Supplementary Information

ITEM DR1. IODP SITE U1417

IODP Site U1417 is located in the distal Surveyor Fan, ca. 60 km from the Surveyor Channel (Fig. DR1), which delivers sediment to Site U1417 through overbank processes (Gulick et al., 2015; Jaeger et al., 2014). Core recovery using the ACP coring system down to ca. 220 m at holes A-D was very good (97% recovery), and the quality of the recovered core was excellent. Detailed lithostratigraphic information on Site U1417 sediments is provided in Jaeger et al. (2014). An elaborate sampling scheme has been developed for Site U1417 to ensure direct correlations and comparability between different proxy records generated by IODP 341 expedition scientists. Sampling intervals have been chosen in due consideration of shipboard bio- and/or magnetostratigraphy, sedimentology and magnetic susceptibility data. Ash layers and turbidites were not sampled.

Fig. DR1: Location of core Site U1417 in the Gulf of Alaska. The white arrow marks the Surveyor Channel.

U1417

Surveyor Channel

GSA Data Repository 2018088

Müller et al., 2018, Cordilleran ice-sheet growth fueled primary productivity in the Gulf of Alaska, northeast Pacific Ocean: Geology, https://doi.org/10.1130/G39904.1.

ITEM DR2. AGE MODEL AND METHODS

Age control is provided by planktic foraminifera 18O isotope stratigraphy and shipboard paleomagnetic and biostratigraphic constraints. Mass accumulation rates have been calculated through conversion of shipboard gamma ray data into dry bulk densities.

Fig. DR2.1: Age model for Site U1417. Top: Comparison of 18O values at Site U1417 with the LR04 stack (Lisiecki and Raymo, 2005); below: Comparison of the high resolution isotopic age model with the IODP Expedition 341 shipboard age model based on biostratigraphy (radiolarians, diatoms, planktic foraminifers) and paleomagnetic age constraints; right: U1417 18O values vs. core depth.

Calculation of mass accumulation rates (MARs) Bulk MARs at Site U1417 were calculated from multiplication of the sedimentation rates (SR) and dry bulk densities (DBD), which were derived from shipboard gamma ray attenuation rates (GRA) using following equations (1)-(3). Track-based non-destructive physical property measurements in ocean drilling often suffer artifacts from incomplete coring recovery within lithified sediments (Walczak et al., 2015). Assuming that BDGRA is influenced by volume loss due to a decreasing core recovery at higher depths, BDGRA is corrected to true BDdiscrete values using offset correction Foff, which is a function of volume loss along the depth (vol.loss) as:

. (1)

With the assumption that Foff is also a function of depth, eq. (1) can be rewritten as:

(2)

At Site U1417, Foff within the studied depth interval (ca. 0-200 m CCSF-B) is negligibly small (Fig. DR2.2: -0.006±0.117, n = 80, 1σ), suggesting that no volume correction is

required in that depth interval. Subsequently, offset corrected BDGRA is converted into DBD, using a linear BDdiscrete-DBDdiscrete relationship at Site U1417 (Fig. DR2.3). Using a robust linear fitting with the LAR technique shows their linear relation (r2 = 1.00, n = 220, residual mean square errors = 0.005) as:

(3)

where coefficients were estimated with 95% CL errors as: S = 1.552±0.004 and C = -1.579±0.006, respectively. Total (bulk) MARs at certain depth/age horizons were calculated by multiplication of DBDGRA and SR derived from the age model assuming constant sedimentation rates between age-tie points. MARs of diatom valves, biogenic opal, and coarse sand were obtained from multiplication of their concentration with total MAR (Fig. DR2.4). We also calculated mean MARs at each Marine Isotope Stage (Fig. DR2.4; colored bars), to capture their mean state between age-tie points.

Fig. DR2.2: Comparison of GRA based BD (BDGRA) and discrete BD (BDdiscrete) at U1417. Top panel: BDGRA (back small dots) and BDdiscrete (red open circles) versus depth. Bottom left panel: offsets (BD-GRA) and mean offset values (solid red line) with its error range (1 σ: dash red lines; 95% CL: gray shadings) above 200 m CCSF-B. Bottom right panel: histogram of BD-GRA at the.

Fig. DR2.3: BDdiscrete-DBDdiscrete relation at Site U1417.

Fig. DR2.4: Total mass accumulation rates at Site U1417 and accumulation rates of coarse sand, biogenic opal and diatoms. Colored bars refer to calculated mean MARs between age-tie points.

ANALYTICAL METHODS 18O analyses and isotope stratigraphy An orbital scale age model for Site U1417 was established from the oxygen isotope stratigraphy of the planktic foraminifer Neogloboquadrina pachyderma, in comparison to the global oxygen isotope stack LR04 (Lisiecki and Raymo, 2005). Ten to twenty specimens of left-coiling N. pachyderma were picked from 150-250 µm size-fractions for stable isotope measurements. The isotope analyses were conducted by MAT252 with a Kiel III sample preparation system at the stable isotope lab at Oregon State University (College of Earth, Ocean, and Atmosphere Sciences). Site U1417 δ18O data were compared to the global composite stack curve LR04, using a dynamic program “MATCH 2.3” (Lisiecki and Lisiecki, 2002). Prior to the matching, all data were normalized in order to obtain a maximum matching efficiency. All age-depth tie points from paleomagnetic reversal events at U1417 (Jaeger et al., 2014) and comparisons to the relative geomagnetic paleointensity at U1417 to the global stack curve (PISO 1500; Channell et al., 2009) were included as initial age constrains for age-matching (Table DR2).

U1417 depth (m CCSF-B)

Age (ka) U1417

depth (m CCSF-B)

Age (ka) U1417

depth (m CCSF-B)

Age (ka) U1417

depth (m CCSF-B)

Age (ka)

2.99 28.48 32.86 172.66 78.17 485.94 128.30 998.58 3.82 32.04 34.02 181.56 79.00 500.18 131.45 1028.84 4.65 35.60 34.52 185.12 80.33 534.00 141.08 1096.48 5.48 39.16 36.51 195.80 85.64 574.94 141.74 1101.82 6.31 42.72 37.34 199.36 86.14 576.72 144.89 1137.42 7.14 46.28 45.14 231.40 87.97 583.84 145.39 1146.32 7.97 49.84 45.64 233.18 88.80 587.40 145.89 1155.22 8.80 53.40 46.14 234.96 90.45 594.52 146.89 1173.02 9.63 56.96 46.97 238.52 103.90 717.34 148.38 1199.72 10.46 60.52 47.80 242.08 105.39 744.04 148.88 1208.62 11.29 64.08 48.63 245.64 105.72 749.38 149.38 1217.52 12.12 67.64 49.46 249.20 106.22 756.50 149.87 1226.42 12.95 71.20 50.29 252.76 106.39 758.28 150.37 1235.32 13.78 74.76 51.12 256.32 107.22 765.40 153.36 1288.72 14.61 78.32 51.95 259.88 107.88 770.74 153.86 1297.62 15.44 81.88 52.78 263.44 108.38 774.30 154.35 1306.52 16.27 85.44 53.94 268.78 109.21 779.64 154.85 1315.42 17.10 89.00 54.77 274.12 110.04 784.98 155.35 1324.32 17.93 92.56 55.60 279.46 110.54 788.54 155.85 1333.22 18.75 96.12 56.43 284.80 111.20 793.88 156.35 1342.12 19.58 99.68 57.26 290.14 111.37 795.66 156.84 1351.02 20.41 103.24 58.09 295.48 112.70 813.46 157.34 1359.92 21.24 106.80 58.92 300.82 112.86 815.24 157.84 1368.82 22.90 113.92 59.75 306.16 113.69 822.36 158.34 1377.72 23.73 117.48 61.41 316.84 114.36 827.70 159.83 1404.42 24.56 121.04 62.24 322.18 115.02 833.04 161.99 1436.46 25.39 124.60 62.74 325.74 115.68 838.38 162.82 1443.58 26.22 128.16 64.23 338.20 116.35 843.72 163.48 1448.92 27.05 131.72 65.89 363.12 117.01 849.06 164.81 1457.82 27.88 135.28 66.39 370.24 117.67 854.40 170.00 1500.00 29.05 142.40 70.04 400.50 119.17 866.86 445.00 5500.00 29.54 145.96 70.87 405.84 119.33 868.64 472.50 6000.00 30.21 151.30 72.53 416.52 123.15 930.94 527.50 6500.00 30.87 156.64 73.03 420.08 124.15 945.18 630.00 9500.00 31.53 161.98 73.86 427.20 125.48 962.98 32.20 167.32 77.18 471.70 127.47 989.68

Table DR2: Site U1417 depth-age tie points from oxygen isotope stratigraphy.

Biomarker analyses Samples of 3-4 gram of freeze-dried and homogenized sediment were microwave-extracted following Kornilova and Rosell-Melé (Kornilova and Rosell-Melé, 2003) using 15 ml of DCM:MeOH (3:1). Total lipid extracts were purified via open column chromatography using silica as stationary phase. Apolar hydrocarbons were eluted with n-hexane, while ketones were obtained using DCM. Alkenones were analysed using gas chromatography-chemical ionization-mass spectrometry (GC-CI-MS). The UK

37 and UK37' indices were calculated

according to the relative abundances of the di-, tri- and tetra-unsaturated C37 alkenones (Brassell et al., 1986; Prahl et al., 1988). The calibration uncertainty is ca. 1°C. Hydrocarbons were analysed using an HP 6890 gas chromatograph fitted with a 30 m DB-5MS column (0.25 mm i.d., 0.25 µm film thickness). Identification of individual n-alkanes was based upon comparisons of their retention times with reference compounds. Deviation for the repeatability of measurements was less than 10%. The TAR ratio was calculated from peak areas of long-chain (C27, C29, C31) against short-chain (C15, C17, C19) n-alkanes (Meyers, 1997). While high TAR values refer to a higher abundance of terrestrial (leaf-wax) lipids, low TAR values indicate a dominance of aquatic (algae) derived short-chain n-alkanes. At Site U1417, TAR values are positively correlated with the other phytoplankton productivity indicators (e.g. Ba/Al; R2=0.42). We hence suggest that the input of land-plant derived long-chain n-alkanes controls TAR variability rather than changes in algal productivity (contributing short-chain n-alkanes). Diatom and biogenic silica measurements Circa 0.5 g freeze-dried sediment were used for diatom studies. Samples were prepared according to the standard randomly distributed microfossils method of Schrader and Gersonde (Schrader and Gersonde, 1978). Qualitative and quantitative analyses were carried out on permanent slides of acid-cleaned material (Permount® mounting medium) at 1000x magnifications using a Zeiss Axiskop (MARUM, University of Bremen, Bremen, Germany). The counting methodology of valves followed Schrader and Gersonde (Schrader and Gersonde, 1978). Several traverses across each cover slip were examined, depending on diatom abundances (between 200 and 500 valves were counted for each cover slip). Two cover slips per sample were scanned in this way. The resulting counts yielded concentration of valves per g-1 (DC), calculated according to Sancetta and Calvert (Sancetta and Calvert, 1988), as follows:

DC = [N] x [A/a] x [V] x [g]

where, [N] number of valves, in an area [a], as a fraction of the total area of a petri dish [A] and the dilution volume [V] in ml. This value is multiplied by the sample amount [g]. Biogenic silica (opal), measured in freeze-dried sediments, was determined with a sequential 1M NaOH-leaching method (Müller and Schneider, 1993). The precision of the overall method based on replicate analyses is between ±0.2 and ±0.4%. IRD analyses IRD is quantified by weighing the coarse sand fraction (250 µm-2 mm) following the method of Krissek (Krissek, 1995). Although it is recognized that the most abundant contributions of glaciers may be in the fine fraction, coarse sand is adopted as a grain size that is coarse enough to not be transported to the sea floor by other means (Hemming, 2004). Coarse sand was separated from 10 cm3 samples by wet and dry sieving after air drying and rinsing with distilled water to remove salts. Each sand sample was examined with a binocular microscope to estimate the volume of terrigenous ice-rafted sediment (in volume percent) in order to exclude biogenic components and burrow fills of manganese and pyrite, which do not have an ice-rafted origin. The precision of measurements is 0.001 grams.

XRF measurements Inorganic geochemical analyses were performed on fused beads using a Bruker Tiger S8 wavelength-dispersive XRF spectrometer. The fused beads were prepared from 0.8 g grinded sediment and 5.6 g lithium borate flux that were melted in a melting machine xrFuse2. Calibrations of the results were performed against international standards. The Ba concentration was determined using the analytical software QUANT-EXPRESS developed by Bruker. Standard deviation of Al concentration is ±0.17%.

ITEM DR3. EOLIAN DUST- & ICEBERG-FERTILIZATION EVENTS AT SITE U1417

For the allocation of eolian dust- vs. iceberg-fertilized productivity events (Fig. DR3), we presume two (admittedly extreme) scenarios: a significantly advanced NCIS sealing coastal as well as in-land dust deposits (hampering eolian-fertilization due to a decreased exposure of dust sources); and a retreated NCIS exposing coastal plains and central Alaskan dust (loess) deposits. In fact, we cannot exclude a continued (additional) airborne transport of Fe-bearing dust to the GoA during intervals of iceberg discharge. We, however, argue that if eolian dust fertilization was a continuous driver of phytoplankton productivity, respective peaks in Ba/Al or diatom abundance should be observable during all IRD minima.

Fig. DR3: Comparison of IRD as coarse sand (gray), TAR (yellow), diatom concentration (dark green), and Ba/Al (light green) records against the global benthic 18O stack (Lisiecki and Raymo,

2005). Vertical gray and light orange lines denote iceberg- and eolian dust-fertilized primary productivity events, respectively.

ITEM DR4. FE-INPUT THROUGH VOLCANIC ASH AND MESOSCALE EDDIES

Iron input and fertilization of GoA surface waters via volcanic ash and anticyclonic mesoscale eddies has the potential to promote phytoplankton blooms and this has been demonstrated in several studies (Crawford et al., 2007; Frogner et al., 2001; Hamme et al., 2010; Ladd et al., 2005; Langmann et al., 2010; Mélançon et al., 2014). Tephra layers are quite abundant in Site U1417 sediments and are documented in the IODP Expedition 341 visual core descriptions (Jaeger et al., 2014). However, while some of these macroscopic ash layers coincide with productivity pulses at Site U1417, others do not (Fig. DR4). Numerous studies have shown that also disseminated ash makes a significant contribution to subarctic North Pacific sediments (e.g. Bailey et al., 2011; Prueher and Rea, 2001). In the absence of geochemical cryptotephra analyses data, we cannot, at this stage, pin-point ash-fertilization as a main driver of the observed productivity pulses. We acknowledge that ash-fertilized phytoplankton blooms potentially intensified dust- and/or iceberg-fertilized productivity events recorded at Site U1417. However, due to the lack of detailed tephra data and based on the observation that not all (visible) tephra-layers in U1417 sediments coincide with productivity events, we assume that volcanic ash-fertilized phytoplankton blooms may be considered as an additional but not major signal in the U1417 record. Further, we do not entirely exclude that mesoscale eddies (permitting cross-shelf transport of Fe) could have contributed to phytoplankton productivity at Site U1417. However, one would have to assume that these eddies were significantly stronger than today to reach distal Site U1417. Crusius et al. (2017) recently stated that “little of the shelf-derived dissolved Fe is transported more than a hundred kilometers beyond the shelf break” and that “other sources of dissolved Fe (including dust) must be important farther offshore”. Finally, with regard to glacial-interglacial changes in the GoA environmental setting, we consider that eddy-fertilization would have been confined to periods of a reduced glacial extent (i.e. when the shelf was not covered by the NCIS).

Fig. DR4: Site U1417 Ba/Al (filled green curve), diatom concentration (dark green curve) and macroscopic ash-layers against core depth. Red diamonds refer to tephra layers that coincide with

iceberg- or dust-fertilized productivity events, while gray circles denote tephra layers that are not associated with an enhanced productivity.

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