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Large scale patterns of marine diatom richness: Drivers and trends in a changing ocean

Authors: Busseni, Greta; Caputi, Luigi; Piredda, Roberta; Fremont, Paul; Hay Mele, Bruno; Campese, Lucia; Scalco, Eleonora; +6 Authors

Large scale patterns of marine diatom richness: Drivers and trends in a changing ocean

Abstract

AbstractAimPlankton 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 this measure, and finally to predict its spatio‐temporal patterns.Location and time periodThis is a global scale study, based on data collected within the 2009–2013 interval during the Tara Oceans expedition.Major taxa studiedThe focus of this study is diatoms. They play an important role in several biogeochemical cycles and within marine food webs, and display high taxonomic and functional richness.MethodsWe 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.ResultsBy 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 conclusionsOur 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 effects of these processes on richness and how these same effects differ from other diversity indices because of the main component of richness: the rare biosphere.

Countries
France, France, Italy, France, France, France, France, France
Subjects by Vocabulary

Microsoft Academic Graph classification: Scale (ratio) Ecology Marine diatom Oceanography Environmental science Species richness

Keywords

[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Global and Planetary Change, Ecology, diatoms; diversity; machine learning; metabarcoding; microscopy; richness; Tara Oceans, Tara Oceans, richne, diatom, diversity, machine learning, metabarcoding, microscopy, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Ecology, Evolution, Behavior and Systematics

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    23
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Average
Top 10%
hybrid
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European Marine Science