title: Patterns of chemical diversity in the Mediterranean sponge Spongia lamella.
abstract: The intra-specific diversity in secondary metabolites can provide crucial information for understanding species ecology and evolution but has received limited attention in marine chemical ecology. The complex nature of diversity is partially responsible for the lack of studies, which often target a narrow number of major compounds. Here, we investigated the intra-specific chemical diversity of the Mediterranean sponge Spongia lamella. The chemical profiles of seven populations spreading over 1200 km in the Western Mediterranean were obtained by a straightforward SPE-HPLC-DAD-ELSD process whereas the identity of compounds was assessed by comparison between HPLC-MS spectra and literature data. Chemical diversity calculated by richness and Shannon indexes differed significantly between sponge populations but not at a larger regional scale. We used factor analysis, analysis of variance, and regression analysis to examine the chemical variability of this sponge at local and regional scales, to establish general patterns of variation in chemical diversity. The abundance of some metabolites varied significantly between sponge populations. Despite these significant differences between populations, we found a clear pattern of increasing chemical dissimilarity with increasing geographic distance. Additional large spatial scale studies on the chemical diversity of marine organisms will validate the universality or exclusivity of this pattern.
authors.affiliation: Center for Advanced Studies of Blanes (CEAB, CSIC), Blanes, Spain.
authors.forename: Charlotte
authors.initials: C
authors.lastname: Noyer
authors.forename: Olivier P
authors.initials: OP
authors.lastname: Thomas
authors.forename: Mikel A
authors.initials: MA
authors.lastname: Becerro
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D002851:Chromatography, High Pressure Liquid; D005163:Factor Analysis, Statistical; D013058:Mass Spectrometry; D008522:Mediterranean Sea; D011161:Porifera / Q000737:chemistry*; D012044:Regression Analysis