Modem Clustering Techniques and A. Vatova's Community Classification
275
Fig.2. The partition obtained by hierarchical clustering with no contiguity constraint from Manhattan distances computed on
relative abundance data was the most similar tn Vatova's classification (see Table 2, first line). A gray circular background marks
the stations (91 out of 252) that belong to clusters that correctly match the Vatova's zoocoenoses
In conclusion, our results clearly indicate
that Vatova's classification of Adriatic Sea
zoocoenoses was defined using criteria that were
not supported only by the information contained
in the species abundance data set. If they had
been, it should have been possible to approximate the original classification, but none of the
clustering procedures we used succeeded in
matching it.
This evidence implies that Vatova's data set
does not include the whole set of descriptors and
additional information that he used to classify
zoocoenoses. Therefore, particular care is needed when Vatova's macrozoobenthos data are to
be compared with more recent data. The only
safe strategy in these cases is the one that takes
into account the minimum level of information
that is contained in Vatova's data set, i.e. presence
data. The latter are more reliable as they are less
influenced by the criteria that were used to collect samples and to record macrozoobenthos
data.
References
Clements FE, Shelford VE (1939) Bio-ecology. Wiley, New York
Jaccard P (1900) Contribution au probleme de l'immigration
post -glaciaire de la flore alpine. Bull Soc Vaudoise Sci Nat
36: 87-130
Jaccard P (1901) Etude comparative de la distribution florale
dans une portion des Alpes et du Jura. Bull Soc vaudoise
Sci Nat 37: 547-579
Jaccard P (1908) Nouvelles recherches sur la distribution florale. Bull Soc Vaudoise Sci Nat 44: 223-270
Lance GN, Williams WT (1966) Computer programs for classification. In: Proc ANCCAC Conf, Canberra, May 1966,
Pap 12/3
Legendre P (1987) Constrained clustering. In: Legendre P,
Legendre L (eds) Developments in numerical ecology.
(NATO ASI Series, voL G14) Springer-Verlag, Berlin
Heidelberg New York Tokyo, pp 289-307
Legendre P, Legendre V (1984) Postglacial dispersal of freshwater fishes in the Quebec peninsula. Can J Fish Aquat
Sci 41: 1781-1802
Sneath PHA, Sakal RR (1973) Numerical taxonomy - the
principles and practice of numerical classification. In:
Freeman WH (ed) San Francisco,XV+ pp 573
Vatova A (1949) La fauna bentonica dell' Alto e Media
Adriatico. Nova Thalassia 3: 3-110
275
Fig.2. The partition obtained by hierarchical clustering with no contiguity constraint from Manhattan distances computed on
relative abundance data was the most similar tn Vatova's classification (see Table 2, first line). A gray circular background marks
the stations (91 out of 252) that belong to clusters that correctly match the Vatova's zoocoenoses
In conclusion, our results clearly indicate
that Vatova's classification of Adriatic Sea
zoocoenoses was defined using criteria that were
not supported only by the information contained
in the species abundance data set. If they had
been, it should have been possible to approximate the original classification, but none of the
clustering procedures we used succeeded in
matching it.
This evidence implies that Vatova's data set
does not include the whole set of descriptors and
additional information that he used to classify
zoocoenoses. Therefore, particular care is needed when Vatova's macrozoobenthos data are to
be compared with more recent data. The only
safe strategy in these cases is the one that takes
into account the minimum level of information
that is contained in Vatova's data set, i.e. presence
data. The latter are more reliable as they are less
influenced by the criteria that were used to collect samples and to record macrozoobenthos
data.
References
Clements FE, Shelford VE (1939) Bio-ecology. Wiley, New York
Jaccard P (1900) Contribution au probleme de l'immigration
post -glaciaire de la flore alpine. Bull Soc Vaudoise Sci Nat
36: 87-130
Jaccard P (1901) Etude comparative de la distribution florale
dans une portion des Alpes et du Jura. Bull Soc vaudoise
Sci Nat 37: 547-579
Jaccard P (1908) Nouvelles recherches sur la distribution florale. Bull Soc Vaudoise Sci Nat 44: 223-270
Lance GN, Williams WT (1966) Computer programs for classification. In: Proc ANCCAC Conf, Canberra, May 1966,
Pap 12/3
Legendre P (1987) Constrained clustering. In: Legendre P,
Legendre L (eds) Developments in numerical ecology.
(NATO ASI Series, voL G14) Springer-Verlag, Berlin
Heidelberg New York Tokyo, pp 289-307
Legendre P, Legendre V (1984) Postglacial dispersal of freshwater fishes in the Quebec peninsula. Can J Fish Aquat
Sci 41: 1781-1802
Sneath PHA, Sakal RR (1973) Numerical taxonomy - the
principles and practice of numerical classification. In:
Freeman WH (ed) San Francisco,XV+ pp 573
Vatova A (1949) La fauna bentonica dell' Alto e Media
Adriatico. Nova Thalassia 3: 3-110