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2.3. MULTIVARIATE COMMUNITY ANALYSIS Multivariate analyses were performed with the software package PRIMER (Plymouth Routines Multivariate Ecological Research). For analysing the community structure the numbers of larvae were standardized to a trawling time of one hour. A Bray – Curtis rank similarity matrix was calculated using root-root transformed data. The root-root transformation has the advantage of scaling the abundant species down and that the similarity coefficient is invariant to a scale change (FIELD et al.1982). Additionally, the Bray Curtis similarity weighs rare species lower in comparing samples and avoids the effect of rare species (FIELD et al. 1982). The similarities between species composition were performed by a hierarchical agglomerative clustering with group average linking and multi – dimensional scaling (MDS), where the dissimilarities are directly proportional to the distance between the interpoints (FIELD et al. 1982). MDS was performed based on different factors, to investigate the effect of seasonal, regional and spatial conditions on the species assemblage. A one-way analysis of similarity (ANOSIM) was applied to determine the significance of trends within the different factors, used already in the preceding analysis. During all calculations only species with a relative abundance of more than 0.2 % of the total catch were included to avoid the effect of rare species (RAMOS et al. 2006). Additionally, specimens in a juvenile or even adolescence development stage were excluded to evade the ontogenetically different behaviour. To deal with the effect of different taxonomical levels all specimens of higher taxonomic level than species level were treated as species, as long as they definitively represent another species. Consequently, all damaged larvae were excluded, since it could not be assured being another species as already identified.

2.4. ANOVA ANALYSIS For investigating the differences in the abundance and diversity of fishes a one factorial ANOVA with the software STATISTICA was performed. The Shannon Index H’, the Pielou’s Index of Evenness J’, the Simpson’s diversity Index D, the total number of species S and the total number of individuals N were grouped to spatial and seasonal factors. Whisker plots with a confidence interval of +/- 95% (Standard error only used at the total number of individuals) indicate significant differences. Before running the ANOVA the normal distribution was tested by using the Kolmogorov-Smirnov & Lillefors (Prof. WAHL M. and Dr. LENZ M., pers. comment). The Levene’s test was performed to check for homogeneity and in case of heterogeneity the data were transformed with ArcSin to buffer the variances (Prof. WAHL M. and Dr. LENZ M., pers. comment). Does the ANOVA show significant differences, a post-hoc test (Bonferroni test) was used to check between which factors the differences are significant (Prof. WAHL M. and Dr. LENZ M., pers. comment).

2.5. GEOGRAPHICAL INFORMATION SYSTEM (GIS) DISTRIBUTION MAPS For illustrating the distribution of the species inhabiting the oceanic and neritic areas during their larval life, maps were created with the GIS program MapInfo Professional 7.5. Information about the habitat of origin of different species was taken from the previous already mentioned identification literature, especially from WHITEHEAD (1986). The habitat types of origin are listed in Table 7. Abundances are indicated by different coloured and sized circles described in the particular maps.


Inf. Téc. Inst. Canario Cienc. Mar. n°13

Spatial and seasonal patterns in species composition of fish larvae in the Canary Islands  
Spatial and seasonal patterns in species composition of fish larvae in the Canary Islands  

Technical report consisting on a comprehensive annotated larvae taxa list with the most important taxonomic characters of this region