Supplementary information

An annually resolved record of Western European vegetation response to Younger

Dryas cooling

Igor Obreht1, Lars Wörmer1, Achim Brauer2,3, Jenny Wendt1, David De Vleeschouwer4, Susanne Alfken1,

Marcus Elvert1, Kai-Uwe Hinrichs1

1Organic Geochemistry Group, MARUM – Center for Marine Environmental Sciences and Department of

Geosciences, University of Bremen, Leobener Str. 8, 28359 Bremen, Germany

2GFZ – German Research Centre for Geosciences, Section Climate Dynamics and Landscape Evolution,

Telegrafenberg, 14473 Potsdam, Germany

3Potsdam University, Department of Earth Sciences, Karl-Liebknecht-Str. 24/25, 14476 Potsdam,

Germany

4Palaeoceanography group, MARUM – Center for Marine Environmental Sciences and Department of

Geosciences, University of Bremen, Leobener Str. 8, 28359 Bremen, Germany

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Supplementary Figure S1. Comparison of amount of successful spectra from TAR and TAR (24-28/14-16 using

mass spectrometry imaging on a 5 cm sample section from core MFM09-A5-UR at a section depth of

23-28 cm. a) Image of the sample section, red rectangles indicate the area where MSI was performed. b)

Spatial distribution of terrestrial aquatic ratio of C26:0 and C16:0 fatty acids (TAR; upper figure; 59.6% data

points with successfully detected C26:0 and C16:0 fatty acids) and TAR(24-28/14-16) (lower figure; 35.3% data

points with successfully detected C14:0, C16:0, C24:0, C26:0, and C28:0 fatty acids). C) Down-core profiles of

horizontally averaged data points of the selected sample. TAR exhibit 241 robust data points from a total

of 246 horizons, while TAR(24-28/14-16) exhibits 204 robust data points.

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Supplementary Figure S2. Cyclicity of TAR (a) ACL (b) time-series from MFM. Spectral analysis was

performed on detrended data and generated in R using Astrochron (Meyers et al., 2018) and applying

the Multi-taper method. Red line is indicative of 99% confidence lever, while blue line of 95% confidence

level. Both, TAR and ACL indicate dominant cyclicity in 40-60 years periods. In addition to that, TAR

exhibit significant cyclicity of ~30 years, while ACL of ~17 years.

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Supplementary Figure S3. The wavelet transform analysis of TAR (a) and ACL (b) from MFM. Data were

obtained in R Statistic using astrochron (Meyers et al., 2018) and and biwavelet libraries. Data were

previously detrended.

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Supplementary Figure S4. Pearson correlation coefficient series for NGRIP d and ACL, and NGRIP d and

TAR and visualization of the correlation with different age model used. TAR and ACL data-series are

resampled to the sample grid of the NGRIP d data. For assuming robust correlation, five different age

models were considered to account for ±10 years uncertainty in converting NGRIP to MFM chronology

(-10 (blue line), -5 (green line), 0 (black line), +5 (orange line) and +10 years (red line)).

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Supplementary Table 1. δ13C values (in ‰) of selected fatty acids (C24, C26, C28) and bishomohopanoic acid

(CBA), modelled minimal contribution of terrestrial sources to concentrations of C26:0 and C28:0 fatty acids

(in %), ACL and ACL corrected for terrestrial fatty acids only (ACL terr). Values marked by * indicate values

larger than 100% due to lower values of δ13C-C24 than δ13C-C26, indicating clear terrestrial origin of C26:0

fatty acids and are considered as 100% in the calculation to obtain ACLterr.

Age (year BP) δ13C24 δ13C26 δ13C28 δ13CBA C26terr (%) C28terr (%) ACL ACLterr

12416 -30.0 -29.9 -31.5 -52.8 100.5* 93.8 26.02 25.9912443 -29.9 -29.2 -31.4 -54.3 103.1* 93.9 25.90 25.8712465 -31.6 -30.5 -33.3 -52.8 104.8* 91.7 26.06 26.0112485 -30.8 -32.0 -34.2 -56.1 95.0 86.5 25.97 25.9012525 -30.1 -29.9 -31.5 -55.7 100.9* 94.4 25.95 25.9212588 -30.4 -29.5 -32.4 -58.0 103.2* 92.8 26.03 25.9912609 -29.7 -29.7 -31.7 -54.4 99.7 91.6 26.01 25.9612630 -30.2 -32.4 -34.3 -59.9 92.7 86.3 26.04 25.9612639 -30.9 -32.7 -33.6 -59.8 93.8 90.8 25.95 25.9012648 -32.4 -36.3 -37.3 -66.6 88.7 85.6 26.12 26.0412656 -32.0 -33.3 -34.6 -67.2 96.2 92.5 26.13 26.0912669 -31.5 -33.2 -35.0 -63.3 94.7 89.1 26.18 26.1212687 -32.9 -35.9 -37.7 -68.2 91.6 86.4 26.07 26.0012702 -32.7 -35.3 -36.4 -71.1 93.2 90.4 25.89 25.8312727 -30.6 -38.3 -40.3 -68.3 79.7 74.3 26.29 26.1512762 -34.7 -42.2 -42.5 -67.7 77.2 76.3 26.24 26.1212796 -32.5 -40.2 -40.3 -66.1 77.3 76.8 26.21 26.0812826 -30.8 -33.3 -33.4 -64.0 92.6 92.1 25.90 25.8512894 -32.1 -40.4 -41.6 -65.7 75.4 71.9 26.20 26.0412945 -33.3 -38.9 -38.7 -63.9 81.9 82.6 26.19 26.1013079 -32.1 -34.1 -34.7 -60.7 93.0 90.9 26.11 26.0613144 -31.4 -37.1 -37.8 -63.3 82.3 80.1 26.14 26.0313158 -30.7 -34.7 -36.7 -61.9 87.1 80.7 26.00 25.8913176 -31.0 -34.6 -35.6 -59.0 87.2 83.7 26.08 26.00

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Supplementary Table 2. The correlation coefficient series of ACL and NGRIP d for each sliding windows

of 160 year width. Five age models were considered to account for ±10 years uncertainty in converting

NGRIP to MFM chronology. Discussed period of time-transgressive cooling is highlighted with bolded

numbers.

Window range (year BP)

Middle (year BP)

ACL-10 and NGRIP d

ACL-5 and NGRIP d

ACL and NGRIP d

ACL+5 and NGRIP d

ACL+10 and NGRIP d

CL 95%

CL 99%

12618-12778 12698 0.21 0.31 0.09 0.18 0.14 0.26 0.3512628-12788 12708 0.22 0.30 0.08 0.20 0.16 0.26 0.3512638-12798 12718 0.21 0.29 0.10 0.18 0.14 0.26 0.3512648-12808 12728 0.21 0.26 0.11 0.21 0.19 0.26 0.3512658-12818 12738 0.23 0.23 0.12 0.25 0.17 0.26 0.3512668-12828 12748 0.24 0.25 0.16 0.30 0.26 0.26 0.3512678-12838 12758 0.27 0.26 0.13 0.33 0.25 0.26 0.3512688-12848 12768 0.29 0.24 0.14 0.32 0.23 0.26 0.3512698-12858 12778 0.32 0.18 0.15 0.32 0.27 0.26 0.3512708-12868 12788 0.34 0.17 0.15 0.27 0.24 0.26 0.3512718-12878 12798 0.38 0.25 0.19 0.28 0.26 0.26 0.35

12728-12888 12808 0.36 0.26 0.31 0.41 0.33 0.260.35

12738-12898 12818 0.21 0.19 0.25 0.42 0.39 0.26 0.3512748-12908 12828 0.12 0.00 0.14 0.32 0.34 0.26 0.3512675-12918 12838 0.05 -0.08 0.04 0.08 0.21 0.26 0.3512676-12928 12848 0.07 -0.03 0.03 0.04 0.18 0.26 0.3512778-12938 12858 0.08 -0.04 0.09 0.09 0.15 0.26 0.3512788-12948 12868 0.08 -0.01 0.12 0.12 0.14 0.26 0.3512798-12958 12878 0.01 -0.04 0.13 0.13 0.15 0.26 0.3512808-12968 12888 0.05 -0.01 0.13 0.10 0.16 0.26 0.3512818-12978 12898 0.07 0.02 0.15 0.08 0.10 0.26 0.3512828-12988 12908 0.05 0.07 0.15 0.08 0.09 0.26 0.3512838-12998 12918 0.02 0.02 0.15 0.12 0.10 0.26 0.3512848-13008 12928 0.01 0.00 0.12 0.09 0.11 0.26 0.3512858-13018 12938 -0.04 -0.03 0.11 0.04 0.05 0.26 0.3512868-13028 12948 -0.04 -0.08 0.03 0.06 0.03 0.26 0.3512878-13038 12958 0.04 0.01 0.06 0.06 -0.02 0.26 0.3512888-13048 12968 -0.01 0.01 0.01 -0.02 -0.04 0.26 0.3512898-13058 12978 0.08 0.07 0.00 0.00 -0.09 0.26 0.3512908-13068 12988 0.05 0.07 0.03 0.07 -0.10 0.26 0.3512818-13078 12998 0.08 0.08 0.05 0.10 -0.07 0.26 0.3512828-13088 13009 0.06 0.11 0.08 0.12 -0.07 0.26 0.3512838-13098 13019 -0.03 0.07 -0.03 0.06 0.00 0.26 0.3512848-13108 13029 -0.05 0.05 -0.07 0.00 -0.04 0.26 0.35

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12858-13118 13039 -0.09 0.00 -0.13 -0.05 -0.16 0.26 0.35

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Supplementary Table 3. The correlation coefficient series of TAR and NGRIP d for each sliding windows

of 160 year width. Five age models were considered to account for ±10 years uncertainty in converting

NGRIP to MFM chronology. Discussed period of time-transgressive cooling is highlighted with bolded

numbers.

Window range (year

BP)

Middle (year BP) TAR-10 and

NGRIP dTAR-5 and NGRIP d

TAR and NGRIP d

TAR+5 and NGRIP d

TAR+10 and NGRIP d

CL 95%

CL 99%

12618-12778 12698 0.25 0.22 0.26 0.26 0.400.31 0.41

12628-12788 12708 0.26 0.22 0.21 0.21 0.350.31 0.41

12638-12798 12718 0.28 0.21 0.21 0.22 0.390.31 0.41

12648-12808 12728 0.29 0.26 0.29 0.28 0.430.31 0.41

12658-12818 12738 0.24 0.15 0.18 0.16 0.310.31 0.41

12668-12828 12748 0.27 0.19 0.22 0.22 0.360.31 0.41

12678-12838 12758 0.28 0.19 0.17 0.18 0.310.31 0.41

12688-12848 12768 0.31 0.25 0.19 0.21 0.310.31 0.41

12698-12858 12778 0.35 0.24 0.19 0.24 0.300.31 0.41

12708-12868 12788 0.36 0.27 0.25 0.29 0.330.31 0.41

12718-12878 12798 0.39 0.33 0.34 0.35 0.390.31 0.41

12728-12888 12808 0.30 0.29 0.35 0.41 0.490.31

0.41

12738-12898 12818 0.08 0.16 0.25 0.37 0.480.31 0.41

12748-12908 12828 -0.06 -0.01 0.08 0.22 0.400.31 0.41

12675-12918 12838 -0.25 -0.17 -0.08 -0.02 0.160.31 0.41

12676-12928 12848 -0.33 -0.24 -0.17 -0.09 0.110.31 0.41

12778-12938 12858 -0.39 -0.34 -0.19 -0.10 0.040.31 0.41

12788-12948 12868 -0.41 -0.36 -0.24 -0.17 -0.020.31 0.41

12798-12958 12878 -0.44 -0.41 -0.28 -0.24 -0.14 0.3 0.41

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1

12808-12968 12888 -0.42 -0.41 -0.31 -0.29 -0.190.31 0.41

12818-12978 12898 -0.44 -0.40 -0.29 -0.33 -0.230.31 0.41

12828-12988 12908 -0.45 -0.39 -0.31 -0.34 -0.230.31 0.41

12838-12998 12918 -0.34 -0.29 -0.20 -0.24 -0.160.31 0.41

12848-13008 12928 -0.28 -0.24 -0.15 -0.19 -0.120.31 0.41

12858-13018 12938 -0.16 -0.12 -0.02 -0.07 -0.020.31 0.41

12868-13028 12948 -0.04 -0.05 0.05 0.00 0.050.31 0.41

12878-13038 12958 0.06 0.09 0.22 0.12 0.130.31 0.41

12888-13048 12968 0.01 0.10 0.20 0.14 0.110.31 0.41

12898-13058 12978 0.07 0.12 0.19 0.16 0.120.31 0.41

12908-13068 12988 0.11 0.13 0.18 0.21 0.110.31 0.41

12818-13078 12998 0.13 0.14 0.18 0.23 0.120.31 0.41

12828-13088 13009 0.09 0.15 0.21 0.23 0.110.31 0.41

12838-13098 13019 0.07 0.13 0.15 0.24 0.130.31 0.41

12848-13108 13029 -0.02 0.04 0.08 0.17 0.090.31 0.41

12858-13118 13039 -0.19 -0.13 -0.09 0.09 0.000.31 0.41

Supplementary discussion

In order to evaluate potential influence of methanotrophic microbial communities on ACL time-series,

we performed end member mixing analyses using δ13C values of fatty acids. δ13C values of the C24:0 fatty

acid are in the range of ~-29‰ to -32‰ (Fig. 5 and Supplementary Table 1) and fit the range of δ13C

characteristic for C3 plants, as well as the range of δ13C of total organic carbon at MFM (~-28‰ to -33‰)

(Fuhrmann et al., 2004). Hence, we can assume that C24:0 fatty acid is not produced as hydroxylated

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derivative by methanotrophs (Bowman et al., 1991). Consequently, we consider δ13C values of the C24:0

fatty acids as representative of the end-member from higher plant sources. Based on the assumption

that aquatic C26:0 and C28:0 fatty acids originate from the same source as bishomohopanoic acid, we

consider δ13C values of bishomohopanoic acid (δ13CBA) as the end-member of additional aquatic sources,

which presumably are mainly methanotrophs. To estimate the admixture of C26:0 and C28:0 fatty acids from

microbial sources and thus validate the impact of microbial contributions and the ACL, we per formed the

end-member mixing analyses using the following equations:

C26terr=(δ13CBA- δ13C26)/(δ13CBA- δ13C24)*100 (1)

C28terr=(δ13CBA- δ13C28)/(δ13CBA- δ13C24)*100 (2)

In Eq. 1 and Eq. 2, C26terr and C28ter present the minimal percentage of C26:0 and C28:0 fatty acids estimated to

originate from terrestrial sources, δ13CBA, δ13C24, δ13C26 and δ13C28 stands for measured δ13C values of

bishomohopanoic acid, C24:0, C26:0 and C28:0 fatty acids, respectively. Results are presented in

Supplementary Table 1 and confirm terrestrial sources as the major contributors to the C26:0 and C28:0

fatty acid pool, to which they contribute from ~75 to 100% for the C 26:0 and from ~72 to 94% for the C28:0

fatty acid. Based on this, we calculated the ACLterr values corrected for their microbial contribution from

our GC-FID data in order to demonstrate and visualize (Fig. 5) the effect of microbial contributions to ACL

variability:

ACLterr=(24*C24+26*(C26terr/100*C26)+ 28*(C28terr/100*C28))/(C24+(C26terr/100*C26)+ (C28terr/100*C28)) (3)

Supplementary references

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Bowman, J.P., Skerratt, J.H., Nichols, P.D., and Sly, L.I. (1991). Phospholipid fatty acid and

lipopolysaccharide fatty acid signature lipids in methane-utilizing bacteria. FEMS Microbiol. Lett.

85, 15–21.

Fuhrmann, A., Fischer, T., Lücke, A., Brauer, A., Zolitschka, B., Horsfield, B., Negendank, J.F.W., Schleser,

G.H., and Wilkes, H. (2004). Late Quaternary environmental and climatic changes in central

Europe as inferred from the composition of organic matter in annually laminated maar lake

sediments. Geochem. Geophys. Geosystems 5.

Meyers, S., Malinverno, A., Hinnov, L., and Moron, V. (2018). astrochron: A computational tool for

astrochronology.

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