J. Plankton Res. 2007 Albaina 851 70

Fine scale zooplankton distribution inthe Bay of Biscay in spring 2004

AITOR ALBAINA* AND XABIER IRIGOIEN

MARINE RESEARCH DIVISION, AZTI FOUNDATION, HERRERA KAIA PORTUALDE, Z/G 20110, PASAIA (GIPUZKOA), SPAIN

*CORRESPONDING AUTHOR: [email protected]

Received January 29, 2007; accepted in principle July 19, 2007; accepted for publication August 9, 2007; published online August 16, 2007

Communicating editor: K.J. Flynn

A fine scale spatial resolution survey (3 15 nautical miles) was conducted during May 2004in the Bay of Biscay (43.3246.128N and 1.294.318W), to study the zooplankton commu-nity during the onset of spring stratification. Cluster analysis classified the 45 most abundant taxainto seven major groups. In the southern part of the surveyed area, a front separating neritic watersfrom eddies off the shelf delimited distinct zooplankton communities. On the northern side of thesurveyed area, river plumes and the generation of internal waves over the shelf break were the mainmesoscale structures determining the composition and abundance of the zooplankton assemblages.Canonical correspondence analysis (CCA) and generalized additive models (GAMs) were used toinvestigate the relationship between zooplankton species distribution and selected environmentalvariables (sea surface temperature and salinity along with water column stratification and fluor-escence pattern). Surface salinity and stratification index were the variables explaining the higherpercentage of the deviance. The results of the survey conducted during May 2004 in the Bayof Biscay suggest that a limited number of environmental variables may be sufficient to attemptstatistical modeling of zooplankton distribution.

INTRODUCTION

Peaks in plankton biomass and species aggregationsappear to occur on a continuum of scales; a variety ofphysical and biological phenomena may interact tospatially aggregate planktonic organisms on scalesranging from micro (centimeters to meters) to meso(kilometers to hundreds of kilometers) depending on thespatial extent of the particular oceanographic structures(Haury et al., 1978; Longhurst, 1981; Owen, 1981).Plankton biomass is generally reported to increase inthe vicinity of fronts between distinct mesoscale oceano-graphic structures (ranging from, approximately, 5 to 50nautical miles) where shifts in species composition alsotake place (e.g. Le Fevre, 1986; Nielsen and Munk,1998; Morgan et al., 2005). Limitations in understandingand predicting plankton distributions in highly dynamicregions arise from a mismatch between the scales atwhich the biological and physical measurements areroutinely made in field surveys and the scales of the

mesoscale structures that influence plankton commu-nities and processes (e.g. Kushnir et al., 1997; Mooreet al., 2003). Much of the research on temporal andspatial variability in plankton communities have beencarried out on a large scale, and there has been a ten-dency to over-average the data (Cowen et al., 1993),thereby overlooking much of the small-scale variabilityin plankton distribution (Lee et al., 2005). Althoughstudies on the effect of mesoscale structures on zoo-plankton have been carried out, these are generallylimited to the effect of a single structure (e.g. one eddy,one front) (e.g. Kingsford and Suthers, 1994; Fernandezet al., 2004; Genin, 2004). On the other hand, there arestudies of the influence of mesoscale structures on zoo-plankton biomass distribution using automatic systems(e.g. Davis et al., 2004; Ashjian et al., 2005; Kimmelet al., 2006), but current taxonomic identification limitsof these methods constrains our understanding of theobserved biomass distributions.

doi:10.1093/plankt/fbm064, available online at www.plankt.oxfordjournals.org

# The Author 2007. Published by Oxford University Press. All rights reserved. For permissions, please email: [email protected]

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In fact, studies on how different mesoscale structurescontribute to shape zooplankton communities over alarge area are scarce because of the difficulties of finescale sampling over a large area together with hightaxonomic resolution. The economic cost of increasingsampling effort in plankton surveys has contributed tothe scarcity of this type of study. However, whensampling icthyoplankton in the context of daily egg pro-duction method (DEPM) surveys (Lasker, 1985), zoo-plankton samples are usually collected with a spatialresolution that resolves the mesoscale. In the Bay ofBiscay, a DEPM is currently applied to estimate theanchovy (Engraulis encrasicolus) spawning biomass duringits peaking spawning period (BIOMAN campaigns; seefor example Motos et al., 1996) collecting zooplanktonsamples with a spatial resolution of 3 15 nauticalmiles over a large area (Fig. 1).Several studies have investigated mesoscale features in

the Spanish part of the Bay of Biscay (e.g. Fernandez et al.,1991, 1993; Gil, 1995; Gil et al., 2002; Gonzalez-Quiroset al., 2003, 2004). However, for the French part of theBay, apart from the Landes coastal upwelling and riverplumes, the occurrence of mesoscale variability is poorlydocumented because most published hydrological data

are historical, with sampling that is not synopticenough to resolve mesoscale features (Puillat et al.,2006). The objective of this study is to exploit theDEPM small-scale resolution to elucidate the effect ofmesoscale structures on zooplankton abundance andspecies composition in a highly dynamic region of theBay of Biscay.

METHOD

The Bay of Biscay is an open oceanic bay located at43.548.58N and surrounded by the north coast ofSpain and the French west coast (Fig. 1). The ecosystemis comprised two shelves with different orientation andwidth and subjected to distinct current and tidal pat-terns that form a dynamic region where several meso-scale structures occur in a constrained area (seeKoutsikopoulous and Le Cann, 1996; Borja andCollins, 2004; for a review). The Spanish part of thesurveyed domain (hereinafter called Cantabrian Seaarea) is characterized by an east-west orientated narrowshelf (1520 nautical miles) and by the absence ofimportant river outflows (Prego and Vergara, 1998).

Fig. 1. Location of the PAIROVET stations (crosses) and (highlighted) the transects which CTD vertical profiles for density and FL are shownin Fig. 4. Isobaths of 100, 200, 1000 and 2000 m are shown along with the position of the Cap-Breton canyon, Marennes-Oleron and Arcachonbays and Gironde and Adour river mouths.

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The French part has a north-south shelf orientation,with width increasing northwards from 30 on theLandes Plateau to 80 nautical miles on the AquitaineShelf shelves). The conspicuous river outflows (Girondeand Adour with, respectively, 900 and 300 m3 s21 meanfreshwater outflows, Puillat et al., 2004) (Fig. 1) alsooccur on the French shelf.Zooplankton samples were collected from 216 May

2004, as part of the Basque Country survey to estimatethe biomass of anchovy (Engraulis encrasicolus) (BIOMAN2004 campaign), in a grid of 267 stations. Consecutivestations were 3 nautical miles apart located in transectsspaced 15 nautical miles apart covering the Bay ofBiscay from 43.328N to 46.128N and from 1.298W to4.318W (Fig. 1). The survey track started in the south-western edge of the domain and ended in the coastalstation of the northernmost transect. Samples were col-lected using vertical hauls of a 150 mm PAIROVET netfitted with a flowmeter and lowered to a maximumdepth of either 100 or 5 m above the bottom at shal-lower stations. The PAIROVET net consists of a pairednet with a mouth aperture of 0.05 m2 that is a versionof the CalVET net (Smith et al., 1985).Net samples were preserved immediately after collec-

tion with 4% borax buffered formalin. The qualitativeand quantitative analysis of zooplankton was carriedout under a stereoscopic microscope and identificationwas made to species or genus level in the majority ofthe holoplanktonic groups, and to general categories inmeroplanktonic forms (Table I). In each sample, aminimum of 200 individuals (all categories included)were counted. When referring to Calanoides carinatus andCalanus helgolandicus, patterns for copepodites IVVI aredescribed. Copepodites IIII could not be distinguishedand were grouped under another category (Calanidaecopepodites IIII) (Table I). Fish eggs abundance wascomputed by sorting the entire sample.The nets were also fitted with a conductivity, tempera-

ture and depth data logger (CTD; model RBR XR-420)with a fluorescence (FL) sensor (Seapoint ChlorophyllFluorometer; Seapoint Sensors, Inc.). Water density(expressed as sigma-t) was calculated for each meter ofwater column and a stratification index (SI) was com-puted by subtracting surface from bottom values.Surface temperature (ST), surface salinity (SS), SI andFL (expressed as FL units per cubic meter) were selectedas representative environmental variables (Table II).Because the cruise does not provide a synoptic view,

satellite images were obtained from IFREMER (InstitutFrancais de Recherche pour lExploitation de la MER)(http://www.ifremer.fr/cersat/facilities/browse/del/gas-cogne/browse.htm) for dates at the beginning (we used25 April instead of 2 May which was cloud-covered)

Table I: Taxonomic list with mean,maximum and minimum values for abundance(ind. m23) and mean values for contribution(%) to total abundance of each taxa

Taxa CodeMean(ind. m23)

Maximun(ind. m23)

Minimun(ind. m23)

Mean(%)

Noctiluca scintillans 4191.38 31 173.00 0.00Foraminifera 212.41 846.40 0.00Jellyshes exceptS. Bitentaculata

JELLY 60.56 553.60 0.00 0.95

Solmundellabitentaculata

SOLMU 13.87 142.20 0.00 0.38

Siphonophora SIPHO 110.89 625.81 0.00 1.86Gastropod veliger GAVEL 38.76 777.57 0.00 0.61Bivalve veliger BIVEL 61.11 2262.02 0.00 0.66Tomopteris spp. 2.58 69.53 0.00 0.07Polychaeta exceptTomopteris

POLYC 24.40 486.74 0.00 0.40

Podon spp. PODON 38.64 324.63 0.00 0.73Evadne nordmanni EVNOR 83.84 1133.80 0.00 1.92Phoronida(Actinotroch larvae)

0.37 42.58 0.00 0.00

Bryozoa(Cyphonautes larvae)

11.75 764.88 0.00 0.07

Ostracoda 1.08 26.16 0.00 0.03Calanoidescarinatus IVVI

CCARI 6.69 73.17 0.00 0.20

Calanoidescarinatus female

0.88 20.91 0.00 0.03

Calanoidescarinatus male

0.38 25.52 0.00 0.01

Calanoides carinatus V 3.39 41.81 0.00 0.10Calanoides carinatus IV 2.03 31.36 0.00 0.06Calanushelgolandicus IVVI

CHELG 76.74 459.55 0.00 1.87

Calanushelgolandicus female

6.77 111.20 0.00 0.13

Calanushelgolandicus male

2.26 37.94 0.00 0.05

Calanushelgolandicus V

33.20 312.49 0.00 0.85

Calanushelgolandicus IV

34.51 276.49 0.00 0.83

Calanidaecopepodites IIII

CI-III 52.35 339.69 0.00 1.14

Calanidaecopepodites III

24.21 243.28 0.00 0.53

Calanidaecopepodites II

15.67 103.83 0.00 0.36

Calanidaecopepodites I

12.47 121.13 0.00 0.25

Mesocalanustenuicornis

MESTE 19.56 263.38 0.00 0.58

Neocalanus robustior 0.20 12.57 0.00 0.01Eucalanus spp. EUCAL 10.43 176.49 0.00 0.26Rhincalanus spp. 0.47 37.36 0.00 0.01Calocalanus spp. CALOC 14.40 158.72 0.00 0.42Ischnocalanus spp. 1.73 55.19 0.00 0.02P-Calanus (Parac./Claus./Pseud./Cteno.copepod)

P-CAL 458.62 3059.52 38.29 7.25

Paracalanus parvus PARAC 44.01 425.14 0.00 0.76Clausocalanus spp. CLAUS 33.54 139.56 0.00 0.88Pseudocalanuselongatus

PSEUD 50.98 903.95 0.00 0.50

Continued

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and end of the survey (16 May) to complement theCTD in situ data. The parameters considered fromsatellite images were ST, Chlorophyll a (Chl a) and inor-ganic suspended particulate matter (SPM) includingcoccoliths (see Gohin et al., 2005 for details).Simpsons diversity index (Simpson, 1949) was calcu-

lated only for the copepod community because of thehigher homogeneity in the taxonomic classification.Multivariate analyses of the sampled stations and therelevant zooplankton taxa were carried out using thesquared Euclidean Wards method cluster (Ward, 1963;Pielou, 1984) applied to log10 transformed abundancevalues using only those taxa that contributed morethan 0.1% of the zooplankton community abundance.Canonical correspondence analysis (CCA) and general-ized additive models (GAMs) were used to investigatethe relationship between zooplankton taxa abundancesand selected environmental variables (ST, SS, SI and FL;Table II). Zooplankton taxa abundances were log10(x1) transformed before analysis. The CCA test wasperformed using version 4.5 of CANOCO (ter Braakand Smilauer, 2002); all canonical axes were used toevaluate the significant variables under analysis byMonte Carlo test (999 permutations). GAMs (Hastieand Tibshirani, 1990) were implemented using the mgcvpackage (version 1.3-17; http://cran.r-project.org/doc/packages/mgcv.pdf ) of R (Wood, 2001). The percentageof explained deviance along with generalized cross-validation (GCV) smoothness estimation was computedfor selected variables (each independently or combined)when modeling the zooplankton spatial distributions.

RESULTS

Environmental variables

The area was sampled during the onset of stratificationas inferred from low surface mean temperature(13.468C, Table II) and from satellite images for ST atthe beginning and at the end of the survey (Fig. 2a and d).

Table I: Continued

Taxa CodeMean(ind. m23)

Maximun(ind. m23)

Minimun(ind. m23)

Mean(%)

Ctenocalanus vanus CTENO 17.32 103.50 0.00 0.46Stephos spp. 0.40 22.49 0.00 0.01Temora longicornis TEMLO 375.86 3504.23 0.00 5.06Temora stylifera 0.13 24.21 0.00 0.00Centropages spp. CENTR 70.71 517.49 0.00 1.16Candacia spp. CANDA 7.26 65.63 0.00 0.21Euchirella spp. 0.04 10.66 0.00 0.00Metridia spp.Pleuromamma spp.

ME-PL 9.60 151.34 0.00 0.28

Euchaeta spp. EUCHA 3.01 48.10 0.00 0.10Pseudophaenna typica 0.23 11.84 0.00 0.01Scolecithricella spp. 0.06 16.07 0.00 0.00Aetidius spp. 0.45 24.91 0.00 0.02Heterorhabduspapilliger

0.32 11.87 0.00 0.01

Diaxis spp. 2.40 92.55 0.00 0.03Anomalocera patersoni 0.17 24.72 0.00 0.00Acartia clausi ACCLA 136.47 1347.79 0.00 2.37Oithona similis OITSI 1068.43 4831.07 190.35 18.72Oithona nana OITNA 209.89 3289.14 0.00 2.45Oithona plumifera OITPL 76.17 739.17 0.00 2.07Cyclopina litoralis 0.05 14.51 0.00 0.00Corycaeus spp. CORYC 83.66 672.73 0.00 1.15Oncaea spp. ONCAE 1872.98 14 257.92 15.34 26.34Euterpina acutifrons EUTER 48.72 973.88 0.00 0.50Microsetella spp. MICRO 27.32 130.75 0.00 0.65Halithalestris croni 0.09 12.77 0.00 0.00Clytemnestra spp. 1.44 42.67 0.00 0.03Aegisthus spp. 0.34 55.60 0.00 0.00Copepoda nauplius COPNA 406.66 3059.52 0.00 5.61Cirripedia CIRRI 58.73 1876.12 0.00 0.71Amphipoda 2.13 56.52 0.00 0.03Isopoda 0.86 51.55 0.00 0.02Decapod larvae DECAP 9.88 379.40 0.00 0.12Euphausiacea EUPHA 14.61 121.64 0.00 0.38Mysidacea 0.98 38.97 0.00 0.02Cumacea 0.06 15.94 0.00 0.00Sagitta spp. SAGIT 7.83 112.19 0.00 0.13Echinodermatalarvae

ECHIN 15.19 206.20 0.00 0.30

Fritillaria spp. FRITI 395.23 7210.17 0.00 7.76Oikopleura spp. OIKOP 90.45 2642.32 0.00 0.89Appendicularia spp. APPEN 32.42 559.57 0.00 0.62Doliolum spp. 0.77 15.61 0.00 0.02Tornaria larvae 0.23 15.26 0.00 0.01Cephalochordata(Branchiostomalanceolatum)

CEPHA 6.61 93.90 0.00 0.14

Anchovy (Engraulisencrasicolus)eggs

ANCHO 1.01 19.12 0.00

Sardine (Sardinapilchardus) eggs

SARDI 2.91 51.55 0.00

Other sh eggs OTFIS 0.98 16.26 0.00Copepoda total 5189.92 23 454.09 895.03 81.17Zooplankton total 6273.74 24 166.70 1033.83 100.00

Column CODE shows the codes used in species cluster where only taxathat conform more than 0.1% of the zooplankton community abundanceare taken into account. The protozoans Noctiluca scintillans andForaminifera were not considered for computing zooplankton totalabundance and statistical analysis (see text for further explanation).

Table II: Mean values and range of variationfor environmental variables used in statisticalanalysis

ST SS SI FL

Mean 13.46 34.41 0.86 1.59Standard deviation 0.60 0.98 0.77 0.89Maximun 15.40 35.96 4.63 5.02Minimun 12.59 29.80 0.00 0.30

ST (8C), SS, SI (kg m23) and FL (relative units m23) calculated from netassociated CTD data logger vertical proles (n 241).


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Fig. 2. Temperature (8C; NOAA 17 satellite), Chlorophyll a (Chl a) (mg m23; SeaWiFS satellite) and inorganic SPMcoccolith (ln g m23;SeaWiFS satellite) satellite images for 25 April 2004 (signaled respectively a, b and c) and 16 May 2004 (d, e and f ); all scales superimposed.Black areas represent clouds presence; a black line signals the sampled domain.


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As a result, the northern, and chronologically lastsampled, transects had the highest temperatures(Fig. 3a). The SI also showed the warming of Biscaywaters during the survey (Fig. 3c). Highest temperatureswere located in the mouth of Gironde estuary. TheAdour and Gironde river plumes (see Fig. 1 forlocation) had low SS (Fig. 3b) and high salinity occurredin the more oceanic part of the sampled grid. Thedominating stratification force in spring was the spread-ing of river plume waters over the shelf (Fig. 3b and c).Although stratification was weak, the neritic to oceandecreasing stratification pattern was also noted indensity vertical profiles (Fig. 4a, c and e), where plumewaters showed a 2030 m depth penetration and amid-shelf extension. The oscillations of pycnoclines withdeclining amplitude from the shelf break clearly sig-naled the generation of internal waves over the slope

(Fig. 4c and e). An upwelling of cold water off Landescoast was detected through satellite imagery (Fig. 2d).Maximum FL was related to river plume waters and

to the shelf break; minimum FL corresponded to theneritic zone in the south of the survey area and to the100200 m depth shelf waters in northernmost trans-ects (Fig. 3d). The vertical distribution of FL showed adistinct pattern for the two peaking areas, revealing asurface maximum and a pycnocline maximum for,respectively, the river plume and shelf break areas(Fig. 4d and f ). In the Cantabrian Sea, a front separatedneritic low FL waters from high FL oceanic waters(Fig. 4b). At the beginning of the cruise, satelliteimagery showed the above-described bimodal patternfor surface Chl a and revealed an oceanic bloom ofphytoplankton coinciding with eddy formation from theshelf break (Fig. 2b and c). By the end of the cruise,

Fig. 3. Spatial distributions of environmental variables computed from CTD data: (a) ST (8C), (b) SS, (c) SI (kg m23) and (d) FL (relativeunits m23); all scales superimposed. Isobaths of 100, 200, 1000 and 2000 m are shown.


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Fig. 4. Vertical (0100 m depth; left axis) profiles of density (sigma-t; upper graphs) and FL (relative units; bottom graphs) for transects signaledin Fig. 1 with axes 3.98W (graphs a and b), 44.128N (graphs c and d) and 45.378N (graphs e and f ). Scales are superimposed and bottomprofile and sampled depths are shown within the graph; distance to the coast in nautical miles (bottom axis). Sigma-t (kg m23) is the densityanomaly of a water sample when the total pressure on it has been reduced to atmospheric pressure (i.e. zero water pressure), but thetemperature and salinity are in situ values.


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satellite images indicated phytoplankton maxima at themouth of the Gironde and at the shelf break (Fig. 2eand f ).

Zooplankton community

From the taxa identified (Table I), although abundant,the protozoans Noctiluca scintillans and foraminiferawere not considered in this study because ofsize-related inadequate sampling. Copepods comprised81.2% of the total zooplankton abundance. The domi-nant groups (60.1% of community abundance;Table I) were copepods Oncaea spp., Oithona similis,P-Calanus (involving the copepodite stages of genusParacalanus, Clausocalanus, Pseudocalanus and Ctenocalanus)and the appendicularian Fritillaria spp. Figure 5 showsthe SS and ST weighted mean abundance values forthe identified taxa.The distribution of zooplankton abundance was

characterized by a pattern with maximum abundancevalues related to shallower stations to minimum ones inmid-shelf depths and an increase in northern shelfbreak locations (Fig. 6a). The spatial pattern for cope-pods differed from that for total zooplankton byshowing low total copepod abundance values associatedwith neritic locations of the Cantabrian Sea (Fig. 6b).Day/night sampling, which would have resolved dielvertical migration, did not affect the abundancesmeasured (data not shown). Simpsons diversity index(S) values for the copepod community are presented inFig. 6c; while highest diversity values corresponded tothe shelf break and Cap-Breton canyon stations, thestations located in shelf waters between both riverplumes had the lowest diversity.Four distinctive groups of stations, namely ST-1,

ST-2, ST-3 and ST-4, were identified as function of thezooplankton composition with the Wards methodcluster analysis (Fig. 7a); groups ST-1 and ST-2 werefurther divided into two subgroups: ST-1A and ST-1B,and ST-2A and ST-2B, respectively. Looking at thespatial distribution of the stations comprised in eachcluster, a clear spatial pattern arose with almost no over-lapping of the stations grouped (Fig. 7b). ST-1 clusterinvolved stations that covered the Cantabrian Sea alongwith waters in the Cap-Breton canyonAdour riverplume zone with subgroups ST-1A and ST-1B occupy-ing, respectively, neritic and more oceanic waters. ST-2cluster comprised the stations over the French part ofthe sampled domain characterized with depths greaterthan 100 m; whereas ST-2A stations followed ST-2Bones in the depth gradient in the Aquitaine Shelf, therewas no such gradient on the Landes Plateau. ST-3 andST-4 groups comprised the inner-shelf community in

French sampled area; ST-4 stations coincided with theGironde river plume waters and were surrounded to thenorth and to the south by stations in cluster ST-3located at the mouth of both Marennes-Oleron andArcachon Bays.The zooplankton taxa dendrogram identified four

large assemblages (TX-A, TX-B, TX-C and TX-D)further subdivided into seven clusters (Fig. 8). TX-A1cluster comprised taxa with neritic preference over theentire grid but with low abundances in the Girondeplume waters such as Acartia clausi, Podon spp., Oikopleuraspp. and Sardina pilchardus eggs (Fig. 9a). TX-A2 showedthe same pattern but was restricted to the French partof the domain and was characterized by meroplanktontaxa such as Bivalve veliger, Echinodermata larvae andPolychaeta larvae (Fig. 9b). TX-B clusters grouped taxareaching the highest abundances, comprising 77% oftotal zooplankton abundance, and with maximumvalues in neritic waters but being also relatively abun-dant in the Gironde plume waters. TX-B1 taxagrouped Oncaea spp., Temora longicornis and Engraulis encra-sicolus eggs among others, with maximum values associ-ated with the Landes cold water upwelling and hardlypresent in the Cantabrian Sea waters (Fig. 9c); TX-B2cluster comprised Oithona similis, P-Calanus category andCopepoda nauplius following a bimodal distributionpattern with high abundances also in shelf break waters(Fig. 9d). TX-C cluster was characterized by the appen-dicularian Fritillaria spp. and the cladoceran Evadne nord-manni and displayed maximum abundance values in theCantabrian Sea neritic waters and a minor secondarypeak in northern shelf break locations (Fig. 9e). TX-Dclusters included taxa restricted to waters deeper than100 m. Species with maximum abundance at the shelfbreak, such as Mesocalanus tenuicornis, Calocalanus spp. andOithona plumifera, formed TX-D1 cluster (Fig. 9f );TX-D2 put together taxa with maximum abundancesin outer-shelf waters such as the copepods Calanus helgo-landicus (developmental stages IVVI) and Eucalanus spp.(Fig. 9g).The speciesenvironment correlation for the CCA

first axis was 0.84 and the cumulative explained var-iance for the speciesenvironmental relationship was74.4%; when adding the second axis this improved to89.3% (Fig. 10). All environmental variables included inthe analysis were significant (P 0.001; 999 MonteCarlo permutations). Zooplankton taxa were groupedby the CCA as in Fig. 8 species Wards cluster analysis(Fig. 10; see legend for further explanation and symbolcorrespondence). TX-A1, TX-A2 and TX-B1 taxaoccurred in the right part of the biplot with lowest SSand highest ST, SI and FL values. TX-C, TX-D1 andTX-D2 occupied the opposite location showing positive


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Fig. 5. SS (left axis) and ST (8C; bottom axis) weighted mean values for identified taxas abundance distribution; only those taxa that conformmore than 0.1% of the zooplankton community abundance are shown (except for CI-III, P-CAL, COPNA, APPEN and OTFIS; codes inTable I).


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correlation with SS and negative one with ST, SI andFL. TX-B2 taxa were located in the origin of the axes.Table III shows GAMs analysis results for species

Wards clusters (Fig. 8; TX clusters) when computingonly one environmental variable each time. Theserevealed that SS and SI were the variables explainingthe higher percentage of the deviance. The resultingcurves when fitting GAMs to all of the TX clustersabundance distributions using selected variables areshown in Fig. 11. The seven clusters differed in theirresponse to selected variables: a sharp decline with SSover 33 and a sharp increase with SI for valueswithin 0 and 2 distinguished TX-A and TX-B taxafrom TX-C and TX-D. TX-A taxa were separatedfrom TX-B ones by the steepness of the slope of therelationships with SS and SI, being steeper in bothcases for TX-B taxa. TX-C taxa deviated from TX-Dones by their marked negative relationship with FL.Within the TX-A group, the significant relationshipwith SI distinguished TX-A2 from TX-A1 taxa. In the

TX-B group, the secondary peak of abundance forTX-B2 species in shelf break habitats was denoted bythe bimodal curve for SS separating them from morecoastal-river plume restricted TX-B1 group of species.The differentiation between TX-D1 and TX-D2 specieswas more subtle and determined by the steeperresponse to SS (in the range .33) and SI (in the range02) in the TX-D1 cluster species when comparingwith the TX-D2 cluster.GAMs allow obtained distributions (TX cluster abun-

dance distributions) to be fitted to multiple predictors;Table IV shows the results for applying GAMs ofincreased complexity to zooplankton data, ranging fromtwo to four predictors (ST, SS, SI and FL), and takinginto account or not interactions between them (seelegend for further explanation). The model explainingthe highest percentage of deviance was (ST, SS, SI) witha mean value for all clusters of 74.4%. AlthoughTX-B1 and TX-B2 reached the maximum percents ofexplained deviance with, respectively, 86.4 and 83.9,

Fig. 6. Spatial distributions of (a) total zooplankton abundance (ind. m23), (b) total copepods abundance (ind. m23) and (c) Simpsons diversityindex (S) values for the copepod community (no units). Higher values for S mean lower diversity; value 1 denotes no diversity (S S(n/N)2; n,number of individuals of one species and N, total number of individuals summing all species). Isobaths of 100, 200, 1000 and 2000 m areshown.


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Fig. 7. (a) Stations cluster. Squared Euclidean Wards method cluster applied to log10 (zooplankton species abundance 1) transformed datausing only taxa that conform more than 0.1% of the zooplankton community abundance (267 cases; 45 taxa), (b) Spatial distribution of differentstations cluster subgroups (symbols correspondence superimposed); 100, 200, 1000 and 2000 m isobaths are shown.


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TX-A2 achieved the minimum value for this modelwith 46.9%.

DISCUSSION

Our results show that when sampled with suitablespatial and taxonomic resolution, environmental vari-ables can be used to characterize specific ranges of zoo-plankton abundance and species composition even inhighly dynamic ecosystems such as that studied here.Although DEPM surveys only provide a snapshot of thezooplankton community on the sampled dates, the rela-tively lack of synopticity related to 2 weeks long surveywas not enough to avoid relating zooplankton commu-nities to mesoscale structures. In this sense, zooplanktoncommunities of the Cantabrian Sea (clusters ST-1A andST-1B; Fig. 7) were governed by eddies located over theshelf break [slope water oceanic eddies (SWODDIES)as described in Pingree and Le Cann (Pingree and LeCann, 1992); Fig. 2b and e] forming a frontal systembetween low FL neritic waters and oceanic ones(Fig. 4b); higher levels of Chl a in Bay of BiscaySWODDIES with respect to surrounding waters alongwith the presence of distinct zooplankton assemblagesinside and outside the SWODDY have been previouslydescribed (Rodrguez et al., 2003; Fernandez et al., 2004;Isla et al., 2004). In the French part of the domain,however, zooplankton communities (clusters ST-2A,ST-2B, ST-3 and ST-4; Fig. 7) were determined by thepresence of river plumes and internal wave generationover the slope. These mesoscale structures produce

(Fig. 4d and f ) a FL peak in the river plume surfacewaters related to the continuous input of nutrients dueto continental drainage (Bergeron and Herbland, 2001),low FL mid-shelf stations and a secondary peak overthe shelf break promoted by deep waters nutrients injec-tion via internal waves mixing (Pingree and Mardell,1981; Holligan et al., 1985). Contrary to Cantabrian Seawaters subjected to SWODDY influence, the zooplank-ton total abundance spatial distribution in Frenchwaters (Fig. 6a) matched well with the above-describedpattern for FL.The observed correspondence between mesoscale

structures and zooplankton communities is quantitat-ively reinforced with the strong speciesenvironmentcorrelation for the CCA (cumulative explained variancefor the speciesenvironmental relationship: 89.3%;Fig. 10) and the high percentage of deviance explainedby GAM analysis (Table IV). Although statistical modelsdo not provide the underlying mechanisms for theobserved relationships, the species groups obtained andtheir relations to environmental variables (Figs 10 and11) can be used to infer potential causes.In this sense, the TX-A1 cluster comprising a neritic

community with lowest abundances in the Gironderiver plume locations (Fig. 9a) might be explained bythe presence of species with resting eggs in their devel-opment cycle that need sea floor resuspension to hatch(e.g. Podon spp. and Acartia clausi) thus requiring shallowhabitats (e.g. Marcus, 1990; Hairston, 1996); but, thesespecies, might be also unable to prosper in the turbidplume waters with a high content of inorganic particles(Froidefond et al., 1998), as shown for Acartia bifilosa

Fig. 8. Species cluster (species code in Table I). Squared Euclidean Wards method cluster applied to log10 (zooplankton species abundance1) transformed data using only taxa that conform more than 0.1% of the zooplankton community abundance.


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Fig. 9. Spatial distribution of different species cluster subgroups (ind. m23; scales superimposed): (a) Cluster TX-A1, (b) Cluster TX-A2,(c) Cluster TX-B1, (d) Cluster TX-B2, (e) Cluster TX-C, (f ) Cluster TX-D1 and (g) Cluster TX-D2. Code names are as in Fig. 8; 100, 200,1000 and 2000 m isobaths are shown.


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inside the estuary (Irigoien and Castel, 1995). On theother hand, the decreasing pattern of TX-A2 clusterspecies abundance from both Marennes-Oleron andArcachon bays locations (Fig. 9b) matches with the tidalflats and the presence of important shellfish farms inboth bays (mainly oyster; OSPAR Commission, 2000) asthe cluster is composed of meroplanktonic forms withbivalve larvae representing 33% of the total abundance.Meroplankton has been previously cited as representing

an important part of the zooplankton community inthese semi-enclosed ecosystems and surrounding areas(Castel and Courties, 1982; dElbee and Castel, 1991;Sautour and Castel, 1993). The abundance gapbetween both meroplankton spreading sites correspond-ing to Gironde river plume waters has also been associa-ted with high SPM values for a filter feedingcommunity to develop (Heip and Herman, 1995).TX-B1 cluster includes typical Bay of Biscay neritic

Fig. 10. CCA biplot for zooplankton taxa abundance and environmental variables. Only zooplankton taxa conforming more than 0.1%relative abundance of the zooplankton community abundance were used (species code as in Table I). Species symbols correspond to Fig. 8clusters: Cluster TX-A1 (black triangles), Cluster TX-A2 (white triangles), Cluster TX-B1 (black circles), Cluster TX-B2 (white circles), ClusterTX-C (crosses), Cluster TX-D1 (black squares) and Cluster TX-D2 (white squares). CCA identifies environmental variables that explaindirections of variance in the species data along one or more axes; in this case, only the first two axes are shown. CCA included fourenvironmental variables: ST, SS, SI and FL. None of the data were weighted. Cumulative explained variance of speciesenvironment relation:89.3% (axes 1 and 2). The length of the environmental arrows and their orientation on the biplot indicate the relative importance of thevariable to each axis; the variables with the longest arrows are most highly correlated with the axes. Environmental arrows represent a gradient;the mean value lies at the origin and the arrow points in the direction of increase.

Table III: Results of GAM analysis for Ward clusters subgroups (Fig. 8; n 241) using each selectedenvironmental variable independently; percentage of explained deviance along with generalized crossvalidation (GCV; in brackets) smoothness estimation were computed

TX-A1 TX-A2 TX-B1 TX-B2 TX-C TX-D1 TX-D2

ST 7.59 (0.24) 18 (0.23) 16.5 (0.18) 21.7 (0.08) 13.6 (0.90) 7.44 (0.36) 14.3 (0.20)SS 13.2 (0.22) 36.4 (0.18) 68.7 (0.07) 54.1 (0.05) 32.5 (0.73) 41 (0.23) 20.1 (0.19)SI 0.925 (0.25) 30.5 (0.20) 55.6 (0.10) 38.2 (0.07) 45 (0.59) 23.7 (0.30) 5.24 (0.22)FL 7.01 (0.24) 6.69 (0.27) 24.1 (0.17) 17 (0.09) 20.9 (0.83) 2.51 (0.37) 0.376 (0.23)

The lowest GCV score for a cluster represents the best tting. ST (8C), SS, SI (kg m23) and FL (relative units m23).


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Fig. 11. Partial nonlinear terms (y-axis) of different species cluster subgroups abundance distributions (codes in left extreme as in Fig. 8;Squared Euclidean Wards method cluster) estimated by means of GAMs using each selected environmental variables independently (variablesvalues in x-axis): ST, SS, SI and FL. The appropriate smoothness for each applicable model term was selected using generalized cross validation(GCV). The solid line in each plot is the estimate of the smooth function, whereas the dashed lines represent the 95% confidence limits. Smoothfunctions are not significant when the confidence region for the smoothing include zero throughout the range of the predictor. Tick marks onx-axis show the locations of the observations on each variable.


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taxa (Albaina and Irigoien, 2004) comprising 46% oftotal zooplankton abundance with maximum abun-dances related to the Landes coast upwelling location(Fig. 9c); springsummer upwelling in the Landes coastis a regularly observed structure (e.g. Jegou and Lazure,1995; Borja et al., 1996, Froidefond et al., 1996), and thepeak abundances could be related to increased primaryproduction due to the injection of nutrients.The observed decrease in abundance in Gironde

river plume in clusters TX-A1, TX-A2 and TX-B1could be a response to extremely high Gironde riveroutflows washing away river plume zooplankton assuggested by Albaina and Irigoien (Albaina andIrigoien, 2004) for a 5-year study of a transect in frontof the Gironde Estuary; in this sense, the 34 015 m3 s21

accumulated flow value, for the 15 preceding days tothe sampling in 2004 was the highest among the onesreached in the above cited work. The huge contributionof Oncaea spp. to cluster TX-B1 and to the entire zoo-plankton community (respectively, 65% and 26% ofmeasured abundance) determined the minimumcopepod diversity values associated with the LandesCoast locations (Fig. 6c); the highest values were relatedto Cap-Breton canyon and shelf break locations.Maximum diversity for copepods in the Cap-Bretoncanyon area has already been observed (dElbee, 2001)and is due to the transport of oceanic species to coastal

stations where both populations merge. On the otherhand, a depth-related increase in diversity from coastalto shelf break locations is a common pattern incopepod communities (see Mauchline, 1998 for areview). TX-B2 cluster taxa were located in the originof the axes of the CCA showing high tolerance to therange of values of selected environmental variables andexplaining their bimodal distribution pattern with pro-minent abundances in almost all the sampled gridstations (Fig. 9d). However, it has to be taken intoaccount that this plasticity of the taxa in the TX-B2cluster is explained by two different reasons. On onehand, P-Calanus and Copepoda nauplius are taxonomi-cal categories involving different species, and thereforethere is no real plasticity but difficulties in separatingthe early stages of the species. On the other hand,Oithona similis, the principal taxa in TX-B2 cluster(55%) and dominating Bay of Biscay spring communityabundance (Albaina and Irigoien, 2004), shows realcapability to adapt to different environments as shownby its widespread distribution (Gallienne and Robins,2001; Nielsen et al., 2002; Castellani et al., 2005).In the Cantabrian Sea, total copepod peak abun-

dances (Fig. 6b) matched with the locations ofSWODDIES and can be related to the associated FLpattern or to mechanical transport from adjacentlocations or a combination of both (as suggested in

Table IV: GAMs for each Ward clusters subgroups (Fig. 8; n 241); two types of models combiningvariables were tested: with or without interaction among variables, respectively case (var.1, var.2,var.3. . .) and (var.1)(var.2)(var.3). . . (see Wood, 2004 for further explanation)

TX-A1 TX-A2 TX-B1 TX-B2 TX-C TX-D1 TX-D2

ST,SS 39.9 (0.18) 42.4 (0.18) 79.3 (0.05) 63.9 (0.05) 52.8 (0.56) 55.7 (0.20) 37.5 (0.17)ST,SI 20.3 (0.23) 33.2 (0.20) 65.3 (0.08) 50 (0.06) 56 (0.52) 31.7 (0.29) 30 (0.19)ST,FL 24.7 (0.22) 27.8 (0.22) 43.6 (0.14) 42.2 (0.07) 37.4 (0.71) 11.9 (0.35) 20 (0.21)SS,SI 45.1 (0.16) 42.4 (0.18) 72.3 (0.07) 57.8 (0.05) 50.5 (0.58) 52.1 (0.21) 35 (0.18)SS,FL 41.8 (0.18) 40.6 (0.18) 72.2 (0.07) 57.5 (0.05) 42.7 (0.66) 53.5 (0.21) 26.8 (0.19)SI,FL 30.7 (0.20) 37.6 (0.19) 66.8 (0.08) 50.3 (0.06) 53.7 (0.55) 34.4 (0.29) 28 (0.20)STSS 23 (0.20) 39.4 (0.18) 71.7 (0.07) 59.3 (0.05) 39.7 (0.67) 42.2 (0.23) 27.5 (0.18)STSI 10.8 (0.23) 32.8 (0.20) 63.6 (0.08) 44.9 (0.06) 52.4 (0.53) 24 (0.30) 14.6 (0.21)STFL 12.7 (0.23) 21.3 (0.23) 35.6 (0.15) 33.6 (0.07) 32.2 (0.73) 8.71 (0.36) 15.2 (0.20)SSSI 44.1 (0.16) 36.6 (0.18) 71 (0.07) 55.2 (0.05) 49.4 (0.58) 46.5 (0.22) 21.2 (0.19)SSFL 21.2 (0.21) 39.6 (0.18) 71.2 (0.07) 57.4 (0.05) 38.6 (0.69) 42.6 (0.23) 22.8 (0.19)SIFL 8.39 (0.24) 33.6 (0.20) 60.6 (0.09) 44.5 (0.06) 51.4 (0.54) 23.7 (0.30) 8.15 (0.22)ST,SS,SI 81.4 (0.10) 46.9 (0.17) 86.4 (0.05) 83.9 (0.03) 77.7 (0.42) 74.7 (0.16) 69.9 (0.13)ST,SS,FL 54.1 (0.16) 42 (0.17) 82.8 (0.05) 64.9 (0.05) 62.7 (0.53) 63.2 (0.21) 74 (0.13)ST,SI,FL 43.9 (0.19) 37.1 (0.19) 74.4 (0.07) 57.4 (0.06) 65.4 (0.49) 56.8 (0.27) 41.4 (0.19)SS,SI,FL 64.1 (0.13) 42.8 (0.17) 78.6 (0.06) 67.8 (0.05) 66.8 (0.53) 72.9 (0.17) 65.6 (0.15)STSSSI 54.6 (0.14) 39.3 (0.18) 75.5 (0.06) 60.8 (0.05) 57.9 (0.50) 51.7 (0.21) 33.1 (0.17)STSSFL 32.4 (0.19) 41.2 (0.18) 74.2 (0.06) 62.3 (0.05) 46.5 (0.62) 43.4 (0.23) 29.9 (0.18)STSIFL 17.5 (0.23) 35.6 (0.20) 68.2 (0.08) 50 (0.06) 57.9 (0.49) 24.1 (0.30) 16.6 (0.20)SSSIFL 50.9 (0.15) 39.8 (0.18) 74.2 (0.06) 58.4 (0.05) 54.4 (0.52) 48.4 (0.21) 24.6 (0.18)ST,SS,SI,FL NA NA NA NA NA NA NASTSSSIFL 61 (0.12) 39.7 (0.18) 78.5 (0.06) 63.1 (0.04) 63.6 (0.45) 52.7 (0.20) 35.5 (0.17)

Percentage of explained deviance along with generalized cross validation (GCV; in brackets) smoothness estimation were computed; the lowest GCVscore for a cluster represents the best tting when comparing models with distinct variables included. ST (8C), SS, SI (kg m23), FL (relative units m23).The model using all variables with interaction was impossible to compute due to insufcient number of cases (NA, not available).


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Fernandez et al., 2004); however, highest zooplanktonabundances in the neritic domain (Fig. 6a) were relatedto high abundances of the TX-C cluster species(Fig. 9e). The appendicularian Fritillaria spp. (mainly F.pellucida) comprised 72% of the cluster abundance; theassociation of F. pellucida with low FL values can be dueto the fact that non-phytoplanktonic material seems tobe an important part of the diet of F. pellucida in theCantabrian Sea (Lopez-Urrutia et al., 2003). Thepresent studys abundances for Fritillaria spp. (maximumof 7210 ind. m23; Table I), a species typical of the Bayof Biscay cold waters at the onset of the spring stratifica-tion (Acuna and Anadon, 1992), agree with measuredtemperatures that are among the lowest recorded inMay for the Bay of Biscay (e.g. Motos et al., 1996; Lavnet al., 1998; Albaina and Irigoien, 2004). The shelfbreak associated maximum abundances for TX-D1cluster species (Fig. 9f ) are explained by their well-known preference for deep habitats comprising the Bayof Biscay oceanic community (e.g. Beaudouin, 1975;Albaina and Irigoien, 2004). However, TX-D2 clustertaxa (Fig. 9 g) inhabiting the mid-shelf habitat charac-terized by low zooplankton total abundances (Fig. 6a)and low FL values (Fig. 3d) deserves further discussion;this ecosystem has been recently identified as a stablehydrological structure (Planque et al., 2006) and presentsa gap in zooplankton abundance between the inner-shelf and shelf break systems (Albaina and Irigoien,2004). Calanus helgolandicus development stages IVVI(CHELG code; Table I) represented 55% of TX-D2cluster abundances. Calanus spp. reproductive successhas been related to depth to avoid the seafloor burial ofeggs previous to hatching (Uye, 2000; Irigoien andHarris, 2003); beside this, retention by dominating cur-rents, predation avoidance and a potential off-shelf over-wintering source population could contribute to explainthe distributions observed and should be taken intoaccount when explaining the recurrent (Beaudouin,1975; Albaina and Irigoien, 2004) mid-outer shelfhabitat for C. helgolandicus in the Bay of Biscay. Morestudies are needed concerning C. helgolandicus populationdynamics in order to elucidate the factors governingthe distribution observed. In this sense, althoughC. helgolandicus is known to overwinter in oceanic deepwaters in the nearby Celtic Sea (Williams and Conway,1988), whether there is overwintering in Bay of Biscaywaters remains unclear (Bonnet et al., 2005; Ceballosand Alvarez-Marques, 2006).Observed and quantified relationships between zoo-

plankton groups and environmental variables can beused for more appropriate sampling design in futuresurveys and for the development of Bay of Biscay zoo-plankton distribution models when implementing

integrated ecosystem models. Although in French watersof the Bay of Biscay, most of ecological works have beenlimited to the study of Gironde river plume waters (e.g.Herbland et al., 1998; Bergeron and Herbland, 2001;Labry et al., 2001; Labry et al., 2002), the present studyshows the influence of different mesoscale structureswithin the bay forcing zooplankton composition anddistribution. In the Bay of Biscay, mesoscale structuresare recurrent and spatially predictable, as demonstratedby the modeling of the spreading process of Frenchriver plumes over the Bay of Biscay shelf (Lazure andJegou, 1998; Puillat et al., 2004) and of the slope internalwaves and their oceanographic effects (Gerkema et al.,2004; Pichon and Correard, 2006), along with the satel-lite monitoring of the eddies (Gohin et al., 2005). Ourresults indicate that this progress in operational physicaloceanography can be translated into detailed biologicalinformation through statistical modeling, if the biologi-cal sampling is carried out with sufficient spatial andtaxonomic resolution.

CONCLUSIONS

Cluster analysis classified zooplankton taxa into sevenmajor groups showing contrasting distributional patterns:although zooplankton communities of the CantabrianSea were governed by eddies located over the shelf break,in the French part of the domain, zooplankton commu-nities were determined by the presence of river plumesand internal wave generation over the slope.Correspondence between mesoscale structures and

zooplankton communities was supported by both thestrong speciesenvironment correlation for the CCA,and the high percentage of deviance explained byGAM analysis. SS and SI were the variables explainingthe higher percentage of the deviance.Environmental variables can be used to characterize

specific ranges of zooplankton abundance and speciescomposition even in highly dynamic ecosystems if thebiological sampling is carried out with sufficient spatialand taxonomic resolution.

ACKNOWLEDGEMENTS

We are grateful to the crew of the R. V. Vizconde deEza and the on board scientists and analysts for theirsupport during sampling and for counting fish eggs.Thanks are due to R. P. Harris for comments. Satelliteimages acquired and processed by the CERSAT(Centre ERS dArchivage et de TraitementFrenchERS Processing and Archiving Facility), part of


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IFREMER (French Research Institute for Exploitationof the Sea). Gironde river daily flow was obtained fromthe harbor authority of Bordeaux.

FUNDING

Doctoral fellowship of the Education, Universitiesand Research Department of the Basque CountryGovernment to A.A.; Spanish Ministry of Research(Ramon y Cajal grant) to X.I.; Projects EIPZI (SpanishMinistry of Research) and IMPRESS (Basque CountryGovernment).

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