J. DulcÏ ic á M. Kraljevic á B. Grbec á A. Pallaoro

Composition and temporal ¯uctuations of inshore juvenile ®shpopulations in the Kornati Archipelago, eastern middle Adriatic

Received: 23 March 1997 /Accepted: 11 April 1997

Abstract Temporal ¯uctuations of species compositionand abundance of ®sh juveniles in the National ParkKornati were studied over 12 months from January toDecember 1992. A total of 40 168 individuals, repre-senting 24 families and 69 species, were collected using a50 m long beach seine. The community was dominatednumerically by a few species: Atherina hepsetus (45.90%),Sarpa salpa (21.21%), Diplodus vulgaris (10.49%), andSymphodus ocellatus (6.98%), constituting over 84.58%of the total catch. Similarity between patterns in theabundance of the 17 most common species were exam-ined using correlation matrix-based principal compo-nent analysis. Results were compared to the abioticfactors leading to the conclusion that only a low amountof variation in the abundance ®eld can be explained bytemperature, salinity and dissolved oxygen.

Introduction

Numerous studies have been published on ®sh popula-tions in lagoons, estuaries and coastal regions in manyparts of the world. Most of the studies are on seasonalvariations in the number of individuals, species diversity,and the in¯uence of abiotic factors on abundance andspecies performance (Haedrich and Haedrich 1974; Allenand Horn 1975; Allen 1982; Allen et al. 1983; Beckley1984; Reina-Hervas and Serrano 1987; Tzeng and Wang1992; Whit®eld 1994; Laegdsgaard and Johnson 1995).However, most of the published material on ®shes in theeastern Adriatic is restricted to taxonomy, general ®sheryaspects, and, to a lesser extent, to the biology of variousspecies (Morovic 1960, 1962, 1965; GrubisÏ ic 1974; Jardas1980 a,b, 1982, 1986, 1996; Jardas and Pallaoro 1989;

DulcÏ ic 1993a, 1995; DulcÏ ic and Cetinic 1993; DulcÏ ic andKraljevic 1995; Kraljevic et al. 1995, 1996; Kraljevic andDulcÏ ic 1996. There have only been a few papers on ju-venile ®sh populations in the eastern Adriatic. Some re-search has dealt with the temporal distribution of youngmugilids in the coastal area of the eastern middleAdriatic (Katavic 1980; Jug-Dujakovic 1988) and somewith feeding of striped sea bream, Lithognathus mo-rmyrus (Froglia 1977; Jardas 1985), and annular bream,Diplodus annularis (Jardas et al. 1986). Previous prelim-inary investigations on juvenile ®sh populations inKornati Archipelago are limited and incomplete, con-cerned just with occurrence and quantity of species(Kraljevic and Jug-Dujakovic 1987; Kraljevic andPallaoro 1991).

The present study provides the ®rst data on thetemporal ¯uctuations in juvenile ®sh composition, di-versity indices and ®sh species association in the coves ofNational Park Kornati (eastern middle Adriatic). Therelative importance of temperature, salinity and dis-solved oxygen on biotic factors was examined usingmultivariate techniques.

Materials and methods

Study area

The Republic of Croatia with a surface area of 88 438 km2 (land,sea and islands) has seven national parks and numerous otherprotected areas. The Kornati Islands lie along the central part ofthe Croatian coast, between Zadar and SÏ ibenik. The Kornati Ar-chipelago covers an area of approximately 224 km2 between Pro-versa (NW) and Samogradska vrata (SE) (Fig. 1) and has 91islands, islets and reefs. The Kornati Islands have the most irreg-ular coastlines of any islands in the Mediterranean. Human activ-ities in the area include ®shing, the traditional occupation ofKornati inhabitants and inhabitants from the island Murter, andtourism (MihelcÏ ic 1997).

Sampling techniques

Sampling was conducted on a monthly basis from January toDecember 1992 from ®ve coves: SÏ ipnata, Lojena, Studena, Lavsa

Marine Biology (1997) 129: 267±277 Ó Springer-Verlag 1997

Communicated by O. Kinne, Oldendorf/Luhe

J. DulcÏ ic á M. Kraljevic á B. Grbec á A. PallaoroInstitute of Oceanography and Fisheries,SÏ etalisÏ te Ivana MesÏ trovic a 63, P.O.B. 500,21000 Split, Croatia

and ZÏ akan (Fig. 1). Fish samples were collected using a 50 m longbeach seine. Net depth at the beginning of wings was 30 cm and250 cm at the central part together with the sac. Outer wings wereof 8 mm mesh size and central sac of 4 mm. The net was alwayshauled from the entrance to the cove (max. 7 m depth) to its innerend. Collected organisms were sorted and preserved in 4% formalin(pH from 8.5 to 9.0). The ®sh species were identi®ed according toSÏ oljan (1975) and Jardas (1996). The juveniles of the species weretaken as specimens with already formed scales, and were taken assuch until the moment of ®rst sexual maturity (Katavic 1984). Thesampling area was characteristically hard, sandy, sandy-clay andsandy-mud laterally overgrown by meadows of Posidonia oceanicaor Cymodocea nodosa. Physical±chemical parameters were mea-sured by classical methods in every cove before net hauling. Tem-perature was measured with a mercury thermometer, salinity with alaboratory inductive salinometer, and dissolved oxygen (DO) withWinkler's method.

Data analysis

Temporal ¯uctuations in community structure, abiotic factors andinteractions between these variables were analysed using multi-variate techniques: multiple linear regression and principal com-ponent analysis (Preisendorfer 1982). Community structure wasspeci®ed by species richness (D), diversity (H¢ ) and evenness (J¢ )using formulae proposed by Margalef (1968), Shannon and Weaver(1949) and Pielou (1966), respectively. The degree of relationshipexisting between these variables and abiotic factors (temperature,salinity and dissolved oxygen) was determined by R2, e.g. the co-e�cient of multiple determination.

Abundance in the species compositions was subject to thecorrelation matrix-based principal component analysis (PCA)(Preisendorfer 1982) to examine a minimal number of groups(clusters) the variability of which describes the maximum amountof the total variability in the ®sh community. The PCA was per-formed on the correlation matrix of standardised variables (zeromean and unit standard deviation). We used Bartlett's test (Fulgosi1988) for testing the signi®cance of the correlation matrix. The

signi®cance of extracted principal components (eigenvalues) weretested with Rule N (Overland and Preisendorfer 1982), usingMonte Carlo simulation of the random matrix of the same size asthe original data matrix. To enhance the interpretation of thecomponents, Varimax orthogonal rotation was applied (Richman1986).

The relationship of species composition between the ®ve sta-tions was compared using Spearman's rank correlation test on thebasis of the yearly catch in terms of number of each individualspecies. For comparing abiotic factors between ®ve sampling lo-cations, an ANOVA model was used.

Results

Temporal ¯uctuations of abiotic factors

Analysis of variance revealed signi®cant correlationsbetween temperature (ANOVA: p < 0.01; df = 3.65;F = 0.14), salinity (F = 2.51) and dissolved oxygen(F = 1.09) among the ®ve sampling stations. Meanmonthly variation in sea temperature, salinity and dis-solved oxygen (DO) averaged over the ®ve coves arepresented in Fig. 2. Mean monthly temperature rangedfrom 11.1 °C (SD = 0.98) in February to 26.2 °C(SD = 1.64) in August. Mean monthly salinity values,however, were more stable (ranging from 37.46 � 1.68to 38.52 � 0.51 psu, with the exception of Novemberwhen the salinity declined sharply to 35.86 � 4.40 psu).Oxygen concentration level ¯uctuated between 6.07 mll)1 (SD = 0.94) and 8.17 ml l)1 (SD = 0.88). While seawater temperature shows typically Adriatic seasonalcycles, seasonal cycles in salinity are not evident, mainlybecause the sampling stations are situated in the coastal

Fig. 1 Locations of the sam-pling stations (d) in the KornatiArchipelago

268

area which is strongly in¯uenced by precipitation andevaporation.

Temporal ¯uctuations in ®sh compositionsand abundance

Spearman's rank correlation coe�cients of speciescomposition between the ®ve stations were signi®cant atp = 0.01, indicating that the rank of species composi-tion was highly correlated with sampling location. So,data for all coves were combined. Sixty-nine species,representing 24 families, were caught between Januaryand December 1992 (Table 1), the highest number wascollected in June (41) and the lowest during the winterperiod from December (23) to March (22). The numberof species captured increased in late spring and earlysummer (May to June) and also in autumn (Septemberto November), and decreased in winter (December toMarch).

A total of 40 168 ®shes were collected: the highestcollection was in April (8958), and the lowest in theperiod from June (1108) to September (1078). Atherinahepsetus (45.895%), Sarpa salpa (21.206%), Diplodusvulgaris (10.488%) and Symphodus ocellatus (6.983%)comprised 84.572% of the total sample (Table 1).A. hepsetus was the dominant species in the collection,and had the highest abundance in April. S. salpa andD. vulgaris had the highest abundance from January toJune, while the abundance of S. ocellatus was highest inthe period from August to December. The remainingspecies (65) comprised from 2.338 to 0.003% of the to-tal catch. The overall value of richness D was 6.42,ranging from 2.35 in March to 5.71 in June. H¢ values¯uctuated from 1.12 in April to 2.79 in June, with anoverall value of 2.94. J¢ ranged from 0.77 to 0.32. Meanmonthly variations in these biotic factors are presentedin Fig. 3.

Multivariate analysis of relationship between bioticand abiotic factors

The relationship between abiotic factors such as tem-perature, salinity and dissolved oxygen (included inmodel as independent variables) and the biotic factors(number of species, number of individuals, diversity andabundances: dependent variables) was analysed usingmultiple linear regression models. The signi®cance levelfor the variables included in the model was set atp < 0.05. Results indicated that variations in abioticfactors could predict more than 85% of monthly varia-tions in number of species mainly because of the inter-action e�ect of temperature and salinity. Variation innumber of individuals showed no signi®cant correlationswith independent variables. Results also suggest thatabout 78% of the variability associated with monthly¯uctuations in diversity could be predicted by the tem-perature and oxygen concentration levels. These resultsindicated that even if there is a temperature ``control-ling'' monthly ¯uctuations of number of species anddiversity, derivation of a non-zero association betweenthese biotic factors and sea water temperature does notnecessarily imply a casual relationship. In temperate seassuch as the Adriatic, most species have internalised theirbiological cycles according to seasonal patterns. Theyspawn or settle in a quite short and well-de®ned periodof the year. So, abundances of many species were posi-tively or negatively correlated with sea water tempera-ture (Table 2), because they settle during the hot or coldseason. This is a reason why multilinear correlationcoe�cients between the number of individuals and watertemperature are nonsigni®cant. Based on the multiplelinear regression model it was found that six of 20common species positively (Coris julis and Mullussurmuletus) or negatively (Diplodus puntazzo, Diplodusvulgaris, Sarpa salpa and Oedalechilus labeo) correlatedwith temperature, indicating that timing for settling ofthe individual species is di�erent. Only one species (Liza

Fig. 2 Monthly variations in the mean sea water temperature (°C),salinity (psu) and dissolved oxygen (ml l)1) in the Kornati Archipel-ago between January and December 1992

269

Table 1 Monthly changes in species composition of juvenile ®sh collected in Kornati Archipelago from January to December 1992

Serial Family, January February March April May Juneno. species

N % N % N % N % N % N %

Clupeidae1 Sardina pilchardus 3 0.03

Engraulidae2 Engraulis encrasicolus 1 0.03 4 0.04

Syngnathidae3 Nerophis ophidion 1 0.03 1 0.014 Syngnathus acus 4 0.13 1 0.035 Syngnathus typhle 2 0.06 1 0.01 2 0.07

Serranidae6 Serranus cabrilla7 Serranus hepatus 1 0.03 2 0.18

Carangidae8 Trachurus trachurus 1 0.09

Sciaenidae9 Sciena umbra

Mullidae10 Mullus barbatus 2 0.03 3 0.11 5 0.4511 Mullus surmuletus 8 0.28 5 0.45

Sparidae12 Boops boops 8 0.28 62 5.6013 Diplodus annularis 23 0.74 1 0.03 3 0.04 34 0.38 264 9.37 36 3.2514 Diplodus puntazzo 74 2.38 75 2.02 84 1.09 129 1.44 23 0.82 31 2.8015 Diplodus sargus 23 0.82 25 2.2616 Diplodus vulgaris 346 11.13 1371 36.96 1150 14.94 858 9.58 304 10.79 106 9.5717 Lithognathus mormyrus18 Oblada melanura 2 0.03 15 0.53 1 0.0919 Pagellus acarne 45 1.60 3 0.2720 Pagellus erythrinus 1 0.04 3 0.2721 Pagrus pagrus 1 0.0922 Sarpa salpa 1743 56.05 663 17.88 2793 36.29 1375 15.35 707 25.10 194 17.5123 Sparus aurata 1 0.01 1 0.04 1 0.0924 Spondyliosoma cantharus 19 0.67 20 1.81

Centracanthidae25 Spicara maena 13 1.1726 Spicara smaris 12 0.39

Pomacentridae27 Chromis chromis

Labridae28 Coris julis 1 0.03 5 0.06 10 0.11 60 2.13 44 3.9729 Labrus merula 1 0.0930 Symphodus cinereus 11 0.35 4 0.11 5 0.06 26 0.29 4 0.14 9 0.8131 Symphodus mediterranues 1 0.0932 Symphodus melanocercus33 Symphodus ocellatus 103 3.31 15 0.40 51 0.66 25 0.28 40 1.42 196 17.6934 Symphodus roissali 2 0.0335 Symphodus rostratus 1 0.0336 Symphodus tinca 7 0.63

Trachinidae37 Trachinus draco

Uranoscopidae38 Uranoscopus scaber 1 0.09

Gobiidae39 Gobius bucehichi 3 0.08 14 0.16 13 0.46 12 1.0840 Gobius cobitis41 Gobius fallax 2 0.06 2 0.05 2 0.02 1 0.0942 Gobius geniporus 2 0.07 1 0.0943 Gobius niger 17 0.46 15 0.19 28 0.31 32 2.8944 Pomatochistus knerii 6 0.19 1 0.03 5 0.06 2 0.02 3 0.2745 Pomatochistus

marmoratus52 0.58

46 Zosterissessorophiocephalus

Callionymidae

11 0.35 6 0.08 25 0.28 86 3.05 44 3.97

47 Callionymus pusillusBlemiidae

48 Aidablennius sphynx 2 0.05 2 0.03 3 0.03

(cont. on p. 271)

270

July August September October November December Total

N % N % N % N % N % N % N %

3 0.008

5 0.012

2 0.05 4 0.01010 0.93 2 0.05 1 0.04 18 0.045

14 1.18 3 0.28 1 0.04 1 0.04 24 0.060

4 0.34 2 0.19 6 0.0153 0.008

1 0.003

2 0.17 2 0.005

14 1.05 20 1.69 44 0.11024 1.80 109 9.21 96 8.91 4 0.16 246 0.612

1 0.08 15 1.39 86 0.2147 0.53 116 9.81 53 4.92 79 3.21 45 1.12 661 1.6463 0.23 1 0.04 111 2.77 59 2.18 590 1.46916 1.20 1 0.08 1 0.09 66 0.16442 3.15 14 1.18 6 0.56 11 0.45 5 0.12 4213 10.488

3 0.08 3 0.00812 0.90 123 10.40 6 0.56 20 0.81 179 0.44611 0.83 59 0.147

1 0.08 1 0.04 6 0.0151 0.08 2 0.00578 5.85 19 1.61 24 2.23 37 1.50 122 3.04 763 28.24 8518 21.206

3 0.00812 0.90 29 2.45 80 0.199

11 0.45 24 0.06012 0.030

86 6.45 8 0.74 94 0.234

31 2.33 25 2.11 41 3.80 24 0.97 20 0.50 1 0.04 262 0.6521 0.003

2 0.15 18 1.52 68 6.31 10 0.41 9 0.22 51 1.89 217 0.5402 0.08 12 0.44 15 0.037

1 0.09 2 0.08 4 0.10 7 0.26 14 0.03569 5.18 302 25.53 152 14.10 1501 60.94 235 5.86 116 4.29 2805 6.9831 0.08 6 0.56 1 0.02 1 0.04 11 0.0271 0.08 2 0.19 1 0.04 1 0.02 2 0.07 8 0.020

8 0.74 6 0.24 1 0.02 22 0.055

1 0.09 1 0.02 2 0.005

1 0.08 5 0.42 1 0.09 8 0.020

2 0.15 18 1.52 5 0.46 3 0.12 4 0.10 4 0.15 78 0.19413 1.10 3 0.08 1 0.04 17 0.042

1 0.08 1 0.09 2 0.05 11 0.0279 0.83 2 0.08 14 0.035

1 0.08 45 3.80 16 1.48 4 0.16 1 0.02 4 0.15 163 0.4061 0.02 18 0.045

52 0.129

194 14.55 17 1.44 25 2.32 55 2.23 157 3.91 3 0.11 623 1.551

1 0.02 1 0.04 2 0.005

28 2.37 1 0.04 36 0.090

(cont. on p. 272)

271

aurata) was negatively correlated with salinity, while theother species' correlations were insigni®cant. This indi-cates that most species could tolerate wide variation ofsalinity. Only two species (Symphodus ocellatus andBoops boops) were signi®cantly correlated with dissolvedoxygen (Table 2).

To consider which species, or group of species, con-tributes signi®cantly to the community structure, prin-cipal component analyses were performed. According tononsigni®cance of the correlation matrix (Bartlett's test)for all determined species (20), PC analysis was done forthe 17 most frequent species in the area of investigation(Liza saliens, Chromis chromis and Boops boops wereexcluded). Correlation matrix (for 17 species) was sig-ni®cant for p = 0.05. The ®rst ®ve principal compo-nents together describe 79.03% of the total abundancevariance: PC1 contributes with 33.86%, PC2 with18.15%, and PC3 with 11.02%. The remaining two ex-tracted principal components contribute with 8.57 and7.42% to the total variability in the abundance ®eld.When using only percentages of total variances it isdi�cult to choose the number of PCs with signi®cantmeanings. Therefore, Rule N was applied. The ®rst threePCs are signi®cant because the eigenvalues of the real

data matrix are smaller than those of the random datamatrix. On the basis of the distribution of rotatedloadings it was possible to distinguish ®ve groups(Fig. 4), but only the ®rst three signi®cantly contributewith di�erent amounts to the total variability in speciesabundance. PC1 has the highest loadings for Atherinahepsetus, Diplodus puntazzo and Chelon labrosus. PC2

has highest loadings for Mullus surmuletus, Oblada me-lanura, Liza ramada and Gobius niger. In the case of PC3,four species were grouped: Coris julis, Diplodus annul-aris, Atherina boyeri and Symphodus ocellatus.

Scores of the ®rst three principal components werecompared with sea water temperature, salinity and DOshowing that only a low variability in abundances can beexplained by these abiotic factors. Signi®cant linearcorrelation was found between temperature and PC2

scores only ( p < 0.10; r = 0.54).

Discussion

The Adriatic Sea is an oligotrophic sea (Zore-Armandaet al. 1987). It is relatively rich in ichthyofauna and ac-cording to Jardas (1996) has 407 ®sh species and sub-

Table 1 (cont.)

Serial Family, January February March April May Juneno. species

N % N % N % N % N % N %

49 Lipophrys dalmatinus 2 0.03 1 0.0450 Lipophrys pavo 2 0.02 5 0.18 8 0.7251 Lipophrys trigloides 2 0.0652 Parablennius incognitus 1 0.03 2 0.07 1 0.0953 Parablennius

sanguinolentus2 0.02 2 0.18

54 Parablenniustentacularis

1 0.03 1 0.01 2 0.07

Sphyraenidae55 Sphyraena sphyraena

Mugilidae56 Chelon labrosus 21 0.68 4 0.11 13 0.17 40 0.45 5 0.4557 Liza aurata 94 3.02 179 4.83 34 0.44 20 0.22 4 0.14 61 5.5158. Liza ramada 1 0.03 23 2.0859 Liza saliens 11 0.35 20 0.54 12 0.4360 Oedalechilus labeo 75 2.41 186 5.01 112 1.45 189 2.11 42 1.49 65 5.87

Atherinidae61 Atherina boyeri 157 4.2362 Atherina hepsetus 564 18.14 1003 27.04 3407 44.27 6110 68.21 1120 39.76 77 6.95

Scorpaenidae63 Scorpaena porcus 2 0.06 1 0.01 1 0.01 1 0.04 2 0.18

Triglidae64 Trigla lucerna

Bothidae65 Arnoglossus lanterna 1 0.0966 Arnoglossus thori67 Bothus podas podas 1 0.01 2 0.18

Soleidae68 Solea impar 1 0.01

Gobiesocidae69 Diplecogaster bimaculata 1 0.03

Total no. of individuals 3110 3709 7696 8958 2817 1108Total no. of species 23 23 22 27 29 41

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species. According to the results of this study, 69 species,either permanently or temporarily, occupy small covesof Kornati Islands. This number represents 17.0% ofAdriatic ichthyofauna.

Juveniles of four species (Atherina hepsetus, 45.90%;Sarpa salpa, 21.21%; Diplodus vulgaris, 10.49% andSymphodus ocellatus, 6.98%) were dominant, forming84.58% of the total. The dominant species of the ®shcommunity in this study area belonged to the productiveand low trophic level species with high ecological e�-ciency. The ®sh entering the coves of Kornati Archi-pelago were mainly in the juvenile stage (as a startingpoint for the ®sh to be considered juvenile total length of1.5 cm was taken, and ®sh were considered juvenilesuntil the point of their ®rst sexual maturity) of devel-opment, and a small number of adults (from their ®rstsexual maturity onwards) were found. This di�erence inabundance can be explained by the fact that the inshorearea is closely related to the presence of certain coastalspecies and of the larvae and juvenile stages of more orless neritic species, which in many cases go through theircomplete biological cycle in this zone. These facts alsoindicate that the study sites probably play an importantrole as a nursery ground for the ®sh during the inshore±

o�shore migration of their early life history. Such areasalso provided suitable food, shelter, and a reduction ofpredation. The nursery function of estuaries and inshorewaters has been well-documented all over the world(Blaber and Blaber 1980; Lenanton 1982; Robertson andDuke 1987; Blaber and Milton 1990). Kraljevic andPallaoro (1991) observed that juveniles of S. ocellatus(35.42%) and A. hepsetus (19.26%) were dominant inthe same area, but only for 3 months during sampling(May, July and October), which is in agreement with ourresults. According to our investigations two families,Atherinidae (46.29%) and Sparidae (36.02%), domi-nated, while Labridae (8.35%), Mugilidae (5.12%) andGobiidae (2.43%) were less abundant and all otherfamilies (19) were rare and occasional (<1.00%). Similarresults were obtained by Kraljevic and Pallaoro (1991),who found that Atherinidae comprised 19.26%, Spar-idae 24.79%, and Labridae 37.88% of the sample, whileMugilidae (4.88%) and Gobiidae (7.60%) were lessabundant.

A high abundance of di�erent species was observedduring two periods in the year: May to June and Sep-tember to November, being characterised by mediantemperatures in comparison to the hot summer and cold

July August September October November December Total

N % N % N % N % N % N % N %

2 0.15 1 0.02 2 0.07 8 0.02018 1.35 18 1.67 8 0.32 2 0.05 61 0.15210 0.75 8 0.20 20 0.050

2 0.08 6 0.0155 0.38 5 0.46 2 0.05 16 0.040

1 0.08 19 1.61 5 0.46 2 0.08 3 0.08 34 0.085

2 0.19 2 0.005

5 0.38 18 1.52 8 0.74 13 0.32 4 0.15 131 0.3265 0.42 24 2.23 215 5.36 36 1.33 672 1.67377 6.51 68 6.31 3 0.08 12 0.44 184 0.45834 2.87 44 4.08 8 0.30 129 0.321

19 1.43 52 4.40 14 1.30 44 1.79 30 0.75 111 4.11 939 2.338

2 0.17 159 0.396661 49.59 50 4.23 316 29.31 627 25.46 2998 74.74 1502 55.59 18435 45.895

1 0.08 1 0.08 8 0.74 3 0.12 3 0.08 23 0.057

1 0.08 1 0.003

1 0.02 1 0.0033 0.28 1 0.04 5 0.012

2 0.15 3 0.28 1 0.02 9 0.022

1 0.003

1 0.003

1333 1183 1078 2463 4011 2702 4016832 32 38 28 35 23 69

273

winter. GrubisÏ ic (1982) and Jardas (1996) indicated thatspring and summer were the spawning periods for mostcommon species in the eastern Adriatic. So, we supposerecruitment timing of these species could be the reasonfor a high abundance during the mentioned periods. Ahigh abundance in autumn was due to the increase ofAtherina hepsetus, Diplodus puntazzo, Oedalechilus labeoand Symphodus ocellatus juveniles, and this could becorrelated with the spawning periods (Jardas 1996) andduration of embryonic development of this species(DulcÏ ic 1993b). Ecological separation of the dominantspecies by recruitment timing resulted in the fact thatspecies did not compete one with the other for the sameniche (Tzeng and Wang 1992). Temporal staggering ofrecruitment may be a mechanism for reducing possibleinterspeci®c competition, as has been observed in other®sh communities (Doherty 1991). Segregation of somesparid species, for example, was seasonal in KornatiArchipelago since they recruit at di�erent times of theyear (Diplodus sargus, Pagellus acarne and Spondylio-soma cantharus in spring; Oblada melanura duringsummer; Diplodus puntazzo at the beginning of autumn;Sarpa salpa during autumn; Diplodus vulgaris at thebeginning of winter), with each species occupying zonespreviously occupied by another species some timebefore.

The Kornati Archipelago ®sh assemblage exhibited agreat range for the values of D (2.35 to 5.71), H¢ (1.12 to2.79), and J¢ (0.32 to 0.77). These values could becomparable with values obtained in studies performed insimilar areas, bays and estuaries (Table 3). This rela-tively wide range of values re¯ects a di�erential utilisa-tion of Kornati Archipelago habitats by various ®shspecies, which is similar to the ®ndings of Allen (1982) inupper Newport Bay, California. McErlean et al. (1973)considered the wide range of richness values as an in-

Fig. 3 Monthly variations in the number of individuals (N ), numberof species (S ), richness, diversity and evenness in the KornatiArchipelago between January and December 1992

Table 2 Coe�cient of multiple determination (R2) identifying the association according to rank of the 20 most dominant species,(abbreviations in parentheses) with temperature, salinity and dissolved oxygen (DO)

Rank no. Serial no. Species Temperature Salinity DO R2 p

1 62 Atherina hepsetus (AH) 0.33 0.342 22 Sarpa salpa (SS) )0.73 0.55 0.083 16 Diplodus vulgaris (DV) )0.72 0.55 0.084 33 Symphodus ocellatus (SO) )0.64 0.45 0.175 60 Oedalechilus labeo (OL) )0.78 0.64 0.046 57 Liza aurata (LA) )0.70 0.64 0.047 13 Diplodus annularis (DA) 0.19 0.628 46 Zoosterisessor ophiocephalus (ZO) 0.51 0.119 14 Diplodus puntazzo (DP) )0.74 0.65 0.0310 28 Coris julis (CJ) +0.72 0.55 0.0811 11 Mullus surmuletus (MS) +0.65 0.48 0.1412 30 Symphodus cinereus (SC) 0.03 0.9713 58 Liza ramada (LR) 0.39 0.2414 18 Oblada melanura (OM) 0.44 0.1715 43 Gobius niger (GN) 0.25 0.4816 61 Atherina boyeri (AB) 0.22 0.5417 56 Chelon labrosus (CL) 0.06 0.9118 59 Liza saliens (LS) 0.12 0.7819 27 Chromis chromis (CC) 0.22 0.5520 12 Boops boops (BB) +0.69 0.54 0.09

274

dicator of the nursery function of a speci®c area. So, wecan suppose that the overall high richness values of ®shassemblages in Kornati Archipelago underline the im-portance of the area as a nursery ground for several localspecies.

The highest number of juvenile individuals in KornatiArchipelago was collected during the period fromMarch to April, and the lowest from June to September.Morovic (1960) and Kraljevic and Pallaoro (1991) sug-gested that ®ngerlings of many species migrate to thedeeper waters of the Kornati Archipelago (>7 m) in thesummer and winter (extremely high and low tempera-tures in the shallow coves). Allen and Horn (1975) foundthat temperature was the main factor a�ecting the ®shpopulation in the Colorado Lagoon. Allen (1982) ob-served that temperature and salinity accounted for 83%of the variation in abundance of individual ®sh inNewport Bay. The high positive correlation of temper-ature to number of species played an important role in®sh migration to and from Kohr-al-Zubair in thenorthwestern Arabian Gulf (Ali and Hussain 1990). Thenumber of species, abundance, and indices of speciesrichness and diversity of the community of ®sh larvaeand juveniles in the Tanshui River estuary were posi-tively correlated with temperature and salinity (Tzengand Wang 1992). The same authors observed that dis-solved oxygen, pH, depth, transparency and current

velocity are also positively or negatively correlated withthe number and abundance of ®sh species (larvae andjuveniles) in the Tanshui River estuary (two speciescorrelated with DO, ®ve species correlated with depth).

It is di�cult to explain species arrangement accordingto PC loadings. However, species in the case of PC1 arespecies (Atherina hepsetus, Diplodus puntazzo, and Che-lon labrosus) which were generally abundant and hadtwo peaks in their abundances during the year (Apriland November). The same conclusion could be drawnfor species in the case of PC2, with a peak in August andpartial peak in September (Mullus surmuletus, Obladamelanura, Liza ramada and Gobius niger). PC3 hashighest loadings for Coris julis, Diplodus annularis, At-herina boyeri, and Symphodus ocellatus, which are ben-thic species associated with Posidonia oceanica beds andcharacterised by a very similar reproduction time (Jar-das 1996).

Substrate type (Carr 1991; Levin 1991) and depth(Garcia-Rubies 1995; Garcia-Rubies and Macpherson1995) are two of the main factors a�ecting ®sh recruit-ment in the shallow waters, and a�ect the abundance,mortality and growth rate of recruits (Connell and Jones1991; Macpherson 1994). It is apparent from the fore-going discussion that a number of parameters in¯uencethe di�erential distribution of juveniles of the speciesstudied. The relative importance of each factor di�ersaccording to species. Perhaps the only commondenominator is the preference of juveniles for relativelyshallow water. There may be several di�erent explana-tions for the shallow distribution of recruits. Di�erentauthors have reported that prey abundance (Jones 1986;Forrester 1990), predation (Doherty and Sale 1985), andthe presence of adult conspeci®cs (Victor 1986; Jones1987) may exert a positive or negative in¯uence on thedistribution and abundance of juveniles. The distribu-tion in shallow waters could be also interpreted as asheltering behaviour from possible predators, becausepredator manoeuvrability may be hampered in shallowwater. It is also possible that sampling design (our choicein number of surveys, speci®c locations, type of net)could partially in¯uence the results.

Preliminary results of the present study provide abasis for establishing the temporal and spatial patterns

Fig. 4 Scatter plot of the loadings along PC1 versus PC2 of 17 mostcommon species. Letter coding see Table 2

Table 3 Diversity index values from the literature

Area D H¢ J¢ Source

Upper Galvestone Bay, Texas 0.11±2.01 Bechtel and Copeland (1970)Colorado Lagoon, California 0.5±1.73 0.03±1.11 0.01±0.57 Allen and Horn (1975)Lower Medway Estuary, Kent 1.5±3.4 0.25±1.89 0.10±0.96 van den Broek (1979)Upper Newport Bay, California 0.42±1.76 Allen (1982)Iriven Bay, west coast of Scotland 1.5±3.08 1.17±1.97 0.57±0.77 Nash and Gibson (1982)Lynn of Lorn, west coast of Scotland 1.4±3.34 1.23±1.95 0.50±0.72 Nash and Gibson (1982)Cabrillo beach area, Los Angeles 0.50±2.50 Allen et al. (1983)Malaga Bay, Spain 1.17±3.00 0.27±0.65 Reina-Hervas and Serrano (1987)Kohr-al-Zubair, northwestern Arabian Gulf 1.17±3.47 1.19±2.36 0.57±0.80 Ali and Hussain (1990)Island el Hierro, Canary Islands 0.57±1.39 Bortone et al. (1991)Four Islands, Canarian Archipelago 0.27±0.78 Falco n et al. (1996)Kornati Archipelago, eastern Adriatic 2.35±5.71 1.12±2.79 0.32±0.77 Present study

275

of recruitment in various ®sh species. Following thisstudy, we recommend long-term research to establishwhether the correlation between biotic factors andtemperature really exists. This should be done aftereliminating seasonal patterns from both data sets. Fur-ther work is needed to elucidate which additional aspectsmay in¯uence the distribution and abundance of juve-niles in the small coves of Kornati Archipelago.

Acknowledgements We dedicate this paper to Mr. Zvonko Mod-rusÏ an and Mr. Miran TurcÏ inov, who supported our work at theNational Park Kornati and died tragically in a car accident on28 March 1997. We are very thankful to R. C uzela Papata,E. KulusÏ ic , D. Dobric , K. KulusÏ ic M. RamesÏ a, N. Stipica, andCÏ . SkracÏ ic (sta� of National Park Kornati) for their great help incollecting the material. Also, we would like to thank the sta� of thechemical laboratory of the Institute of Oceanography and Fisheriesfor their help in chemical analysis and to N. Skakelja for technicalpreparation of the manuscript. The authors express their gratitudeto the Ministry of Science, Technology and Informatics of theRepublic of Croatia for their ®nancial support.

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