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  5. Using citizen science to estimate surficial soil Blue Carbon stocks in Great British saltmarshes

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Article
en
2022

Using citizen science to estimate surficial soil Blue Carbon stocks in Great British saltmarshes

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en
2022
Vol 9
Vol. 9
DOI: 10.3389/fmars.2022.959459

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Laurence Jones
Laurence Jones

UK Centre for Ecology & Hydrology

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Craig Smeaton
Annette Burden
Paulina Ruranska
+7 more

Abstract

A new saltmarsh soil dataset comprising of geochemical and physical property data from 752 soil samples collected through a sampling program supported by citizen scientists has been brought together with existing data to make the first national estimates of the surficial (top 10 cm) soil OC stock for Great British (GB) saltmarshes. To allow the inclusion of secondary data in the soil stock estimate a new bespoke organic matter to organic carbon conversion for GB saltmarsh soil was developed allowing organic matter data measured using loss-on-ignition to be convert to organic carbon content. The total GB surficial soil OC stock is 2.320 ± 0.470 Mt; English saltmarshes hold 1.601 ± 0.426 Mt OC, Scottish saltmarshes hold 0.368 ± 0.091 Mt OC, and Welsh saltmarshes hold 0.351 ± 0.082 Mt OC. The stocks were calculated within a Markov Chain Monte Carlo framework allowing robust uncertainty estimates to be derived for the first time. Spatial mapping tools are available to accompany these stock estimates at individual saltmarsh habitats throughout GB. This data will aid in the protection and management of saltmarshes and represents the first steps towards the inclusion of saltmarsh OC in the national inventory accounting of blue carbon ecosystems.

How to cite this publication

Craig Smeaton, Annette Burden, Paulina Ruranska, Cai Ladd, Angus Garbutt, Laurence Jones, Lucy McMahon, Lucy C. Miller, Martin W. Skov, William E. N. Austin (2022). Using citizen science to estimate surficial soil Blue Carbon stocks in Great British saltmarshes. , 9, DOI: https://doi.org/10.3389/fmars.2022.959459.

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Publication Details

Type

Article

Year

2022

Authors

10

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.3389/fmars.2022.959459

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