2017
DOI: 10.3389/fmicb.2017.01696
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From the Surface to the Deep-Sea: Bacterial Distributions across Polymetallic Nodule Fields in the Clarion-Clipperton Zone of the Pacific Ocean

Abstract: Marine bacteria regulate fluxes of matter and energy essential for pelagic and benthic organisms and may also be involved in the formation and maintenance of commercially valuable abyssal polymetallic nodules. Future mining of these nodule fields is predicted to have substantial effects on biodiversity and physicochemical conditions in mined areas. Yet, the identity and distributions of bacterial populations in deep-sea sediments and associated polymetallic nodules has received relatively little attention. We … Show more

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Cited by 55 publications
(75 citation statements)
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“…The taxonomic composition varied across the different realms of the water column, where, for example, Cyanobacteria had higher average relative abundance in the epipelagic compared with lower depths and Gammaproteobacteria had higher average relative abundance at lower depths compared with the epipelagic (Supporting Information Fig. S2; see also Lindh et al ., ). In the epipelagic and mesopelagic regions variation in environmental factors independent of spatial factors exerted significant control on total bacterioplankton composition (Table ; Fig.…”
Section: Resultsmentioning
confidence: 97%
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“…The taxonomic composition varied across the different realms of the water column, where, for example, Cyanobacteria had higher average relative abundance in the epipelagic compared with lower depths and Gammaproteobacteria had higher average relative abundance at lower depths compared with the epipelagic (Supporting Information Fig. S2; see also Lindh et al ., ). In the epipelagic and mesopelagic regions variation in environmental factors independent of spatial factors exerted significant control on total bacterioplankton composition (Table ; Fig.…”
Section: Resultsmentioning
confidence: 97%
“…Raw sequence data generated from Illumina Miseq were processed as described in Lindh et al . () using the UPARSE pipeline (Edgar, ). Sequence reads were merged and quality filtered and subsequently clustered into OTUs at 99% 16S rRNA gene sequence similarity.…”
Section: Methodsmentioning
confidence: 99%
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