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Sounding out maerl sediment thickness: an integrated data approach.
Sheehy, Jack; Bates, Richard; Bell, Michael; Porter, Jo.
Affiliation
  • Sheehy J; International Centre for Island Technology, Heriot-Watt University, Orkney Campus, Robert Rendall Building, Franklin Road, Stromness, Orkney, KW16 3AW, Scotland. jackmichaelsheehy@gmail.com.
  • Bates R; School of Earth and Environmental Sciences, University of St Andrews, Bute Building, Queen's Terrace, St Andrews, KY16 9TS, Scotland.
  • Bell M; International Centre for Island Technology, Heriot-Watt University, Orkney Campus, Robert Rendall Building, Franklin Road, Stromness, Orkney, KW16 3AW, Scotland.
  • Porter J; International Centre for Island Technology, Heriot-Watt University, Orkney Campus, Robert Rendall Building, Franklin Road, Stromness, Orkney, KW16 3AW, Scotland.
Sci Rep ; 14(1): 5220, 2024 Mar 03.
Article in En | MEDLINE | ID: mdl-38433221
ABSTRACT
Maerl beds are listed as a priority marine feature in Scotland. They are noted for creating suitable benthic habitat for diverse communities of fauna and flora and in supporting a wide array of ecosystem services. Within the context of climate change, they are also recognised as a potential blue carbon habitat through sequestration of carbon in living biomass and underlying sediment. There are, however, significant data gaps on the potential of maerl carbon sequestration which impede inclusion in blue carbon policy frameworks. Key data gaps include sediment thickness, from which carbon content is extrapolated. There are additional logistical and financial barriers associated with quantification methods that aim to address these data gaps. This study investigates the use of sub-bottom profiling (SBP) to lessen financial and logistical constraints of maerl bed sediment thickness estimation and regional blue carbon quantification. SBP data were cross validated with cores, other SBP data on blue carbon sediments, and analysed with expert input. Combining SBP data with estimates of habitat health (as % cover) from drop-down video (DDV) data, and regional abiotic data, this study also elucidates links between abiotic and biotic factors in determining maerl habitat health and maerl sediment thickness through pathway analysis in structural equation modelling (SEM). SBP data were proved to be sufficiently robust for identification of maerl sediments when corroborated with core data. SBP and DDV data of maerl bed habitats in Orkney exhibited some positive correlations of sediment thickness with maerl % cover. The average maerl bed sediment thickness was 1.08 m across all ranges of habitat health. SEM analysis revealed maerl bed habitat health was strongly determined by abiotic factors. Maerl habitat health had a separate positive effect on maerl bed sediment thickness.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep Year: 2024 Document type: Article Affiliation country: United kingdom Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep Year: 2024 Document type: Article Affiliation country: United kingdom Country of publication: United kingdom