Marine Biology

, Volume 151, Issue 6, pp 2245–2253 | Cite as

Evaluating day–night changes in shallow Mediterranean rocky reef fish assemblages by visual census

  • Ernesto AzzurroEmail author
  • Antonio Pais
  • Pierpaolo Consoli
  • Franco Andaloro
Research Article


Ecological information on coastal fish distribution patterns and habitat use can be greatly improved by nocturnal samplings and observations. To this purpose, the structure of a Mediterranean fish assemblage inhabiting the shallow rocky littoral of Linosa Island (Sicily Strait, Italy) was examined by using visual census to detect possible diel variations in species composition and abundance. Day–night fish distribution patterns were investigated by multivariate and univariate analyses. Overall, 42 fish taxa belonging to 19 families were recorded: 35 during the day and 24 during the night. Seventeen species were common to both diurnal and nocturnal assemblages. Within the diurnal assemblage, Chromis chromis was the most represented species (37.2%), followed by Thalassoma pavo (23.2%) and Sparisoma cretense (10.8%). Within the nocturnal assemblage, the most abundant taxon was Atherina spp. (33.9%), followed by Apogon imberbis (26.4%) and Boops boops (11.5%). Our results indicated wide variation in the abundance and species composition during the day and during the night. Multi Dimensional Scaling plot showed a clear-cut separation between the two assemblages and analysis of similarities found significant differences as well. SIMPER analysis revealed that ten species individually contributed by more than 2.5% to the dissimilarity between diurnal and nocturnal assemblages, T. pavo, C. chromis and S. cretense being the first three species in order of decreasing percentage. ANOVA performed on species richness and fish abundance detected significant differences between diurnal and nocturnal assemblages, the latter showing far lower average values for both variables.


Fish Assemblage Fish Abundance Fish Assemblage Structure Visual Census Fish Taxon 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work forms part of E.A.’s PhD thesis. We thank Prof. O. Carnevali for assisting in this research, Dr. E. Fanelli for critical reading of the manuscript and for her contributions during the field-work, Dr. G.S. Helfman for the help with literature Dr. M. Milazzo for useful suggestions and Dr. E. Mostarda for English revision. Finally, the authors would like to thank three anonymous referees for their useful criticism, which significantly improved this paper.


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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Ernesto Azzurro
    • 1
    Email author
  • Antonio Pais
    • 2
  • Pierpaolo Consoli
    • 1
  • Franco Andaloro
    • 3
  1. 1.Laboratory of MilazzoICRAM, Central Institute for Marine ResearchMilazzoItaly
  2. 2.Sezione di Acquacoltura ed Ecologia Marina, Dipartimento di Scienze ZootecnicheUniversità degli Studi di SassariSassariItaly
  3. 3.ICRAM, Central Institute for Marine Research, STS PalermoPalermoItaly

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