Helgol Mar Res (2004) 58:6270 [615944]

Helgol Mar Res (2004) 58:62–70
DOI 10.1007/s10152-003-0169-8
ORIGINAL ARTICLE
Chariton-Charles Chintiroglou ·
Panagiotis Damianidis · Chryssanthi Antoniadou ·Marina Lantzouni · Dimitris Vafidis
Macrofauna biodiversity of mussel bed assemblages
in Thermaikos Gulf (northern Aegean Sea)
Received: 20 February 2003 / Revised: 22 October 2003 / Accepted: 10 November 2003 / Published online: 12 December 2003
/C23 Springer-Verlag and AWI 2003
Abstract Biomonitoring of mussel bed assemblages can
provide valuable information about the impact of pollu-tion on hard substrate assemblages. This study of Mytilus
galloprovincialis mussel beds in Thermaikos Gulf (north-
ern Aegean Sea) deals with the spatial and temporalstructure of the associated fauna. Samples were collectedand abiotic factors were measured in two successiveyears. Common biocoenotic methods were employed toanalyze the data. The samples could be separated intothree groups, with summer and winter samples beingclearly different. A total of 100 species were found:polychaetes and crustaceans were the most dominant taxa.The assemblage shows high diversity with respect tospecies abundance. Biotic interactions within the assem-blage appear to influence its composition, although thetotal evenness remains unaffected in space and time. TheM. galloprovincialis assemblages can be found in clean as
well as in polluted waters and, therefore, are of greatinterest in biomonitoring studies.
Keywords Infralittoral · Hard substratum · Mussel beds ·
Biomonitoring
Introduction
Mussel bed ( Mytilus galloprovincialis LMK) assemblages
can develop in clean and moderately polluted as well aspolluted waters (e.g. Bellan-Santini et al. 1994; Damian-idis and Chintiroglou 2000). Therefore, biomonitoring of
these assemblages can provide valuable information aboutthe impact of pollution on hard bottom communities (e.g.Wenner 1988).
There is adequate information about the structure of M.
galloprovincialis assemblages from various regions in the
Mediterranean Sea, especially from the western Mediter-ranean coasts (Bellan 1969, 1980; Bellan-Santini 1969,1981; Desrosiers et al. 1982, 1986; Hong 1983; Tursi etal. 1984; Tsuchiya and Bellan-Santini 1989), whileinformation on the Aegean Sea is relatively limited(Kocatas 1978; Topaloglou and Kihara 1993; Lantzouniet al. 1998; Damianidis and Chintiroglou 2000). Manyauthors have put emphasis on the importance of theseassemblages in biomonitoring studies (see Thiel andUllrich 2002). Damianidis and Chintiroglou (2000)reported that the abiotic factors at all sampling siteswithin Thermaikos Gulf do not fluctuate in time. There-fore, any variation in the composition of M. galloprovin-
cialis assemblages has to be attributed to biotic factors.
This study aims at the investigation of the spatial and
temporal structure of the fauna associated with M.
galloprovincialis assemblages on the eastern coast of
Thermaikos gulf.
Methods
Study area
The sampling sites were selected on the basis of their historical
background, as well as the exposure of the assemblages and the
depth of their occurrence. Of all locations with artificial hard
substrate along the east coast of Thessaloniki Bay, two appeared to
be very similar in bathymetric distribution and exposure of M.
galloprovincialis populations: the piers of Agia Triada (ST1) and
Perea (ST2) (Fig. 1). These piers were constructed 25 years ago and
are supported by concrete pillars, which comprise the substrate for
the mussel beds. At these sampling sites, the M. galloprovincialis
populations develop a uniform physiognomic aspect, with large
numbers of mussels covering an area that extends from the lower
infralittoral zone down to a depth of 2.5 m.Communicated by H.-D. Franke
C.-C. Chintiroglou ( )) · P. Damianidis · C. Antoniadou ·
M. LantzouniDepartment of Zoology, School of Biology,
Aristotle University of Thessaloniki,
Box 134, 54006 Thessaloniki, Greecee-mail: chintigl@bio.auth.grFax: +30-2310-998269
D. Vafidis
Fisheries Research Institute of Kavala,Nea Peramos, 64007 Kavala, Greece

Physico-chemical factors
During this study, physico-chemical factors such as salinity (S‰),
conductivity ( mS/cm), water clarity (m), dissolved oxygen (mg/l),
temperature (/C30C) and total hydrodynamics were measured. All
measurements were made using WTW (Wissenschaftlich-Techni-
sche Werkstaetten, Weilheim, Germany) and Lovibond Checkit
(Dortmund, Germany) micro-electronic equipment and water
clarity was examined using the Secchi disc. These measurements
were conducted monthly at each sampling site and the results have
already been reported by Damianidis and Chintiroglou (2000).
Sampling methods
Sampling was carried out while scuba diving. Samples were taken
as described by Chintiroglou and Koukouras (1992). The area
covered by the quadrat sampler was 400 cm2(Stirn 1981; Bakus
1990). Three replicates were taken each time. The samples, 24 in
total, were collected during winter and summer of 1994 and 1995.
After sampling, the specimens were preserved in 10% formalin and
were transferred to the laboratory for further treatment. All samples
were collected by the same scuba diver.
Data analysis
Common biocoenotic methods were employed to analyze the faunal
composition of the M. galloprovincialis assemblages (Bellan-
Santini 1981; Damianidis and Chintiroglou 2000). Hence, the
numerical abundance ( N) on a scale of 1 m2, the mean dominance
(D) and the frequency ( f) were estimated. Also Shannon-Weaver’s
(H0), and Margalef ( d) and Pielou’s Evenness ( J0) were calculated
on a log 2basis (Daget 1979).
Seasonal differences in the mean numbers of individuals were
tested using one-way ANOVA and multiple comparisons. All data
were then converted to logarithms. The Spearman rank correlation
coefficient ( rs) was employed to determine the relation of the
number of mussels ( AbM) with faunal abundance ( mAb) and
richness ( R).
The numerical abundance data, obtained per sampling station,
were analyzed using cluster and multidimensional scaling (mds)
techniques, based on the Bray-Curtis similarity, using the PRIMER
package (see Clarke and Green 1988; Clarke and Warwick 1994).
The square root transformation was applied in order to increase the
contribution of the rare species (Clarke and Warwick 1994). The
significance of the multivariate results was assessed using the
ANOSIM test. SIMPER analysis was performed in order to identify
the percentage contribution of each species to the overall similarity
within a site and the dissimilarity among sites (Clarke 1993). Theabove were carried out to examine the similarity degree of samples,
in both space and time.
Results
Composition of the assemblage
A total of 100 species were found associated with
M. galloprovincialis assemblages in Thermaikos gulf
(Table 1). The distribution of these species in majortaxonomic groups is given in Table 2. The dominantgroups are polychaetes (37.5%) and crustaceans (30.9%).As shown in Table 1, 17 species were distinguished as“very common” ( f/C2150%), 26 as “rare” ( f<10%), and 57 as
“common” (10%< f<50%).
Among the very common species, the polyclad
Stylochus sp. and the decapods Pilumnus hirtelus and
Pisidia longicornis have been described as the main
predators of mussels (see Galleni et al. 1977; Damianidisand Chintiroglou 2000). The cirripeds Balanus perforatus
andB. trigonus , the polychaete Serpula vermicularis and
Bryozoa sp1, are well-known as organisms that oftensettle on mussel shells (Bussani 1983; Damianidis andChintiroglou 2000). The rest of the very common speciesare free motile organisms which employ various modes offeeding. The tube-building peracarids are detritivores(Barnard 1958, 1963; Isaac et al. 1994), Ophiothrix sp.
(P/C216r/C155s 1976) is a suspensivore, and the polychaeteStaurocephalus rudolphii is a carnivore (Fauchald and
Jumars 1979).
Relationships between fauna and structure of mussel beds
According to Tsuchiya and Nishihira (1986), the mor-
phology and relative age of the mussels in an assemblagecan play a significant role in the composition of theassociated fauna. Therefore, the correlations of musselabundance with species richness and faunal abundance,respectively, were examined.
For both summer and winter samples, faunal abun-
dance ( mAb) and richness ( R) were not correlated ( P>0.5)
with the mussel abundance ( Ab
M).
Diversity
A total of 17,090 individuals, representing 100 faunal
species, were examined. As shown in Table 1, the numberof species and the diversity indices ( H
0,dandJ0), were
determined for each sampling station and season (winter/summer). The number of species ranged from 37 to 49 inwinter, and from 45 to 60 in summer. The diversityindices ranged proportionately as they appeared to behigher in the summer samples (Table 1).
Fig. 1 Map showing Thermaikos Gulf and the two sampling sites
(ST1, ST2)63

Table 1 A list of species found in the Mytilus galloprovincialis assemblage at two stations in Thermaikos Gulf, in summer and winter of 1994 and 1995. WWinter, Ssummer, ffrequency,
mAb mean abundance, Dppartial mean dominance, ddiversity index, H0Shannon Index, J0Equitability Index
Species ST1 W94 ST2 W94 ST1 W95 ST2 W95 ST1 S94 ST2 S94 ST1 S95 ST2 S95 Total
f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p
Eudendrium
sp.100 66 66 100 42
Cereus
pentuculatus33 8 0.02 4 1 0.006
Podocoryna
sp.33 4
Leptoplana
sp.66 66 0.59 100 83 0.66 100 317 3.50 66 42 0.12 33 17 0.06 808 4.40 46 167 0.936
Stylochus
sp.66 33 0.30 33 8 0.07 33 8 0.11 100 308 0.87 100 183 0.69 66 167 0.91 100 892 4.09 62 200 1.123
Turbellaria
sp166 91 0.81 33 17 0.13 100 83 1.11 66 125 1.38 33 33 0.09 33 100 0.54 41 56 0.316
Turbellaria
sp233 83 0.74 33 17 0.05 66 142 0.77 17 30 0.170
Nemertina
sp.133 8 0.09 4 1 0.006
Nematoda 33 325 2.89 66 25 0.20 100 342 0.97 66 458 1.73 33 108 0.50 37 157 0.884
Phascolosomagranulatum33 8 0.04 4 1 0.006
Amphitrite
variabilis33 8 0.07 33 33 0.27 66 25 0.28 100 150 0.42 33 17 0.06 33 17 0.08 37 31 0.176
Autolytus
prolifer33 8 0.11 66 33 0.18 12 5 0.029
Capitella
capitata33 8 0.05 66 42 0.19 12 6 0.035
Capitellides
giardi33 33 0.13 4 4 0.023
Ceratonereis
costae33 8 0.07 33 8 0.11 66 33 0.37 33 8 0.05 66 17 0.08 29 9 0.053
Chaetozone
setosa100 58 0.52 33 25 0.07 17 10 0.059
Cirratulus
sp.100 50 0.40 33 75 0.83 66 67 0.19 66 125 0.47 66 75 0.34 41 49 0.275
Eulalia
sanguinea66 58 0.64 33 8 0.02 66 50 0.27 21 15 0.082
Exogone
gemmifera33 8 0.07 33 42 0.33 33 33 0.13 66 50 0.23 21 17 0.094
Harmothoe
areolata33 8 0.07 33 8 0.03 8 2 0.012
H. impar 66 75 0.60 33 8 0.11 66 25 0.09 33 8 0.05 25 15 0.082
H. reticulata 100 58 0.52 100 75 0.21 33 33 0.13 33 17 0.09 33 23 0.129
H. spinifera 100 367 3.26 100 67 0.53 33 17 0.18 33 8 0.02 33 58 0.32 66 17 0.08 46 67 0.374
Heterocirrusalatus33 25 0.14 33 8 0.04 8 4 0.023
Heteromastus
filiformis33 8 0.02 33 8 0.03 33 125 0.68 33 42 0.19 17 23 0.129
Hydroides
elegans33 8 0.07 33 50 0.40 33 33 0.44 66 325 3.59 33 42 0.12 66 142 0.77 33 75 0.421
H. pseudo-
uncinata66 108 0.86 33 17 0.22 66 175 0.66 33 25 0.14 66 633 2.91 33 120 0.673
Kefersteinia
cirrata33 58 0.46 33 42 0.46 33 50 0.14 66 92 0.35 66 100 0.46 29 43 0.240
Lubrineris
coccinea33 8 0.02 66 25 0.09 12 4 0.023
L. funchalensis 33 8 0.11 66 42 0.12 66 17 0.06 100 33 0.18 33 17 0.08 37 15 0.082
Lysidiceninetta33 8 0.03 33 8 0.05 8 2 0.012
Magalia
perarmata100 275 2.44 66 17 0.22 33 17 0.18 66 300 0.85 33 76 0.427
Marphysa
fallax33 8 0.07 33 8 0.02 33 8 0.03 12 3 0.018
M. sanguinea 33 8 0.07 33 17 0.09 8 3 0.01864

Table 1 (continued)
Species ST1 W94 ST2 W94 ST1 W95 ST2 W95 ST1 S94 ST2 S94 ST1 S95 ST2 S95 Total
f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p
Nematonereis
unicornis33 8 0.05 4 1 0.006
Nereis caudata 33 17 0.15 33 8 0.09 66 33 0.09 100 42 0.19 29 13 0.070
N. zonata 33 25 0.11 4 3 0.018
Ophiodromuspallidus66 92 1.01 100 333 0.94 100 275 1.50 33 225 1.03 37 116 0.650
Perinereis
cultrifera33 8 0.07 33 8 0.09 33 8 0.04 12 3 0.018
Phyllodoce
rubiginosa66 25 0.22 100 42 0.33 66 50 0.14 33 17 0.06 100 33 0.15 46 21 0.117
Platynereis
dumerilii33 8 0.07 66 75 0.60 33 8 0.09 33 8 0.02 66 42 0.19 29 18 0.099
Polydora caeca 66 17 0.15 66 67 0.53 66 42 0.16 33 25 0.14 66 50 0.23 37 25 0.140
P. ciliata 66 33 0.30 33 8 0.11 33 8 0.09 33 17 0.06 100 83 0.45 33 19 0.105
Polyopthalmuspictus33 8 0.07 33 17 0.06 8 3 0.018
Potamila
reniformis33 17 0.06 4 2 0.012
Potamoceros
triqueter100 283 2.52 33 33 0.27 100 42 0.12 33 8 0.05 33 46 0.257
Prionospio
malmgrenii33 8 0.11 100 2,108 5.97 100 1,625 6.12 33 142 0.77 100 208 0.96 46 511 2.873
Sabellaria
spinulosa66 25 0.22 33 150 1.20 33 25 0.07 33 33 0.13 33 17 0.09 25 31 0.176
Serpula
concharum33 158 1.26 33 25 0.07 33 433 1.63 12 77 0.433
S. vermicularis 33 17 0.15 100 150 1.20 66 92 1.22 66 1,125 12.43 100 508 1.44 66 1,575 5.93 100 283 1.54 100 200 0.92 79 494 2.774
Sprirobranchus
polytrema100 2,483 19.79 33 8 0.11 33 8 0.03 21 313 1.775
Staurocephalus
rudolphii66 33 0.30 33 8 0.11 100 533 1.51 100 150 0.56 100 267 1.45 100 175 0.80 62 146 0.819
Syllis krohnii 33 8 0.07 66 17 0.05 66 33 0.13 33 8 0.05 25 8 0.047
S. prolifera 33 8 0.11 66 17 0.05 66 33 0.13 33 8 0.05 25 8 0.047
Terebellalapidaria33 8 0.07 66 50 0.55 33 58 0.22 100 242 1.32 33 17 0.08 33 47 0.263
Cerithium
repestre33 8 0.07 33 8 0.11 33 8 0.09 12 3 0.018
Hanomia
ephipium33 8 0.02 4 1 0.006
Hiatella rugosa 66 50 0.44 33 8 0.02 66 208 0.78 33 8 0.04 25 34 0.193
Hexaplextrunculus33 8 0.09 66 125 0.35 100 417 1.57 66 33 0.18 66 133 0.61 41 90 0.503
Hinia
incrassata33 17 0.05 4 2 0.012
Mytilus gallo-
provincialis100 5,142 45.7 100 4,475 35.66 100 2,300 30.60 100 2,233 24.68 100 8,375 23.7 100 10,408 39.18 100 5,108 27.83 100 5,742 26.36 100 5,473 30.743
Odostomia sp. 33 8 0.07 4 1 0.006
Aora sp. 33 8 0.07 33 8 0.11 8 2 0.012
Amphithoeramondi33 17 0.15 33 8 0.07 8 3 0.018
Athanas
nitescens100 233 2.07 66 125 1.00 66 50 0.67 33 8 0.09 100 1,233 3.49 66 250 0.94 100 200 1.09 100 258 1.19 79 295 1.656
Balanus
eburneus100 100 1.33 33 17 0.09 33 8 0.04 21 16 0.088
B. perforatus 100 617 5.48 100 233 1.86 100 1,592 21.18 100 2,167 23.94 100 183 0.52 100 233 0.88 100 208 1.13 100 425 1.95 100 707 3.973
B. trigonus 66 167 1.48 100 1,383 11.02 100 775 10.31 100 217 2.39 100 1,092 3.09 100 717 2.70 100 2,600 14.16 100 917 4.21 96 983 5.524
Copepoda 100 117 1.04 66 100 0.80 33 8 0.11 33 33 0.37 100 125 0.35 33 58 0.22 46 55 0.310Corophiumacherusicum100 592 1.67 33 8 0.03 17 75 0.421
C. acutum 66 50 0.67 66 33 0.37 66 308 0.87 66 42 0.16 66 83 0.45 100 33 0.15 54 69 0.386
C. sextonae 33 8 0.07 66 17 0.13 33 8 0.11 66 50 0.55 66 25 0.07 33 14 0.076
Corophium sp. 33 25 0.28 100 11,400 32.26 100 6,583 24.78 100 4,842 26.37 100 9,242 42.43 54 4,011 22.534
Erichthoniusbrasiliensis66 42 0.33 33 8 0.09 33 17 0.05 66 100 0.38 66 42 0.23 100 75 0.34 46 35 0.19965

Table 1 (continued)
Species ST1 W94 ST2 W94 ST1 W95 ST2 W95 ST1 S94 ST2 S94 ST1 S95 ST2 S95 Total
f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p f mAb D p
Diogenes
pugilator33 8 0.11 4 1 0.006
Elasmopus
rapax100 25 0.22 100 417 3.32 100 1,258 16.74 100 1,017 11.23 50 340 1.908
Euridice
tuberculata33 8 0.07 4 1 0.006
Jassa
marmorata100 100 0.89 100 192 1.53 33 8 0.11 33 92 1.01 33 49 0.275
Lembos
websteri66 50 0.44 8 6 0.035
Leptochelya
savignii66 25 0.22 33 8 0.07 33 17 0.05 17 6 0.035
Maera
inaequipes100 33 0.30 100 450 3.59 100 283 3.77 33 75 0.83 66 117 0.33 100 100 0.38 100 383 2.09 100 400 1.84 87 230 1.293
Microdeuto-
pussp.33 8 0.09 33 8 0.02 33 8 0.05 12 3 0.018
Pachygrapsus
marmoratus25 0.07 33 8 0.03 33 17 0.09 33 17 0.08 12 8 0.047
Parhyale
aquilina33 17 0.15 4 2 0.012
Palaemon sp. 66 17 0.22 8 2 0.012
Pilumnus
hirtelus100 158 1.41 100 150 1.20 100 342 4.55 66 167 1.84 100 483 1.37 100 350 1.32 100 267 1.45 100 217 0.99 96 267 1.498
Pisidia
longicornis100 1,167 10.37 100 700 5.58 100 308 4.10 100 217 2.39 100 3,792 10.73 100 700 2.63 100 375 2.04 100 683 3.14 100 993 5.576
Sphaeroma
serratum33 8 0.07 4 1 0.006
Stenothoe
cavimana33 8 0.07 4 1 0.006
Tanais sp. 66 33 0.27 66 67 0.74 100 233 0.66 66 33 0.13 66 17 0.09 33 33 0.15 50 52 0.293
Thoralus
cranchii100 25 0.22 66 17 0.13 66 33 0.44 33 8 0.09 100 133 0.38 100 100 0.38 33 8 0.05 62 41 0.228
Unidentified
Amphipoda66 42 0.46 66 67 0.36 17 14 0.076
Nymphon sp. 33 8 0.07 33 8 0.11 33 8 0.02 33 8 0.05 17 4 0.023
Proxichilidi-dae sp.66 25 0.33 33 8 0.09 12 4 0.023
Bryozoa sp.1 33 100 66 33 100 66 50
Bryozoa sp.2 33 4
Ophiothrix sp. 100 1,375 12.22 100 358 2.86 66 192 2.12 100 1,675 4.74 100 917 3.45 100 900 4.90 100 517 2.37 83 742 4.166
Paracentrotuslividus33 17 0.15 33 8 0.07 66 25 0.07 33 17 0.08 21 8 0.047
Styella plicata 33 17 0.18 33 67 0.19 33 33 0.18 33 8 0.04 17 16 0.088
Gobius sp. 33 8 0.09 33 8 0.02 33 8 0.03 12 3 0.018
No. indi-viduals1,352 1,509 906 1,094 4,246 3,189 2,212 2,619 17,090
No. species 49 46 37 44 60 51 54 45 100
d 49 46 37 44 60 51 54 45 100
ShannonIndex ( H
0)7.12 6.39 5.27 6.11 7.52 6.47 6.64 5.55 10.13
Equitability
Index ( J0)3.94 3.74 3.1 3.54 3.29 3.44 3.46 2.77 4.1166

Abundance
The comparison of the faunal abundance in time (within
and between years) and in space (sampling sites) wasbased on the examination of the null hypothesis that theabundance of the fauna does not differ significantly. One-way ANOVA was used to detect the exact differences andshowed an equal distribution of the abundance of thefauna in winter as well as in summer samples ( F=0.58,
df=1,3, P=0.64 in winter samples, and F=2.47, df=1,3,
P=0.14 in summer samples).Affinity of sampling in space and time
The affinity of all sampling sites is given in Fig. 2. Both
analyses (cluster and non-metric mds) indicate a separa-tion of samples into three main groups at about 50%similarity level. The winter samples from 1995 formgroup A, the winter samples from 1994 group B and thesummer samples from both years (1994 and 1995) groupC. Summer and winter samples are separated, indicatingseasonality of the benthic assemblages. The two stationswere not separated. Samples from successive years wereonly separated in winter. The stress value for the two-dimensional mds configuration is 0.01, indicating anexcellent ordination of samples (Clarke and Warwick1994). The performance of a one-way ANOSIM test gaveglobal R=1 at a significance level of P<0.005, so the
separation of the three groups (A, B and C) wasconfirmed. Group A showed an average similarity of62%. As identified by SIMPER analysis, five species ( M.
galloprovincialis ,B. perforatus ,Elasmopus rapax ,Pi-
sidia longicornis andB. trigonus ) were responsible for
60% of the average similarity, and 15 species for 90%.Group B reached an average similarity of 57%, withseven species ( M. galloprovincialis ,Pisidia longicornis ,
Ophiothrix fragilis ,B. perforatus ,B. trigonus ,Pilumnus
hirtelus and Athanas nitescens ) covering 60% of this
similarity, and 22 species 90%. Finally, group C reachedan average similarity of 67%, with eight species(Corophium sp.,M. galloprovincialis ,B. trigonus ,O.
fragilis ,Pisidia longicornis ,Prionospio malmgreni ,S.
vermicularis andPilumnus hirtelus ) being responsible for
60% of the similarity, and 26 species for 90%. As regardsthe divergence between groups, we found that group Ahad an average dissimilarity percentage of 50% withgroup B (21 species contributed 60% and 55 species 90%of this value) and 57% with group C (16 speciescontributed 60% and 54 species 90%), while the dissim-ilarity percentage between groups B and C was 50% (22species contributed 60%, and 58 species 90%). It is quiteclear that only a few species are important for character-izing the groups, while most of them are important fordifferentiating the groups.
Discussion
Photophilic soft algae communities probably have thehighest faunal and flora diversity of all benthic bio-coenoses in the Mediterranean (P/C216r/C155s 1982; Bellan-Santini et al. 1994). The assemblage of mussel beds ofM. galloprovincialis in Thermaikos Gulf belongs to this
type of biocoenosis, showing high diversity with respectto species abundance. One hundred animal species wererecorded during this study, 17 of which were character-ized as very common ( f/C2150%), and 57 as common
(10%< f<50%). The recorded species have been reported
by many authors as members of the assemblages ofsublittoral photophilic algae (Bellan-Santini 1969; Sal-danha 1974; Kocatas 1978; Bellan 1980; Hong 1983;
Fig. 2 Affinity of the sampling sites according to cluster and non-
metric multidimensional sampling analysesTable 2 Distribution of the species found in the assemblage to the
level of major taxa
Taxa Number of species Percentage %
Polychaeta 45 37.5
Crustacea 31 30.39
Mollusca 9 8.82
Turbellaria 4 3.92
Cnidaria 3 2.94
Bryozoa 2 1.96
Echinodermata 2 1.96
Nemertina 1 0.98
Nematoda 1 0.98
Sipunculida 1 0.98
Pantopoda 1 0.98
Ascidiacea 1 0.98
Pisces 1 0.9867

Desrosiers et al. 1986; Marinopoulos 1988; Chintiroglou
and Koukouras 1992; Topaloglou and Kihara 1993;Bellan-Santini et al. 1994; Lantzouni et al. 1998; Baxe-vanis and Chintiroglou 2000; Damianidis and Chin-tiroglou 2000).
The biodiversity of M. galloprovincialis assemblages
in Thermaikos Gulf differs from those reported for otherMediterranean and northern European sites (Table 3).Most authors have used similar methods for the study ofhard substrates (based mostly on work by Bellan-Santini1969) (Table 3), yet data from different geographicalareas are difficult to compare. The highest speciesabundance ( R=131) was found in the infralittoral zone
of the Portuguese coast. The clean waters of Marseilles,Ismir and Thermaikos Gulf also show high speciesabundance, while species abundance was relatively lowin the Bosporus, on Danish coasts, in the midlittoral zoneof the Portuguese coast and in the polluted waters ofMarseilles. The respective values in Japan and Chileranged around 65, while 89 species were counted in Italyand 56 in Aberffraw (N Wales).
Table 3 also shows that polychaetes and crustaceans
are the most important taxonomic groups of the assem-blage, contributing almost 50% of the total faunal speciesabundance. The abundance of these groups, however,varies from one area to another and also seems to bedependent on the specific features of each study area(polluted/non-polluted; midlittoral/supralittoral), a factthat was also reported by Thiel and Ullrich (2002).Saldanha (1974), for instance, recorded fewer polychaetesand more crustacean species on the coasts of Portugal,while D’Anna et al. (1985) recorded exactly the opposite
for Sicily. Kocatas (1978) found 35 polychaete and 32crustacean species in the Izmir Bay, whereas Topaloglouand Kihara (1993) reported 10 polychaete and 22crustacean species for the Bosporus. Seed and Suchanek(1992) drew the same conclusions, even though theMediterranean mussel assemblages were not the focus oftheir work. The total diversity of mussel assemblages inthe studied areas shows no significant variations. Fur-thermore, significant similarities exist at the taxonomiclevel. It should also be noted that, according to Damian-idis and Chintiroglou (2000), there is no significantdifference in the composition of the dominant species:this implies that the structure of the polychaete fauna ofM. galloprovincialis assemblages in the Mediterranean
Sea is largely homogeneous.
An important part of the study of mussel assemblages
is the study of interactions between the structure ofmussel populations and the associated fauna (Tsuchiyaand Nishihira 1986; Lintas and Seed 1994). These studieshave produced contradictory results. According toTsuchiya and Nishihira (1986), the structure of musselbeds in the Pacific Ocean (Japan) has a direct effect on thediversity of the assemblages. Lintas and Seed (1994)suggested that the fauna associated with M. edulis appear
to be related largely to mussel density. Damianidis andChintiroglou (2000) reported similar results on thepolychaete fauna of mussel beds in Thermaikos Gulf. Inthe present study, however, no relationship was foundbetween mussel density and the abundance and diversityof the assemblage. As regards the structure (= distributionTable 3 Literature data on M. galloprovincialis assemblages. QQuadrat, Ccore, INFR infralittoral, MID midlittoral, Ppolluted, NPnon-
polluted
Source Location Ecological
zoneSampling
methodSurface
(cm2)No.
faunal
speciesNo. poly
chaete
speciesNo.
crustacean
speciesPollution
of biotope
Bellan-Santini (1969) Marseilles INFR Q 400 43 13 14 P
Bellan (1969, 1980) Marseilles INFR Q 400 98 25 24 NP
Kocatas (1978) E Aegean Sea INFR Q 400 111 35 32 P
Bellan (1980) NW
Mediterranean
SeaINFR Q 400 20/114.3 NP
Bellan (1980) NW
Mediterranean
SeaINFR Q 400 20/78.2 P
Thiel and Ullrich (2002) Chile INFR Q 100 62 15 14 NP
Svanne and
Setyobudiandi (1996)Denmark INFR C 282 43 13 10 NP
Lintas and Seed (1994) N Wales MID & INFR Q 25 59 4 25 NP
Tiganus (1979) Black Sea INFR Q ?? ?22 ? ? ?
Topaloglou and Kihara
(1993)Bosporus INFR Q 400 48 10 22 NP
D’Anna et al. (1985) Sicily, Italy INFR Q 400 89 32 8 P & NP
Tsuchiya and Nishihira
(1986)N Japan INFR Q 100 69 27 17 NP
Tsuchiya and
Bellan-Santini (1989)Marseilles INFR Q 100 99 33 30 NP
Damianidis and
Chintiroglou (2000)Thermiakos
GulfINFR Q 400 48 NP
Saldanha (1974) Portugal INFR Q 500 131 27 36 NP
Saldanha (1974) Portugal MID Q 500 67 10 8 NP68

of size classes of the populations) of the M. galloprovini-
cialis populations, there is certain information in Le
Breton and Chintiroglou (1998) indicating an unevendistribution in space and time. Although information isstill limited, it appears that biotic interactions have astrong effect on the composition of the assemblage, whichseems to decrease when the assemblage is studied as awhole. In this case, the composition of the assemblages islargely even in space and time. Nevertheless, attentionshould be paid to any variations in order to understand thebiotic interactions in hard substrate assemblages (seeDamianidis and Chintiroglou 2000).
The evenness of the studied assemblage showed some
variation in space, and particularly in time, while the totalhomogeny of the faunal composition remained unaffect-ed. The separate analyses conducted by Lantzouni et al.(1998) and Damianidis and Chintiroglou (2000) producedsimilar results.
In conclusion, there is now adequate information about
M. galloprovincialis assemblages, although there are still
open questions. For biomonitoring of marine benthicassemblages, knowledge of the structure and function ofM. galloprovincialis assemblages can play an important
role. The main advantage of studying such assemblages,on a smaller or wider scale, is their similar physiognomicappearance (Reish 1971; Wenner 1988). As these assem-blages can be found in clean as well as in polluted waters,they are of great interest in biomonitoring studies (seeWenner 1988).
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