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

被引:33
作者
Busseni, Greta [1 ]
Caputi, Luigi [1 ]
Piredda, Roberta [1 ]
Fremont, Paul [1 ,2 ]
Hay Mele, Bruno [1 ]
Campese, Lucia [1 ]
Scalco, Eleonora [1 ]
de Vargas, Colomban [3 ,4 ]
Bowler, Chris [5 ]
d'Ovidio, Francesco [6 ]
Zingone, Adriana [1 ]
Ribera d'Alcala, Maurizio [1 ]
Iudicone, Daniele [1 ]
机构
[1] Stn Zool Anton Dohrn, I-80121 Naples, Italy
[2] Univ Paris Saclay, Univ Evry, Inst Francois Jacob, Genom Metab,CEA,Genoscope,CNRS, Evry, France
[3] Sorbonne Univ, Stn Biol Roscoff, CNRS, Roscoff, France
[4] Tara Oceans GOSEE, Res Federat Study Global Ocean Syst Ecol & Evolut, Paris, France
[5] PSL Univ Paris, INSERM, Ecole Normale Super IBENS, Inst Biol,Ecole Normale Super,CNRS, Paris, France
[6] Sorbonne Univ, CNRS, Lab Oceanog & Climat Expt & Approches Numer LOCEA, Paris, France
来源
GLOBAL ECOLOGY AND BIOGEOGRAPHY | 2020年 / 29卷 / 11期
基金
欧盟地平线“2020”;
关键词
diatoms; diversity; machine learning; metabarcoding; microscopy; richness; Tara Oceans; SPECIES RICHNESS; GLOBAL PATTERNS; DIVERSITY; PHYTOPLANKTON; BIODIVERSITY; SEQUENCES; PLANKTON; CARBON; MODEL;
D O I
10.1111/geb.13161
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
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 this measure, and finally to predict its spatio-temporal patterns. Location and time period This is a global scale study, based on data collected within the 2009-2013 interval during theTaraOceans 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, and display 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, chlorophyllaand 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 conclusions 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 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.
引用
收藏
页码:1915 / 1928
页数:14
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