Siliceous Rhizaria abundances and diversity in the Mediterranean Sea assessed by combined imaging and metabarcoding approaches

Abstract

Siliceous Rhizaria (polycystine radiolarians and phaeodarians) are significant contributors to carbon and silicon biogeochemical cycles. Considering their broad taxonomic diversity and their wide size range (from a few micrometres up to several millimetres), a comprehensive evaluation of the entire community to carbon and silicon cycles is challenging. Here, we assess the diversity and contribution of silicified Rhizaria to the global biogenic silica stocks in the upper 500 m of the oligotrophic North-Western Mediterranean Sea using both imaging (FlowCAM, Zooscan and Underwater Vision Profiler) and molecular tools and data. While imaging data (cells m-3) revealed that the most abundant organisms were the smallest, molecular results (number of reads) showed that the largest Rhizaria had the highest relative abundances. While this seems contradictory, relative abundance data obtained with molecular methods appear to be closer to the total biovolume data than to the total abundance data of the organisms. This result reflects a potential link between gene copies number and the volume of a given cell allowing reconciling molecular and imaging data. Using abundance data from imaging methods we estimate that siliceous Rhizaria accounted for up to 6% of the total biogenic silica biomass of the siliceous planktonic community in the upper 500m of the water column.

Morphological and taxonomic diversity of mesozooplankton is an important driver of carbon export fluxes in the ocean

“…This computation was chosen to prevent overestimation of the individual's biovolume, due to unfolded copepods' antennae for example (as done in Monferrer et al., 2022). Then, each individual biovolume was multiplied by its density factor to account for the water volume sampled, and a taxonomic‐specific factor to get the individual dry weight from individual biovolume value.…”

“…While both metabarcoding and imaging techniques can provide information on the temporal and spatial distribution of zooplankton communities and their environmental dynamics (Vilgrain et al., 2021), imaging data is also able to quantify taxa's abundance and biomass (e.g., Monferrer et al., 2022). Hence, it would be ideal to combine high throughput image acquisition methods with metabarcoding to improve zooplanktonic community studies (Bucklin et al., 2019).…”

“…Hence, it would be ideal to combine high throughput image acquisition methods with metabarcoding to improve zooplanktonic community studies (Bucklin et al., 2019). Each of these approaches has uncertainties (Monferrer et al., 2022) but when combined, many resolution issues are resolved. For example, metabarcoding fills in some of the limited size spectrum resolution of imaging techniques (MacNeil et al., 2022) and allows a joint study of zooplankton communities taxonomic and functional aspects.…”

Gelatinous matrix, an original strategy to cope with oligotrophy in Nassellaria (Radiolaria)

“…The access to this environment allowed them to become important contributors to the planktonic food web of an ecosystem with potentially low predators. However, caution is required when interpreting metabarcoding data [59, 60]. Life cycle of Radiolaria remains poorly understood, with the belief that the release of small bi-flagellated cells (referred to as swarmers) by mature cells plays a role in their reproductive cycle [61, 62].…”

Rhizaria in the oligotrophic ocean exhibit clear temporal and vertical variability

“…Firstly, taxonomists have been able to greatly refine the understanding of evolutionary relationships amongst these diverse protists (Aurahs et al, 2009; Biard et al, 2015; Cavalier-Smith et al, 2018; Decelle et al, 2013, 2012; rev by Biard, 2022a). DNA metabarcoding studies have revealed insights into the distributional patterns (Biard et al, 2017; Blanco-Bercial et al, 2022; Decelle et al, 2013; Llopis Monferrer et al, 2022; Mars Brisbin et al, 2020; Sogawa et al, 2022), ecological relationships (Decelle et al, 2012; Nakamura et al, 2023), and contribution to biogeochemical fluxes (Guidi et al, 2016; Gutierrez-Rodriguez et al, 2019). Transcriptomic and proteomic approaches also have been used to quantify Rhizaria contribution to community metabolism (Cohen et al, 2023).…”