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Astronomically controlled aridity in the Sahara since at least 11 million years ago

Nature Geoscience volume 15, pages 671–676 (2022)Cite this article

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Abstract

The Sahara is the largest hot desert on Earth. Yet the timing of its inception and its response to climatic forcing is debated, leading to uncertainty over the causes and consequences of regional aridity. Here we present detailed records of terrestrial inputs from Africa to North Atlantic deep-sea sediments, documenting a long and sustained history of astronomically paced oscillations between a humid and arid Sahara from over 11 million years ago. We show that intervals of strong dust emissions from the heart of the continent predate both the intensification of Northern Hemisphere glaciation and the oldest land-based evidence for a Saharan desert by millions of years. We find no simple long-term gradational transition towards an increasingly arid climate state in northern Africa, suggesting that aridity was not the primary driver of gradual Neogene expansion of African savannah C4 grasslands. Instead, insolation-driven wet–dry shifts in Saharan climate were common over the past 11 Myr, and we identify three distinct stages in the sensitivity of this relationship. Our data provide context for evolutionary outcomes on Africa; for example, we find that astronomically paced arid intervals predate the oldest fossil evidence of hominid bipedalism by at least 4 Myr.

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Fig. 1: African hydroclimate compared with global change over the past 11 Myr.
Fig. 2: Relationship between lithophile element ratios and hydrogen and carbon isotopic compositions of plant waxes at Site 659.
Fig. 3: Strong response of African hydroclimate to astronomical forcing recorded at Site 659.
Fig. 4: Radiogenic isotope signature of Site 659 lithic fraction compared with values of PSAs reveals consistent source.

Data availability

The data presented in this study are available in the Zenodo repository (https://doi.org/10.5281/zenodo.6594643).

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Acknowledgements

This research was funded through ERC advanced grant CDREG no. 322998 (D.J.B.) and the Royal Society Challenge Grant CHG\R1\170054 (P.A.W.) and Wolfson Merit Award WM140011 (P.A.W.). Additional funding came from University of Southampton’s GCRF strategic development fund grant 519016 (P.A.W. and A.J.C.), advanced ERC grant T-GRES ref. 340923 (B.D.A.N. and R.D.P.) and a Royal Society Tata University Research Fellowship (B.D.A.N.). We thank the Natural Environment Research Council for partial funding of the mass spectrometry facilities at the University of Bristol (contract no. R8/H10/63). Financial support was also received from the Deutsche Forschungsgemeinschaft (DFG) (U.R. and T.W.), including project 242225091 (T.W).

This research used samples provided by (I)ODP, which was sponsored by the US National Science Foundation and participating countries under management of Joint Oceanographic Institutions, Inc. We thank W. Hale, H. Kuhlman and A. Wülbers of the Bremen Core Repository and R. K. James, A. McCombie and C. Evans for laboratory assistance, A. Calder for discrete XRF analysis and V. Lukies for assistance with XRF core scanning. Biostratigraphic information was provided by J. Backman, and S. Mulitza supplied the geochemical endmember unmixing code. We thank D. McGee, J. Tierney, T. Ezard, C. Gamble, A. Pike, T. Herbert, K. Grant, S. Feakins, E. Rohling and S. Mulitza for discussions and feedback that helped to improve this manuscript.

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Authors and Affiliations

  1. University of Southampton, Waterfront Campus, National Oceanography Centre, Southampton, UK

    Anya J. Crocker, Rachael H. James, Matthew J. Cooper, Chuang Xuan & Paul A. Wilson

  2. Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK

    Anya J. Crocker, Colin P. Osborne & David J. Beerling

  3. Organic Geochemistry Unit, School of Chemistry, School of Earth Sciences and Cabot Institute for the Environment, University of Bristol, Bristol, UK

    B. David A. Naafs & Richard D. Pancost

  4. MARUM—Center for Marine Environmental Sciences, University of Bremen, Bremen, Germany

    Thomas Westerhold & Ursula Röhl

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Contributions

A.J.C., P.A.W., C.P.O. and D.J.B. designed the study. A.J.C. and T.W. performed the XRF measurements and developed the age model. B.D.A.N. generated the n-alkane δ13C data, and M.J.C. and A.J.C. generated the radiogenic isotope data. A.J.C. performed the sediment endmember unmixing. A.J.C. and P.A.W. led the analysis and interpretation of results with input from all authors. A.J.C., P.A.W., D.J.B. and C.P.O. led the writing of the manuscript with contributions from all other authors.

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Correspondence to Anya J. Crocker.

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Nature Geoscience thanks David McGee and Jessica Tierney for their contribution to the peer review of this work. Primary Handling Editor: James Super, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Comparison between hydroclimate proxies measured at Site 659.

a, b, c, Bulk sediment [Al + Fe]/[Si + K + Ti] (orange), δD signatures of C31 n-alkanes (pale blue, 1σ error bars)39,40, ln[Zr/Rb] (green, pale colours indicate low element counts). d, e, f, Generalised additive model (GAM)99 fit of Site 659 [Al + Fe]/[Si + K + Ti] data shown by black line with grey shaded confidence band (2 standard error). Black crosses indicate original data points with resampled data points used in Kendall’s tau-b correlation tests indicated by red circles (see Supplementary Information). a, d, late Pleistocene, b, e, late Pliocene, c, f, early Pliocene.

Extended Data Fig. 2 Coherency spectra comparing our data from Site 659 to published dust and hydroclimate records from the same and nearby sites.

Green dashed line marks 90% Monte Carlo false-alarm level. a & b, Coherency between the dust % estimates from Site 659 of ref. 11 and our ln[Ca/Fe] (a) and dust flux (b) estimates over the last 8 Myr. c, Coherency between our estimated dust fluxes and those of ref. 15 from nearby site MD03-2705 over the last 240 kyr. d, e, f, Coherency between our [Al+Fe]/[Si+K + Ti] values and C31 n-alkane δD values from Site 659 from refs. 39,40 for three time slices in the Quaternary (d) and Pliocene (e, f).

Extended Data Fig. 3 Comparison between methods for calculating dust fluxes to marine sediments over the last 250 kyr.

a, Red: modal dust flux estimates from Site 659 based on a geochemical end-member unmixing approach, with orange lines marking ± 1 standard deviation of 500 realizations. Blue: Dust flux estimates from site MD03-2705 (directly adjacent to Site 659) calculated by 230Th normalization13 with error bars indicating ± 1 standard deviation. b, Generalized Additive Model99 fit of Site 659 median dust fluxes shown by black line with grey shaded confidence band (2 standard error). Black crosses indicate original data points with resampled data points used in Kendall’s tau-b correlation tests indicated by red circles (see Supplementary Information).

Extended Data Fig. 4 Box and whisker plot illustrating co-variation in sediment colour and geochemistry at Site 659.

Top: [Al + Fe]/[Si + K + Ti], bottom: ln[Zr/Rb]. Data are plotted from “light” and “dark” sediment layers (as defined by the method described in the Supplementary Information) for each of the three time stages (Stage I: 11.15 – 6.7 Ma, Stage II: 5.75 – 3.5 Ma, Stage III: 2.25 – 0 Ma). Box indicates interquartile range (IQR) with line marking median value, outliers (>1.5 IQR from median) marked with circles and whiskers drawn to the maximum/minimum values excluding outliers. Mann-Whitney-Wilcoxon tests were used to test the null hypothesis that samples from light and dark layers have identical continuous distributions with equal medians for each time interval. All resulting p-values were <0.001, giving >99.9% confidence that the differences between light and dark layers are significant. See Supplementary Information for further discussion.

Extended Data Fig. 5 Wavelet analysis of Site 659 geochemical records.

Comparison between continuous wavelet power spectra of calibrated ln[Ca/Fe] (top) and [Al + Fe]/[Si + K + Ti] (bottom) data on the astronomically-tuned age model (left) and an untuned age model based solely on biostratigraphic and magnetostratigraphic datums14,69 (right). Thick black contours designate the 5% significance level against red noise and the cone of influence is shown as a lighter shade, where edge effects may cause distortion. Data were detrended and smoothed (5-point moving average) prior to the wavelet analyses. Separate spectra were also generated for the older and younger sections of the full record to reduce the impact of temporal changes in cycle amplitude on the detected frequencies. Analyses were performed and figures generated using the Matlab code of ref. 74. See Supplementary Information for further discussion.

Extended Data Fig. 6 REDFIT spectral analysis75 of Site 659 geochemical records.

Top: ln[Ca/Fe] ratios, middle: calibrated [Al + Fe]/[Si + K + Ti] ratios, bottom: median dust flux values. Data are divided into the three time stages discussed in the text. Left: Stage III (2.25–0 Ma), centre: Stage II (5.75–3.5 Ma), right: Stage I (11.15–6.9 Ma). Green curves mark the false-alarm level at the 95% confidence level, red curves indicate AR(1) red noise models. Orange lines and numbers indicate the frequencies equivalent to periods (in kyr) of major astronomical cycles (precession, obliquity and eccentricity). Analysis performed and figures created using PAST software100. See Supplementary Information for further discussion.

Extended Data Fig. 7 Running statistical analysis of Site 659 geochemical data, comparing 1 Myr data bins.

a, Mann-Whitney-Wilcoxon test log(p) values to detect shifts in central tendency (see Supplementary Information). Low values indicate extremely low probabilities that the two data bins have the same central tendency. b, Estimated difference in location between the two data bins divided by the interquartile range of the complete data set, with 95% confidence interval plotted. Note that [Al + Fe]/[Si + K + Ti] is plotted on an inverted axis. c, Ansari-Bradley test log(p) values to detect shifts in dispersion. Low values indicate extremely low probabilities that the two data bins have the same dispersion. d, Ratio of scales between the two data bins, with 95% confidence interval plotted. Orange: calibrated [Al + Fe]/[Si + K + Ti], green: ln[Zr/Rb] (with XRF counts <300 removed), red: median dust flux (g cm−2 kyr−1). Grey shading indicates intervals of greatest change in the geochemical time series revealed by statistical analyses.

Extended Data Fig. 8 Cross-plots of strontium and neodymium isotopic signature of lithic fraction of Site 659 sediments.

Data coloured by: a, the proportion of the lithic fraction attributed to dust by end-member unmixing ([dust]/[dust+riverine]), b, co-registered ln[Zr/Rb] values. Red marks samples dominated by dust/coarse grains, blue marks samples dominated by riverine inputs/fine grains. c, Data coloured by age, where stage I (pink) is the oldest (>6.9 Ma), stage III (blue) is the youngest (<2.25 Ma) and grey indicates samples from the transition between stages II and III (3.5–2.25 Ma). Individual samples are marked by crosses and mean values for each age range are shown by circles, with error bars indicating 1 standard deviation.

Extended Data Fig. 9 Grain size distributions of the end-members calculated from the lithic fraction of ODP Site 659.

Grain size derived end-member 1 (EM1) in blue and grain size derived end-member 2 (EM2) in red compared to: a, Modern dust samples recorded offshore NW Africa from ref. 57 in grey. b, As (a) but with just the most proximal measurements to Site 659 (M41/1 D4, centered at 19.73°N, 17.91°W) plotted. c, The grain size end members of ref. 12 from site GeoB7920-2 (20.75°N, 18.58°W). Yellow and orange dashed lines indicate the end members attributed to fine and coarse dust respectively, with the riverine end member shown in green. d, All Site 659 lithogenic grain size distributions (black).

Extended Data Fig. 10 Comparisons between grain size and geochemical proxies at Site 659.

a & b, [Al + Fe]/[Si + K + Ti] ratios of the coarse and fine fractions of (a) 12 sediment samples from Site 659 sieved at 10 μm and analysed by discrete XRF analysis with sample ages are listed along the top and (b) desert surface soil and aeolian dusts from four locations in the Sahara-Sahel dust corridor, analysed by inductively coupled plasma mass spectrometry and grouped into <12 μm and >12 μm size fractions, from ref. 101. CB: Chad Basin, HM: Hoggar Massif, WS: Western Sahara, HAR: Harmattan. c & d, The proportion of lithogenic grain size derived end-member 1 (grain size EM1, attributed to fine riverine inputs) plotted against the sediment geochemical ratios c [Al + Fe]/[Si + K + Ti] and d ln[Zr/Rb]. Data points are coloured by sample age, where the youngest samples are in blue and the oldest in orange.

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Supplementary Figs. 1–8 and Discussion.

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Crocker, A.J., Naafs, B.D.A., Westerhold, T. et al. Astronomically controlled aridity in the Sahara since at least 11 million years ago. Nat. Geosci. 15, 671–676 (2022). https://doi.org/10.1038/s41561-022-00990-7

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