Aurore André, Frédéric Quillévéré, Raphaël Morard, Yurika Ujiié, Gilles Escarguel, Colomban de Vargas, Thibault de Garidel-Thoron, Christophe J. Douady

The use of planktonic foraminifera in paleoceanography requires taxonomic consistency and precise assessment of the species biogeography. Yet, ribosomal small subunit (SSUr) DNA analyses have revealed that most of the modern morpho-species of planktonic foraminifera are composed of a complex of several distinct genetic types that may correspond to cryptic or pseudo-cryptic species. These genetic types are usually delimitated using partial sequences located at the 3'end of the SSUrDNA, but typically based on empirical delimitation. Here, we first use patristic genetic distances calculated within and among genetic types of the most common morpho-species to show that intra-type and inter-type genetic distances within morpho-species may significantly overlap, suggesting that genetic types have been sometimes inconsistently defined. We further apply two quantitative and independent methods, ABGD (Automatic Barcode Gap Detection) and GMYC (General Mixed Yule Coalescent) to a dataset of published and newly obtained partial SSU rDNA for a more objective assessment of the species status of these genetic types. Results of these complementary approaches are highly congruent and lead to a molecular taxonomy that ranks 49 genetic types of planktonic foraminifera as genuine (pseudo)cryptic species. Our results advocate for a standardized sequencing procedure allowing homogenous delimitations of (pseudo)cryptic species. On the ground of this revised taxonomic framework, we finally provide an integrative taxonomy synthesizing geographic, ecological and morphological differentiations that can occur among the genuine (pseudo)cryptic species. Due to molecular, environmental or morphological data scarcities, many aspects of our proposed integrative taxonomy are not yet fully resolved. On the other hand, our study opens up the potential for a correct interpretation of environmental sequence datasets.