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Data from: Large scale patterns of marine diatom richness: drivers and trends in a changing ocean.

Citation

Busseni, Greta et al. (2021), Data from: Large scale patterns of marine diatom richness: drivers and trends in a changing ocean., Dryad, Dataset, https://doi.org/10.5061/dryad.wh70rxwk6

Abstract

Aim Plankton diversity is a pivotal element of marine ecosystem stability and functioning. A major obstacle in the assessment of diversity is the lack of consistency between patterns assessed by molecular and morphological data. This work aims to reconcile the two in a single richness measure, to investigate the environmental drivers affecting such measure, and finally to predict its spatio-temporal patterns. Location & Time period This is a global-scale study, based on data collected within the 2009-2013 interval during the Tara Oceans expedition. Major taxa studied The focus of this study is diatoms. They play an important role in several biogeochemical cycles and within marine food webs, while displaying a high taxonomic and functional richness. Methods We integrate measures of diatom richness across the global ocean using molecular and morphological approaches, giving particular attention to the rare biosphere. We then perform a machine-learning-based analysis of these reconciled patterns to extrapolate diatom richness at the global scale and to identify the main environmental processes governing it. Finally, we model the response of diatom richness to climate change. Results By filtering out 0.3% of the rarest operational taxonomic units, molecular-based richness patterns show the best possible match with the morphological approach. Temperature, phosphate, chlorophyll a and the Lyapunov exponent are the major explainers of these reconciled patterns. Global scale predictions provide a first approximation of the global geography of diatom richness and of the possible impacts of climate change. Main conclusion Our models suggest that diatom richness is controlled by different processes characteristic of distinct environmental scenarios: lateral mixing in highly dynamic regions, and both nutrient availability and temperature elsewhere. We present herein the implications of these processes on richness and how these same implications differ from other diversity indices because of the main component of richness: the rare biosphere.

Methods

Supplementary data 1:

Diatoms ribotypes validated by the taxonomic and phylogenetic check, their total abundance and their count in every Tara Oceans sample.

Supplementary data 2:

Morphology-based diatom richness estimated by light microscopy analysis of Tara Oceans net samples

Supplementary data 3:

Relative abundance matrix of identified diatom genera in the size fraction 20-180 μm. The first sheet shows the relative abundances at the genus level in each station obtained by the Tara Oceans metabarcoding samples (filtered Swarm d1). OTUs representatives have been annotated to Genebank and later aggregated by genus. The second sheet specifies the coordinates and sampling depth of every sample id present in the first matrix.

Supplementary data 4:

Abundance matrix of the Swarm (d1) metabarcode of Tara Oceans as resulting from the filtering process. Each row corresponds to a Swarm OTU and represents its abundance in the 20-180 μm Tara Oceans samples.