The Full Hierarchical Structuration of Species Abundances Reliably Inferred from the Numerical Extrapolation of Still Partial Samplings: A Case Study with Marine Snail Communities in Mannar Gulf (India)

The detailed analysis of Species Abundance Distributions (“S.A.D.s”) can shed light on how member-species organize themselves within communities, provided that the complete distribution of species abundances is made available first. In this perspective, the numerical extrapolation applied to incomplete “S.A.D.” can effectively compensate for S.A.D.s incompleteness, when having to deal with substantially incomplete samplings. Indeed, almost as much information can be released from extrapolated “S.A.D.s” as would be obtained from truly complete “S.A.D.s”, although the taxonomic identities of unrecorded species remain of course ignored by numerical extrapolation.

To take full advantage of this new approach, a recently developed procedure allowing the least-biased numerical extrapolation of “S.A.D.s” has been applied to three partially sampled gastropods communities associated to coral-reef in Mannar Gulf (S-E India).

The following main results were derived from the three numerically completed “S.A.D.s”: (i) once completed, all three numerically “S.A.D.s” fairly well comply with the log-normal model, suggesting that, in all three communities, the process of hierarchical structuration of species abundances likely involves the combined contributions of many independent factors; (ii) moreover, the same holds true for each of the two coexisting feeding guilds (primary and secondary consumers) considered separately; (iii) when compared to secondary consumers, the guild of primary consumers has a much lower species richness but, on the other hand, exhibits a more strongly structured distribution of species abundances, which materializes not only in term of the apparent unevenness of species abundances but also after having disentangled the genuine intensity of the underlying process driving the hierarchical structuration.

All the preceding features are shared in common by the three communities studied, in line with the similarity of their environmental contexts. Only minor features can actually slightly distinguish between communities, reflecting the difference in distances between them.