Quantifying the taxonomic diversity in real species communities

We analyze several florae (collections of plant species populating specific areas) in different geographic and climatic regions. For every list of species we produce a taxonomic classification tree and we consider its statistical properties. We find that regardless of the geographical location, the climate and the environment all species collections have universal statistical properties that we show to be also robust in time. We then compare observed data sets with simulated communities obtained by randomly sampling a large pool of species from all over the world. We find differences in the behavior of the statistical properties of the corresponding taxonomic trees. Our results suggest that it is possible to distinguish quantitatively real species assemblages from random collections and thus demonstrate the existence of correlations between species.

Published in:
Journal Of Physics A-Mathematical And Theoretical, 41, -
Presented at:
Workshop on Complex Networks - from Biology to Information Technology, Pula, ITALY, Jul, 2007

 Record created 2010-11-30, last modified 2018-03-17

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