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Keywords:

  • Southern Ocean;
  • chlorophyll;
  • gross primary production;
  • net community production;
  • oxygen isotopes;
  • phytoplankton

Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. 5. Summary
  8. Acknowledgments
  9. References
  10. Supporting Information

[1] In connection with the Palmer LTER program, mixed layer water samples were collected during the cruise of the L.M. Gould in Jan., 2008 at 49 stations on a 20 × 100 km grid in the West Antarctica Peninsula (WAP) region of the Southern Ocean. In this study, [O2]/[Ar] ratios and the triple isotope composition of dissolved O2 were measured, and were used to estimate net community O2 production (NCP) and gross primary O2production (GPP), respectively. These estimates are further converted to carbon export production, primary production and the f-ratio. Our measurements give NCP ranging from −3 to 76 mmol O2 m−2 day−1 (−25 to 650 mg C m−2 day−1), and GPP from 40 to 220 mmol O2 m−2 day−1 (180 to 1010 mg C m−2 day−1). The O2 NCP/GPP ratios range from −0.04 to 0.43, corresponding to f-ratios of −0.08 to 0.83. NCP and the NCP/GPP ratio are highest in the northern coastal areas, and decrease to lower values toward the southern coastal area and the open ocean. The inshore-offshore gradient appears to be regulated primarily by iron availability, as supported by the positive correlation between NCP and Fv/Fm ratios (r2 = 0.22, p < 0.05). Mixed layer depth (MLD) is inversely correlated with NCP (r2 = 0.21, p < 0.002) and NCP/GPP (r2 = 0.21, p < 0.02), and highest NCP occurred in the fresh water lenses probably formed from melted coastal glaciers. These results suggest that export production and the f-ratio increase where water stratification is intensified by input of fresh meltwater, and that mixed layer stratification is the major factor regulating NCP in the inner-shelf and coastal regions. Along-shelf variability of phytoplankton community composition is highly correlated with NCP, i.e., NCP increases when the diatom-dominated community in the south transitions to the cryptophyte-dominated one in the north. A high correlation is also observed between NCP and the logarithm of the surface chlorophyll concentration (r2 = 0.72, p < 0.0001) , which makes it possible to estimate carbon export as a function of Chl a concentration in this region.

1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. 5. Summary
  8. Acknowledgments
  9. References
  10. Supporting Information

[2] Estimating export production, and understanding its controlling mechanisms, are essential for understanding the global cycles of carbon and other bioactive elements. Previous studies have indicated that export production and the export efficiency (the f-ratio, defined byEppley and Peterson [1979]), can be regulated by a wide range of properties, e.g., temperature [Laws et al., 2000], community or food web structure [Ducklow et al., 2001], light [Hannon et al., 2001] and availability of various nutrients [Pollard et al., 2009]. There have also been modeling studies that attempted to estimate export production from surface chlorophyll concentration and ancillary properties [Dunne et al., 2007; Hidalgo-Gonzalez and Alvarez-Borrego, 2004; Iverson et al., 2000; Laws et al., 2000]. Ultimately controls on export production need to be examined in a variety of ecosystems spanning a range of forcing properties.

[3] One site of particular interest is the west Antarctica Peninsula (WAP) region of the Southern Ocean, which has been intensively studied in the past two decades by the Palmer Long-Term Ecological Research Project (LTER,Ducklow et al. 2007). This polar region consists of a highly productive coastal and continental shelf zone (CCSZ), a relatively productive seasonal ice zone, and a less productive permanently open ocean zone [Tréguer and Jacques, 1992; Ducklow et al., 2007]. It thus is characterized by large seasonal and spatial variability of primary and export production. This region has been surveyed by LTER January cruises since 1993 at a resolution of 100 × 20 km, and a large data set of hydrological and ecological properties have been collected during these cruises [Ducklow et al., 2007]. The observed spatial variability of primary production (PP) is thought to be regulated mainly by the stability of the water column and the nutrient concentrations. Vernet et al. [2008]found that PP is enhanced where the water column is strongly stratified as a result of fresh water input from sea-ice and the melting of coastal glaciers. Higher PP was also found where nutrient-enriched upper circumpolar deep water (UCDW) intruded into the inner shelf and mixed up into the surface water there [Prézelin et al., 2000]. Although export production has been measured in the region by a moored sediment trap [Ducklow et al., 2008] and by drifting cylindrical traps and the 234Th method [Buesseler et al., 2010], no studies have measured export production at the same high spatial resolution as other environmental properties.

[4] In samples from the summer cruise in 2008, we made estimates of export production and the f-ratio by utilizing properties of dissolved O2 in mixed layer water samples collected at each grid station. The isotopic composition of dissolved O2 in the mixed layer gives a measure of the fraction of dissolved O2 derived in situ from photosynthesis [Luz and Barkan, 2000]. The O2 supersaturation in excess of argon (Ar) supersaturation reflects biological supersaturation of O2 [Reuer et al., 2007]. These anomalies with respect to air saturation values are maintained by gross primary O2 productivity (GPP) and respiration (R), and reflect the rate of GPP and net community O2 productivity (NCP). GPP can be calculated from the isotope anomaly and gas transfer velocity (estimated from a wind speed parameterization). The net flux of biological O2 to the atmosphere, calculated from the O2 supersaturation in excess of Ar and the gas exchange velocity, equals NCP. Since storage of organic carbon in the mixed layer is modest with respect to NCP [Ducklow et al., 2007], NCP approximates carbon export production [Falkowski et al., 2003].

[5] Our work thus gives new high resolution maps of export production and the f-ratio. In this paper, we report these results, and analyze the correlation of the productivity with other environmental and ecological properties, e.g., sea surface temperature (SST), mixed layer depth (MLD), nutrients, and phytoplankton community composition. Through these relationships, we examine the major factors regulating export production in the region, and test hypotheses about the mechanisms through which environmental factors control carbon export.

2. Methods

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. 5. Summary
  8. Acknowledgments
  9. References
  10. Supporting Information

2.1. Sampling Strategy and Hydrological Data

[6] The Palmer LTER sampling grid stretches 900 km alongshore, with 10 transect lines (No. 000-900), 100 km apart, perpendicular to the WAP. Each of these transect lines has about 10 stations which are spaced 20 km apart (Waters and Smith, 1992). The 2008 cruise spanned five transect lines (No. 200-600, seeFigure 1) and covered about 50 stations in the grid from Jan. 6–29, climatologically a period of high carbon flux in the annual cycles according to the long-term sediment trap data [Ducklow et al., 2008]. A pair of surface samples for analysis of dissolved O2properties, together with samples for macro-nutrient profiles, pigment profiles, etc., were collected at each station. Conductivity-temperature-depth (CTD) profiles and oxygen concentration profiles were measured at the stations, and temperature, salinity, oxygen, and variable fluorescence (Fv/Fm) were measured underway. Mixed layer depth was taken as the depth where the absolute difference of potential temperature to the surface (Δθ = |θ0 − θd|) = 0.2°C [Dong et al., 2008]. Euphotic zone depth (Zeu) was determined where PAR was 1% of the surface value.

image

Figure 1. Location of the West Antarctica Peninsula and sampling grid of the cruise Lawrence M. Gould in Jan. 2008. The black dashed line delimits the sampling area, and the black filled dots indicate the stations where samples were collected for analysis of the oxygen properties. The centers of the colorer open circles indicate the locations where variable fluorescence (Fv/Fm) were measured and selected based on the criterion described in the text (section 3.3). The colors and sizes of these circles reflect the magnitude of the Fv/Fm ratios.

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2.2. O2 NCP and GPP

[7] A pair of mixed layer water samples, 150 to 350 ml in volume, were collected and stored in pre-evacuated and pre-poisoned flasks. The dissolved O2/Ar ratios and the triple oxygen isotopic compositions (16O/17O/18O) were measured on a Finnigan Delta Plus XP or a Finnigan Mat 252 Dual Inlet Mass Spectrometer. The detailed methods for sample collection and analysis are summarized by Hendricks et al. [2004] and Reuer et al. [2007]. Using the gas exchange rate parameterized from wind speed, the O2/Ar ratios are converted to NCP and the triple oxygen isotopic compositions are converted to GPP, following the approach described by Quay et al. [1993], Luz and Barkan [2002], and Hendricks et al. [2004], using the numerical method of Reuer et al. [2007]. These methods assume a constant MLD and productivity over the period of about 1 week prior to the sample collection, and they assume that there is no significant vertical exchange of water across the bottom of the mixed layer. They involve wind speeds and the gas transfer velocity parameterized in terms of wind speed [Reuer et al., 2007; Sweeney et al., 2007].

2.2.1. Δ(O2/Ar) and NCP

[8] O2 and Ar have similar solubilities. While Ar is conservative with respect to biological processes, O2 saturation is altered by photosynthesis and respiration. Thus, Ar can correct for physical saturation due to warming, bubble entrainment, mixing and atmospheric pressure variations. The deviation of the O2/Ar ratio from its saturation concentration ratio is defined as:

  • display math

This term represents the biological O2 supersaturation. NCP is then calculated as:

  • display math

where ρ is the density of the surface water, and k is the gas exchange rate. NCP, in units of mmol O2 m−2 day−1, stands for daily averaged the air-sea flux of O2 over a period of up to several weeks [Reuer et al., 2007], and can be converted to carbon NCP using O2/C = 1.4 [Laws, 1991].

2.2.2. Triple Oxygen Isotopic Composition and GPP

[9] The isotopic composition of dissolved oxygen is reported in the δ notation, but in units of per meg (part per million) rather than per mil, i.e.,

  • display math

where denotes for the heavier isotopes, i.e., 17O and 18O. The standard used here is atmospheric oxygen. δ17O and δ18O of dissolved O2vary with several processes, i.e., photosynthesis, respiration and gas exchange. The degree of mass-independent fractionation is:

  • display math

where 0.518 is the coefficient associated with the mass-dependent fractionation [Luz and Barkan, 2009]. Dark respiration introduces mass-dependent fractionation of17O and 18O in a steady state so that 17Δ is not altered by respiration [Angert et al., 2003]. By contrast, photosynthesis adds O2 with 17Δ of 249 per meg [Luz and Barkan, 2000], which is identical to the oxygen isotopic composition of seawater. Gas exchange shifts 17Δ toward 8 per meg [Reuer et al., 2007], the value in equilibrium with air O2 (which by definition has 17Δ = 0). Thus, 17Δ reflects the fraction of dissolved oxygen produced by photosynthesis. 17Δ = +8 per meg when all O2 is dissolved atmospheric O2, and +249 per meg when all dissolved O2 comes from photosynthesis. In a system at steady state, GPP can be estimated by the approximation given by Hendricks et al. [2004]:

  • display math

where 17ΔSat = 8 per meg, 17ΔW = 249 per meg and 17ΔDiss is the measured value of a sample.

[10] O2 GPP can be converted to 14C PP, using the ratio of gross O2 production/14C PP of 2.7 diagnosed by Marra [2002]. At steady state, and assuming the production rate of dissolved organic carbon (DOC) is much smaller than NCP, carbon NCP is approximately equal to particulate carbon export production, and O2 NCP/GPP is about half of the f-ratio defined byEppley and Peterson [1979].

2.2.3. Gas Exchange Rate (k)

[11] Daily 10 m wind speeds from the NCEP/NCAR reanalysis [Kalnay et al., 1996] are used to calculate the gas transfer velocity (piston velocity) following the formula of Sweeney et al. [2007]. As the O2 concentration of the samples is dependent on the gas exchange history of the surface water, a weighting technique is used to account for the variability of wind speed and gas transfer velocity during 60 days prior to the date the samples were collected (see Reuer et al. [2007] for details). Therefore, the k values calculated from this method represent the weighted average of the influence of wind speeds in the past two months, weighted heavily to the week or so before samples were collected.

[12] Wind speeds were measured on the cruise with an R.M. Young sensor on the vessel, and were converted to true wind speeds. A systematic bias of NCEP/NCAR wind speed from the daily average of the true wind speed is observed (Figure S1 in the auxiliary material). Linear regression analysis gives: true wind speed (m s−1) = 1.0 × NCEP/NCAR wind speed + 2.8 (m s−1), r2 = 0.63, n = 39.

[13] The bias is also observed by comparing daily average wind speed measured at Palmer Station and the NCEP/NCAR wind speed from 2000–2010 (Figure S1), with measured wind speed (m s−1) = NCEP/NCAR wind speed (m s−1) + 3, r2 = 0.28, n = 3731.

[14] The bias observed in these comparisons indicates that NCEP/NCAR reanalysis tends to underestimate wind speed consistently in the study region. The regression equation relating wind speeds measured on board the ship to NCEP/NCAR values is thus used to correct for the wind speed.

2.3. Nutrients, Chlorophyll, and Other Plant Pigments

[15] Samples for dissolved inorganic nutrients (nitrate, phosphate and silicate) were analyzed following in-line filtration through GF/F filters and frozen storage (−20°C). Nutrient concentrations were determined by standard flow infection analysis protocols using a Lachat QuikChem 8000 (Lachat Instruments Div., Zellweger Analytics, Inc. Loveland, CO).

[16] Concentration of chlorophyll a was estimated fluorometrically. Seawater aliquots were filtered though Millipore HA filters, the filters extracted in 90% acetone and stored frozen for 24 h [Smith et al., 1981]. Concentrations of pigments in acetone were measured using a digital Turner Designs fluorometer that was calibrated with pure Chl a dissolved in 90% acetone.

[17] Phytoplankton pigments were determined using High-Performance Liquid Chromatography (HPLC) as follows. Filters were extracted in 90% grade acetone and ultrasonicated while held in a −20°C bench-top cooler for 10 seconds, stored at −80°C for 24 hours and pre-filtered through a 0.45 μM Whatman nylon Pradisk filters before injection. Samples were separated using an Agilent Technologies (Hewlett-Packard) 1100 Series HLC system, equipped with G1314A variable wavelength (fixed at 440 nm), G1315A diode array (scanning 330–800 nm) and G1321A fluorescence (440 nm excitation, 650 nm emission) detectors. Solvents were degassed using a vacuum degasser and column temperature was maintained at 25°C with a G1316A column thermostat. Agilent Technologies ChemStation for LC 3D software was used for system control and data collection and peaks were quantified at 440 nmM on the VWD. Further details are given byKozlowski [2008].

2.4. Phytoplankton Community Structure

[18] Using the CHEMTAX program [Mackey et al., 1996], average accessory pigment concentrations in the mixed layer determined by HPLC were used as chemotaxonomic markers to reconstruct the phytoplankton community composition in the mixed layer of the WAP region. With an initial matrix of accessory pigments to Chl a ratios in the major phytoplankton groups, CHEMTAX uses factor analysis and a steepest descent algorithm to optimize the pigment ratios, and calculates the contribution of each group to total Chl a [Mackey et al., 1996, 1998]. To run CHEMTAX program in this study, we used a localized “wAP” method that has been validated by long-term HPLC data set (1995–2007) collected in the WAP region [Kozlowski et al., 2011]. As described by Kozlowski et al. [2011, Table 5], this method uses a initial pigment ratio matrix that includes 6 accessory pigments (chlorophyll c2, fucoxanthin, 19′ butanoyloxyfucoxanthin , 19′ hexanoyloxyfucoxanthin, alloxanthin andchlorophyll b) in 5 representative phytoplankton groups in the study region (diatoms, cryptophytes, type 4 haptophytes, mixed flagellates, and prasinophytes). The configuration parameters for the CHEMTAX run were identical as listed by Kozlowski et al. [2011]. In particular, the ratio limits for the run was set to 500, which allowed the program to modify the pigment ratio (r) from r/6 to 6r.

2.5. Sea Ice Extent

[19] The 25 × 25 km sea ice concentration data, generated from the Nimbus-7 SSMR and DMSP SSM/I Passive Microwave [Fetterer et al., 2007], were retrieved from the National Snow and Ice Data Center, University of Colorado, Boulder Colorado. Following the method described by Stammerjohn et al. [2008], these data are used to determine the time that a station was free of sea ice before it was occupied on the cruise.

3. Results

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. 5. Summary
  8. Acknowledgments
  9. References
  10. Supporting Information

[20] Major results of this study are summarized in Table S1.

3.1. Hydrography

[21] The hydrographic structure of the upper water column in Jan. 2008 was similar to that described by Klinck et al. [2004] and Smith et al. [1999]. Generally, the surface water had a potential temperature (θ) > 0°C and salinity <34 per mil. This layer represented the summer Antarctic Surface Water (AASW). The low salinity of this water reflects the influence of sea-ice and coastal glacier meltwater [Dierssen et al., 2002; Smith et al., 1999; Vernet et al., 2008]. A 50–100 m thick layer with higher salinity (33.8 to 34.2) and lower θ (0 to −1.5°C) was present below the summer AASW . The coldest (Tmin) water was the remnant of winter water(WW) that had been cooled to the freezing point during the previous winter. Its core usually lay around 80–100 m. Below 100 m, the cold WW transitioned to the warmer and saltier UCDW intrusion, with 0.5 < θ < 2°C and salinity >34.6 per mil [Prézelin et al., 2000].

[22] The absence of core WW deserves at some places a closer examination. In the northern coastal region, the potential temperature at the depth of the temperature minimum ranged from −0.8 to 0.3°C, much higher than the upper limit of WW temperature (−1.2°C) suggested by Martinson et al. [2008] (Figure 2a). Salinity at the Tmin layer in this region was >34.2, also greater than the upper limit (34.13) given by Martinson et al. [2008] (Figure 2b). The high temperature and salinity observed at the Tmin layer in this region suggest intense vertical mixing with both surface water above and modified UCDW below, which may have been brought to the WW depth by upwelling [Smith et al., 1999; Prézelin et al., 2000].

image

Figure 2. (a) Potential temperature and (b) salinity at the depth of temperature minimum (Tmin), (c) sea surface temperature (SST), (d) sea surface salinity (SSS), (e) mixed layer depth (MLD), and (f) the ratio of integrated PAR in the mixed layer to that in the euphotic zone for Jan. 2008 in the Palmer LTER grid. The dark line shows the location of shelf break, and the dashed line shows the western boundary of the coastal area. Area between the two lines is referred as shelf area in the text. Black dots indicate locations where samples were collected. Grid Station 0 (km) is in the vicinity of the inshore boundary of the study region shown in Figure 1.

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[23] Sea surface temperature (SST) in the coastal and inner shelf areas was high (>1.5°C) compared with that offshore (Figure 2c). In contrast, sea surface salinity (SSS) showed less variability in most of the region, except to the southwest of the Anvers Island where salinity was extremely low (Figure 2d).

[24] Upper water column stratification was strengthened by the input of fresh sea-ice and coastal glacier meltwater. The mixed layer in the WAP region was generally shallow, with a mean depth for all stations of 24 ± 10 m (Figure 2e). Hydrographic data along lines 300–600 indicated a MLD 20–30 m deep, with the bottom of the mixed layer tilting slightly downward from onshore to offshore. In places where there was a warmer and fresher water lens, the water column was more strongly stratified and the MLD was shallower than 10 m. Along line 200, where there was no fresh water patch in the surface, the mixed layer was deep (∼50 m) in the nearshore area, and shoaled to ∼35 m toward offshore. MLDs along this line were the deepest in the study region.

[25] The depth of the euphotic zone (zeu) ranges from 25–94 m over the region, with a mean of 59 ± 16 m. The euphotic layer was thinnest in the northern shelf and coastal regions (line 200–300), and thickened toward the southern region and the offshore region. zeu exceeded the MLD over the region, with the mean zeu-MLD = 37 ± 16 m. As shown inFigure 2f, absorbed PAR in the mixed layer (PARMLD) accounts for 51–91% (mean = 80 ± 11%) of the total PAR in the euphotic zone (PAReu). The distribution of PARMLD/PAReu indicates that our estimates of NCP and GPP represent a major fraction of euphotic zone productivity over most of the study region.

3.2. Nutrients

3.2.1. Surface Nutrient Concentration

[26] Concentrations of macro-nutrients in the surface water were generally high. The phosphate concentrations ranged from 0.6 to 2.2 mmol m−3, with a mean of 1.5 ± 0.2 mmol m−3. Concentrations were higher offshore, and decreased to lower values in coastal areas (Figure S3a). Concentration less than 1 mmol m−3 occurred only in Marguerite Bay (inshore part of line 200), where PP and chlorophyll are usually high in austral summer [Ducklow et al., 2007]. By contrast, silicate concentrations were higher inshore, with peak values of 87 mmol m−3, and decreased toward the open sea to as low as 27 mmol m−3 (Figure S3b). Although large variability existed, the range of surface nutrient concentrations indicate that macro-nutrients are unlikely to limit productivity in this region.

3.2.2. Integrated Nutrient Uptake

[27] Following the methods of Serebrennikova and Fanning [2004], depth-integrated drawdown of macro-nutrients were calculated as the sum of decrease of nutrient concentration above the core of the remnant of winter water (WW), i.e., the depth of minimum temperature. This method assumes that surface water down to 100–150 m was homogeneous in winter, and nutrient concentrations at the core of the WW have not varied significantly during the growth of phytoplankton in spring and summer [Klinck et al., 2004; Serebrennikova and Fanning, 2004].

[28] Phosphate drawdown (ΔP, ranging from 7 to 40 mmol m−2) in the shelf area had the highest mean (24 ± 6 mmol m−2), while the average ΔP in the coastal and the offshore areas were 20 ± 6 and 18 ± 8 mmol m−2, respectively. The largest ΔP occurred in the northern inner shelf and coastal areas (Figure S3c).

[29] Silicate drawdown (ΔSi) varied by nearly a factor of 9 from 190 to 1700 mmol m−2, considerably more than that of ΔP. ΔSi was higher in the open sea (with the mean of 730 ± 360 mmol m−2) and decreased toward the coast (with the mean of 630 ± 290 and 470 ± 280 mmol m−2, respectively, in the shelf and coastal areas). Thus, it showed a trend which was inverse to that of ΔP (Figure S3d).

3.3. Photosynthetic Competency (Fv/Fm)

[30] Iron concentrations in the WAP region have been reported only by Martin [1990], who measured iron concentrations (7.4 nmol kg−1) during late summer of 1989 in surface water of the Gerlache Strait east of Anvers Island. As an alternative, the photosynthetic competency (Fv/Fm) of Photosystem II (PSII) of the surface water phytoplankton was measured for Jan. 2008. The measured Fv/Fm varied from 0.26 to 0.56, with a mean of 0.39 ± 0.08 (n = 20). Strong diurnal signals were observed in most of the measurements, with peak values occurring in the dawn and strong depression of the ratios at noon as a result of intensive photo inhibition of the phytoplankton in surface water. To eliminate the imprint of diurnal signals on the spatial variations, we selected Fv/Fm within a limited range of photosynthetically active radiation (PAR). Our PAR window corresponds to the raw values of 0 to 200 mV measured by the PAR sensor (Figure S2). It encompasses the period from midnight to ∼4 a.m. local time when Fv/Fm ratios increased from the dark condition to ward the maximum values. An average value of these selected Fv/Fm ratios in one day is calculated and applied to stations occupied during hours of the measurement window. The calculated Fv/Fm decreased from inshore to offshore, with average values of 0.41 ± 0.03, 0.37 ± 0.1 and 0.30 ± 0.03 in the coastal, shelf and offshore areas, respectively (Figure 1). Fv/Fm in the shelf area decreased from north to south, with high values around 0.5 occurring about 20 km to the southwest of Anvers Island.

3.4. O2 Properties and Production

3.4.1. 17Δ and the O2 GPP

[31] Sample pairs from 26 stations on lines 200, 400 and 600 were analyzed concurrently for both 17Δ and Δ(O2/Ar), and samples from another 20 stations on line 300 and 500 were analyzed only for Δ(O2/Ar) (Figure 5a).

[32] The 17Δ ranged from 17 to 72 per meg, with a mean of 43 ± 15 per meg. The precision of the measurements is quantified by the agreement of measurements of a pair of samples on each station. In this study, the root mean square (RMS) deviation from the mean of the sample pairs was ±5 per meg, corresponding to the population standard deviation of ±7 per meg.

[33] The gas exchange coefficient (k) calculated from the wind speed was in the narrow range of 2.3 to 2.9 m day−1. Using these k values in equation (5) gives the GPP in this region from 40 to 220 mmol O2 m−2 day−1 (Figure 3a). According to the photosynthetic quotient given by Marra [2002], O2 GPP approximates 2.7 × 14C production. Therefore, our estimates of O2 GPP are equivalent to 14C productivity of 180–1010 mg C m−2 day−1.

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Figure 3. (a) Gross primary production (GPP), (b) net community production (NCP), and (c) NCP/GPP ratio for Jan. 2008 in the Palmer LTER grid. Note that there are no GPP and NCP/GPP data on line 300 and 500, and the interpolations used in Figures 3a and 3c are mainly intended to show the values and trends of GPP and NCP/GPP ratios on line 200, 400 and 600.

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[34] There was a clear cross-shelf trend of the GPP distribution. The average GPP was highest in the coastal area (180 ± 40 mmol O2 m−2 day−1, n = 3), high in the shelf (150 ± 50 mmol O2 m−2 day−1, n = 13), and much lower offshore (90 ± 40 mmol O2 m−2 day−1, n = 10). In the inner-shelf and coastal areas, GPP was similarly high in the southern and northern lines (200 and 600), while it was slightly lower in the central part (line 400).

3.4.2. Δ(O2/Ar) and the O2 NCP

[35] For all stations, Δ(O2/Ar) varied from −0.3 to +10.9 %. The mean Δ(O2/Ar) was 2.5 ± 2.4%. Δ(O2/Ar) was ≥0, within the measurement error, for all samples, indicating that mixed layer water in this region was dominantly autotrophic. The RMS deviation from the mean of duplicates was ±0.27%, and the population standard deviation is 0.37%. NCP calculated from these measurements and the k values ranged from −3 to 76 mmol O2 m−2 day−1 (Figure 3b), or −25 to 650 mg C m−2 day−1 when applying the O2 NCP:Carbon NCP stoichiometry of 1.4 given by Laws [1991].

[36] GPP explains 39% of the variance in NCP (Figure 5b). The sense of the relationship is as expected: NCP are higher where GPP is higher. However, while GPP decreased from the coastal to the open sea areas, the spatial variation of NCP was more complicated. NCP was highest on average in the shelf area (27 ± 15 mmol O2 m−2 day−1, n = 26) and had the largest variation. The average rate of NCP and its variance were less in the coastal area (20 ± 8 mmol O2 m−2 day−1, n = 6). NCP in the open sea area was consistently low at the time of our observations (3 ± 5 mmol O2 m−2 day−1, n = 14). The large variation of NCP in the shelf area was mainly due to an along-shore gradient; i.e., NCP was much greater in the northern shelf than in the south. Highest NCP was found in the mid-shelf along line 600, about 50 km to the west of Anvers Island.

[37] NCP is highly correlated with Δ(O2/Ar) (n = 46, r2 = 0.96, p < 0.0001), while much less correlated with the gas exchange rate (n = 46, r2 = 0.25, p < 0.0005). Therefore, the uncertainty in the estimates of wind speed and calculation of the gas exchange rate will not significantly affect the variability of NCP estimated by our method.

3.4.3. NCP/GPP Ratios and the f-Ratios

[38] O2 NCP/GPP ratios measured at 26 stations ranged from −0.04 to 0.43 (Figure 3c). Using O2/C = 1.4 and O2 GPP/14C PP = 2.7, the f-ratio is about two times the O2 NCP/O2 GPP ratio. Thus, f-ratios in the regionranged from nearly 0 to 0.83.

[39] The variance of NCP accounts for most of variance in NCP/GPP ratios (r2 of NCP and NCP/GPP = 0.9, n = 26, p < 0.0001), and the spatial distribution of NCP/GPP is similar to that of NCP. NCP/GPP ratios in the shelf area were generally high and variable (0.20 ± 0.11). Ratios in the coastal region and open sea were lower (mean = 0.12 ± 0.05 and 0.02 ± 0.03, respectively). Similar to that of the NCP, NCP/GPP was highest in the northern coastal region, and was lower in the southern coastal region.

3.4.4. Uncertainties of the Estimates

[40] Uncertainties in the calculated values of NCP and GPP mainly arise from uncertainties in the gas exchange coefficient and the analytical uncertainties of the Δ(O2/Ar) and the 17Δ . The standard error of ±0.27% in the Δ(O2/Ar) measurements is ±11% of the mean Δ(O2/Ar) value. The standard error of ±5 per meg corresponds to an uncertainty of ±2% in mean photosynthetic O2 concentration. Using the average saturation [O2] of 350 mmol m−3 and the average k of 2.3 m day−1 over the study region, these standard errors give the uncertainties of ±2 mmol O2 m−2 day−1 and ±3 mmol O2 m−2 day−1 in NCP and GPP, respectively.

[41] According to Sweeney et al. [2007], the wind speed parameterization we adopted in this study gives an uncertainty of ±32% in the gas transfer velocity. Combining this error with the analytical uncertainties yields an overall uncertainty of ±34% (±5 mmol O2 m−2 day−1) in NCP, and ±33% (±40 mmol O2 m−2 day−1) in GPP.

[42] The error analysis indicates that the major fraction of the uncertainties in NCP and GPP is from the error in the gas exchange rate calculation. As k is eliminated in the calculation of the NCP/GPP ratios, our NCP/GPP have a considerable smaller uncertainty (±12%, or 0.02 in NCP/GPP).

3.5. Community Structure

[43] Distribution of phytoplankton composition in the mixed layer is presented in Figure 4. The CHEMTAX run gave an root mean square error (RMSE) of 3.4%, which is smaller than the average of the uncertainties (8.0 ± 5.4%) in the CHEMTAX calculations for the 12 year data set [Kozlowski et al., 2011].

image

Figure 4. Contribution (%) of (a) diatoms, (b) cryptophytes, (c) type 4 haptophytes, and (d) mixed flagellates to total Chl ain the surface water derived from the HPLC-CHEMTAX analysis for Jan. 2008 in the Palmer LTER grid.

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[44] Diatoms and cryptophytes contributed significantly to the total Chl a in the WAP region. The contribution of diatom (fdiat) ranged from 0 to 71%, with the mean = 31 ± 18% (n = 45) . Diatoms were dominant in most of the offshore areas and the southern coast and shelf areas, and had high contribution in Marguerite Bay (Figure 4a). In the northern shelf and coastal areas, the fraction of diatom chlorophyll was generally less than 10%.

[45] Cryptophytes accounted for 0 to 97% of the contribution to total Chl a (mean of fcryp= 34 ± 35%). They were dominant in the coast and shelf areas north of line 300, and were most important in the inner-shelf of line 500 and 600 (Figure 4b).

[46] Type 4 haptophytes are primarily represented by Phaeocystis antarctica in this region [Kozlowski et al., 2011], and they were less dominant compared with diatoms and cryptophytes (fhap from 0 to 59 %, mean = 20 ± 17%). They have relatively high contribution west of the shelf break (Figure 4c).

[47] The mixed flagellates had low contribution to total Chl a in most of the study region (fmix from 0 to 57 %, mean = 13 ± 15%), except in a narrow area (about 20 km wide) to the east of the shelf break and to the north of line 300 (Figure 4d).

[48] Prasinophytes contributed least to the total Chl a, and were hardly identified in the study region (fpra from 0 to 14 %, mean = 2.5 ± 3.8%).

[49] Although there may be considerable inter-annual variability and additional uncertainty due to different methods, phytoplankton composition derived from the HPLC-CHEMTAX analysis for Jan. 2008 in this region is quite comparable to that observed in previous studies using similar methods or microscopic analysis. These studies all observed high abundance of diatoms and cryptophytes relative to other groups in the region, with cryptophytes dominating only in the northern inshore area [Garibotti et al., 2003; Moline et al., 2004; Kozlowski et al., 2011].

4. Discussion

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. 5. Summary
  8. Acknowledgments
  9. References
  10. Supporting Information

[50] Previous studies have identified two major factors that are key to the ecosystem structure and dynamics in the WAP region. The first is sea-ice and coastal glacier runoff. Supply of fresh water during sea-ice retreat and melting of glaciers enhances the strength of upper water column stratification, and thus, the availability of light to phytoplankton in the mixed layer [Dierssen et al., 2002; Smith and Nelson, 1986; Buesseler et al., 2003]. In a 12 year time series (1995–2006) analysis, Vernet et al. [2008] observed that primary productivity is higher where the mixed layer is shallower. In addition, warmer and fresher water lenses originating from glacier melt are usually favored by cryptophytes. Glacier meltwater can thus shift community composition and alter the food web, and could potentially regulate productivity [Moline et al., 2004].

[51] The second important process in this region is the intrusion of UCDW into the shelf, which supplies nutrients to the surface water by vertical mixing and upwelling, and enhances primary productivity [Prézelin et al., 2000, 2004; Garibotti et al., 2003].

[52] Although these processes play an important role in regulating primary productivity, it is still unclear how they influence export productivity in this region. With our estimates of NCP, NCP/GPP and the environmental and ecological properties, we carried out Type I linear regression analyses and examined the role of several factors in regulating NCP and export efficiency. Although linear relationships were assumed for the calculation, we focused on the trends of relationships rather than the exact functionality relationships between NCP and the environmental properties. r2 and p were used as indication of the strength of the trends.

4.1. Influence of Water Column Stratification

[53] As mentioned above, warming and freshening of the surface water in the coast and shelf areas was a result of fresh water supply from sea-ice retreat and melting of coastal glaciers. This supply accounts for the formation of a shallow mixed layer [Smith and Nelson, 1986]. Correlation analysis between NCP and environmental properties indicates that NCP was positively correlated with SST (n = 46, r2 = 0.36, p < 0.0001, see Figure S4a), and inversely correlated with MLD (n = 46, r2 = 0.21, p < 0.002, see Figure 5c). A similar relationship was observed between MLD and the NCP/GPP ratio (n = 26, r2 = 0.21, p < 0.02, see Figure 5d), and between MLD and the volumetric NCP, i.e., NCP/MLD (Figure S4b).

image

Figure 5. X-Y plots of the results of the correlation studies of (a)17Δ versus Δ(O2/Ar), (b) NCP versus GPP, (c) NCP versus MLD, (d) NCP/GPP versus MLD, (e) daily average NCP (NCPPO4) derived from depth integrated phosphate drawdown versus NCP estimated from the [O2]/[Ar] ratios, and (f) NCP versus Fv/Fm. Dashed line in Figure 5e is the 1:1 line of NCPPO4 and NCP.

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[54] The correlation study suggests that strengthening of mixed layer stratification and shoaling of the mixed layer enhance export production and the f-ratio in the WAP region, particularly in the coast and shelf regions (r2 = 0.35 for NCP versus MLD, n = 32, p < 0.001), consistent with MLD being a key factor in regulating export production in this region. NCP in the offshore region was generally low regardless of variation of MLD, and associated with low GPP and Chl a in this region. Low offshore NCP is probably also a consequence of severe iron limitation (see section 4.2).

4.2. Influence of Nutrient Supply

4.2.1. Phosphate Uptake and NCP

[55] Depth-integrated phosphate drawdown (ΔP), derived from the method of Serebrennikova and Fanning [2004], records the production during the growing season, while our O2 NCP examines production in the timescale of 1–2 weeks. To make phosphate drawdown comparable to our NCP, we calculate the daily averaged NCP (NCPPO4), based on the part of ΔP in the mixed layer:

  • display math

where 106 is the assumed stoichiometric ratio of C:P [Redfield et al., 1963], 1.4 is the O2:C NCP ratio [Marra, 2002], and Δt is the length of the growth season. Since phytoplankton growth in the WAP region usually begins after ice retreat [Ducklow et al., 2007], Δt is estimated by the period from the starting day of ice retreat to the date the samples were collected on a station.

[56] NCPPO4 is plotted versus NCP (Figure 5e). In most of the central shelf region, the NCPPO4 ≈ NCP, indicating that our estimates of NCP are similar to the level of production during the growing season up to the time of sampling. In the offshore and southern inshore regions, NCPPO4 was much higher than NCP. This implies that NCP had decreased to a lower level at the time of the cruise, and NCP could be much higher in an earlier stage of the growing season. In the northern shelf and coastal regions, most stations have their NCPPO4 ≪ NCP. Thus, these regions in Jan. may represent a situation of rapidly rising NCP, or peak NCP, relative to the beginning of the growth season.

[57] Seasonal cycle and spatial pattern of phytoplankton blooms in the WAP region are closely associated with the sea-ice retreat, and the ice-edge associated blooms usually start in the open sea in October and moves toward the coast as sea-ice retreats [Smith et al., 2008]. Thus, the relationship of NCPPO4 and NCP indicates different stages of the growth season from offshore to inshore, and south to north. At the time of the cruise, the southern and offshore regions could be in the situation of a declining bloom, while the northern and inshore regions was probably in the growth or mature stage of a bloom.

4.2.2. Iron and NCP

[58] Iron concentrations are likely to be higher in the coastal and shelf waters than offshore, due to iron supply from both the coast and intrusions of UCDW [Ducklow et al., 2007; Prézelin et al., 2000]. The inferred decrease of iron toward the open sea is thought to account for the inshore-offshore gradient of PP observed in previous studies [Ducklow et al., 2007; Vernet et al., 2008; Garibotti et al., 2003].

[59] The Fv/Fm is used as an indicator of iron limitation in this study. Although Fv/Fm could be affected by various factors such as light, temperature, phytoplankton, nutrient levels [Cavender-Bares, 2004] and phytoplankton community structure [Suggett et al., 2004, 2009], iron repletion is observed as the dominant factor that enhances Fv/Fm in the High Nutrient Low Chlorophyll (HNLC) regions of the Southern Ocean [Boyd et al., 1999; Boyd and Abraham, 2001; Strutton et al., 1997; Suggett et al., 2009]. As most of our study region resembles the HNLC regions, the spatial variation of Fv/Fmin this region can reflect iron-induced growth stress of phytoplankton.

[60] In our study, Fv/Fm and NCP are positively correlated (n = 20, r2 = 0.22, p < 0.05), indicating that NCP and export are higher where iron stress of phytoplankton is relieved (Figure 5f). The correlation between Fv/Fmand NCP helps explain the across-shelf decrease of NCP. In the outer-shelf and offshore area, the Fv/Fmratios are the lowest (around 0.3), and the NCP are low, indicating iron limitation of export production. However, the along-shore decrease of NCP in the coastal area is not tightly associated with Fv/Fm ratios, which were similarly high in the southern and northern coastal region. In iron replete regions, other factors influence NCP.

4.3. Influence of Community Structure

[61] As mentioned in section 3.5, community structure for Jan. 2008 is very similar to that observed in the previous studies. Diatoms dominated the most of the southern region, and cryptophytes dominated the northern coast and inner-shelf region. Chl ain these two groups of phytoplankton account for more than 80% of the total Chl a in the inner-shelf and coastal regions. Diatoms are usually associated with ice-edge blooms in the region [Garibotti et al., 2003], while cryptophytes are observed to favor fresher, warmer and more strongly stratified water [Moline et al., 2004]. Therefore, the difference in community composition in the coast and inner-shelf region is thought to be a seasonal progression. The diatom-dominated assemblage in the south represents an ice edge community. The cryptophyte-dominated assemblage in the north is a late summer community, where sea-ice retreated earlier after exerting its own influence, and influence of glacier meltwaters became strong [Garibotti et al., 2003].

[62] Diatoms are usually assumed to be the most important taxon in regulating export production in the Southern Ocean [Boyd and Newton, 1999; De La Rocha and Passow, 2007]. High export production is usually found at places where blooms of diatoms occur [Buesseler, 1998]. Our data indicates a complicated correlation between diatoms and NCP (Figure 6a). First, NCP and NCP/GPP in the offshore region was always low (∼0), and diatom Chl a concentration (chldiat) in this region was low (<0.05 mg m−3). In the coast and shelf regions, stations with relatively high diatom Chl a concentration coincided with the mid-range of NCP (∼10–40 mmol O2 m−2 day−1). At locations where diatoms were less dominant or absent, NCP spanned from the lowest to the highest end of the range. The largest NCP observed in this region all occurred at places of low fdiat and low to intermediate level of diatom Chl a concentration.

image

Figure 6. (a) Relationship of NCP with Chl a concentration in diatoms. (b) Relationship of NCP with Chl a concentration in cryptophytes. (c) Ternary plot showing the contribution of diatoms, cryptophytes and all other examined groups to total Chl a. Point closer to the upper corner of the triangle has a higher contribution of diatoms to the total Chl a, and point closer to the lower right corner has a higher contribution of cryptophytes. The colors of the circles indicate the magnitude of NCP. (d) The same ternary plot with the colors of the circles showing the magnitude of surface Chl a concentration. (e) Relationship of surface Chl a concentration with NCP. (f) Relationship of surface Chl aconcentration with NCP/GPP ratios. Note that the scales of the x-axes in Figures 6e and 6f are logarithmic, and the dashed lines are the regression lines of NCP versus ln(Chl a) and NCP/GPP versus ln(Chl a), respectively.

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[63] Places with high NCP and a low fraction of diatoms were dominated by cryptophytes. There is an positive correlation between NCP versus fcryp and NCP versus chlcryp wherever cryptophytes were present (n = 19, r2 = 0.65 and 0.76, respectively, both have p < 0.0001, see Figure 6b). To further exam the influence of the transition between the major phytoplankton groups on NCP and Chl a, we plot the contribution of diatoms, cryptophytes and the sum of all other groups against NCP and Chl a. Total Chl a and NCP increased when diatoms were replaced by cryptophytes, and reached peak values when the fraction of cryptophytes was larger than 80% of the three groups (Figures 6c and 6d).

[64] The enhancement of NCP from diatom-dominated to cryptophyte-dominated community could be attributed to the alteration of food web, which is regulated by sea-ice and coastal glacier dynamics. Diatoms are the preferred food source for krill [Haberman et al., 2003], while cryptophytes are favored by salps [Moline et al., 2004]. In addition, krill life histories require a period of sea ice cover [Siegel et al., 1990; Smetacek and Nicol, 2005; Quetin and Ross, 2003] and krill are declining with reductions in sea ice cover along the WAP [Atkinson et al., 2004]. In contrast, sea ice inhibits salp presence and activity [Siegel and Piatkowski, 1990; Loeb et al., 1997], and cryptophyte growth is favored later in the season after sea ice retreat and when glacier runoff is near its seasonal maximum. Therefore, the timing of sea-ice retreat, the input of glacier meltwater, and the phytoplankton composition, facilitate high salp-to-krill ratio in the northern coastal and inner-shelf region and lower ratio in the south [Garibotti et al., 2003]. Salps produce large and rapidly sinking fecal pellets [Bruland and Silver, 1983].Therefore, the cryptophyte-salp pathway could have a higher efficiency exporting carbon, which might have led to the high NCP and NCP/GPP observed in the northern region. This hypothesis is to be further tested with the zooplankton composition data from the same cruise.

4.4. The Relationship Between NCP and Chl a

[65] One significant and interesting relationship captured by this work is the high correlation of the natural logarithm of surface Chl a with NCP (n = 43, r2 = 0.72, p < 0.0001, see Figure 6e) and NCP/GPP (n = 25, r2 = 0.55, p < 0.0001, Figure 6f). Several attempts have been made in previous studies to estimate export production and the f-ratios from phytoplankton biomass and Chl a concentrations [Baines and Pace, 1994; Dunne et al., 2005, 2007; Eppley and Peterson, 1979; Laws et al., 2000]. The high spatial resolution of our estimates of NCP and NCP/GPP ratios allow us to derive local algorithms in the WAP region.

[66] Dunne et al. [2005] concluded, by analyzing a global data set of new or export production, that the f-ratio could best be expressed as a function of temperature and the logarithm of average Chl a concentration in the euphotic zone, i.e.

  • display math

where the term Chleu (μg/L) stands for the average Chl a concentration in the euphotic zone.

[67] Following the format of the equation given by Dunne et al. [2005], we derive following equation to best fit our data:

  • display math

The SST term is ignored here because SST is close to zero in this region. The f-ratio predicted with this equation accounts for 72% of the variance in observed f-ratios. Our equation is not fully comparable to theDunne et al. [2005]equation because our analysis pertains to the mixed layer while theirs pertains to the euphotic zone, and because ours is restricted to one particular ocean ecosystem or province. Nevertheless, the two equations agree closely over most of the chl rangeof our samples. Our equation demonstrates the potential for a local algorithm that converts Chl a concentration measurements to the f-ratio and14C PP, and calculates NCP from the product.

5. Summary

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. 5. Summary
  8. Acknowledgments
  9. References
  10. Supporting Information

[68] In this work, we obtained estimates of NCP, GPP and NCP/GPP ratios for January, 2008 at high spatial resolution in the WAP region, and performed correlation studies between NCP(NCP/GPP) and various environmental and ecological properties.

[69] The open ocean region west of the shelf break, and part of the outer-shelf region, is characterized by generally low NCP and NCP/GPP, strong iron limitation, and dominance of prymnesiophytes. NCP can be very low in this region, even when MLD < 20 m. Therefore, iron availability may be the most important factor regulating export production in this region, and distribution of iron might be the main factor that determines the inshore-offshore gradient of GPP, NCP, and community composition.

[70] Export production in the coast and inner-shelf region is generally limited by factors other than iron. The northern area is characterized by high NCP (with the highest NCP occurring in this area), and high iron availability (based on variable fluorescence). It is dominated by cryptophytes. The mixed layer is usually shallow in the region. The compact relationship between NCP and MLD indicates that shallow stratification enhances export production and thus plays a important role in regulating NCP. Input of fresh glacier meltwater, and stratification of the water column, apparently lead to the dominance of cryptophytes, and this could potentially further enhance export production through alteration of the food web.

[71] The southern coast and shelf region presumably have similar levels of iron concentration as the northern. It is distinguished from the northern region by its lower NCP, deeper mixed layer, and the dominance of diatoms. This region may represent an earlier stage in the seasonal succession before the replacement of diatoms by cryptophytes. Low NCP in this region is mainly due to the weaker stratification of the water column, which may also prevent the bloom of cryptophytes.

[72] Diatom blooms can clearly lead to high f-ratios and rapid export. However, in our study domain, export was greatest from cryptophyte-dominated communities, presumably due to packaging of organic matter by their grazers.

[73] Overall, our observations and correlation studies indicate that export production is limited by iron, MLD, and community structure in some areas of the study region. During the time of our study, there was a tight relationship between export production and surface Chl a level regardless of changing environmental properties.

Acknowledgments

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. 5. Summary
  8. Acknowledgments
  9. References
  10. Supporting Information

[74] This research was supported by NSF-OPP grant 0823101 to Ducklow and NASA Earth and Space Sciences Fellowship to Huang. We thank all the scientists and the crew on L. M. Gould for collecting samples and making underway measurements, and acknowledge Raytheon Polar Services for assistance with shipboard operations. We are grateful to Bruce Barnett in Bender's lab and Wendy Kozlowski in Vernet's lab for assistance in analyzing samples and processing data. This is Palmer LTER contribution 0386.

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  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. 5. Summary
  8. Acknowledgments
  9. References
  10. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. 5. Summary
  8. Acknowledgments
  9. References
  10. Supporting Information

Auxiliary material for this article contains one table and four figures.

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FilenameFormatSizeDescription
gbc1860-sup-0001-readme.txtplain text document4Kreadme.txt
gbc1860-sup-0002-ts01.txtplain text document5KTable S1. Summary of sampling time and locations, sea surface temperature, sea surface salinity, mixed layer depth, gas exchange rate, ΔO2/Ar, 17Δ,estimates of NCP, GPP and the NCP/GPP ratios, surface chlorophyll concentration, and depth-integrated phosphate and silicate drawdown.
gbc1860-sup-0003-fs01.tifTIFF image411KFigure S1. Comparison of wind speed derived from NCEP/NCAR analysis with daily average “true wind” speed measured on the ship during the cruise in January 2008 and daily average wind speed measured at Palmer Station for 2000–2010.
gbc1860-sup-0004-fs02.tifTIFF image834KFigure S2. Diurnal variation of Fv/Fm ratios January 2008 and the values selected by applying the raw PAR measurement window of 0–200 mV.
gbc1860-sup-0005-fs03.tifTIFF image5552KFigure S3. Surface phosphate concentration, surface silicate concentration, depth-integrated phosphate drawdown, and depth-integrated silicate drawdown
gbc1860-sup-0006-fs04.tifTIFF image164KFigure S4. NCP versus SST for January 2008 and volumetric NCP versus MLD for January 2008.

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