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Deep-Sea Research II 50 (2003) 3083–3101

*Correspondin

804-684-7399.

E-mail addres

0967-0645/$ - see

doi:10.1016/j.dsr2

Biogeochemical climatologies in the Ross Sea, Antarctica:seasonal patterns of nutrients and biomass

Walker O. Smith Jr.a,*, Michael S. Dinnimanb, John M. Klinckb, Eileen Hofmannb

a Virginia Institute of Marine Science, College of William and Mary, Gloucester Pt., VA 23062, USAb Center for Coastal Physical Oceanography, Old Dominion University, Norfolk, VA 23529, USA

Received 20 May 2002; received in revised form 21 May 2003; accepted 15 July 2003

Abstract

The seasonal patterns of nutrient (nitrate and silicic acid) and chlorophyll distributions in the Ross Sea are

formulated by two independent methods. The first procedure compiles all available data from cruises from 1970 to the

present and generates a three-dimensional grid for the months from November through February using an iterative

difference-correction scheme. The second method uses a three-dimensional circulation model and the phytoplankton

standing stock climatology to investigate the effects of currents and phytoplankton uptake on nutrient distributions.

The two approaches produced similar results, although the circulation model produced distributions that were more

variable in space due to its finer resolution. The nutrient distributions were characterized by elevated concentrations in

early spring and gradual reductions to ca. 15 and 40mM (nitrate and silicic acid, respectively) in summer. Nutrient

depletion did not occur despite the favorable growth conditions (elevated macronutrient concentrations, strong vertical

stratification) in summer, suggesting that an alternative limitation (such as by dissolved iron concentrations) occurs.

Chlorophyll concentrations reached ca. 6mg l�1 in December and declined thereafter. Seasonal primary production

calculated from the nitrate deficits and the circulation model suggested that production was ca. 73 g C m�2, slightly

lower but similar to other estimates using independent methods. Using the nutrient climatology, losses (vertical flux

plus respiration) through Feb. 15 from the upper 100 m were ca. 50% of the seasonal production, and the rest of the

organic production was removed after that date. Results also suggest that carbon export from the surface layer may

vary significantly in space and time.

r 2003 Elsevier Ltd. All rights reserved.

1. Introduction

The Ross Sea is one of the Antarctic’s mostproductive seas and is characterized by extensive,recurrent phytoplankton blooms and large sedi-mentary deposits of biogenic material. Indeed,

g author. Tel.: +1-804-684-7709; fax: +1-

s: wos@vims.edu (W.O. Smith Jr.).

front matter r 2003 Elsevier Ltd. All rights reserve

.2003.07.010

phytoplankton growth there is unusual withregard to a number of features. For example,growth begins in late October (Smith and Gordon,1997), similar to or before that of more northerlyregions with greater solar radiation fluxes (e.g., thePolar Front region; Landry et al., 2001). Growth isextensive in austral spring and largely limited byirradiance (Smith et al., 2000; Smith and van Hilst,2003), but in summer becomes limited by ironavailability (Fitzwater et al., 2000; Sedwick et al.,

d.

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2000; Olson et al., 2000). Olson et al. (2000) foundthat all species appeared to have a similarreduction in photosynthetic capacity duringsummer and attributed this reduction to irondeficiency. Macronutrients remain elevatedthroughout the Ross Sea, except in isolatedlocations (Nelson and Smith, 1986).

The relationships among vertical stability, nu-trients, phytoplankton biomass and growth havebeen studied in the Ross Sea for a number of years(e.g., Holm-Hansen et al., 1977; El-Sayed et al.,1983; Smith and Nelson, 1985; Nelson et al., 1996;Arrigo et al., 1999). As such, an extensive data sethas become available to assess the variations inboth space and time in properties such asphytoplankton biomass (chlorophyll a concentra-tions), nutrients, salinity and temperature. How-ever, the cruises were not distributed evenlythroughout the growing season, with most beingconducted during the mid-summer period.Furthermore, many were concentrated in thesouthern Ross Sea, close to the sites of the majorsupport facilities (the US base McMurdo Stationon Ross Island, and the Italian base Stazione BaiaTerranova in Terra Nova Bay). Hence, it has beendifficult to describe the canonical distribution ofproperties over the entire season and continentalshelf. Furthermore, while a number of large-scaleclimatologies for ice distributions, temperature,salinity and nutrients exist (e.g., Comiso et al.,1993; Conkright et al., 1998; Louanchi and Najjar,2000), their application and reliability with regardto the extremes of the Southern Ocean such as theRoss Sea are unsubstantiated. In order to comparevariations from the long-term mean among yearsor between regions, such a ‘‘mean’’ needs to beestablished using multi-year data and interpolatedin space and time. To date, no nutrient orchlorophyll climatology for the Ross Sea has beencompiled.

Biogeochemical models that utilize couplednumerical formulations of both physical andbiological processes have become important toolsin assessing the importance of a variety ofprocesses in marine systems (Hofmann andLascara, 1998). For example, recent biogeochem-ical models of the equatorial Pacific have demon-strated the importance of iron limitation as a

control to phytoplankton growth (Chai et al.,1996), as well as the relative importance of DOMto the export of carbon from the surface layer(Ducklow et al., 1995; Hansell et al., 1997).Despite their use in other regions, fewer modelshave been generated for the Southern Ocean,largely because the extant database has beeninadequate to address both the regional physicsand biology. However, with the completion ofrecent large field efforts such as Joint Global FluxProgram (JGOFS) in the Antarctic, models haverecently been designed to assess the influence ofphysical processes on biological rates and distribu-tions. Arrigo et al. (2003) developed a model thatincorporated biological and nutrient (nitrate andiron) dynamics into an ocean circulation model,and used sea ice concentrations derived from the20-year climatology for the Ross Sea. The model’sresults followed the general pattern observed in1996, but did not address the modeled distribu-tions in relation to the mean conditions of theRoss Sea or its interannual variations. Goffartet al. (2000) formulated a one-dimensional modelof biological processes, and related the temporalsequence of the phytoplankton in the Ross Sea toice concentrations and water column stratification.Lancelot et al. (2000) also developed a one-dimensional model and applied it to varioussituations of the Scotia-Weddell Seas, and con-cluded that short-term wind events and the inputof iron are critical in controlling the seasonalpatterns of phytoplankton growth and distribu-tion. Other, specific models exist for variousregions and purposes (e.g., Mitchell and Holm-Hansen, 1991; Markus, 1999), but to date therehas been no regional model for the Ross Sea thatseeks to understand the precise physical–biologicalcoupling on seasonal time scales.

The objectives of this study are (a) to generate aregional climatology for a number of biogeo-chemically important variables such as chloro-phyll, nitrate and silicic acid, (b) to construct asimplified biophysical model of the Ross Sea thatincludes off-shelf forcing with the observed meanice concentrations and distributions, and (c) toconstrain carbon fluxes using both the climatolo-gies and model. Specifically, this paper synthesizesall extant nutrient and chlorophyll data for the

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Ross Sea continental shelf and generates atemporally resolved (November–February) clima-tology for the region. This climatology in turn isused to estimate seasonal productivity and export,as well as the interactions with the physicalcirculation regime (Dinniman et al., 2003). Thisregional estimate can be used to assess theinterannual and spatial variations of productionand export within the Ross Sea, as well as tocompare the seasonal productivity to other areasin the Antarctic. We also introduce a simplifiedbiophysical model that utilizes the climatology toestimate rates of nutrient uptake and phytoplank-ton growth. The model is not intended to provide atool to test all aspects of the ecology andbiogeochemistry of the Ross Sea, but rather tosee if a simple model, using appropriate para-meters derived from the literature, can simulatemany of the temporal patterns observed in theclimatology (and to investigate what factors needto be included to improve the relationship betweenthe two). The Ross Sea is important because itrepresents an extreme condition (with regard toproductivity and biomass) relative to the entireAntarctic. Furthermore, the Southern Ocean is

Table 1

Sources of field observations used in the generation of the gridded cl

Cruise Dates Year

Eltanin 27 Jan. 27–Feb. 5 1967

Glacier Jan. 17–22 1982

Glacier 83-1 Jan. 26–Feb. 2 1983

Glacier 83-2 Feb. 4–8 1983

Polar Star Jan. 28–Feb. 26 1985

Italica 88 Jan. 21–Feb. 10 1988

Polar Duke 90-8 Jan. 12–Feb. 15 1990

Polar Duke 92-2 Feb. 5–Feb. 28 1992

Polar Sea Jan. 22–Feb. 3 1994

Palmer 94-6 Nov. 10–Dec. 8 1994

Italica 94 Nov. 14–Dec. 20 1994

Italica 95-2 Jan. 22–Feb. 20 1995

Palmer 95-8 Dec. 10–Jan. 10 1995/6

Italica 96 Jan. 20–Feb. 9 1996

Palmer 96-4 Oct. 2–Nov. 8 1996

Palmer 96-6 Dec. 11–Jan. 8 1996/7

Palmer 97-1 Jan. 13–Feb. 11 1997

Palmer 97-3 April 12–May 3 1997

Palmer 97-8 Nov. 5–Dec. 13 1997

Palmer 97-9 Dec. 20–Jan. 10 1997/8

recognized as the most important region in theglobal marine carbon cycle (Sarmiento and LeQu!er!e, 1996; Sarmiento et al., 1998) by virtue ofthe large reservoir of unutilized nutrients, andhence any alterations induced by large-scaleclimate changes potentially could greatly impactthe Southern Ocean and have large impacts onglobal biogeochemical processes.

2. Materials and methods

Data were collected from the literature andavailable databases to generate a set of observa-tions that in turn were objectively analyzed andinterpolated to a uniform grid. The data used,periods of collection, and sources are listed inTable 1 and are available in digital format viahttp://usjgofs.whoi.edu/las/servlets/dataset. Somenutrient data from some cruises were not included,since the deep-water (X200 m) concentrationsappeared to deviate substantially from thosevalues obtained using accepted, automated, mod-ern techniques (e.g., Gordon et al., 2000). A fewstations also were included from the World Ocean

imatology

Number of stations Reference

11 El-Sayed et al. (unpublished)

30 Biggs and Amos (1983)

36 Nelson and Smith (1986)

6 Smith (unpublished)

39 Biggs et al. (unpublished)

39 Catalano and Benedetti (1990)

68 Nelson et al. (1996)

52 Nelson et al. (1996)

38 Smith (unpublished)

77 Smith and Gordon (1997)

19 Catalano et al. (1997)

78 Catalano et al. (1997)

86 Smith and Gordon (1997)

38 Catalano et al. (1997)

24 Gordon et al. (2000)

98 Arrigo et al. (1999)

32 Gordon et al. (2000)

13 Gordon et al. (2000)

37 Gordon et al. (2000)

83 Arrigo et al. (2003)

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Database 98 to extend the data set used (Conk-right et al., 1998); these stations included weremostly off the continental shelf. We used nitrateand silicic acid, as these nutrients most clearlyreflect the influence of diatomaceous and non-siliceous forms on phytoplankton biomass. Allchlorophyll concentrations were determined viafluorescence after extraction in 90% acetone,except for a few recent cruises in which chlorophyllvalues were determined using high performanceliquid chromatography. Direct comparison of thetwo methods in the Ross Sea showed little or nodifference (r2 ¼ 0:98; Bidigare et al., unpublished).Most of the stations were occupied on thecontinental shelf, but a few were sampled in thedeeper waters of the Ross Sea Gyre (Fig. 1). Amonthly climatology for the months of Novem-ber–February was objectively analyzed to filterspatial noise and interpolated to a uniform grid.

Fig. 1. Location of stations included in the chlorophyll and nutrient

circulation model.

An iterative difference-correction scheme (Cress-man, 1959) was used that was very similar to thatemployed by Levitus (1982). The annual analyzedfield is constructed with four iterations usingsuccessively smaller radii of influence (1541,1211, 881 and 771 km), which are the same usedby Levitus (1982). The annual field is the firstapproximation for the monthly fields that areconstructed with six iterations with smaller radii(1541, 881, 550, 220, 110 and 55 km). Although thesmaller radii are finer than the ‘‘seven or eight’’grid points (771 km in longitude and 200–300 kmin latitude) recommended by Levitus, we weremore concerned with representing some of thespatial variability in the high density of availablemeasurements in the western Ross Sea and lessworried about having smooth spatial derivativesor dampening small scale variability. The databasewas gridded on the same vertical and horizontal

climatologies. The unshaded area represents the domain of the

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(1� resolution) as the World Ocean Atlas 98. Thevertical resolution was not constant, but varied withdepth (e.g., the top 14 layers are 0, 10, 20, 30, 50, 75,100, 125, 150, 200, 250, 300, 400 and 500 m).

The circulation of the Ross Sea was modeledwith the Rutgers/UCLA Regional Ocean ModelSystem as described by Dinniman et al. (2003).The model was used to quantify and delineate thebiological and physical processes on the distribu-tions of biogeochemical variables in the region.Twenty-four vertical intervals and a horizontalspacing of 5 km were used. Nutrient uptake wasmodeled by imposing a biological uptake responseon the physical circulation regime. Phytoplanktonbiomass changed through time by using data fromthe chlorophyll climatology (i.e. they were notcomputed, but rather were imposed). Chlorophyllconcentrations after mid-February were assumedto linearly decrease to an arbitrary backgroundlevel (0.1 mg l�1) by mid-March. Nitrate removalwas modeled as a function of biomass (asestimated from chlorophyll concentrations) andnitrate concentrations using a Monod formulation(Dugdale and Goering, 1967; Riebesell and Wolf-Gladrow, 2002). A Ks value of 0.1 mmol l�1 (at thelower range of values observed in polar oceans;Cochlan and Bronk, 2001), and a Vmax value of0.0025 h�1 were initially used. However, uptakerates in the Ross Sea are not constant with time(Hu and Smith, 1998; Cochlan and Bronk, 2001),so we modeled the spring–early summer periodusing a Vmax value of 0.0036 h�1 and a summerrate of 0.0018 h�1. Because iron limitation reducesnitrate uptake in the Ross Sea during summer(Sedwick and DiTullio, 1997; Olson et al., 2000),this function implicitly represents iron limitation.The transition from high to low uptake ratesoccurred on day 90 (December 15). Given theelevated nutrient concentrations normally foundthroughout the Ross Sea, the Vmax value was thecontrolling variable in computing nutrient uptake.

Silicic acid uptake was computed from nitrateuptake using a constant Si:N ratio. The observedSi:N ratio is a function not only of assemblagecomposition, but of the physiology of micronu-trient uptake. Diatoms have an absolute require-ment for silicic acid, although cells are generallyquite plastic with regard to their response to

external concentrations (that is, they can make‘‘thinner’’ frustules in low silica environments).Other algal groups, such as cryptomonads andPhaeocystis sp., do not remove silicic acid at all.Therefore, the composition of the assemblage is afirst-order determinant on the Si:N uptake ratio.This ratio is also controlled by micronutrients, inthat under conditions of limiting iron concentra-tions nitrate uptake is drastically reduced, while Siuptake is relatively uninfluenced (Hutchins andBruland, 1998; Takeda, 1998), resulting in elevatedSi:N uptake ratios. In general, under iron-repleteconditions the Si:N uptake ratio is about 1:1(Hutchins and Bruland, 1998). This effect is thuspotentially coincident with that of assemblagecomposition. In our simplified model the Si:Nuptake ratio was 0.55 through Day 90, and wasincreased to 4.0 thereafter, which reflects both theeffects of iron and assemblage composition onsilica uptake.

The model’s nutrient values were initialized withthe November climatology and then were allowedto advect, diffuse and be subjected to uptake oncethe circulation model had run for 60 days (i.e.from September 15 to November 15). Except for avery weak relaxation at the model open bound-aries (see Dinniman et al., 2003), the nutrientclimatologies after November are not ‘‘used’’ bythe model (see below) except for comparison. Themodel was run for 1 year, and although longersimulations were completed, our intent was tocompare the seasonal cycle with that described bythe nutrient and chlorophyll climatology.

A variation of the model was run to computeprimary productivity. Instead of using the chlor-ophyll values to compute the nutrient uptake (andhence distributions), we used the initial nutrientvalues and calculated the net nutrient uptake fromthe nutrient climatology as the change in nutrientconcentration at each point in space. In addition,we also calculated the chlorophyll concentrationsthat resulted from this nutrient uptake by using theconversion 1.0 mM nitrate removed=1.0 mg l�1

chlorophyll produced. These concentrations alsowere influenced by advection and vertical diffu-sion. The seasonal nutrient removal was thenconverted to carbon units using the Redfieldratio. Such a calculation generates a substantial

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overestimate of chlorophyll concentrations be-cause the time-dependent losses due to bothaggregate formation and enhanced vertical fluxesof large particles and zooplankton grazing are notexplicitly included. These concentrations can becompared to the chlorophyll climatologies toestimate net losses from the surface layer.

3. Results

3.1. Climatology of nutrients and biomass

The temporal changes in nitrate concentrationsin general were inversely correlated with those ofchlorophyll, as expected. Nitrate concentrationswere elevated (ca. 30 mM) in November, with someremoval in the south-central polynya (Fig. 2a).Removal in spring was rapid, so that by December

Fig. 2. Distribution of nitrate at 20 m in (a) November, (b) December

generated from all available data. The 20 m depth was chosen as this is

The white line is the 1000 m isobath.

and January, concentrations throughout the ice-free region were reduced to less than 22 mM in thesouthern Ross Sea (Figs. 2b–d). Concentrationsless than 15 mM (the maximum seasonal removal)were noted in some regions in February. Up toone-half of the euphotic zone nitrate was removedby seasonal production. Silicic acid concentrationswere generally uniform in November (Fig. 3a), butdecreased through February (Figs. 3b–d). Thelowest values observed in the silicic acid climatol-ogies are ca. 42 mM. Biological assimilation ap-peared to be the major factor in controllingnutrient concentrations, as diffusive input fromdepth was minor due to the relatively strongvertical stratification that occurs in late spring andsummer.

The seasonal climatology of chlorophyll con-centrations is generally the inverse of nitrate(Fig. 4). In November the maximum biomass

, (c) January and (d) February, as deduced from the climatology

largely within the euphotic zone at all locations in the Ross Sea.

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Fig. 3. Distribution of silicic acid at 20 m in (a) November, (b) December, (c) January and (d) February, as deduced from the

climatology generated from all available data. The 20 m depth was chosen as this is largely within the euphotic zone at all locations in

the Ross Sea. The white line is the 1000 m isobath.

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was found in the south-central region(>3.0 mg l�1) between 167–172�E and 178–180�W (the site of the Ross Sea polynya), withlow (o0.5 mg l�1) levels found under ice (Fig. 4a).Concentrations increased rapidly, reaching theirmaximum in the polynya in December (ca.6.0 mg l�1; Fig. 4b), and also increasing broadlyeast of 170�W to values greater than 2 mg l�1.Maxima within the polynya in January decreasedto ca. 4.5 mg l�1, with substantial increases alongthe coast of Victoria Land (Fig. 4c). In areas offthe continental shelf, chlorophyll concentrationsdecreased to less than 0.5 mg l�1. In Februarybiomass levels continued to decrease throughoutmuch of the region but increases were noted in theeastern region (Fig. 4d). We emphasize, however,that the climatological means not only reflect theobserved concentrations, but also are influenced

by the number of observations in any particularregion. Few observations have been made in theeastern region, and the enhanced values there mayreflect the influence of a single data source, sincewe cannot know how representative those datamight be. The maxima observed during thisperiod, however, were significantly less than thoseobserved in December within the Ross Seapolynya.

3.2. Modeled distributions of nutrients and biomass

The modeled nutrient distributions were similarto the climatologies (see Table 2 for a directcomparison), although there was much moremesoscale variability in the modeled distributionsdue to the finer spatial resolution of the modelwhen compared to the observational data (5 vs.

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Fig. 4. Distribution of chlorophyll at 20 m in (a) November, (b) December, (c) January and (d) February, as deduced from the

climatology generated from all available data. The white line is the 1000 m isobath.

Table 2

Comparison between the nutrient climatology with the concentrations of nitrate and silicate predicted by the model

Date

December 13 January 12 February 11 February 11�

Nitrate

Modeled [NO3�] 24.2 22.0 21.8 21.0

Climatology [NO3�] 24.1 22.1 21.9 21.9

Mean error 0.1 �0.1 �0.2 �0.9

RMS error 2.09 2.45 2.76 3.37

Silicic acid

Modeled [Si(OH)4] 68.9 59.9 57.4 55.9

Climatology [Si(OH)4] 69.2 58.4 54.5 54.5

Mean error �0.3 1.5 2.9 1.5

RMS error 2.63 5.779 8.05 7.45

Note: The comparison is at every grid point in the model domain in the top layer of the model. The last column (February 11�)

represents the same data but with modeled values being influenced only by biological processes. All nutrient concentrations expressed

in mM. Nitrate and silicate concentrations in November were 29.5 and 71.8mM, respectively.

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60 km; Figs. 5 and 6). Mesoscale variations innutrients and biomass are known to occur withinthe Ross Sea (Hales et al., unpublished), but thecauses of these variations remain unclear. Themodeled nitrate distributions showed a broad areaof reduced nitrate concentrations south of 75�S(ca. 20 mM) in January (Fig. 5b), and furtherreductions in February (Fig. 5c). Seasonal minimawere similar between the model output and theclimatology, showing minimum values of ca. 12and 14 mM, respectively. The modeled valuesappear to show nutrient concentrations to besomewhat lower in the central Ross Sea duringsummer than the climatology, and lower off thecontinental shelf in February as well. The model’snitrate levels increase in winter due to increasedvertical mixing and advective inputs from off theshelf, but the September nitrate concentrations(that is, concentrations after the model has run for

Fig. 5. Modeled distributions of nitrate concentrations at 20 m in

distributions are the climatological distribution pictured in Fig. 2a. T

1 year) are ca. 2.5 mM too low (data not shown).We believe that this difference is caused both bythe lack of a remineralization function within thewater column, and by the absence of some physicalprocesses (e.g., double diffusive exchanges, tides)that may generate vertical mixing in winterthrough much of the water column. Regardless,the model generally simulated the seasonal pro-gression of nitrate concentrations that have beenobserved in the Ross Sea.

Modeled silicate concentrations also were gen-erally similar to the Si climatology in magnitude,but showed significant differences in space (Figs.6a–c). For example, the February climatologysuggested a broad minimum north of the northeastshelf-break (Fig. 3d), whereas the modeled valuesin that sector were much greater (ca. 10 mMgreater). Similarly, the modeled minimum waslocated in the central Ross Sea (minimum modeled

(a) December, (b) January and (c) February. The November

he white line is the 1000 m isobath.

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Fig. 6. Modeled distributions of silicic acid concentrations at 20 m in (a) December, (b) January and (c) February. The November

distributions are the climatological distribution pictured in Fig. 2a. The white line is the 1000 m isobath (the approximate location of

the shelf break).

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and climatological concentrations of silicic acidwere 42 and 48 mM, respectively). However, nodouble diffusive fluxes were included in the model,and others (e.g., Pr!ezelin et al., 2000) have foundthat these can be important in controlling surfacenutrient concentrations at least for some portionsof the seasonal cycle. Spatial differences betweenthe climatology and modeled values also suggestthat a firmer understanding of the factors thatcontrol species composition in the Ross Sea areimportant in improving the predictions of silicate.

When chlorophyll was computed from thechanges in climatological nitrate concentrations,the modeled chlorophyll distributions and concen-trations in January and February are generallycomparable to the biomass climatology, butnoticeable differences in December occurred, with

the modeled values being much greater than theobserved distributions, particularly near the iceshelf. This may be due largely to the low numberof data points during this period (relative toNovember) and at this location, but also maysuggest that the net loss rate used (0.04 d�1) is toolow in these months, and/or that the loss rate isnot seasonally constant, as was suggested by Smithand Asper (2000).

To assess the relative importance of physicaland biological processes in the model in producingthe predicted nutrient and biomass distributions,we ran simulations with and without operatingphysical processes. Removal of the physicalprocesses (advection and diffusion) resulted insurprising little difference between the two simula-tions in mean nutrient concentrations during the

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spring months. Specifically, the mean Februarynitrate concentration in the surface layer was 21.8and 21.0 mM for the model simulation with andwithout physical processes, respectively, and themean silicate concentrations were 57.4 and55.9 mM (Table 2). However, at some locations(such as near the Ross Ice Shelf) the simulationwithout physics produced much lower nutrientconcentrations (almost a 2-fold difference). Thissuggests that at some locations physical processesare important in introducing significant amountsof nutrients into the surface layer even duringsummer. For example, a calculation of the nitratebudget in the top 100 m of the Ross Sea polynyaregion (Fig. 7) shows that while the biologicaluptake is the dominant term for the total budget inthis region through spring and summer, thecombined physics terms (advection and diffusion)are significant by early summer and dominate byaustral fall. Regardless, the difference between themean concentrations calculated by the two modelswas surprisingly small until the effects of con-vective overturn in austral autumn became sig-nificant. Physical processes were very important incontrolling the distribution of nutrients, and muchless so in controlling the magnitude of the nutrientin the upper layer.

Fig. 7. Nitrate budget for the top eight layers of the model (approxim

contributions due to biological uptake, horizontal advection, vertical

4. Discussion

The climatology generated is a useful index towhich individual stations and years can becompared, largely because interannual variationsin physical characteristics and some biologicalfeatures within the Southern Ocean can besubstantial. For example, large interannual varia-tions in ice concentrations among years have beenobserved in all sectors of the Antarctic (Comisoet al., 1993), and the positions of the various frontsin the Antarctic Circumpolar Current changedramatically between years (Moore et al., 1999).Bird and krill populations also fluctuate dramati-cally between years (Knox, 1994). However,interannual changes in phytoplankton biomassand productivity are much more poorly knownbecause of the difficulty of spatial and seasonalvariations. By generating the climatology of theRoss Sea region, variations from this ‘‘mean’’ canbe assessed.

One example of this type of comparison is thecontrast between the nitrate climatology of Feb-ruary (Fig. 3d) with values reported by Smith andNelson (1985) along the coast of Victoria Land.They found two stations where nitrate concentra-tions were below the analytical limits of detection.

ately the upper 100 m) of the Ross Sea polynya region defining

advection and vertical diffusion.

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In contrast, the climatological mean for thisregion is ca. 14 mM, suggesting that during thatone particular season conditions were such toallow phytoplankton growth to a much greaterextent than normal. Because it is now wellestablished that iron plays a paramount role incontrolling seasonal production in the Ross Sea(Sedwick and DiTullio, 1997; Sedwick et al., 2000;Olson et al., 2000), we would suggest that in 1983(the year of the Smith and Nelson (1985)study) the amount of iron released by ice orsediments into the surface waters along the coastof Victoria Land was much greater than normal,which in turn allowed the massive bloom ofdiatoms to grow and accumulate. It is alsopossible that the surface concentrations of ironat the start of the bloom’s onset were greater, butit is difficult to understand how such large(approximately a doubling of iron concentrations)could occur independently of other nutrientconcentrations.

Table 3

Variability of nitrate and silicic acid concentrations within the surface

southern Ross Sea

Nutrient

Mean concentration (mM), entire season, 76�300S, 164�E

Standard deviation

Minima

Maxima

Number of observations

Mean concentration (mM), entire season, 76�300S, 178�W

Standard deviation

Minima

Maxima

Number of observations

Mean concentration (mM), January 19, 76�300S, 164�E

Standard deviation

Minima

Maxima

Number of observations

Mean concentration (mM), January 20–21, 76�300S, 178�W

Standard deviation

Minima

Maxima

Number of observations

Note: Nutrient concentrations were used only at depths less than 30 m

To further inspect interannual variations, acomparison of interannual variability of nitrateand silicic acid concentration data was made fortwo sites in the Ross Sea, 76�300S, 164�E and76�300S, 178�W (Table 3). The variability in thewestern region is substantial, with minima andmaxima of nitrate and silicate on the date ofJanuary 19 being 3.4 and 30.6 mM, and 47.6 and76.0 mM, respectively. Mean nitrate and silicateconcentrations at this location and date were 21.4(79.7) and 66.9 (78.8) mM. Seasonal differenceswere greater for the two nutrients, with meanseasonal concentrations of nitrate and silicic acidbeing 12.0 and 47.3 mM, respectively. Because thisregion experiences more pronounced interannualvariations in ice cover (Comiso et al., 1993), thegreater differences largely result from the effects ofice on irradiance and subsequent phytoplanktongrowth. Conversely, the variability in the centralregion appears to be smaller, with the January 20–21 minima/maxima being 14.3 and 26.5 mM for

layer of two locations (76�300S, 164�E; 76�300S, 178�W) in the

Nitrate Silicic acid

12.0 47.3

7.3 18.3

2.4 16.5

30.6 76.0

83 83

25.1 70.1

5.8 7.2

14.1 50.4

30.6 77.2

166 164

21.4 66.9

9.7 8.8

3.4 47.6

30.6 76.0

11 11

17.7 68.0

3.8 3.1

14.3 65.0

26.5 75.1

17 17

from stations within 70.5� of the location.

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nitrate, and 65.0 and 75.1 mM for silicate (Table 3).Mean concentrations were 17.7 (73.8) and 68.0(73.0) mM for nitrate and silicate, respectively.The two regions exhibited similar mean concen-trations of both nitrate and silicate in mid-January, which is surprising because the centralregion is known to be a site of large Phaeocystis

antarctica blooms, whereas the western site isconsidered to be the site of large diatom blooms(Smith and Nelson, 1985). Mean nitrate concen-tration for the two regions for the entire seasonwere significantly different, however (12.0 vs.25.3 mM, respectively), which suggests that nitrateuptake in the western site continues throughFebruary (and is dominated by diatoms), whereasthe central site experienced net nutrient replenish-ment due to increased vertical mixing and biolo-gical remineralization (and reduced uptake,perhaps due to iron limitation). Clearly, theeastern site had relatively little silicic acid uptake,suggesting that the nitrate removal was attribu-table to P. antarctica.

Inclusion of a variable Si:N uptake ratio isimportant to get realistic seasonal trends of silicicacid. When a constant Si:N uptake ratio (2.0) wasused (rather than the spring value of 0.6 and thesummer value of 4.0), silicic acid concentrations inDecember were substantially lower (by up to10 mM) than those observed in the climatologicalcomposite, but were similar for January andFebruary (data not shown). The December differ-ence likely reflects the importance of the composi-tion of the phytoplankton assemblage on nutrientuptake. Phaeocystis antarctica has been found in anumber of studies to reach its maximum abun-dance in late December and early January(DiTullio and Smith, 1996; Arrigo et al., 1999;Smith and Asper, 2001), whereas diatoms (thegroup responsible for silicic acid uptake) are foundin greatest abundance later in the year. Using amean Si:N uptake apparently allowed for theannual silicic acid uptake to be approximatelycorrect but skewed the seasonal trends.

Primary production can be estimated by anumber of independent methods. The first is byusing the chlorophyll climatology and a modelednitrate concentration and uptake rate, and con-verting the integrated nitrate uptake to carbon

units using the Redfield ratio (C:N ratios of thebulk particulate matter in the Ross Sea generallyconform to this ratio; Arrigo et al., 2000; van Hilstand Smith, 2002). Because nitrate concentrationsnever approach those of the saturation constant,uptake and productivity are largely a function ofthe biomass derived from the chlorophyll clima-tology and the maximum rate of nutrient uptake.We analyzed three areas in the Ross Sea: the RossSea polynya, Terra Nova Bay (the site of the TerraNova Bay polynya), and the entire continentalshelf. The results of this suggest that increase inproductivity occurs at similar times throughoutthe Ross Sea and is greatest in the Ross Seapolynya, where the maximum productivity ex-ceeded 2.5 g C m�2 d�1 in mid-December (Fig. 8a).This value is nearly identical to the maximummeasured by Smith et al. (2000). The maximumproductivity in Terra Nova Bay was slightly lessthan 1 g C m�2 d�1, also similar to that previouslymeasured (Saggiomo et al., 1998). A secondmaximum in Terra Nova Bay occurred as well inlate January, but this was only B0.5 g C m�2 d�1.Maximum productivity in Terra Nova Bay isknown to be delayed relative to that in the RossSea polynya (Arrigo and McClain, 1994), and thisis thought to result from strong katabatic windsthat generate deeper vertical mixing in spring andearly summer. Our results suggest that an earlier,previously unmeasured productivity maximumalso may occur, but because of the use of a time-dependent Vmax estimate, such a maximum needsto be verified by in situ measurements. Themodeled seasonal trends are similar to thosedescribed by Nelson et al. (1996); however, theyestimated the absolute rates to be ca. 1 g C m�2 d�1

over the growing season (Nelson et al., 1996; Table4), whereas the modeled estimate for a similar timeperiod is 0.75 g C m�2 d�1. Differences between thetwo likely result from differences in estimatingnitrate uptake (short-term measurements extrapo-lated over monthly time scales vs. monthlyestimates using a low uptake rate).

A second way to estimate the productivity of theregion is by simply using the nitrate climatology,calculating the net nitrate removal through time,and converting this uptake to carbon units via theRedfield ratio (Fig. 8b). Although the seasonal

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3

2

1

0

2.5

1.5

0.5

26-Oct 25-Nov 25-Dec 24-Jan 23-Feb 25-Mar

Date

Prim

ary

Pro

duct

ivity

(g

C m

-2 d

-1)

Prim

ary

Pro

duct

ivity

(g

C m

-2 d

-1)

Ross Sea Shelf

Ross Sea Polynya

Terra Nova Bay Polynya

1.2

0.8

0.6

0.4

0.2

1

025-Nov 5-Dec 15-Dec 25-Dec 4-Jan 14-Jan 24-Jan

Date

Ross Sea Shelf

Ross Sea Polynya

Terra Nova Bay Polynya

(a)

(b)

Fig. 8. Estimated productivity of the Ross Sea polynya region in the southern Ross Sea, the Terra Nova Bay region, and the entire

Ross Sea continental shelf. The estimates are derived from (a) nitrate uptake that results from the climatological chlorophyll

distributions, and (b) nitrate uptake as assessed from the nitrate climatology. All nitrate concentrations converted to carbon units using

the Redfield ratio.

Table 4

Estimates of mean annual primary production of the Ross Sea

Primary production (g C m�2 y�1) Method of estimation Reference

140–170 Satellite biomass changes Arrigo and McClain (1994)

91–216 Biomass changes Nelson et al. (1996)

200 Nutrient disappearance Smith and Gordon (1997)

200a Satellite biomass estimates and model Arrigo et al. (1998)

98–106 Satellite biomass estimates and model Arrigo et al. (2003)

73a Chlorophyll climatology This study

a Assumed a growing season from November 1 to February 28.

W.O. Smith Jr. et al. / Deep-Sea Research II 50 (2003) 3083–31013096

patterns are less resolved than in the estimate fromthe chlorophyll climatology, the productivityassessed using this approach provides an interest-ing comparison to that derived from the modeled

nitrate uptake. Productivity estimated in TerraNova Bay is within 30% of that estimated fromthe chlorophyll climatology, and that for the entireshelf is within 20% in spring. However, nitrate-

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disappearance productivity exceeds the chloro-phyll-based productivity by a factor of two insummer, which may result from non-Redfielduptake by diatoms in the region (Rubin et al.,1998; Arrigo et al., 1999, 2000). Estimatedproductivity in the Ross Sea polynya shows theopposite trend; that is, nitrate-disappearancebased productivity (relative to chlorophyll-basedproductivity) is 76% and 55% less than thatderived from chlorophyll in spring, respectively,but the two were equal in summer. We believe thatthe lack of temporal resolution in the nitrateclimatology reduces the accuracy of the produc-tivity estimate based on nitrate disappearance, andalso suspect that non-Redfield uptake ratios ofcarbon and nitrogen in this region may influencethis estimate as well.

Because the community loss rate is set at aconstant 0.04 d�1, this also suggests that the lossesincrease in late summer. Indeed, this has beensuggested by Asper and Smith (1999) based onvertical flux data, and by Smith and Asper (2001)based on a one-dimensional nitrogen budget of thesouthern Ross Sea. The causes for the increasedlosses in summer are likely two-fold: increasedaggregate formation at high biomass levels (andhence increased vertical flux of organic matter dueto passive settling of larger particles), and in-creased zooplankton grazing (and the subsequentproduction of rapidly sinking fecal material).Zooplankton in polar regions are typically un-coupled to the unimodal peak in phytoplanktonproduction (Cushing, 1981), and therefore grazingpressure and losses would be expected to lagsignificantly behind production. Unfortunately, noseasonal analysis of grazing pressure in the RossSea presently is available to quantitatively assessthe extent of the zooplankton-mediated losses.

When the model is continued through a fullannual cycle, the nutrient concentrations do notreturn to the observed climatology by earlySeptember, with nitrate concentrations reachingca. 27 mM (data not shown). This suggests thatthere may be an underestimate of advective ordiffusive vertical fluxes into the surface layerduring winter, or that biological recycling (nitrifi-cation) is a quantitatively significant process in re-establishing nitrate concentrations to levels found

in early spring. Nitrification rates are slow in polarwaters (Karl, 1993), but given the relatively longtime periods in winter, even slow rates wouldresult in the significant input of nitrate fromreduced forms. Ammonium concentrations foundin mid-January suggest that ammonium oxidationto nitrate over winter might result in an increase ofca. 1 mM nitrate over the entire water column(Smith and Asper, 2000). However, few data existto quantify the depth of mixing during this period,but if nutrients were not to return to theclimatological mean, then the deficit would con-tinue to increase through time and lead to a highlyunstable condition. Changes to the vertical mixingmodel or inclusion of double diffusion mayincrease surface nutrients over the winter. Despitethese differences, the model generally describedsimilar patterns of nutrient distributions whencompared to the climatological mean, suggestingthat the model provides an adequate (albeitsimplified) description of physical and biologicalprocesses. Furthermore, this minor offset is notcritical because our objective was to modelseasonal patterns rather than interannual varia-tions.

It is also possible to estimate export (heredefined as all organic matter produced within theupper 100 m that has been either remineralized orthat has sunk in particulate form to depths greaterthan 100 m) from the biomass climatology. Wechose five locations to estimate losses: 76�300S,178�W, 73�330S, 176�530E, 76�300S, 167�300E,75�100S, 164�150E (Terra Nova Bay), and72�300S, 172�300E. The production of organicmatter was calculated from the nitrate disappear-ance (sensu Smith and Asper, 2000; Sweeney et al.,2000), and added to the initial particulate organicnitrogen that existed prior to growth. The amountof PON present in the water column at the end ofthe growing season (February 15) was estimatedfrom chlorophyll, and compared to the amountthat should have been present in the water columnhad no losses occurred (Table 5). All units wereconverted to nitrogen, with appropriate conver-sions from chlorophyll using a time-dependentN:chl ratio (Smith et al., 2000). These crudeestimates suggest that during this period of 105days on average 46% of the total organic load had

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Table 5

Estimates of losses of organic matter from the surface layer based on the climatological values of nitrate and chlorophyll of five

locations

Latitude Longitude Final nitrate

(mmol m�2)

Final chlorophyll

(mg m�2)

Nitrogen lost from

surface layer

(mmol m�2)

N remaining/total

production (%)

76�300S 178�W 2436 67.3 349.5 50.4

73�330S 176�530E 2691 31.2 275.6 62.7

76�300S 167�300E 2211 77.5 523.1 56.9

75�100S 164�150E 2282 118.1 249.7 29.4

72�300S 172�300E 2778 46.9 109.3 31.1

Note: Initial integrated (0–100 m) nitrate and chlorophyll concentrations were assumed to be 3125 mmol m�2 and 5 mg m�2,

respectively. An ammonium concentration of 50 mmol m�2 is also assumed to occur at the end of the computed growing season. Period

of growth is from Day 306–411 (Nov. 1–Feb. 15).

W.O. Smith Jr. et al. / Deep-Sea Research II 50 (2003) 3083–31013098

disappeared from the upper 100 m. Furthermore,by assuming that the respiration (remineralization)vertical flux ratio was 3 (that reported by Smithand Asper, 2001), the mean estimated vertical fluxwas B100 mmol N m�2. This value is similar toactual short-term flux rates measured in theSouthern Ross Sea (Asper and Smith, 1999), andalso suggests that the other half of the seasonalproduction (which is remaining in the watercolumn as particulate material) will either beremineralized or sink from the surface layer inlate summer/early autumn. Late summer maximaof vertical fluxes are commonly encountered in theRoss Sea (e.g., Dunbar et al., 1998; Accorneroet al., 1999; Collier et al., 2000), and the estimatesof flux from the climatology is consistent withthese direct measurements.

Model simulations with and without physicalprocesses (Table 2), run to assess the relative roleof physical vs. biological effects, suggested thatthere was relatively little quantitative influence ofphysical processes (advection, vertical diffusion)on the surface concentration of nutrients insummer, although the distribution was noticeablyimpacted by horizontal advection. In addition,both simulations were quite similar to the clima-tological distributions, which implies that themodeled physical processes are realistic approx-imations of those occurring in situ. Some spatialdifferences in the effects were noted, in that someareas showed enhanced biological effects in theabsence of physical processes, whereas othersshowed diminished effects. A large difference was

noted near the Ross Ice Shelf, which suggests thatmore detailed ice shelf processes are required toadequately simulate biological processes in thisregion. Regardless, the comparison shows thedominance of biological uptake in controlling thenutrient concentrations in summer in the Ross Sea.A similar importance in biological uptake has beenshown in other areas of the Southern Ocean as well(Hoppema and Goeyens, 1999; Hoppema et al.,2000). This does not imply that physical processesplay little or no role in regulating nutrientconcentrations and distributions; indeed, physicalprocesses are overwhelmingly important in earlyspring, autumn and winter when biological pro-cesses are minimal.

In conclusion, the climatology generated fornutrients and chlorophyll in the Ross Sea repre-sents the mean seasonal progression and isvaluable in assessing both short-term variationsand long-term changes with respect to observed,historical distributions. Using these data inconjunction with a numerical model also offersinsights into the processes that are important incontrolling organic matter standing stocks in thesurface layer of the Ross Sea. For example,both taxonomic composition and the effectsof iron are important in establishing thequantitative and qualitative patterns of nitrateand silicate distributions. The combination ofboth a three-dimensional biophysical modelwith historically observed distributions confirmsthe hyperproductive nature of the southernRoss Sea.

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Acknowledgements

This research has been supported by NSF grantsOCE-0001799 (WOS), OPP-0087401 (WOS) andOCE-9911731 (EH, JK). We also thank the Officeof Computing and Communications Services atOld Dominion University for the use of the SunHPC 10000 on which the simulations were run.Drs. Guilio Catalano and Douglas Biggs kindlyprovided the data collected as part of the variousItalica and Glacier cruises to the Ross Sea.

References

Accornero, A., Bergamasco, A., Monaco, A., Tucci, S., 1999.

Particle fluxes at the edge of the Ross Ice Shelf: the role of

physical forcing. In: Spezie, G., Manzella, G.M. (Eds.),

Oceanography of the Ross Sea Antarctica. Springer, Milan,

pp. 177–196.

Arrigo, K.R., McClain, C.R., 1994. Spring phytoplankton

production in the western Ross Sea. Science 266, 261–263.

Arrigo, K.R., Worthen, D.L., Schnell, A., Lizotte, M.P., 1998.

Primary production in Southern Ocean waters. Journal of

Geophysical Research 103, 15587–15600.

Arrigo, K.R., Robinson, D., Worthen, D., Dunbar, R.,

DiTullio, G., Van Woert, M., Lizotte, M., 1999. Phyto-

plankton community structure and the drawdown of

nutrients and CO2 in the Southern Ocean. Science 283,

365–367.

Arrigo, K.R., Dunbar, R.B., Robinson, D.H., Worthen, D.L.,

Leventer, A.R., Barry, J., DiTullio, G.R., Van Woert, M.,

Lizotte, M.P., 2000. Phytoplankton taxonomic variability in

nutrient utilization and primary productivity in the Ross

Sea: community structure and the drawdown of nutrients

and CO2 in the Southern Ocean. Journal of Geophysical

Research 105, 8827–8846.

Arrigo, K.R., Worthen, D.L., Robinson, D.H., 2003. A

coupled ocean–ecosystem model of the Ross Sea. Part 2:

iron regulation of phytoplankton taxonomic variability and

primary production. Journal of Geophysical Research 108,

3231 (doi:10.1029/2001JC000856).

Asper, V.A., Smith Jr., W.O., 1999. Particle fluxes during

austral spring and summer in the southern Ross Sea.

Journal of Geophysical Research 104, 5345–5359.

Biggs, D.C., Amos, A.F., 1983. Oceanographic data from the

southwestern Ross Sea, January 1982: STD and nutrient

chemistry programs. Technical Report 83-3-T, Department

of Oceanography, Texas A&M University, 167pp.

Catalano, G., Benedetti, F., 1990. Distribution of nutrients in

the Terra Nova Bay and in the Ross Sea. National Scientific

Commission for Antarctica, Oceanographic Campaign

1987–88, Data Report, I, pp. 61–83.

Catalano, G., Predonzani, S., Ruffini, S., 1997. Dissolved

oxygen and nutrient distribution in the Ross Sea during the

1995 austral summer (RV Italica cruise, Leg 2). In: Faranda,

F.M., Guglielmo, L., Povero, P. (Eds.), National Pro-

gramme for Antarctic Research ROSSMIZE 93–95 Data

Report, pp. 111–134.

Chai, F., Lindley, S.T., Barber, R.T., 1996. Origin and

maintenance of high nitrate condition in the equatorial

Pacific. Deep-Sea Research II 43, 1031–1064.

Cochlan, W.P., Bronk, D.A., 2001. Nitrogen uptake kinetics in

the Ross Sea, Antarctica. Deep-Sea Research II 48,

4127–4153.

Collier, R., Dymond, J., Honjo, S., Manganini, S., Francois,

R., Dunbar, R., 2000. The vertical flux of biogenic and

lithogenic materials in the Ross Sea: moored sediment trap

observations during the US-JGOFS AESOPS study. Deep-

Sea Research II 47, 3491–3520.

Comiso, J.C., McClain, C.R., Sullivan, C.W., Ryan, J.P.,

Leonard, C.L., 1993. Coastal Zone color scanner pigment

concentrations in the Southern Ocean and relationships to

geophysical surface features. Journal of Geophysical Re-

search 98, 2419–2451.

Conkright, M.E., O’Brien, T., Levitus, S., Boyer, T.P.,

Antonov, J., Stephens, C., 1998. World Ocean Atlas 1998,

Vol. 11: Nutrients and Chlorophyll of the Pacific Ocean.

NOAA Atlas NESDIS 36. United States Government

Printing Office, Washington, DC, 245pp.

Cressman, G.P., 1959. An operational objective analysis

scheme. Monthly Weather Review 87, 329–340.

Cushing, D.H., 1981. Temporal variability in production

systems. In: Longhurst, A.R. (Ed.), Analysis of Marine

Ecosystems. Academic Press, New York, pp. 443–472.

Dinniman, M.S., Klinck, J., Smith Jr., W.O., 2003. Cross shelf

exchange in a model of the Ross Sea circulation and

biogeochemistry. Deep-Sea Research II, in press.

DiTullio, G.R., Smith Jr., W.O., 1996. Relationship between

dimethylsulphide and phytoplankton pigment concentra-

tions in the Ross Sea, Antarctica. Deep-Sea Research I 42,

873–892.

Ducklow, H.W., Carlson, C.A., Bates, N.R., Knap, A.H.,

Michaels, A.F., 1995. Dissolved organic carbon as a

component of the biological pump in the North Atlantic

Ocean. Philosophical Transactions of the Royal Society,

London B 348, 161–167.

Dugdale, R.C., Goering, J.J., 1967. Uptake of new and

regenerated forms of nitrogen in primary productivity.

Limnology and Oceanography 12, 196–206.

Dunbar, R.B., Leventer, A.R., Mucciarone, D.A., 1998. Water

column sediment fluxes in the Ross Sea, Antarctica (I):

atmospheric and sea ice forcing. Journal of Geophysical

Research 103, 30741–30759.

El-Sayed, S.Z., Biggs, D.C., Holm-Hansen, O., 1983. Phyto-

plankton standing crop, primary productivity, and near-

surface nitrogenous nutrient fields in the Ross Sea,

Antarctica. Deep-Sea Research 30, 871–886.

Fitzwater, S.E., Johnson, K.S., Gordon, R.M., Coale, K.H.,

Smith Jr., W.O., 2000. Trace metal concentrations in the

ARTICLE IN PRESS

W.O. Smith Jr. et al. / Deep-Sea Research II 50 (2003) 3083–31013100

Ross Sea and their relationship with nutrients and growth.

Deep-Sea Research II 47, 3159–3178.

Goffart, A., Catalano, G., Hecq, J.H., 2000. Factors control-

ling the distribution of diatoms and Phaeocystis in the Ross

Sea. Journal of Marine Systems 27, 161–175.

Gordon, L.I., Codispoti, L.A., Jennings Jr., J.C., Millero, F.J.,

Morrison, J.M., Sweeney, C., 2000. Seasonal evolution of

hydrographic properties in the Ross Sea, Antarctica, 1996–

1997. Deep-Sea Research II 47, 3095–3118.

Hansell, D.A., Carlson, C.A., Bates, N.R., Poisson, A., 1997.

Horizontal and vertical removal of organic carbon in the

equatorial Pacific Ocean: a mass balance assessment. Deep-

Sea Research II 44, 2115–2130.

Hofmann, E.E., Lascara, C.M., 1998. An overview of

interdisciplinary modeling for marine ecosystems. In:

Robinson, A.R., Brink, K.H. (Eds.), The Sea—the Global

Coastal Ocean: Processes and Methods, Vol. 10. Wiley,

New York, pp. 507–540.

Holm-Hansen, O., El-Sayed, S.Z., Franceschini, G.A., Cuhel,

R.L., 1977. Primary production and the factors controlling

phytoplankton growth in the Southern Ocean. In: Llano, G.

(Ed.), Adaptations within Antarctic Ecosystems. Gulf

Publishing Company, Houston, pp. 11–50.

Hoppema, M., Goeyens, L., 1999. Redfield behavior of carbon,

nitrogen and phosphorus depletions in Antarctic surface

water. Limnology and Oceanography 44, 220–224.

Hoppema, M., Goeyens, L., Fahrback, E., 2000. Intense

nutrient removal in the remote area off Larsen Ice Shelf

(Weddell Sea). Polar Biology 23, 85–94.

Hu, S., Smith Jr., W.O., 1998. The effects of irradiance on

nitrate uptake and dissolved organic nitrogen release by

phytoplankton in the Ross Sea, Antarctica. Continental

Shelf Research 18, 971–990.

Hutchins, D.A., Bruland, K.W., 1998. Iron-limited diatom

growth and Si:N uptake ratios in a coastal upwelling

regime. Nature 393, 561–564.

Karl, D.M., 1993. Microbial processes in the Southern Oceans.

In: Friedeman, E.I. (Ed.), Antarctic Microbiology. Wiley-

Liss, New York, pp. 1–63.

Knox, G.A., 1994. The Biology of the Southern Ocean.

Cambridge University Press, Cambridge, GB, 444pp.

Lancelot, C., Hannon, E., Becquevort, S., Veth, C., de Baar,

H.J.W., 2000. Modeling phyto-plankton blooms and carbon

export production in the Southern Ocean: dominant

controls by light and iron in the Atlantic sector in austral

spring 1992. Deep-Sea Research I 47, 1621–1663.

Landry, M.R., Brown, S.L., Selph, K.E., Abbott, M.R.,

Letelier, R.M., Christensen, S., Bidigare, R.R., Casciotti,

K., 2001. Initiation of the spring phytoplankton increase in

the Antarctic Polar Front Zone at 170 W. Journal of

Geophysical Research 106, 13903–13915.

Levitus, S., 1982. Climatological Atlas of the World Ocean.

NOAA Professional Paper 13. US Government Printing

Office, Washington, DC, 173pp.

Louanchi, F., Najjar, R.G., 2000. A global monthly climatol-

ogy of phosphate, nitrate and silicate in the upper ocean:

spring–summer export production and shallow reminerali-

zation. Global Biogeochemical Cycles 14, 957–977.

Markus, T., 1999. Results from an ECMWF-SSM/I forced

mixed layer model of the Southern Ocean. Journal of

Geophysical Research 104, 15603–15620.

Mitchell, B.G., Holm-Hansen, O., 1991. Observations and

modeling of the Antarctic phytoplankton crop in relation to

mixing depth. Deep-Sea Research 38, 981–1007.

Moore, J.K., Abbott, M.R., Richman, J.G., 1999. Location and

dynamics of the Antarctic Polar Front from satellite sea

surface temperature data. Journal of Geophysical Research

104, 3059–3074.

Nelson, D.M., Smith Jr., W.O., 1986. Phytoplankton bloom

dynamics of the western Ross Sea II. Mesoscale cycling of

nitrogen and silicon. Deep-Sea Research 33, 1389–1412.

Nelson, D.M., DeMaster, D.J., Dunbar, R.B., Smith Jr., W.O.,

1996. Cycling of organic carbon and biogenic silica in the

Southern Ocean: estimates of water column and sedimen-

tary fluxes on the Ross Sea continental shelf. Journal of

Geophysical Research 101, 18519–18532.

Olson, R.J., Sosik, H.M., Chekalyuk, A.M., Shalapyonok, A.,

2000. Effects of iron enrichment of phytoplankton in the

Southern Ocean during late summer: active fluorescence

and flow cytometric analyses. Deep-Sea Research II 47,

3179–3200.

Pr!ezelin, B.B., Hofmann, E., Mengelt, C., Klinck J, M., 2000.

The linkage between Upper Circumpolar Deep Water

(UCDW) and phytoplankton assemblages on the West

Antarctic Peninsula continental shelf. Journal of Marine

Research 58, 165–202.

Riebesell, U., Wolf-Gladrow, D.A., 2002. Supply and uptake of

inorganic nutrients. In: Williams, P.J.le B., Thomas, D.N.,

Reynolds, C.S. (Eds.), Phytoplankton Productivity: Carbon

Assimilation in Marine and Freshwater Ecosystems. Black-

well Science, Oxford, GB, pp. 109–140 (Chapter 5).

Rubin, S.I., Takahashi, T., Chipman, D.W., Goddard, J.G.,

1998. Primary productivity and nutrient utilization ratios in

the Pacific sector of the Southern Ocean based on seasonal

changes in seawater chemistry. Deep-Sea Research I 45,

1211–1234.

Saggiomo, V., Carrada, G.C., Mangoni, O., D’Alcala M, R.,

Russo, A., 1998. Spatial and temporal variability of size-

fractionated biomass and primary production in the Ross

Sea (Antarctica) during austral spring and summer. Journal

of Marine Systems 17, 115–128.

Sarmiento, J.L., Le Qu!er!e, C., 1996. Ocean carbon dioxide

uptake in a model of century scale global warming. Science

274, 1346–1350.

Sarmiento, J.L., Hughes, T.M.C., Stouffer, R.J., Manabe, S.,

1998. Simulated response of the ocean carbon cycle to

anthropogenic climate warming. Nature 395, 245–249.

Sedwick, P.N., DiTullio, G.R., 1997. Regulation of algal

blooms in Antarctic shelf waters by the release of iron

from melting sea ice. Geophysical Research Letters 24,

2515–2518.

Sedwick, P.N., DiTullio, G.R., Mackey, D.J., 2000. Iron and

manganese in the Ross Sea, Antarctica: seasonal iron

ARTICLE IN PRESS

W.O. Smith Jr. et al. / Deep-Sea Research II 50 (2003) 3083–3101 3101

limitation in Antarctic shelf waters. Journal of Geophysical

Research 105, 11321–11336.

Smith Jr., W.O., Asper, V.A., 2000. A balanced nitrogen budget

of the surface layer of the southern Ross Sea, Antarctica.

Geophysical Research Letters 27, 2721–2724.

Smith Jr., W.O., Asper, V.A., 2001. The influence of

phytoplankton assemblage composition on biogeochemical

characteristics and cycles in the southern Ross Sea,

Antarctica. Deep-Sea Research I 48, 137–161.

Smith Jr., W.O., Gordon, L.I., 1997. Hyperproductivity of the

Ross Sea (Antarctica) polynya during austral spring.

Geophysical Research Letters 24, 233–236.

Smith Jr., W.O., Nelson, D.M., 1985. Phytoplankton bloom

produced by a receding ice edge in the Ross Sea: spatial

coherence with the density field. Science 227, 163–166.

Smith Jr., W.O., van Hilst, C.M., 2003. Effects of assemblage

composition on the temporal dynamics of carbon and

nitrogen uptake in the Ross Sea. In: DiTullio, G.R.,

Dunbar, R.B. (Eds.), Biogeochemical Cycles in the Ross

Sea. Antarctic Research Series, American Geophysical

Union, Washington, DC, in press.

Smith Jr., W.O., Marra, J., Hiscock, M.R., Barber, R.T., 2000.

The seasonal cycle of phytoplankton biomass and primary

productivity in the Ross Sea, Antarctica. Deep-Sea

Research II 47, 3119–3140.

Sweeney, C., Smith Jr., W.O., Hales, B., Hansell, D.A.,

Carlson, C.A., Codispoti, L.A., Gordon, L.I., Millero,

F.J., Takahashi, T., 2000. Nutrient and TCO2 uptake and

export ratios in the Ross Sea. Deep-Sea Research II 47,

3395–3422.

Takeda, S., 1998. Influence of iron availability on nutrient

consumption ratio of diatoms in oceanic waters. Nature

393, 774–777.

van Hilst, C.M., Smith Jr., W.O., 2002. Photosynthesis/

irradiance relationships in the Ross Sea, Antarctica and

their control by phytoplankton assemblage composition and

environmental factors. Marine Ecology Progress Series 226,

1–12.