Eur. Phys. J. B 65, 459–467 (2008) DOI: 10.1140/epjb/e2008-00341-4

Linking air-sea energy exchanges and European anchovypotential spawning ground

R. Grammauta, D. Molteni, G. Basilone, C. Guisande, A. Bonanno, S. Aronica, G. Giacalone, I. Fontana, M. Zora,

B. Patti, A. Cuttitta, G. Buscaino, R. Sorgente and S. Mazzola

Eur. Phys. J. B 65, 459–467 (2008)DOI: 10.1140/epjb/e2008-00341-4 THE EUROPEAN

PHYSICAL JOURNAL B

Linking air-sea energy exchanges and European anchovypotential spawning ground

R. Grammauta1, D. Molteni1, G. Basilone2, C. Guisande3, A. Bonanno2,a, S. Aronica2, G. Giacalone2, I. Fontana2,M. Zora2, B. Patti2, A. Cuttitta2, G. Buscaino2, R. Sorgente4, and S. Mazzola2

1 Dipartimento di Fisica e Tecnologie Relative (DIFTER), Universita degli Studi di Palermo, Viale delle Scienze, Ed. 18, 90128Palermo, Italy

2 Istituto per l’Ambiente Marino Costiero, IAMC – CNR, Via L. Vaccara 61, 91026 Mazara del Vallo (TP), Italy3 Facultad de Ciencias, Universidad de Vigo, Campus Universitario, 36310 Vigo, Spain4 Istituto per l’Ambiente Marino Costiero, IAMC – CNR, c/o IMC Loc. Sa Mardini, 09170 Oristano, Italy

Received 8 April 2008 / Received in final form 8 July 2008Published online 10 September 2008 – c© EDP Sciences, Societa Italiana di Fisica, Springer-Verlag 2008

Abstract. The physical and chemical processes of the sea greatly affect the reproductive biology of fishes,mainly influencing both the numbers of spawned eggs and the survivorship of early stages up to therecruitment period. In the central Mediterranean, the European anchovy constitutes one of the mostimportant fishery resource. Because of its short living nature and of its recruitment variability, associatedto high environmental variability, this small pelagic species undergo high interannual fluctuation in thebiomass levels. Despite several efforts were addressed to characterize fishes spawning habitat from theoceanographic point of view, very few studies analyze the air-sea exchanges effects. To characterize thespawning habitat of these resources a specific technique (quotient rule analysis) was applied on air-seaheat fluxes, wind stress, sea surface temperature and turbulence data, collected in three oceanographicsurveys during the summer period of 2004, 2005 and 2006. The results showed the existence of preferredvalues in the examined physical variables, associated to anchovy spawning areas. Namely, for heat fluxesthe values were around −40 W/m2, for wind stress 0.04–0.11 N/m2, for SST 23 ◦C, and 300 − 500 m3s−3

for wind mixing. Despite the obtained results are preliminary, this is the first relevant analysis on theair-sea exchanges and their relationship with the fish biology of pelagic species.

PACS. 89.60.-k Environmental studies – 89.75.-k Complex systems

1 Introduction

Almost all the processes that determine the properties ofthe ocean take place at the sea surface and are related tothe interactions between the atmosphere and the ocean [1].The air-sea fluxes of momentum, water and heat are ofparticular importance, in relation to the patterns of cur-rents, salinity and temperature. Such fluxes are also ofgreat concern to meteorologists and an important compo-nent of coupled models of the atmosphere-ocean systemused in studies of climate and climate changes.

The ocean receives energy through the air-sea inter-face by exchange of momentum, which also represents asource of kinetic energy, and by exchanges of heat andwater which locally modify the buoyancy of the fluid, andso act as a source of potential energy generating internalpressure forces [2].

The radiant energy flux to and from the ocean surfacecomprises the solar (or shortwave) component in the wave-

a e-mail: angelo.bonanno@irma.pa.cnr.it

length band 0.3 to 3 μm, and the terrestrial (longwave orinfrared) component from 3 to about 50 μm.

The surface sensible heat flux (QH) and the latent heatflux (QL) are two important components of the air-seaenergy exchange. While the former is strongly conditionedby the difference between sea surface temperature (SST)and air potential temperature, the latter occurs during thephase changes of water.

The magnitude and distribution of the shearing stressproduced by the wind on the sea surface is fundamen-tal to the wind-driven component of the ocean circulationand is essential to drive ocean models. The surface windstress has a direct relationship with the remixing of thefirst layers of the water and the mixed layer depth is pro-portional to the magnitude of the forcing [3–5]. The ma-rine ecosystem functioning is influenced by different phys-ical processes, through changes in the temperature, lightand mixing regimes [6–9]. Therefore, to better understandthe ecosystem dynamics, it is important to know and tomonitor both the abundance and distribution of marinebiological populations and the physical environment,

460 The European Physical Journal B

which may have important effects upon the biological re-sources.

Clupeoids populations, mainly anchovy and sardine,have undergone large interannual fluctuations in totalbiomass, worldwide [10]. Because of the short life spanof these species, the high variability in recruitment suc-cess determines rapid fluctuations in the population abun-dance. Many studies highlight the role of environmen-tal conditions in determining recruitment success of smallpelagic fish species [11–16], generally linking this successto survival of early life history stages, from larvae to ju-veniles [17–20]. Several efforts were addressed to studyand to model key environmental features which drive theEuropean anchovy (Engraulis encrasicolus L 1758) to theselection of a particular area as a spawning site [21–26].

The actions of surface forcing, derived from the at-mospheric energetic motions like wind stress and heatfluxes, are the major causes of mixing of the upper layer.This part of water column is called mixed layer (ML) andis defined as the surface layer of the sea where there isnearly no variation in density with depth, i.e. a quasi-homogeneous region [27]. This homogeneity is caused byturbulence through the action of mechanical mixing bywind stress and the action of convective mixing by surfacebuoyancy fluxes.

The mixed layer of the ocean and the related processesinfluence the ocean’s biological production. Many studiesin Kuroshio Extension regions show that changes in themixed layer depth and in temperature influence biologicalproduction [28] and that these changes are significantlyrelated to the mortality of the Japanese sardine [29].

When the mixed layer deepens, nutrients from sub-thermocline depths are brought up into the mixed layer.As a result, phytoplankton production increases and thegrowth of fish is augmented [30]. Temperature, along withphotoperiod, controls fish spawning, while wind-drivenmixing effects determine the depth of the upper mixedlayer [31].

In the Strait of Sicily (Central Mediterranean sea;Fig. 1) the knowledge of the linking between physical en-vironmental features and spawning site location is stillpoor.

The circulation of the water masses in the area can beschematized with a two-layer model: the Modified Atlanticwater (MAW) that flows toward east in the upper layerand the Levantine Intermediate Water (LIW) that movestoward west in the lower layer [32]. The flow of the MAW,locally denominated Atlantic Ionian Stream (AIS), drivesthe surface circulation [33]. The high spatial and tempo-ral variability of the AIS [34,35] induces changes in theintensities of energy exchanges between sea and MarineAtmospheric Boundary Layer (MABL).

The thermohaline structure in the whole study area isstrongly influenced by the AIS pattern and, consequently,the horizontal heat advection linked to the AIS is be-lieved to be a dominant factor in the energetic budget ofthis area. Vertical profiles of oceanographic variables (tem-perature, salinity, etc.) are the result of different forcinginputs like heat advection, air-sea heat exchanges, wind

stress, etc., and highlight the effects of specific phenomenaof the area like upwelling or downwelling. In the presentwork the air-sea heat fluxes, based on in situ collecteddata, are considered as a general index of the dynamics ofthe mixed layer, which takes into account the above citedforcings.

The main aim of the present study is to character-ize the anchovy spawning habitat in terms of satellitederived sea surface temperature (SST, ◦C), wind mixing(m3/s3) and air-sea interface energy exchanges, i.e. heatflux (QT = −(QH + QL), W/m2) and surface wind stress(τ , N/m2).

2 Material and methods

This research work has been performed on the data col-lected during three summer oceanographic surveys onboard the R/V Urania in the Strait of Sicily (centralMediterranean sea; Fig. 1) in the years 2004, 2005 and2006.

The three surveys were part of the AMECO project(“Mediterranean Anchovy, Growth and Oceanography”.Marine sciences applied to the management of the renew-able resources of the sea: the case study of the anchoviespopulation in the Strait of Sicily). The research activitiesdeveloped in the framework of the AMECO project werealso finalized to the study of the anchovy population inthe strait of Sicily in relation to physical and biologicalprocesses. The first oceanographic survey “ANSIC 2004”was carried out in the period 17th June–6th July 2004,the second survey “BANSIC 2005” in the period 3rd–25thJuly 2005, and the oceanographic survey “BANSIC 2006”in the period 29th July–14th August 2006.

A multidisciplinary set of data has been acquired in thestudy area (Fig. 1) on a station grid of 4×4 nautical milesin sea zones closer to the coasts; a grid of 12× 12 nauticalmiles was adopted for the off-shore areas. In each stationichthyioplankton samples have been collected by means ofa Bongo40 net, which is composed by two coupled netswith the inlet mouth diameter of 40 cm and mesh size200 μm. The plankton oblique tows were carried out to adepth of 100 m, wherever possible, with a constant speedof 2 knots. The filtered water volume of each mouth wasmeasured by a calibrated flow-meters (type G.O. 2030).

A total of 206 samples were collected in the 2004 sur-vey, 220 in the 2005 survey and 112 in the 2006 survey.Laboratory based sorting permitted to evaluate the num-bers of anchovy eggs and larvae in each station. High eggsdensities were considered as proxy of the spawning sites lo-cations. Larvae were considered less representative of theoriginal spawning area position due to the currents trans-port processes [36], and for this reason were not consideredin the present analysis.

In order to characterize the anchovy spawning habi-tat, a quotient rule analysis QI [24,26,37] was performedon anchovy eggs vs. SST, wind mixing index, windstress and heat flux. This technique permits to estab-lish whether the eggs distribution patterns are or not re-lated to specific habitat conditions. Quotient values were

R. Grammauta et al.: Linking air-sea energy exchanges and European anchovy potential spawning ground 461

Fig. 1. Study area with sampling stations (dots) in the period 2004–2006.

plotted against environmental factors, reflecting ‘selection’(quotient values >1) or ‘avoidance’ (quotient values <1)for a specific environmental variable range (category).

Sea surface temperatures (SST) have been ob-tained from daily satellite images acquired by theAVHRR (Advance Very High Resolution Radiome-ter) sensor installed on board the NOAA satel-lites (http://eoweb.dlr.de:8080/servlets/template/welcome/entryPage.vm).

Data collected by the hull mounted (2 m depth) tem-perature sensor were used both to check SST values ob-tained from satellites images and to estimate surface tem-perature in stations close to the coast. In such cases theestimation of SST was performed using the procedure sug-gested by Donlon et al. [38] and by Fairall et al. [39]. Theestimated SST values and the data collected by the me-teorological station installed on board the research vesselhave been used for calculating the energy fluxes, accord-ing to the procedure described by Rutghersson et al. [40].Fluxes were calculated from measured mean parametersusing the Bulk formulae, see equations (1), (2) and (3)below:

τ = ρa CD U2 (1)

QH = ρacpCHU(TS − θ) (2)

QL = LρaCEU(qS − q) (3)

where τ (N/m2), QH (W/m2) and QL (W/m2) are thevertical turbulent fluxes of momentum, sensible and latentheat. In the above formulae CD, CH and CE are the trans-fer coefficients for momentum, sensible heat and latentheat, dependent from the atmospheric stability conditions;L = 2.5×106 J kg s−1 is the latent heat of vaporization; Uand qS are the mean wind speed and the specific humiditycalculated at 10 m above the sea surface; ρa is the densityof the wet air at the surface, cp = 1004.67 J kg−1 K−1

is the specific heat of the dry air and θ is the potentialtemperature of the air calculated by the relationship (4):

θ = Ta + 0.0098zr (4)

where Ta is the air temperature measured at zr = 10 m.TS and qS are the sea surface temperature and the specifichumidity.

The heat flux from the ocean (QTotal in W/m2) wascalculated as the sum of net shortwave and longwave ra-diation (RNet, W/m2) and fluxes of latent and sensibleheat. In particular, a first analysis took into considerationthe total heat flux (positive downward direction), see

QTotal = −(QH + QL) + RNet (5)

462 The European Physical Journal B

Table 1. Total number of stations in each survey and number of stations considered in the analysis.

Number of StationsSurvey Number of Number of Number of stations with Anchovy eggs Night Day

Bongo 40 stations Fluxes stations with anchovy eggs and Fluxes Stations StationsAnsic 2004 206 127 40 28 10 18Bansic 2005 220 120 63 39 11 28Bansic 2006 112 86 52 38 20 18Total 538 333 155 105 41 64

Fig. 2. Colour maps of the considered physical variables: (a) Mean SST (◦C) satellite maps, (b) absolute values of Wind Stress(N/m2) and (c) Heat Flux (Latent + Sensible heat).

A second step considered the heat flux without the netradiation RNet; in this case the considered heat flux was:

QT = −(QH + QL). (6)

The energy transferred through the water column by thewind creates turbulence in the surface layers. Therefore, awind-mixing index in the upper layer is usually calculatedas the cube of wind speed (U3) [41]. The estimation ofenergy fluxes and wind-mixing index, based on measuredmean parameters in each station, was not performed inall the stations of the study area (Fig. 1) since the meteo-rological station did not work continuously for the wholeperiod of each survey.

Moreover, the quotient analysis considered all the sta-tions in which anchovy eggs were collected and air-seafluxes were estimated. Table 1 summarizes both the num-ber of the available stations and the number of stations

included in the quotient analysis. The Table 1 shows alsothe number of stations sampled during daytime and night-time.

3 Results

The maps of mean sea surface temperatures (SST) ac-quired by satellites during the oceanographic surveys areshown in Figure 2a. The main difference among surveysis the temperature range of the “Bansic 2006” which wasthe only carried out in later summer (1–15 august). Forthe surveys conducted in 2005 and 2006 lower SST valuesare observed in more coastal areas singling out the effectsof coastal upwelling. During the 2004 survey a colder seaarea was located in the north-western part of the studyarea (Fig. 2a).

R. Grammauta et al.: Linking air-sea energy exchanges and European anchovy potential spawning ground 463

The estimated wind stress τ (N/m2), in absolute value,and heat flux QT (W/m2) for the three surveys are shownin figures 2b and 2c. Due to the malfunctioning of themeteorological station the energy fluxes in these figures donot cover the whole study area. Figures 2b and 2c do notpresent synoptic plots, since measured mean parametersin each station were used to contour wind stress and heatflux, but they show air-sea energy fluxes recorded duringthe anchovy eggs collection.

The average values and confidence intervals of WindStress, Wind Mixing, SST and Heat Fluxes estimated inall the available stations are reported in Table 2.

During the 2004 and 2006 surveys the heat flux QT

showed a decreasing trend moving eastward in the studyarea (see Fig. 2c). A different pattern was observed in the2005 survey; the western sea area, on the Adventure Bank(Fig. 1), had a positive mean heat flux QT (+ 53.1 W/m2),due to upwelling phenomenon [42] that moved up sub-surface colder sea water. In the south-eastern part of thestudy area, between the southern Sicily coast and Malta,the average heat flux QT is −12.7 W/m2 and the averagelatent heat flux (QL) is 22.3 W/m2. In the same surveyalso a sea area located in the western Ionian sea was in-vestigated (Figs. 2b and 2c); here SST and surface salinityvalues were higher than in the Strait of Sicily [43,44] andthe mean heat flux QT was −108.6 W/m2.

Anchovy eggs densities (number of eggs/m3), as re-sulted from the ichthyoplanktonic sorting, for the threeoceanographic surveys are shown in Figure 3. The mainspawning ground during the 2004 survey was located inthe coastal waters between Sciacca and Gela (Fig. 3a);smaller eggs densities were also present in more coastalwaters close to Mazara and in the northern part of theMaltese shelf. During the 2005 survey the eggs densityspatial distribution pattern (Fig. 3b) was complementaryto the one observed in the previous year, with two mainspawning areas located on the Adventure Bank and onthe northern part of the Maltese shelf. The spatial pat-tern in 2006 was similar to 2005 but with lower densities(Fig. 3c).

3.1 Characterization of anchovy spawning ground

3.1.1 Heat flux

The estimated average values of sensible and latent heatfluxes for each survey (Tab. 2) show that in the study areathe relative contribution of QH was higher than QL onlyduring the 2005 survey. This result suggests that heat fluxQT can not be considered as a proxy of water temperaturebut, on the contrary, the latent heat flux is quite importantin the habitat characterization.

A first quotient analysis was carried out on the eggdensities in relation to total heat flux (QTotal) data. Theresults highlighted several peaks in the entire variationrange of heat flux (Fig. 4) but with values slightly higherthan 1 that is the minimum significance level for QI. Suchpattern does not suggest any clear cue for spawning loca-

Fig. 3. Eggs density distribution evaluated during the oceano-graphic surveys Ansic 2004 (a), Bansic 2005 (b) and Bansic2006 (c).

tion even if it appears affecting in some degree the anchovyspawning selection.

Therefore, the cumulative dataset was divided in twogroups relative to day and night stations (Figs. 5a and 5b).In this case the quotient index analysis showed clearerresults, with completely different range values betweenday and night. In particular, during the night (Fig. 5a),

464 The European Physical Journal B

Table 2. Average values and confidence intervals of Wind Stress, Wind Mixing, SST and Heat Fluxes (QH , QL and QT ) inthe whole study area

Surveyτ (N/m2) Wind Mixing (m3/s3) SST (C◦) QH(W/m2) QL(W/m2) QT (W/m2)

Average ± CI Average ± CI Average ± CI Average ± CI Average ± CI Average ± CIAnsic 2004 0.0193 ± 0.0045 85.42 ± 22.40 22.25 ± 0.30 −0.45 ± 0.99 +27.26 ± 4.16 −26.81 ± 4.73Bansic 2005 0.0470 ± 0.0090 271.71 ± 60.10 24.25 ± 0.35 −13.74 ± 3.95 +4.53 ± 9.37 +9.21 ± 12.48Bansic 2006 0.0816 ± 0.0148 421.93 ± 73.47 24.00 ± 0.37 +0.39 ± 2.75 +57.45 ± 10.69 −57.84 ± 12.63

Q Total (W/m2)-20

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Fig. 4. Frequency distribution of total heat flux (left axis),and anchovy quotients of eggs densities (eggs/m2) vs. totalheat flux (right axis) at stations sampled in the Strait of Sicily(see Tab. 1).

which is the period when anchovy spawning events takeplace, two main peaks (–100 and 0 W/m2) become evi-dent. During daytime, due to the net solar radiation con-tribution, the variable range was larger than the night one,and the QI revealed several peaks. The daytime QTotal

gave no useful information for the characterization of an-chovy spawning habitat. Probably, the large solar radia-tion range hided the real eggs distribution pattern relatedto the heat flux.

In order to use as much as possible the available sta-tions data (Tab. 1), a further quotient index analysis wasperformed taking into consideration the heat flux QT ,i.e. excluding the net radiation. The results in Figure 6ashow a unique peak (–40 W/m2) during night-time butwith high representativeness (see number stations and QIvalue). This result is in agreement with the QI analy-sis shown in Figure 5a; the range around the peak at−100 W/m2 in Figure 5a corresponds to the range aroundthe peak at −40 W/m2 in Figure 6a, since the meannet radiation during the nights of the surveys was about−50 W/m2.

Finally, all the available stations were analysed in re-lation to the heat flux QT , obtaining the QI distributionfor both day and night stations (Fig. 6b). The obtainedresults confirm the peak at –40 W/m2 estimated in thenight-time stations (Fig. 6a). A further peak is evident at60 W/m2 which corresponds to only eight of the daytimeperformed stations.

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Fig. 5. Frequency distribution of heat flux QTotal (left axis),and anchovy quotients of eggs densities (eggs/m2) vs. heat fluxQTotal (right axis) at stations sampled in night-time (a) andin day-time (see Tab. 1).

3.1.2 Wind Stress and SST

Figure 7 shows the results of the quotient index analysison wind stress data. The main peaks, in relation to theQI and the number of stations, correspond to 0.04 and0.1 N/m2; higher wind stress values correspond to verysmall number of eggs stations.

The results of the QI analysis performed on windmixing index are similar to the ones obtained on windstress; the optimal spawning conditions are in the range300–500 m3/s3 (Fig. 8).

R. Grammauta et al.: Linking air-sea energy exchanges and European anchovy potential spawning ground 465

QT (W/m2)

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Fig. 6. Frequency distribution of heat flux QT (left axis), andanchovy quotients of eggs densities (eggs/m2) vs. heat flux QT

(right axis) at stations sampled in night-time (a), and in bothday- and night-time (see Tab. 1).

Wind Stess (N/m2)0.0

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Fig. 7. Frequency distribution of Wind Stress (left axis), andanchovy quotients of eggs densities (eggs/m2) vs. Wind Stress(right axis) at stations sampled in the Strait of Sicily (seeTab. 1).

U3 (m3/s3)

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Fig. 8. Frequency distribution of wind-mixing turbulenceindex (left axis), and anchovy quotients of egg densities(eggs/m2) vs. wind-mixing turbulence index (right axis) at sta-tions sampled in the Strait of Sicily (see Tab. 1).

SST(°C)17 18 19 20 21 22 23 24 25 26 27 28

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Fig. 9. Frequency distribution of sea surface temperature(SST) (left axis), and anchovy quotients of egg densities(eggs/m2) vs. SST (right axis) at stations sampled in the Straitof Sicily (see Tab. 1).

The quotient index analysis performed on SST (Fig. 9)indicates that the spawning habitat of anchovy is charac-terized by a main peak at 23 ◦C; such result is in agree-ment with values reported in literature in the study area,which indicate as optimal temperature for anchovy spawn-ing the range 19–23 ◦C [36,45].

4 Discussion and conclusions

In the Strait of Sicily the study of possible influences ofmarine physical processes on the biology of small pelagicfish species is important in order to better understand thedynamics of such populations. In fact, also in the studyarea these species experienced strong and unlikely pre-dictable fluctuations [46–48]. In the last decade severalstudies have been carried out in this area both on adultsand on early life stages [36,43,45]. From multidisciplinarysurveys, for example, it was possible to recognize alongthe southern coast of Sicily several spawning and nursery

466 The European Physical Journal B

areas for anchovy and also to schematize a transportmodel to explain the distribution patterns of anchovy lar-vae in relation to the surface circulation [36].

The spawning intensity and location of the spawninggrounds of important small pelagic fishes are generallyassociated with areas of high productivity (e.g., riverineoutflows, upwelling areas and fronts). It has been hypoth-esized that fluctuations of small pelagic fish populationsare affected by changes in ocean climate in terms of theextent and spatiotemporal location of suitable spawninghabitats [49]. Several biological and environmental vari-ables, like spawning stock biomass, mixed layer depth,turbulence and food availability, appear strictly linked tothe selection of spawning locations [23,26,50].

The objective of the present work was to explore theeffects of some physical variables in structuring the suit-ability of the anchovy reproductive habitat. From litera-ture studies, anchovy eggs are mainly found in warm wa-ters, with SST between 17 and 23 ◦C [50]; the anchovyspawning habitat in NW-Mediterranean is characterizedby a main temperature peak around 17–19 ◦C. In theStrait of Sicily the main peak of the QI analysis is at23 ◦C while the spawning habitat temperatures, as sug-gested in Figure 9, are in the range 21–24 ◦C. In the Cen-tral Mediterranean these temperatures are characteristicof the stratified season. In fact, anchovy spawning seasonbegins when temperature warms at the end of spring andextends throughout the summer [51].

Findings on SST are in agreement with other stud-ies accomplished for the Bay of Biscay anchovy, where itwas observed that when modelling the potential spawninghabitat, the best hydrological predictors were mainly thebottom temperature and the mixed layer depth followed,with less extent, by SST [23].

The general hypothesis behind the link between earlystages mortality and wind stress could be explained asfollow: turbulence, generated by wind or other forces,may enhance the survival of planktonic predators infood-limited environments through an increase in the preyencounter rate. Rothschild et al. [52] made four specificpredictions: (i) both predator and prey may adjust theirvertical position to take advantage of turbulence variationin the water column; (ii) the structure of prey patches maydepend on the relative velocities and the relative concen-trations of predator and prey; (iii) vertical nutrient fluxeswill be enhanced in nutrient-limited environments; and(iv) turbulent processes provide a link between large scaleoceanographic phenomena (wind speed) and microscaleevents (feeding success). In relation to the point (i), de-spite the existence of several literature studies focusedon the relationship between water column turbulence andfeeding success of fish larvae [53] and references therein, itis not easy to derive clear relationships and it appears thatthe stratified nature of the water column, rather than tur-bulence or wind mixing, better explains the vertical distri-bution of fish larvae [54]. One of the main reasons for thisdiscrepancy could be related to the assumption (often nottrue) that derived indexes on water column turbulence ac-curately reflects the induced encounter probability. For in-

stance wind based estimates of turbulence underestimatethe dissipation of kinetic energy in the upper mixed layerand are of limited predictive value [53].

The instabilities produced by wind stress are one of themajor causes of sea water mixing. In the present study thewind mixing index appears related to the spawning selec-tion process, even if higher QI values were not stronglysupported by the number of stations in the 300–500 tur-bulence classes, which were only 12 and 11 respectively.Indeed, further data may help in the future to betterevaluate its importance on the spawning site selection be-haviour of anchovy.

The upwelling observed along the southern coast ofSicily is mainly driven by the AIS meanders and cyclonicvortices [33]. Moreover, it is well known and documentedby bibliography [32,42] that wind stress may modulatethe upwelling strength in the study area. From the bio-logical point of view the upwelling phenomenon tends tomodify the temperature regime of surface waters, coolingthem below the optimal temperatures for anchovy spawn-ing [36,45]. Therefore, in this paper the major effects ofwind stress were taken into account by analysing bothsea water mixing (wind mixing index) and temperatureregime.

It is well documented that variations of heat fluxesinduce changes of mixed layer depth, hmix, from daily tointerannual time scales [4,5]. Furthermore, heat fluxes alsoaffect the mixing rate of the surface layer. In the presentwork, due to the high dynamics of the sea water circula-tion in the Strait of Sicily, the air-sea heat fluxes, based onin situ collected data, were considered as a general indexof the dynamics of the mixed layer. The QT or QTotal val-ues estimated during night-time are more representativeof the characteristics of the anchovy spawning sites, sincespawning process of this fish species is recognised to occurin this time interval. Day-time estimates are less represen-tative, since a transport process is active in the area, butmay be used, with the necessary attention, to increase thenumber of useful observations.

The preliminary results obtained in this work sug-gest that air-sea fluxes and SST, and in less extent thewind induced turbulence, may be considered proxies of afavourable anchovy spawning sites, where adult specimensmay meet optimal environmental features for reducing themortality of the spawning products. Further investigationsand surveys for data collection are necessary in order tounderstand how the biological variability can be coupledto water column stability/turbulence.

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