Links between iron supply, marine productivity, sea surface temperature and CO2 over the last 1.1 Ma

Links between iron supply, marine productivity, sea surface temperature, and CO 2 over the last 1.1 Ma Alfredo Martı´nez-Garcia, 1 Antoni Rosell-Mele´, 1,2 Walter Geibert, 3,4,5 Rainer Gersonde, 6 Pere Masque´, 1 Vania Gaspari, 7 and Carlo Barbante 7,8 Received 3 July 2008; revised 9 October 2008; accepted 27 October 2008; published 14 February 2009. [1] Paleoclimatic reconstructions have provided a unique data set to test the sensitivity of climate system to changes in atmospheric CO 2 concentrations. However, the mechanisms behind glacial/interglacial (G/IG) variations in atmospheric CO 2 concentrations observed in the Antarctic ice cores are still not fully understood. Here we present a new multiproxy data set of sea surface temperatures (SST), dust and iron supply, and marine export productivity, from the marine sediment core PS2489-2/ODP Site 1090 located in the subantarctic Atlantic, that allow us to evaluate various hypotheses on the role of the Southern Ocean (SO) in modulating atmospheric CO 2 concentrations back to 1.1 Ma. We show that Antarctic atmospheric temperatures are closely linked to changes in SO surface temperatures over the last 800 ka and use this to synchronize the timescales of our marine and the European Project for Ice Coring in Antarctica (EPICA) Dome C (EDC) records. The close correlation observed between iron inputs and marine export production over the entire interval implies that the process of iron fertilization of marine biota has been a recurrent process operating in the subantarctic region over the G/IG cycles of the last 1.1 Ma. However, our data suggest that marine productivity can only explain a fraction of atmospheric CO 2 changes (up to around 40–50 ppmv), occurring at glacial maxima in each glacial stage. In this sense, the good correlation of our SST record to the EDC temperature reconstruction suggests that the initial glacial CO 2 decrease, as well as the change in the amplitude of the CO 2 cycles observed around 400 ka, was most likely driven by physical processes, possibly related to changes in Antarctic sea ice extent, surface water stratification, and westerly winds position. Citation: Martı´nez-Garcia, A., A. Rosell-Mele´, W. Geibert, R. Gersonde, P. Masque´, V. Gaspari, and C. Barbante (2009), Links between iron supply, marine productivity, sea surface temperature, and CO 2 over the last 1.1 Ma, Paleoceanography,24, PA1207, doi:10.1029/2008PA001657. 1. Introduction [2] The causes of the glacial/interglacial (G/IG) variations in atmospheric CO 2 concentrations observed in the Antarctic ice cores [Luthi et al., 2008; Petit et al., 1999; Siegenthaler et al., 2005] are still under debate. It is likely that the full 80–100 ppmv range of fluctuations in atmospheric CO 2 can only be successfully explained by a combination of physical and biogeochemical mechanisms that are involved in the regulation of the oceanic carbon reservoir [Abelmann et al., 2006; Francois et al., 1997; Kohler et al., 2005; Sigman and Boyle, 2000; Sigman et al., 2004; Stephens and Keeling, 2000; Toggweiler et al., 2006]. [3] The process of iron fertilization of marine biota [Martin, 1990] has received significant attention in recent years, both as a driver of CO 2 during G/IG cycles [Kohfeld et al., 2005; Kohler et al., 2005; Watson et al., 2000] and in the context of mitigation strategies to counteract anthropogenic CO 2 emissions [Buesseler and Boyd, 2003; Chisholm et al., 2001, 2002; Johnson and Karl, 2002]. According to the iron hypothesis [Martin, 1990], an increase in the atmospheric supply of iron by dust during glacial periods, may have stimulated marine productivity in the high-nutrient low-chlorophyll (HNLC) regions (mainly the Southern Ocean, and the North and Equatorial Pacific), contributing to the reduction of atmospheric CO 2 concentrations. The effect of iron on marine ecosystem structure and productivity has been proven by a series of short-term in situ iron enrichment experiments, but also by observations of phytoplankton blooms induced by natural iron fertilization [Blain et al., 2007; Boyd et al., 2007]. While the efficacy of artificial iron experiments to sequester organic carbon to the deep ocean is still under controversial discussion [Buesseler et al., 2008], the study of natural iron fertilization results in a significant increase in carbon export with increasing iron supply [Blain et al., 2007]. PaleoceanoPALEOCEANOGRAPHY, VOL. 24, PA1207, doi:10.1029/2008PA001657, 2009 1 Institut de Cie`ncia i Tecnologia Ambientals, Universitat Auto`noma de Barcelona, Bellaterra, Catalonia, Spain. 2 Institucio´ Catalana de Recerca i Estudis Avanc¸ats, Barcelona, Catalonia, Spain. 3 School of Geosciences, University of Edinburgh, Edinburgh, UK. 4 Dunstaffnage Marine Laboratory, Scottish Association for Marine Science, Oban, UK. 5 Formerly at the Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany. 6 Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany. 7 Institute for the Dynamics of Environmental Processes, CNR, Venice, Italy. 8 Department of Environmental Sciences, University Ca’Foscari of Venice, Venice, Italy. Copyright 2009 by the American Geophysical Union. 0883-8305/09/2008PA001657 PA1207 1of14 graphic and model results indicate that increased iron availability could explain up to one half of the observed CO 2 drawdown in the last glacial period [Gaspari et al., 2006; Kohfeld et al., 2005; Watson et al., 2000]. [4] Recent modeling studies have shown that the full G/IG atmospheric CO 2 variability could only be explained by considering several physical processes driven by the complex interaction among sea ice cover, surface water stratification and the position of the westerly winds around Antarctica [Francois et al., 1997; Kohler et al., 2005; Sigman et al., 2004; Stephens and Keeling, 2000; Toggweiler et al., 2006]. According to this view, during glacial stages cold temperatures promoted an expansion of the Antarctic sea ice cover, inducing stratification of the polar ocean, limiting ocean ventilation, and allowing more carbon to be trapped in the deep ocean [Francois et al., 1997; Sigman and Boyle, 2000; Stephens and Keeling, 2000]. The northward migration of the westerly winds associated with cold glacial temperatures acted as a positive feedback, preventing the upwelling of CO 2 -rich deep waters around Antarctica, and contributing further to the isolation of the deep ocean from the atmosphere that kept atmospheric CO 2 concentrations low during glacial stages [Toggweiler, 1999; Toggweiler et al., 2006; Toggweiler and Russell, 2008]. [5] Understanding the interplay between these mechanisms through time is thus of crucial importance to gauge their effect on atmospheric CO 2 . However, little is known about their evolution beyond the last two glacial stages. The paleoclimatic reconstruction from the Antarctic ice cores generated by the European Project for Ice Coring in Antarctica (EPICA) community provided a unique record of atmospheric CO 2 concentrations [Luthi et al., 2008; Petit et al., 1999; Siegenthaler et al., 2005] , and also the opportunity to assess the role of iron supply, sea ice extent and wind intensity on the marine carbon cycle over the last eight glacial cycles [Wolff et al., 2006]. However, ice core records only allow indirect inference of these processes in the marine realm, and it is unlikely that they can be extended beyond their current time span in the near future. [6] Here we present independent estimates of iron and dust supply, marine productivity and sea surface temperature (SST) over the last 1.1 Ma from a deep-sea sediment record (PS2489-2/ODP Site 1090) located in the subantarctic South Atlantic (Figure 1). The region studied is particularly influential for the marine carbon reservoir through changes in westerly winds position [Toggweiler et al., 2006] and iron fertilization of marine biota [Brovkin et al., 2007; Kohfeld et al., 2005]. Moreover, SST changes at this site are strongly influenced by the movements of the isotherms related to the Antarctic Circumpolar Current (ACC) frontal system which, in fact, determine the extension of the Antarctic sea ice cover during the G/IG cycles through the Pleistocene [Gersonde et al., 1999]. We discuss the marine data in combination with a new high-resolution record of terrestrial iron supply from the EPICA Dome C (EDC) ice cores. At the marine site a combination of organic and inorganic proxies allows us to quantify iron and dust fluxes, as well as their effect on marine productivity, in the same sedimentary record. In this sense, the data set represents a marine counterpart of the EDC record over the last 800 ka, and provides new information on past changes in SST, dust and iron supply and marine productivity back to 1.1 Ma, allowing us to assess the role of marine processes in modulating atmospheric CO 2 concentrations through time. 2. Material and Methods 2.1. Site Location and Core Material (PS2489-2/ODP Site 1090) [7] ODP Site 1090 (42°54.8 0 S, 8°53.9 0 E) was recovered during ODP Leg 177 in the central part of the Subantarctic Zone at 3700 m water depth (Figure 1). In order to obtain a continuous record of the Pleistocene, samples from the nearby core PS2489-2 (42°52.4 0 S, 8°58.4 0 E) were analyzed for the interval from 0 to 500 ka, following the approach described by Becquey and Gersonde [2002]. Sediment cores were sampled at a resolution of 1–5 ka for core PS2489-2 and 2 ka for ODP Site 1090. The interval of overlap of the two cores is indicated in Figure 2 and shown in detail in the online Auxiliary Material. 1 No significant differences were found in SST, biomarkers concentrations and MAR in this interval between the two cores (see Figure S1 of the Auxiliary Material). The composite record is referred in the text as site PS2489-2/ODP1090. 2.2. Age Model [8] The initial age model for PS2489-2 [Becquey and Gersonde, 2003] and ODP Site 1090 [Venz and Hodell, 2002] was generated by benthic oxygen isotopes correlation, and it is used in Figure 2. In Figures 3–7 we use a new age model modified by graphic correlation of our alkenonebased SST to the ice core temperature reconstruction from the EPICA project [Jouzel et al., 2007], using the new EDC3 chronology [Parrenin et al., 2007] and the software Analyseries [Paillard et al., 1996]. This allows for direct comparison of the continental and marine records in the same timescale. Nonetheless, the correlation of the SST and the atmospheric temperature from EDC is good before this adjustment of the age model, as evidenced by the good agreement between the d 18 O of PS2489-2/ODP1090 and the Lisieky and Raymo (LR) stack (Figure 2a). Depth/age pointers for site PS2489-2/ODP1090 obtained after the correlation of the two records are available in Table S1 of the online Auxiliary Material. 2.3. Biomarkers Analysis [9] The method employed for biomarkers analysis has been described in detail elsewhere [Kornilova and RosellMele, 2003; McClymont et al., 2007]. Briefly, sediment samples were freeze-dried, homogenized, and 1–5 g of sediment were microwave extracted. Organic extracts were analyzed using a Thermo Trace gas chromatogram fitted with a flame ionization detector, in splitless injection mode, using helium as carrier gas (1.5 ml/min constant flux). Chromatographic separation of the organic compounds was achieved using an Agilent HP-1 capillary column of 60 m length, 0.25 mm internal diameter, and 0.25 mm film thickness, fitted to a 5 m precolumn. The oven temperature 1 Auxiliary materials are available in the HTML. doi:10.1029/ 2008PA001657. PA1207 MARTI ´NEZ-GARCIA ET AL.: IRON, PRODUCTIVITY, AND SST OVER 1.1 MA 2of14 PA1207 wasprogrammedtobeheldat80°Cfor1min,then increased at 20°C/min to 120°C, at 6°C/min until 320°C, and held for 20 min. The identification of the different compounds was achieved through comparison of the chromatographic relative retention times of the target compounds with standards. Several selected samples were analyzed by mass spectrometry to confirm peak identities and the absence of coeluting peaks. [10] To estimate SST the U K37 paleotemperature index [Brassell et al., 1986; Prahl and Wakeham, 1987] is used in preference to U K37 0 in this study as it has been shown to be better correlated to annual mean SST in high latitudes [Bard et al., 2000; Bendle and Rosell-Mele, 2004; Rosell-Mele et al., 1995; Rosell-Mele, 1998]. The reproducibility of the procedure was evaluated using a homogeneous sediment standard, extracted with every batch of 14 samples. The relative analytical errors were below 0.5°C in SST estimates and below 10% in the determination of n-alkanes and alkenones concentration, which is within the range of the analytical error of the method [Rosell-Mele et al., 2001]. 2.4. Multielemental Analysis [11] Fe, Al, U, 232 Th, U, and Re concentrations were determined on 50 mg of freeze-dried sediment, digested in a pressure-assisted microwave system using 3 ml of subboiling distilled HNO 3 , 2 ml of suprapur 1 HCl and 0.5 ml of suprapur 1 HF, together with the isotopic spikes for isotope dilution measurement of U and Th (see section 2.5). The sediment and acid mixture were placed in microwave vessels and kept closed at 205°C during 40 min. Afterward, samples were taken to dryness by gentle heating in the microwave using an evaporation accessory connected to a vacuum pump. The near dry samples were redissolved in 5 ml HNO 3 and heated to 160°C. After a volumetric dilution to 50 ml, a subsample of 5 ml together with Rh as an internal standard was further diluted to 50 ml for the Figure 1. Location of Site PS2489-2/ODP1090 and European Project for Ice Coring in Antarctica (EPICA) Dome C ice record. Solid lines indicate the present-day position of the different oceanic fronts according to Belkin and Gordon [1996]. Dashed blue lines correspond to modern sea ice boundaries according to Comiso [2003]. Dashed gray line represents Last Glacial Maximum (LGM) winter sea ice edge reconstruction according to Gersonde et al. [2005]. STF, Subtropical Front; SAF, Subantarctic Front; PF, Polar Front; WSI, Winter Sea Ice; SSI, Summer Sea Ice; WSILGM , Winter Sea Ice during the LGM. PA1207 MARTI ´NEZ-GARCIA ET AL.: IRON, PRODUCTIVITY, AND SST OVER 1.1 MA 3of14 PA1207 Figure 2. Organic and inorganic tracers concentration at Site PS2489-2/ODP1090. (a) Lisiecki and Raymo (LR) d 18 O global stack (blue) [Lisiecki and Raymo, 2005] and PS2489-2/ODP1090 d 18 O (gray) [Becquey and Gersonde, 2003; Venz and Hodell, 2002]. Marine Isotope Stages (MIS) are shown for reference. (b) Alkenone sea surface temperature (SST). (c) Long-chain odd carbon-numbered n-alkanes (C 23 – 33 ) concentration (blue) and iron concentration (red). (d) Al (brown) and 232 Th (black) concentration. (e) Ice rafted debris IRD (black) [Becquey and Gersonde, 2002] and percentage of lithogenic material (magenta). (f) C 37 alkenones concentration (green) and percentage of total organic carbon (TOC) (black) [Diekmann and Kuhn, 2002]. (g) Re (blue) and authigenic U (red) concentrations. Shaded areas highlight high-productivity intervals when alkenones concentration and TOC start to increase from the interglacial value. Black and blue lines on top of the Figure 2 show the intervals covered by PS2489-2 and ODP Site 1090 samples, respectively. Age model according to Venz and Hodell [2002]. PA1207 MARTI ´NEZ-GARCIA ET AL.: IRON, PRODUCTIVITY, AND SST OVER 1.1 MA 4of14 PA1207 multielement analysis by Inductively Coupled Plasma SectorField Mass Spectrometry (ICP-SFMS, Element2, Thermo Scientific). Sensitivity was increased using an APEX Q desolvation system (typically about 2,000,000 cps/ppb for U at a nominal flow rate of 100 mL sample @ 1275 W plasma power). All calibrations were done with dilutions of certified standard solutions. External reproducibility was evaluated using the NIST standard reference material 2702 (inorganics in marine sediment), except for Re. With each batch of samples, two procedural blanks were run. Abundant elements (Al and Fe) were analyzed in high resolution and detected in the ‘‘analog’’ counting mode. The remaining elements reported here were measured in low-resolution mode, and detected by ion counting (Re) or in the automatically cross-calibrated ‘‘both’’ mode (analog or ion counting, depending on count rate). Average relative errors for Fe and Al were 1.8 and 2.1% (1s), respectively. External reproducibility for Fe in NIST 2702 was 5.6% and, due to very high concentrations in the reference material, only 15% for Al. The reported concentrations for uranium and thorium samples younger than 330 ka were obtained by isotope dilution (see section 2.5). 2.5. Thorium and Uranium Isotopes Analysis [12] The remaining volume of the full digested solution was used for the measurement of uranium and thorium isotopes by isotope dilution (only samples within the interval 0–330 ka). 229 Th and 236 U spikes were added prior to the microwave digestion of the sample. The solution was treated with three successive steps of iron precipitations, which retain Th and U but remove most of the other metals. The precipitate was redissolved in HNO 3 (3 M). Afterward, Fe, Th, and U were separated using 2 ml columns filled with UTEVA 1 resin. Prior to column separation, 250 mLofa1M aluminum nitrate solution was added to the sample to prevent the effect of matrix components (mainly phosphates) on UTEVA 1 resin efficiency. Added aluminum can effectively tie up the phosphate preventing its interference with Th uptake by the resin [Horwitz et al., 1992]. The eluted Th and U fractions were heated to near dryness and redissolved in 8 M HNO 3 twice. Afterward, the two fractions were dissolved in 1 M HNO3 and analyzed by ICP-SFMS in low-resolution mode (1200 W plasma power, nominal flow rate 100 mL via APEX Q desolvation system). 229 Th and 230 Th were measured by ion counting, 232 Th in analog mode (automatically cross-calibrated with the counting mode). All U isotopes were measured in ion counting mode, except 238 U, which was calculated from 235 U. Adequate corrections were applied to account for tailing from 232 Th, as monitored by the masses 231.5 and 230.5. Mass bias of the instrument was monitored externally by a solution of U in natural isotopic composition, supplied by the Physikalisch-Technische Bundesanstalt Braunschweig (PTB). Dead time correction (25 ns) was applied. For 230 Th, all results with less than 100 counts per second or 1sratio error > 5% were discarded (typical count rates for Figure 3. Marine versus terrestrial dust and Fe fluxes over the last 330 ka. (a) EPICA Dome C Fe flux (black) and dust flux (red) [EPICA Community Members, 2004]. (b) PS2489-2/ODP1090 230 Th-normalized Fe flux (black) and Fe mass accumulation rate (MAR) (red). (c) PS2489-2/ODP1090 230 Th-normalized dust flux (black) and percent of iron in dust (red). The age model was obtained by correlation of marine and continental temperature profiles (see section 2.2). PA1207 MARTI ´NEZ-GARCIA ET AL.: IRON, PRODUCTIVITY, AND SST OVER 1.1 MA 5of14 PA1207 230 Th were 300–5000 cps for the samples, 10,000 cps for the standard). The external reproducibility of the method was evaluated by duplicate analysis of the UREM 11 standard reference material [Hansen and Ring, 1983], in each batch of 24 samples, and it was found to be overall 3% (1s). The mean 230 Th activity found in UREM 11 was 43.60±1.31 dpm/g (1s), n = 13. 2.6. Flux Calculations and Associated Errors [13] 230 Th ex was calculated according to Francois et al. [2004], using a 232 Th/ 238 U activity ratio of 0.4, and a 234 U/ 238 U activity ratio in the lithogenic end-member of 0.9. In absence of complicating factors such as large postdepositional sediment redistribution or sediment inputs from shallower depths, 230 Th ex can be readily converted into preserved vertical mass fluxes of a specific sedimentary compound [Francois et al., 2004; Frank et al., 2000; Geibert et al., 2005]. Taking into account some potential variability of the lithogenic 232 Th signal (7 ppmv– 13 ppmv), analytical errors in some 230 Th ex0 of up to 35%, as well as potential deviations from constant vertical 230 Th flux at this location, we are confident that actual lithogenic fluxes are within 50% of the reported values for the 230 Th-normalized data (to 330 ka). Beyond this age, 230 Th ex is not applicable owing to 230 Th decay and the increasing uncertainty of the method (see Figure S2 of the Auxiliary Material). 2.7. Fe Determination in EPICA Dome C Ice Cores [14] As the ice cores are often contaminated for various metals on the outside due to the drilling fluid and core handling, each 5-cm-long section of an ice core was decontaminated by three repeated washings in ultrapure Milli-Q water until 60% of the original sample was melted off [Delmonte et al., 2002]. This decontamination procedure resulted as being a good compromise in terms of efficiency, with respect to the more strictly chiselling decontamination method for iron [Gabrielli et al., 2005]. [15] Dissolvable Fe concentrations were determined by means of Inductively Coupled Plasma Sector Field Mass Spectrometry, ICP-SFMS (Element2, Thermo Scientific), in melted samples at pH 1, after at least 24 h from acidification (HNO 3 Ultrapure, Romil, Cambridge, UK). Special care was given to resolve the interference of 40 Ar 16 Oon 56 Fe by taking advantage of the medium resolution capability (m/Dm = 4000) of the sector field mass spectrometer. An exhaustive description of working conditions and measurement parameters were previously reported elsewhere [Barbante et al., 1997; Planchon et al., 2001]. The external calibration curve method was used for the quantification of the metal, with concentrations in the standard solutions (ICUS-1616, Ultra Scientific, North Kingstown, USA) ranging from 5 10 4 to 50 ng g 1 . A typical precision of 15%, in terms of relative standard deviation, was extrapolated from the results obtained for selected samples only, Figure 4. Linear regression between the concentrations of some elements measured at Site PS2489-2/ ODP1090: (a) n-alkanes versus Fe, (b) alkenones versus Fe, (c) alkenones versus n-alkanes, and (d) n-alkanes versus 232 Th. PA1207 MARTI ´NEZ-GARCIA ET AL.: IRON, PRODUCTIVITY, AND SST OVER 1.1 MA 6of14 PA1207 because of the very low volume available for all the samples. The element concentrations were converted in depositional fluxes by multiplying the elemental concentration by the water equivalent accumulation data estimated by Parrenin et al. [2007]. 3. Results and Discussion 3.1. Dust and Iron Supply to the Subantarctic Atlantic [16] Lithogenic fluxes through time are derived from the combined analysis of long chain odd-numbered n-alkanes, three inorganic tracers for lithogenic material (Al, Fe and 232 Th), and 230 Th ex as an indicator of vertical mass flux. In deep-sea records, redistribution of bottom sediments can significantly alter vertical flux estimates. The 230 Th normalization method accounts for this process, and is used to convert concentrations of individual sedimentary compounds to their vertical fluxes [Francois et al., 2004]. This enables us to determine vertically received lithogenic and iron fluxes at site PS2489-2/ODP1090 back to 330 ka. Beyond this age, 230 Th ex is not applicable owing to 230 Th decay and increasing uncertainty (see section 2.6). Our data indicate relatively low sediment focusing in the record PS2489-2/ODP1090 during the last 330 ka (Figure 3). This contradicts the view that deep-ocean sediment recirculation is a significant source of iron to the SO sediments during glacial periods [Latimer et al., 2006; Latimer and Filippelli, 2007]. Although this may influence drift sites [Latimer and Filippelli, 2007], it seems clear that this is not the case in other areas of the SO [Kumar et al., 1995], such as that of PS2489-2/ODP1090. The close agreement between mass accumulation rates (MAR) and vertical fluxes in our record in the interval 0–330 ka, and their close correlation with EDC fluxes (Figure 3), justifies the assumption that MAR represents vertical fluxes in the older parts of the core. [17] The distribution of n-alkanes in our record exhibits a clear predominance of long-chain odd carbon-numbered n-alkanes (i.e., CPI 25– 35 values between 3 and 9). This is representative of inputs of leaf waxes from terrestrial plants [Eglinton and Hamilton, 1967], which are commonly found in the organic fraction of eolian dust over the Atlantic Ocean [Simoneit, 1977]. Other significant sources of n-alkanes, such as from ice rafted debris (IRD) from the Antarctic continent and/or from the Patagonian ice sheet [Hulton et al., 2002], are hence negligible as the geochemical signatures would correspond to mature organic material eroded by icebergs [Rashid and Grosjean, 2006; Rosell-Mele et al., 1997], and the n-alkanes distribution would present a nonlong-chain odd carbon-numbered predominance (CPI values around 1). Therefore, we conclude that the n-alkanes in our record most likely reflect changes in the input of windborne continental material from South American sources. [18] Al and Fe are elements associated with the lithogenic fraction of marine particles that provide independent estimates of the input of continental material [Calvert and Figure 5. (a) Lisiecki and Raymo (LR) d 18 O global stack (blue) [Lisiecki and Raymo, 2005] and n-alkanes concentration from Site PS2489-2/ODP1090 (magenta). MIS are shown for reference. (b) Temperature reconstruction from EPICA ice cores (black) [Jouzel et al., 2007] and alkenone-based SST from Site PS2489-2/ODP 1090 (red). (c) Atmospheric CO 2 concentration from the EPICA ice cores (blue) [Luthi et al., 2008; Petit et al., 1999; Siegenthaler et al., 2005] and alkenones concentration from Site PS2489-2/ ODP1090 (green). The age model was obtained by correlation of marine and continental temperature profiles (see section 2.2). PA1207 MARTI ´NEZ-GARCIA ET AL.: IRON, PRODUCTIVITY, AND SST OVER 1.1 MA 7of14 PA1207 Pedersen, 2007]. Moreover, 232 Th concentration can be used to assess quantitatively the fraction of lithogenic material in marine sediment cores (Figure 2e), as its concentration in lithogenic open ocean deposits is uniform at 10 ppm [Anderson et al., 2006; Sayles et al., 2001; Winckler et al., 2008]. The strong positive correlation observed between the concentrations and 230 Th corrected fluxes of inorganic tracers and n-alkanes over the entire record (e.g., Fe versus n-alkanes correlation, r 2 = 0.79), suggest similar sources and transport pathways (Figures 2 and 4). In this sense, the good agreement between the organic and inorganic tracers and the EDC dust and iron records, together with the results from 232 Th/ 230 Th analysis, imply that the supply of lithogenic material to our site is dominated by changes in the eolian input of terrigenous material through time. However, in some intervals additional sources (e.g., IRD) may have occasionally contributed to increase the supply of lithogenic material (Figure 2e), and hence of Fe [Raiswell et al., 2006; Smith et al., 2007; Walter et al., 2000]. The relative importance of the redistribution of lithogenic material by surface currents and intermediate waters, that could eventually return to the surface by upwelling [Blain et al., 2007], is difficult to evaluate. However, eolian supply is a more likely source of lithogenic material in the core site, as the potential chemical interactions that may have affected the organic and inorganic tracers during transport are bound to be less important during eolian transport than in the case of oceanic recirculation. Therefore, we conclude that an eolian source of lithogenic material (and hence of Fe) explains more simply the clear correlation observed between the n-alkanes and the inorganic tracers, however, in some intervals a contribution from other sources (e.g., IRD) cannot be totally discarded. [19] By considering that lithogenic material is supplied by wind, we can give a quantitative estimation of the flux of dust to the ocean over the last 330 ka (Figure 3c), providing a better characterization of South American dust flux. We observe a clear G/IG dust flux variability of around 1 g m 2 a 1 of dust (50 mg m 2 a 1 of iron) for interglacial periods, to around 4–5 g m 2 a 1 (200 mg m 2 a 1 of iron) for glacial stages. This is in good agreement with other Fe reconstructions in the region [Kumar et al., 1995], and confirms previous suggestions pointing to a 4 to fivefold increase in South American dust source strength during glacial stages [Kumar et al., 1995; Lambert et al., 2008]. This G/IG variability falls well within the Dirtmap inventory estimates for the source region [Kohfeld and Harrison, 2001] and represents a southwestern marine end-member of South American dust flux variability. In this sense, it is interesting to note that our glacial value is almost ten times Figure 6. Exponential regression curves between (a) n-alkanes and SST, (b) alkenones and SST, (c) n-alkanes and global benthic d 18 O[Lisiecki and Raymo, 2005], and (d) alkenones and EPICA atmospheric CO 2 [Luthi et al., 2008; Petit et al., 1999; Siegenthaler et al., 2005]. Figures 6a and 6b correspond to the regression of the two variables measured in the same samples of core PS2489-2/ ODP1090. In the case of Figures 6c and 6d, given the differences in sampling resolution of the records, the series have been linearly interpolated to 2 ka before the regression. Shaded gray area in Figure 6d indicates values above 230 ppmv of CO 2 . PA1207 MARTI ´NEZ-GARCIA ET AL.: IRON, PRODUCTIVITY, AND SST OVER 1.1 MA 8of14 PA1207 Figure 7. Comparison of the marine and terrestrial records over the last 1.1 Ma. (a) Temperature reconstruction from EPICA ice cores (black) [Jouzel et al., 2007] and alkenone-based SST from Site PS2489-2/ODP1090 (red). MIS are shown for reference. (b) Atmospheric CO 2 concentrations from the EPICA ice cores [Luthi et al., 2008; Petit et al., 1999; Siegenthaler et al., 2005]. Dashed line indicates the CO 2 level when productivity starts to increase above the average interglacial value. Filled area illustrates CO 2 concentrations below 230 ppmv. Glacial terminations are shown for reference. (c) EPICA Fe flux (blue) and Site PS2489-2/ODP1090 Fe flux (red). (d) EPICA insoluble dust (light brown) and Site PS2489-2/ODP1090 long-chain odd carbon-numbered n-alkanes (C 23– 33 ) mass accumulation rate (MAR) (blue). (e) Site PS2489-2/ODP1090 C 37 alkenones MAR (green) and TOC MAR [Diekmann and Kuhn, 2002] (black). Shaded areas highlight the high-productivity intervals when alkenones MAR are three times higher than the average interglacial value. The age model was obtained by correlation of marine and continental temperature profiles (see section 2.2). PA1207 MARTI ´NEZ-GARCIA ET AL.: IRON, PRODUCTIVITY, AND SST OVER 1.1 MA 9of14 PA1207