Planktonic community structure and carbon cycling in the Arabian Sea as a result of monsoonal

29 Pages·2002·1.04 MB·English

JournalofMarineSystems36(2002)239–267
www.elsevier.com/locate/jmarsys
Planktonic community structure and carbon cycling in the
Arabian Sea as a result of monsoonal forcing:
the application of a generic model
J.C. Blackford*, P.H. Burkill1
PlymouthMarineLaboratory,ProspectPlace,PL13DH,Plymouth,UK
Received9March2001;accepted20June2002
Abstract
TheArabianSeaexhibitsacomplexpattern ofbiogeochemical andecologicaldynamics,whichvarybothseasonally and
spatially. These dynamics have been studied using a one-dimensional vertical hydrodynamic model coupled to a complex
ecosystem model, simulating the annual cycle at three contrasting stations. These stations are characterised by seasonally
upwelling,mixed-layer-deepeninganda-seasonaloligotrophicconditions,respectively,andcoincidewithextensivelymeasured
stations on the two JGOFS ARABESQUE cruises in 1994. The model reproduces many spatial and temporal trends in
production,biomass,physicalandchemicalproperties,bothqualitativelyandquantitativelyandsogivesinsightintothemain
mechanismsresponsibleforthebiogeochemicalandecologicalcomplexity.Monsoonalsystemsaretypifiedbyclassicalfood
web dynamics, whilst intermonsoonal and oligotrophic systems are dominated by the microbial loop. The ecosystem model
(ERSEM),developedfortemperateregions,isfoundtobeapplicabletotheArabianSeasystemwithlittlereparameterisation.
Differencesinin-situphysicalforcingaresufficienttorecreatecontrastingeutrophicandoligotrophicsystems,althoughthelack
oflateraltermsareprobablythegreatestsourceoferrorinthemodel.Physics,nutrients,lightandgrazingareallshowntoplaya
role in controlling production and community structure. Small-celled phytoplanktons are predicted to be dominant and sub-
surfacechlorophyllmaximaarerobustcentersofproductionduringintermonsoonperiods.Analysisofcarbonfluxesindicatethat
physically driven outgassing of CO predominates in monsoonal upwellingsystems but ecological activity may significantly
2
moderateCO outgassingintheArabianSeainterior.
2
D2002Elsevier ScienceB.V.All rights reserved.
Keywords:Ecologicalmodeling;ArabianSea;Carboncycle;Planktoncommunity;1Dwatercolumnmodel
1. Introduction
* Corresponding author. Tel.: [phone]; fax: +44- TheArabianSea(Fig.1)isanunusualandcomplex
1752-633101. ocean basin. Bounded to the north, west and east by
E-mailaddress:[email protected](J.C.Blackford).
land and exceeding depths of 4000 m and although
1 Present address: Southampton Oceanography Centre, Uni-
tropical, the basin is continually influenced by the
versity of Southampton, Waterfront Campus, Southampton SO14
3ZH,UK. seasonally reversing monsoonal winds (Swallow,
0924-7963/02/$-seefrontmatterD2002ElsevierScienceB.V.Allrightsreserved.
PII:S0924-7963(02)00182-3
240 J.C.Blackford,P.H.Burkill/JournalofMarineSystems36(2002)239–267
Fig.1.GeographicalpositionofthemodelledstationsintheArabianSea.
1991). These winds produce complete reversal of the satellite derived, ocean colour images of the basin.
surface currents and generate a range of contrasting These have shown accumulation of high chlorophyll
oceanographicconditions(Burkilletal.,1993a).Thus concentrations at the end of the SWM with lower
surfaceconditionscanrangefromeutrophydrivenby concentrations at other times (Banse and English,
seasonal upwelling through to oligotrophy generated 2000).ForthemainSWMperiod,satelliteinformation
by aseasonal strong stratification (Yoder et al., 1993). has been poor because of the dense monsoon cloud
Between June and September, the South West Mon- base and the difficulties of working at sea during the
soon (SWM) blows as the concentrated, low-level monsoon.Tobetterunderstandthesystemparticularly
Findlater Jet (Findlater, 1974). This creates strong at this time, international biogeochemical process
Ekman transport that induces upwelling of inorgani- studieswereplannedaspartoftheJointGlobalOcean
cally rich deep water in the north–west of the region FluxStudy,andtheresultsarenowbeingpublished,for
(Kindle, 2002), with downwelling and mixed layer exampleinDeep-SeaResearch(Burkilletal.,1993a,b;
deepening observed to the south–east of the jet. Van Weering et al., 1997; Smith, 1998, 1999, 2000,
Although more moderate, the North–East Monsoon 2001; Burkill, 1999a; Gage et al., 2000; Pfannkuche
(NEM,December–February)alsoentrainsdeepwater andLochte,2000)withasynthesisreportproducedby
into the photic zone. By contrast, the inter-monsoon Watts et al. (2002). Some of the results from these
periods, with weak and variable winds permit the studies are surprising. Although we now know that
development of well-stratified systems largely devoid primaryproductioncanreach4gCm(cid:1)2day(cid:1)1inthe
of nutrients in the surface layer. In the south of the vicinity of the Omani coast at the end of SWM
region, away from the influence of the monsoon (Savidge and Gilpin, 1999), production during the
winds, seasonal mixing is slight, with thermal strat- SWMcanbelowerthanduringthemainNEMperiod
ificationandadeepnutriclinepredominatingthrough- in the North East of the region (Marra et al., 1998;
outthe year (Schott andMcCreary, 2001). Gundersonetal.,1998)wheredeepconvectivemixing
SWM induced upwelling has been considered to duetocoldwindsblowingofftheIndiansubcontinent
generatethehighestratesofprimaryproductionwhile cangenerateproductionratesthataveragemorethan1
the NEM has been thought to be biologically less gCm(cid:1)2day(cid:1)1overtheseason(Wiggertetal.,2000).
dynamic.Much of this understanding has arisen from Similarlyexperimentalstudiesatseahaveshownthat
J.C.Blackford,P.H.Burkill/JournalofMarineSystems36(2002)239–267 241
phytoplankton growth rates were similar during both CO partialpressuresinsurfacewaters(Mintropetal.,
2
monsoons(Landryetal.,1998). 1999),whichenhancethefluxofcarbondioxidetothe
During the stratified inter-monsoonal periods deep atmosphere.Highwindspeedsalsoincreasetherateof
chlorophyll maxima are observed at depths of 40–60 exchange between atmosphere and ocean. The high
m. In the offshore, oligotrophic regions, deep chlor- rates of primary production, and its subsequent respi-
ophyllmaximaareobservedtypicallyataround80m ration ordecomposition,may howeverinfluence CO
2
(Savidge and Gilpin, 1999). In oligotrophic areas and levelsinthephoticzone.Physicallymediatedchanges
duringtheintermonsoon,theecologicalcommunityis in salinity and the biological influence on total alka-
dominated by smaller cells (Jochem et al., 1993; linityviaNspeciationmayalsoacttomodifypCO in
2
Burkill et al., 1993b) and recycling of carbon and surface waters. In well-mixed regions that experience
nutrientswithinthephoticzoneisalsoobservedtobe downwelling, the high levels of entrainment driven
animportantfeature.Duringthemonsoons,largecells primary production may lead to CO drawdown.
2
such as diatoms and subsequently their meso-grazers WhereEkmanpumpingisslightorabsentandsurface
contributemoretocycling(Owensetal.,1993;Tarran primary production small, air–sea fluxes may be less
et al., 1999). Also of importance is the exudation of significant. Sinking of a significant proportion of
dissolved organic carbon (DOC) and subsequent sec- production is also observed (Buesseler et al., 1998),
ondary production via bacterial utilisation, which, seemingly associated with large cell communities in
although less variable, plays a significant part in the wake of monsoon events. Garrison et al. (2000)
carbon cycling in the region (Pomroy and Joint, states that considerable evidence links carbon cycling
1999; Ducklow, 1993). andexport tofood web structure.
The biogeochemical response to the seasonally This study aims, by use of a coupled ecosystem-
reversing monsoonal forcing is complex. Studies on physical model, to reproduce the ecological observa-
carbon dioxide in the Arabian Sea have shown a tions and quantify the biogeochemical fluxes of car-
substantial increase in dissolved inorganic carbon in bon in the Arabian Sea as they vary on both seasonal
thecoastalregionsduetostrongupwellingintheSW and spatial scales. Given the complexity exhibited by
monsoon. This was also accompanied by very high this system it isimportantto use an ecosystem model
Fig.2.Theecosystemmodelflowdiagramindicatingthecarbonandnutrientpathwaysbetweenthefunctionalgroups.
242 J.C.Blackford,P.H.Burkill/JournalofMarineSystems36(2002)239–267
capable of reproducing the variety of food web cruises held in 1994 as part of the international
structures found in the region. Hence the choice of JGOFS Arabian Sea Process Study (Burkill, 1999b).
the European Regional Seas Ecosystem Model The first cruise sampled the late SWM period, whilst
(ERSEM, Baretta et al., 1995; Fig. 2) that simulates the second cruise sampled the autumn inter-monsoon
the cycling of carbon, nitrogen, phosphorous and and early Northeast monsoon transition (INEM
silicon within size-resolved phytoplankton and zoo- cruise). Whilst the goal is to replicate and elucidate
plankton communities and the microbial loop. In this theArabesquecruises dataset,referenceisalsomade
respect, the study extends on previous modelling of tothe1994–1996USJGOFSArabianSeaexpedition
the region that has employed simpler representations (Smith et al., 1998a), which sampled a qualitatively
oftheecosystem(e.g.McCrearyetal.,1996;Keen et similar transect from the coast of Oman to the
al., 1997; Ryabchenko et al., 1998; McCreary et al., Oceanic interior. Results from the US JGOFS and
2001). The compromise employed here, in order to ARABESQUE cruises are generally qualitatively and
keepthestudycomputationallytractable,butalsodue quantitatively similar (Garrison et al., 2000).
to the lack of boundary conditions is to confine the Thephysicalmodelsystemutilisestheequationsof
studytoafinallyresolved1Dverticalphysicalmodel theMellor–Yamadaturbulenceclosuremodelandthe
andomitallhorizontalprocesseswiththeexceptionof vertical diffusion submodel of the Princeton Ocean
upwelling. Although this lack of horizontal termsisa Model (Blumberg and Mellor, 1980; Mellor and
significant omission form the model, studies have Yamada, 1982). This coupled Princeton/Mellor–
shown that local forcing is the dominant mediator of Yamada/ERSEMmodelhasbeenappliedsuccessfully
water column dynamics in the region during all but to water columns in the Adriatic (Allen et al., 1998;
the latter stages of the southwest monsoon (Fischer, Vichietal.,1998a,b)andtheMediterraneanSea(Allen
2000; Rochford et al., 2000). etal.,inpress),butnotpreviouslytotropicalregions.
Anumberofquestionsarealsoposedbythisstudy.
Firstly, can the ecological model, developed for tem-
peratesystems,reproducethedynamicsoftheArabian 2. The model
Sea system? Secondly, to what extent can differences
inin-situphysicalforcinggeneratethecomplextrends 2.1. Physics and physical forcing
in community structure across the region without
recourse to advective mechanisms? Thirdly, what The Princeton/Mellor–Yamada physical model
mechanismscausespecificcommunitytypestoestab- determines vertical temperature, turbulent kinetic
lish? Finally, does regional productivity influence the energy and diffusion coefficient profiles. The model
Arabian Sea’sability tobe a source or sink of CO ? isforcedbyseasurfacetemperature,salinityandwind
2
The coupled model has been applied to three stress fields for 1994. Surface wind vectors are taken
contrasting stations in the Arabian Sea (Fig. 1, Table from the ECMWF (European Centre for Medium-
1), which range from seasonally upwelling to near range Weather Forecasts) model with a resolution of
a-seasonal oligotrophy. These stations were exten- 12 h (Fig. 3). Daily values of sea surface temperature
sively sampled by the two UK JGOFS ‘‘Arabesque’’ are derived from the Comprehensive Ocean Atmos-
phere DataSet(COADS)usingmonthlymean values
averaged over the years 1993–1995. The inaccuracy
Table1
Space–timecoordinatesofthemodelledArabesquecruisestations inmodelledsurfaceheatfluxdata(Welleretal.,1998)
and lack of a measured time series has precluded its
Station Latitude Longitude Depth Arabesquecruise:
(jN) (jE) datesonstation,1994 use here. Surface salinities are derived from the US
JGOFS database using qualitatively similar stations
C210 C212
(Table 2). Incident solar radiation is calculated as a
A1 19 59 3397 4–7Sept., 21–26Nov.
functionoflatitudeanddaylength(DobsonandSmith,
30Sept.
A3 16 62 3927 13–14Sept., 30–6Nov/Dec. 1988), modified by monthly mean values of cloud
28Sept. coveragainderivedfromtheCOADS1993–1995data
A7 8 67 4705 19–21Sept. 10–13Dec. set.Backgroundlightextinctioncoefficientshavebeen
J.C.Blackford,P.H.Burkill/JournalofMarineSystems36(2002)239–267 243
Fig.3.Annualcycleofwindspeedanddirectionfor(a)stationA1,(b)A3,(c)A7,asderivedfromtheECMWFmodel.DueNorthequatesto
verticallyupwards,Westtotheleft,etc.
chosen to fit the 1% light depths measured on station vat (1986), which differentiates between a smooth
(Table 2). surface regime (wind speed<3.6 m s(cid:1)1), a rough
Thephysicalmodelconsidersthetop200mofthe surface regime (3.6–13.0 ms(cid:1)1) andbreaking waves
watercolumndividedinto40equallayersof5m.The (>13.0 m s(cid:1)1). Oxygen saturation is calculated from
lower boundaryisconsidered tobeadiabaticwith the theformulaofWeiss(1970)whilstthesurfaceaeration
exception of nutrients, CO , O , temperature and rateusestheempiricalformuladescribedinAllenetal.
2 2
salinity, which are held to constant values (Table 2). (1998).
At the upper boundary atmospheric exchange of CO InordertoreproducetheEkmanderivedupwelling
2
and O are modelled. The partial pressure of CO in observed in the region for station A1, an additional
2 2
the atmosphere is parameterised from Goyet et al. vertical velocity has been parameterised from wind
(1998)intherange335.0–355.0Aatmwithminimum speed and direction. The Princeton model derives
values recorded from October to December and max- horizontal velocities for each layer (I) which may be
imum values recorded in January and February. Car- equated to a lateral loss of water mass (A), a propor-
I
bonatechemistryandthepartialpressureofCO inthe tionofwhich(p)isreplacedbywaterupwellingfrom
2
water are calculated using the equations described in below,theremainderbylateraladvectivegains.Sofor
Tayloretal.(1991),whichutilisetheHansson(1973) each layer, with U representing upwelling loss and
I
equilibriumcoefficientsandWeiss’(1974)calculation U upwellinggain:
I(cid:1)1
of CO solubility. In the absence of modelled pH,
2 U ¼U þpA
salinitynormalizedtotalalkalinityistakenfromMill- I(cid:1)1 I I
eroetal.(1998) (NTA=2290Amolkg(cid:1)1)andmodi- The constant p is chosen to give appropriate vertical
fied according to the surface salinity. Gas transfer upwellingvelocities,inthiscase2mday(cid:1)1at100m
piston velocity is parameterised from Liss and Merli- fromShietal.(2000).Upwellingisassumedtooccur
244 J.C.Blackford,P.H.Burkill/JournalofMarineSystems36(2002)239–267
Table2 Arabesque cruises (Burkill, 1999b). These wind pat-
Physical parameters and boundary conditions applied to each ternsaretheprimaryinfluenceonthephysicalstructure
modelledstation
ofthewatercolumn,itsseasonalityandhenceecolog-
Unit Station icalactivity.
A1 A3 A7 At station A1 (Fig. 3a), the (ECMWF model) SW
Physical monsoon initially forms in May and following a
Background Amol 1.0e(cid:1)5 1.0e(cid:1)5 1.0e(cid:1)5 breakdown in early June becomes established from
viscosity mid-Juneonwards.Windspeedsexceed13ms(cid:1)1for
Background m(cid:1)1 0.04 0.04 0.04
the remainder of June, July and the first half of
extinction
Backgroundsilt mg(cid:7)m(cid:1)3 750.0 350.0 250.0 August, thereafter dropping steadily, although the jet
maintainsitsdirectionuntilmid-September.Theinter-
Surface monsoonlastsonlyamonthwiththeNEwindpattern
pCO2(air) Aatm 350.0 350.0 350.0 establishing itself by mid-October, breaking down in
Salinitymax psu 36.40 36.50 36.65
early December and thereafter intermittent until the
Salinitymin psu 35.70 36.00 35.25
end of January. Wind speeds are significantly less
Lowerboundary whencomparedwiththeSWmonsoon.AtstationA3
Temperature jC 15.0 15.0 14.0 (Fig. 3b), the SW monsoon starts earlier, lasts longer
Salinity psu 35.8 35.8 35.3 andhasconsistentlyhigherwindspeeds(>15ms(cid:1)1)
Oxygen mmol(cid:7)m(cid:1)2 5.0 5.0 10.0
than at A1. Additionally the NE monsoon has faster
Carbondioxide mmol(cid:7)m(cid:1)2 2250.0 2250.0 2250.0
Phosphate mmol(cid:7)m(cid:1)2 2.30 2.30 2.30 mean wind speeds and is more consistent than at A1.
Nitrate mmol(cid:7)m(cid:1)2 25.0 25.0 25.0 At station A7 (Fig. 3c), wind speeds are low and the
Ammonium mmol(cid:7)m(cid:1)2 0.0 0.0 0.0 SWmonsoonmuchlessdistinctthanateitherstations
Silicate mmol(cid:7)m(cid:1)2 30.0 30.0 30.0 A1 or A3.
only when wind direction veers within 18j of true 2.3. The ecosystem model
south–west. This reproduces the observed seasonal
signal of upwelling in the region well (Halpern et al., The ecosystem model applied here is the ERSEM
1998; Rixen et al., 2000). The resulting upwelling model (Baretta et al. 1995, Fig. 2) which has been
velocities for station A1 develop from May, peak in appliedinavarietyofphysicalcontextsfrom1Dto3D
July and subside by mid-September. The resulting including the North Sea (Patsch and Radach, 1997;
change in concentration for any state variable (C) is Lenhart et al., 1997; Broekhuizen et al., 1995), the
I
therefore given by: AdriaticSea(Allenetal.,1998;Vichietal.,1998a,b)
and the Mediterranean Sea (Zavaterelli et al., 2000;
DC ¼U (cid:4)C (cid:1)ðU þpA Þ(cid:4)C
I I(cid:1)1 I(cid:1)1 I I I Allen et al., in press). For this study, the pelagic
Thus simulations including upwelling are not conser- components of ERSEM have been used. These and
vativeandexperiencehorizontal lossterms aswell as themodificationsspecifictotheArabianSeastudyare
verticalgains.Thesimulationofdownwellingismore briefly described. A mathematical description of
problematic as horizontal boundary conditions are ERSEM can be found in the two ERSEM special
vital to formulating inputs to the system. With this issues (Baretta et al., 1995; Ebenho¨h et al., 1997 and
information unavailable a simulation of downwelling subsequent papers), the World Wide Web (http://
hasnot been attempted. www.pml.ac.uk/ecomodels/ersem.htm) and particu-
larly in theindividual papers cited below.
2.2. Wind forcing ERSEM is conceived as a generic model, which
when applied on a basin scale should be capable of
TheECMWFmodelprovidesarealisticspatialand correctly simulating the spatial pattern of ecological
temporal distribution of wind vectors for the Arabian fluxes throughout the seasonal cycle and across
Sea basin (Weller et al., 1998) (Fig. 3), which are in eutrophic to oligotrophic gradients (Baretta-Bekker
close agreement with the winds measured during the et al., 1997). The model uses three principle units
J.C.Blackford,P.H.Burkill/JournalofMarineSystems36(2002)239–267 245
of currency—carbon, nitrogen and phosphorus—with be more readably degradable by bacteria, due to a
each functional group containing these three pools. higher surface area to volume ratio) and has a lower
Theinclusionofthesilicatecycleallowsadistinction sedimentation rate than its larger counterpart. The
between diatom and non-diatom production. Inor- dissolved fraction is divided into labile and semi-
ganic nitrogen is sub-divided into ammonium and labile fractions, with DOM production being divided
nitratecompartmentsenablingthedistinctionbetween equally into each. This allows at least a crude repre-
new and recycled production. sentation of the range of organic compounds in the
Fourfunctionalgroupsdescribethephytoplankton, dissolved fraction, some of which may be directly
nominally picophytoplankton characterised as less taken up by bacteria, some of which requires further
than 2 Am diameter, flagellates (between 2 and 20 degradation before bacterial utilization. Parameters
Am), dinoflagellates (greater than 20 Am) and dia- relating to POM and DOM are included in Table 3.
toms. Phytoplankton dynamics are mediated by pho- Bacteria and heterotrophicflagellates represent the
tosynthesis (as a function of temperature and light microbial loop (Baretta-Bekker et al., 1995, 1997).
availability), respiration (both basal and active), Bacteria utilise labile DOM and are also responsible
excretion (nutrient-stressed and active), lysis, mortal- for the degradation of POM to DOM. Semi labile
ity and predation. Phytoplankton contain internal DOMisconsideredtobecomelabileattherateof1%
nutrientpoolsandthusvaryingC/N/Pratios.Nutrient per day. Bacteria compete with phytoplankton for
uptake is a function of the difference between the nutrients andarepredatedbyheterotrophicflagellates
internal and external pools (Ebenho¨h et al., 1997).
Two size classes, the micro- andmesozooplankton
represent zooplankton. The processes of ingestion,
Table3
respiration, excretion and mortality contribute to the Bacteriamodelparameters
overallgrowthrateofthepopulation.Microzooplank-
Description Unit Bacteria
ton, with variable internal C/N/P ratios (Baretta-Bek-
Assimilationrateat10jC day(cid:1)1 8.38
ker et al., 1995, 1997) predate on picophytoplankton,
Halfsaturationoxygenlimitation – 0.3125
flagellates and bacteria, whilst the mesozooplankton Fractionofsmalldetritus – 0.05
compete for flagellates but also predate on the dia- availableforB1
toms and dinoflagellates. Mesozooplankton are trea- Fractionoflargedetritus – 0.005
availableforB1
ted as a biomass based predation model, identical in
Assimilationefficiency – 0.4
construct to the microzooplankton description. Given
Assimilationefficiencyatlow – 0.2
the lack of diurnal processes and the lack of dynamic oxygenconcs
mesozooplankton predators in the current application Basalrespirationat10jC day(cid:1)1 0.3
the case for developing a vertical migration meso- Mortalityrate day(cid:1)1 0.05
Maxcell-quotumN mmolN 0.0126
zooplankton model is slight. Further, given the con-
(mgC)(cid:1)1
sistent warm temperatures in the region, it is
Maxcell-quotumP mmolP 0.000786
hypothesised that mesozooplankton are more respon- (mgC)(cid:1)1
sive than populations in cold temperate regions MichaelisconstantforPuptake mmolPm(cid:1)3 0.5
(Roman et al., 2000) and so are more readily mod- MichaelisconstantforNuptake mmolNm(cid:1)3 1.0
C/Nratio(Redfield) – 6.625
elled by a simple biomass approach.
Dissolutionofdissolvedorganics day(cid:1)1 0.05
Excretion and lysis products from all the ecolog-
toinorganics
ical functional groups appear as both dissolved and Relativenitrificationrate day(cid:1)1 0.05
particulate organic matter (DOM and POM), each of Sedimentconcfor0.01day(cid:1)1 mgm(cid:1)3 2000.0
which are here sub-divided into two classes. The nitrificationrate
Rateofconversionofsemi-labile day(cid:1)1 0.01
particulates are divided into large and small catego-
tolabileDOM
ries, the larger plankton (mesozooplankton, diatoms, Sedimentationrateoflarge mday(cid:1)1 7.5
dinoflagellates, microzooplankton) contribute to the POMclass
large POM class with the smaller plankton producing Sedimentationrateofsmall mday(cid:1)1 0.3
the smaller POM. The smaller POM is considered to POMclass
246 J.C.Blackford,P.H.Burkill/JournalofMarineSystems36(2002)239–267
Table4 data,eachmodelledwatercolumnhasbeenrunforat
Opticalphytoplanktonparameters least20yearsusingrepeatingforcingfunctionsinorder
Description Unit Value toremoveanyperturbationsduetoinitialconditions.
Minimumvalueofoptimalirradiance wm(cid:1)2 4.00
Maximumdailyshiftinoptimalirradiance – 0.25
Photosyntheticallyavailableirradiance – 0.50 3. Model results
Adaptationdepth m 10.00
3.1. Physical variables
that are in turn grazed by the larger zooplankton. All
the consumers are also considered to graze within Thephysicalmodelproducesgoodapproximations
their functional group and pseudo cannibalistic terms to observed mixed layer depths (Figs. 4a and 5). The
areincluded.Fig.2summarisestheinteractionsofthe annual cycle of thermal mixing and stratification
functional groups. Ecosystem parametersaregiven in produced by the model (Fig. 6a) agrees well with
Tables 3–7. trends reported for the region (Angel, 1984; Gardner
The simulations have been made using SESAME et al., 1999). Stations A1 and A3 both exhibit strong
(SoftwareEnvironmentforSimulationandAnalysisof stratification during the inter-monsoon periods, with
MarineEcosystems;Ruardijetal.,1995).Thephysical pronounced mixing events associated with the SW
model uses a semi-implicit finite difference scheme monsoon and to a lesser extent the NE monsoon.
forward in time and centered in space. The net trans- Duringthemonsoons,thebaseoftheeuphoticzoneis
portofthebiologicalvariablesarecalculatedusingthe in the mixed layer, whilst during the inter-monsoon
physical model and then passed into SESAME where periods it lies in the thermocline, consistent with
theyareintegratedalongwiththebiogeochemicalrates Brock et al. (1993). The SWM Arabesque cruise
ofchange using avariabletimestep Euler method. coincideswithaperiodofrapiddecreaseinsimulated
mixed layer depth at both stations A1 and A3.
2.4. Initial conditions Relaxation after mixing events appears to be reason-
ably rapid. The INEM cruise coincides with the end
Startingwithverticaldistributionsofphysics,chem- of a fairly stable simulated thermal structure and the
istry and biology derived from literature and cruise initial mixed layer deepening associated with the
Table5
Phytoplanktonmodelparameters
Description Unit Diatoms Flagellates Picoplankton Dinoflagellates
Assimilationrate(10jC) day(cid:1)1 2.0 2.25 3.15 1.6
Basalrespiration(10jC) day(cid:1)1 0.2 0.2 0.2 0.2
Exudationundernut.stress – 0.05 0.10 0.15 0.05
Activityrespiration – 0.2 0.45 0.5 0.45
RedfieldN/Cratio mmolN(mgC)(cid:1)1 0.0126 0.0126 0.0126 0.0126
MinimalN/Cratio mmolN(mgC)(cid:1)1 0.00687 0.00687 0.00687 0.00687
MaximumN/Cratio mmolN(mgC)(cid:1)1 0.0252 0.0252 0.0252 0.0252
RedfieldP/Cratio mmolP(mgC)(cid:1)1 0.786e(cid:1)3 0.786e(cid:1)3 0.786e(cid:1)3 0.786e(cid:1)3
MinimalP/Cratio mmolP(mgC)(cid:1)1 0.428e(cid:1)3 0.428e(cid:1)3 0.428e(cid:1)3 0.428e(cid:1)3
MaximumP/Cratio mmolP(mgC)(cid:1)1 0.157e(cid:1)2 0.157e(cid:1)2 0.157e(cid:1)2 0.157e(cid:1)2
AffinityforNO (mgC)(cid:1)1day(cid:1)1 0.0025 0.0025 0.0025 0.0025
3
AffinityforNH (mgC)(cid:1)1day(cid:1)1 0.01 0.01 0.015 0.01
4
AffinityforPO (mgC)(cid:1)1day(cid:1)1 0.0025 0.0025 0.0025 0.0025
4
Nutrientstressthreshold – 0.70 0.75 0.75 0.75
Nutrientstresssedimentationrate mday(cid:1)1 5.0 0.0 0.0 5.0
Minimallysisrate day(cid:1)1 0.05 0.05 0.05 0.05
SiuptakeMichaelisconstant mmolSim(cid:1)3 0.3 – – –
StandardSi/Cratio mmolSi(mgC)(cid:1)1 0.03 – – –
J.C.Blackford,P.H.Burkill/JournalofMarineSystems36(2002)239–267 247
Table6
Zooplanktonmodelparameters
Description Unit Heterotrophicflagellates Microzooplankton Mesozooplankton
Assimilationrateat10jC day(cid:1)1 1.63 0.8 0.33
Foodconcentrationwhererelativeuptakeis0.5 mgCm(cid:1)3 120.0 80.0 40.0
Assimilationefficiency – 0.4 0.5 0.6
FractionofexcretiongoingtoDOM – 0.5 0.5 0.5
Basalrespirationrateat10jC day(cid:1)1 0.02 0.02 0.02
Oxygensaturationwhererespirationis0.5 mmolm(cid:1)3 7.8125 7.8125 7.8125
Excretedfractionofuptake – 0.5 0.5 0.5
Mortalityduetooxygenlimitation day(cid:1)1 0.25 0.25 0.25
Temperatureindependentmortality day(cid:1)1 0.05 0.05 0.075
Max.quotumN/C mmolN(mgC)(cid:1)1 0.0167 0.0167
Max.quotumP/C mmolP(mgC)(cid:1)1 0.001 0.001
Lowerthreshold(mgCm(cid:1)3)forfeeding mgCm(cid:1)3 15.0 10.0 1.0
DampingcoefficientinN-excr. day(cid:1)1 0.5 0.5
DampingcoefficientinP-excr. day(cid:1)1 0.5 0.5
onset of the NEM. Annual cycles of mixed layer 7a). Modelled surface nitrate at A3 during the SWM
depth and euphotic depth for A3 closely match the cruise period are lower than measured, (<0.5 mmol
mooring data for the similarly located US JGOFS m(cid:1)3c/w>5mmolm(cid:1)3).Duringtheinter-monsoons
mooring (Kinkade et al., 2001). Station A7 exhibits a and at the permanently oligotrophic station A7, mod-
deeper, essentially permanent thermal stratification in elled surface levels of nitrate are extremely low and
the absence of strong wind forcing. correspondverycloselywithmeasuredvalues(<0.25
mmolm(cid:1)3atA1, <0.1mmol(cid:7)m(cid:1)3atA3andA7),as
3.2. Nutrients do the nutricline depths as evidenced in Fig. 7d–f.
Both modelled and observed N/P ratios are low
The modelled nitrate cycle (Fig. 6b) and modelled (<10.0) indicating phosphate limitation is not a fea-
profiles validated by measurements (Fig. 7) show a ture ofthe region.
progressive deepening of thenutricline from North to TherangeofammoniumasmeasuredontheSWM
Souththatisdisturbedonlybythemonsoonalmixing cruise is well reproduced by the model, concentra-
events. At A1 modelled surface concentrations of tionspeakat4.07mmol(cid:7)m(cid:1)3atA1,1.52mmolm(cid:1)3
nitrateexceed5mmol(cid:7)m(cid:1)3duringtheSWmonsoon, at A3 and 0.68 mmol m(cid:1)3 at A7, comparing with
comparingwellwithobservedvaluesintherange3–7 measured peak values of 4.05, 1.91 and 0.74, respec-
mmol(cid:7)m(cid:1)3 (Woodward et al., 1999). The position of tively (Woodward et al., 1999). In contrast with
thenutriclinealsoagreeswellwithmeasurements(Fig. measurements that show a more diffuse distribution
in the surface mixed layer, albeit highly variable,
modelled ammonium exhibits a sub-surface maxima
Table7
at all stations, deepening progressively with distance
Feeding(preference)matrix
from the Omani coast. Peak ammonium concentra-
From To
tions are typically found above the nitrate nutricline
Heterotrophs Microzoos Mesozoos and just below the areas of peak phytoplankton
Bacteria 1.0 0.5 – concentration.
Picophytoplankton 1.0 1.0 0.1 Modelled silicate profiles show good agreement
Flagellates – 1.0 1.0
withdataatA1andA7withbothsurfacemixedlayer
Diatoms – – 1.0
concentrations and nutricline depth corresponding to
Dinoflagellates – – 1.0
Heterotrophicflagellates 0.2 1.0 0.5 measurements (Woodward et al., 1999). A similar
Microzooplankton – 0.2 1.0 mismatch as observed with the nitrate is evident at
Mesozooplankton – – 0.2 A3, modelled surface layer silicate during the SWM
248 J.C.Blackford,P.H.Burkill/JournalofMarineSystems36(2002)239–267
Fig.4.ComparisonsofmodelresultswithdatafromtheArabesquecruises;(a)1%lightdepth(m),(b)mixedlayerdepth(m),(c)phytoplankton
biomass(gCm(cid:1)2),(d)zooplanktonbiomass(gCm(cid:1)2),(e)bacterialbiomass(gCm(cid:1)2),(f)primaryproduction(gCm(cid:1)2d(cid:1)1),(g)bacterial
production(gCm(cid:1)2day(cid:1)1).Modelledvaluesaregivenonthex-axis,observationsonthey-axis.Thesolidlinerepresents1:1correspondence.
Thebarson(f)and(g)representtherangeofmeasureddata.
beingtoolow(0.4c/w1.7mmolm(cid:1)3)andnutricline agreementwith observeddeepchlorophyllmaximaat
depth too deep. 35, 60 and 70 m, respectively (Barlow et al., 1999;
Savidge and Gilpin, 1999) (Fig. 8a). The biomass
3.3. Primary producers associatedwiththedeepmaximadeclinewithdistance
from the Omani coast, at the oligotrophic A7 being
At each modelled station, inter-monsoonal periods about one third that of the biomass at A1. Modelled
arecharacterisedbydeepproduction/biomassmaxima monsoonal periods are characterised by surface
at35m(A1),55m(A3)and75m(A7),inreasonable blooms at A1 and A3. In agreement with data the