Large-scale predictions of salt-marsh carbon stock based on simple observations of plant community and soil type

Ford, Hilary; Garbutt, Angus ORCID: https://orcid.org/0000-0002-9145-9786; Duggan-Edwards, Mollie; Pagès, Jordi F.; Harvey, Rachel; Ladd, Cai; Skov, Martin W.. 2019 Large-scale predictions of salt-marsh carbon stock based on simple observations of plant community and soil type. Biogeosciences, 16 (2). 425-436. https://doi.org/10.5194/bg-16-425-2019

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Official URL: http://dx.doi.org/10.5194/bg-16-425-2019

Abstract/Summary

Carbon stored in coastal wetland ecosystems is of global relevance to climate regulation. Broadscale inventories of this “blue” carbon store are currently lacking and labour intensive. Sampling 23 salt marshes in the United Kingdom, we developed a Saltmarsh Carbon Stock Predictor (SCSP) with the capacity to predict up to 44 % of spatial variation in surface soil organic carbon (SOC) stock (0–10 cm) from simple observations of plant community and soil type. Classification of soils into two types (sandy or not-sandy) explained 32 % of variation in SOC stock. Plant community type (five vegetation classes) explained 37 % of variation. Combined information on soil and plant community types explained 44 % of variation in SOC stock. GIS maps of surface SOC stock were produced for all salt marshes in Wales (∼4000 ha), using existing soil maps and governmental vegetation data and demonstrating the application of the SCSP for large-scale predictions of blue carbon stores and the use of plant community traits for predicting ecosystem services.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.5194/bg-16-425-2019
UKCEH and CEH Sections/Science Areas:	Soils and Land Use (Science Area 2017-)
ISSN:	1726-4170
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
NORA Subject Terms:	Ecology and Environment
Date made live:	20 Feb 2019 16:26 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/522326

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.5194/bg-16-425-2019

UKCEH and CEH Sections/Science Areas:

Soils and Land Use (Science Area 2017-)

ISSN:

1726-4170

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

NORA Subject Terms:

Ecology and Environment