N-cycling genes and transcript abundance data in Shelf Sea Biogeochemistry (SSB).

Tait, Karen

Description

This dataset contains abundances of N-cycling genes and transcripts from microbes collected in the Celtic Sea (April 2014; March 2015; May 2015; August 2015). Sediments were collected from NIOZ cores on Shelf Sea Biogeochemistry (SSB) research cruises DY008, DY021, DY030 and DY034 and transported back to Plymouth Marine Laboratory (PML) where nucleic acid was extracted and quantitative and reverse transcriptase quantitative PCR (qPCR and RTqPCR) measurements of the abundance of key genes and transcripts involved in nitrogen cycling made by Karen Tait. Four contrasting sediment types within the Celtic Sea were compared: mud (station A), sandy mud (station I), muddy sand (station H) and sand (station G). Sediments were sub-sampled from a NIOZ core using 50 mL syringes with the barrel cut off and sectioned into three (0 – 1 cm; 3 – 5 cm and 6 – 8 cm). Five replicate cores were processed for each sediment type. The data were collected as part of the Shelf Sea Biogeochemistry (SSB) research programme as part of the Biogeochemistry, Macronutrient and Carbon Cycling in the benthic layer (BMCC) research programme. SSB was co-funded by the Natural Environment Research Council (NERC) and the Department for Environment, Food and Rural Affairs (Defra). The programme took a holistic approach to the cycling of nutrients and carbon and the controls on primary and secondary production in UK and European shelf seas, to increase understanding of these processes and their role in wider biogeochemical cycles. The British Oceanographic Data Centre (BODC) created the metadata entry and is responsible for holding master copies of the data.

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Mentions (0)

Metrics

Dataset Index

0.2

FAIR Score

35%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

British Oceanographic Data Centre, Natural Environment Research Council

Assigned Domain

Subfield

Ocean Engineering

Field

Engineering

Domain

Physical Sciences

Confidence Score

42%

Source

Scholar Data Model

Keywords

biota

Normalization Factors

FT

57.69

CTw

1.00

MTw

1.00