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Nonlinear forcing of climate on mountain denudation during glaciations

Abstract

Denudation is one of the main processes that shapes landscapes. Because temperature, precipitation and glacial extents are key factors involved in denudation, climatic fluctuations are thought to exert a strong control on this parameter over geological timescales. However, the direct impacts of climatic variations on denudation remain controversial, particularly those involving the Quaternary glacial cycles in mountain environments. Here we measure in situ cosmogenic 10Be concentration in quartz in marine turbidites of two high-resolution cores collected in the Mediterranean Sea, providing a near-continuous (temporal resolution of ~1–2 kyr) reconstruction of denudation in the Southern Alps since 75 kyr ago (ka). This high-resolution palaeo-denudation record can be compared with well-constrained climatic variations over the last glacial cycle. Our results indicate that total denudation rates were approximately two times higher than present during the Last Glacial Maximum (26.5–19 ka), the glacial component of the denudation rates being \(1.5_{ - 1.0}^{ + 0.9}\) mm yr−1. However, during moderately glaciated times (74–29 ka), denudation rates were similar to those today (0.24 ± 0.04 mm yr1). This suggests a nonlinear forcing of climate on denudation, mainly controlled by the interplay between glacier velocity and basin topography. Hence, the onset of Quaternary glaciations, 2.6 million years ago, did not necessarily induce a synchronous global denudation pulse.

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Fig. 1: The Var watershed and sedimentary system.
Fig. 2: Climate, sediment provenance and flood proxies compared to denudation rates.
Fig. 3: Schematic representations of denudation dynamics in the Var watershed.
Fig. 4: Comparison of denudation rates and sea surface temperature proxy data.

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Data availability

The datasets generated and analysed during the current study are available from the ORDaR Repository: https://doi.org/10.24396/ORDAR-46 (Supplementary Table 1, raw 10Be data), https://doi.org/10.24396/ORDAR-47 (Supplementary Table 2, core age models), https://doi.org/10.24396/ORDAR-48 (Supplementary Table 3, εNd data), https://doi.org/10.24396/ORDAR-49 (Supplementary Table 4, denudation rates), https://doi.org/10.24396/ORDAR-50 (Supplementary Table 5, glacial erosion rates) and https://doi.org/10.24396/ORDAR-51 (Supplementary Table 6, Monte Carlo draw parameters).

Code availability

The MATLAB code used to determine glacial erosion rates is available upon request to P.-H.B. (blard@crpg.cnrs-nancy.fr).

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Acknowledgements

This research was funded by the ANR JC EroMed project (no. ANR-17-CE01-0011-01; Principal Investigator P.-H.B.). This work is part of the PhD thesis of A.M., whose scholarship was jointly supported by the CNRS and the Région Grand Est. The ASTER AMS national facility (CEREGE, Aix en Provence) is supported by the INSU/CNRS, the ANR, through the ‘Projets thématiques d’excellence’ programme for the ‘Equipements d’excellence’ ASTER CEREGE action and IRD. Fruitful discussions with C. Petit, V. Godard and L. Bonneau benefited the design of the study and interpretation of the results. We are grateful to L. Léanni and R. Braucher for their expertise in 10Be wet chemistry at LN2C/CEREGE and to A. Trinquier at IFREMER for the Nd measurements. R. Dennen is acknowledged for proofreading and improving the overall readability of the manuscript. D.L.B., G.A. and K.K. are members of the ASTER Team.

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Contributions

A.M., P.-H.B., S.T., J.C. and S.J.J. designed the study. P.-H.B., S.T., S.M. and A.M. collected the samples for analysis. A.M. prepared the samples for 10Be and Nd analysis. D.L.B., G.A. and K.K. measured the 10Be/9Be ratios using the French Service National AMS ASTER. A.M., P.-H.B., J.C., S.T. and S.M. analysed the data. A.M. wrote the initial manuscript and all authors commented and contributed to the final version.

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Correspondence to Apolline Mariotti.

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Extended data

Extended Data Fig. 1 Analyzed 10Be concentrations in the 50–100 μm sand fraction vs those measured in the 100–250 μm sand fraction.

Analytical uncertainties on each measurement are 1σ. Uncertainties on the best-fit regression line are 2σ.

Extended Data Fig. 2 Neutron production rates as a function of sample age.

10Be production (spallation) rates according to the ice-free and glaciated scenarios as a function of time.

Extended Data Fig. 3 Percentage of quartz-bearing rocks covered by ice as a function of time.

Glacier surface-mass balance was computed using a Positive-Degree-Day model with the annual average temperature at 2 000 m: present day = 3.4 °C, 23 ka = −5.6 °C, 43 ka = −3.6 °C and 59 ka = −3.9 °C (paleotemperatures derived from local δ18O SST, equation S1). Winter-summer amplitude is 16.8 °C and annual precipitations are 1500 mm.a−1. Our model yields ELA of 3350 m (present), 1950 m (23 ka), 2260 m (43 ka) and 2200 m (59 ka) with an ablation gradient of 6 mm(w.e.).a−1.m−1. Weather data are from Meteo France (https://donneespubliques.meteofrance.fr), paleo temperatures calculated using S1 and the local lapse rate of 6.1 °C/km50.

Extended Data Fig. 4 Mixing of MIS 4-3 sediments required to lower 10Be concentrations to LGM values.

Proportion of sediments previously stored in MIS 4–3 moraines required to lower the MIS 4–3 10Be concentration to the average LGM value. CB1 correspond to mixing moraine sediments with a null 10Be concentration. CB2 correspond to mixing moraine sediments with a 10Be concentrations of 2.53 × 103 at.g−145.

Extended Data Fig. 5 Average glacial cover during MIS 4–3 (blue) and the average ELA during MIS 4–3 (white).

In red, the perimeter of ice cover below the ELA indicates where moraines may have accumulated.

Extended Data Fig. 6 Impact of moraine height on denudation rates in case of sediment mixing.

Impact of moraine thickness on the calculated denudation rates as a function of the sediment proportion originating from recycled moraines.

Extended Data Fig. 7 Pure glacial erosion rates.

Glacial erosion rates (computed with the Monte Carlo approach) for individual samples from 14.26 ka to 73.86 ka.

Extended Data Fig. 8 Composite glacial erosion rates obtained for the three periods, MIS 4–3, LGM and deglaciation.

These Monte Carlo draws assume a mixing between 10Be-poor glacial material and fluvial sediments. n=1e6 draws.

Extended Data Fig. 9 Modeled ice thicknesses and velocity at MIS 3 (up) and LGM (bottom).

Right: Ice velocity fields at MIS 3 (up) and LGM (bottom), according to the ice flow model of Harper and Humphrey, 200363.

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Mariotti, A., Blard, PH., Charreau, J. et al. Nonlinear forcing of climate on mountain denudation during glaciations. Nat. Geosci. 14, 16–22 (2021). https://doi.org/10.1038/s41561-020-00672-2

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