sites with selected scales of 15 (A), 25 (B), 35 (C), and 45 (D). The exponential decline in stock trend is present for all scales. The main change is the range of measured curvature values. It is likely that at the 35 and 45 wavelet scales, the fastest (sharpest sites) are underestimated values.

Extended Data Fig. 3 OC% measured on the fine fraction, ff, of samples.

(A) and calculated SOC density (B) values for measured soil samples across all soil depths and site locations. Data are colored by the site’s corresponding hilltop curvature, Cht, value A. OC% (percentage of ff mass that is carbon) declines with depth. Inset shows extended x-axis to include two outlier samples with OC% values > 10%. B. SOC density, calculated following Eq. 1, also declines with depth. The incorporation of a coarse fraction mass correction (1 – fc) exemplifies one way soil properties influence SOC density, and thus SOC stock. Slower eroding sites with low Cht values (blue), not only have deeper profiles, but also have SOC density values greater than faster eroding sites (red).

Extended Data Fig. 4 Coarse, fc (black), and fine, ff (light gray), fraction data with depth for all field sites.

Site hilltop curvature (Cht) becomes more convex from top left (Cht = -0.0038 m-1) to bottom right Cht = -0.0855 m-1, and thus modeled erosion rate E increases. Soil profiles become thinner and coarser as fc values increase from ~ 0.36 to 0.90 with faster erosion rates. From field observations, we observed material in the fc also becomes more rounded with slower erosion rates, compared to coarse angular fc material at the fast-eroding sites.

Extended Data Fig. 5 Organic Carbon Density data with depth.

Total SOC (black circles), MaOC (blue), and POC density (gray) decline with depth for each site. Site hilltop curvature (Cht) becomes more convex from top left (Cht = -0.0038 m-1) to bottom right Cht = -0.0855 m-1, and thus modeled erosion rate E increases. Fast eroding sites are dominated by POC fraction, while MaOC dominates at the slower sites. Note site RL9S1 has one outliner off the plot with a value of 113.8 kgm-3.

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Hunter, B.D., Roering, J.J., Silva, L.C.R. et al. Geomorphic controls on the abundance and persistence of soil organic carbon pools in erosional landscapes. Nat. Geosci. 17, 151–157 (2024).

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