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Large-scale predictions of salt-marsh carbon stock based on simple observations of plant community and soil type. / Ford, Hilary; Garbutt, Angus; Duggan-Edwards, Mollie et al.
In: Biogeosciences, Vol. 16, No. 2, 25.01.2019, p. 425-436.

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Ford H, Garbutt A, Duggan-Edwards M, Pages JF, Harvey R, Ladd C et al. Large-scale predictions of salt-marsh carbon stock based on simple observations of plant community and soil type. Biogeosciences. 2019 Jan 25;16(2):425-436. doi: 10.5194/bg-16-425-2019

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TY - JOUR

T1 - Large-scale predictions of salt-marsh carbon stock based on simple observations of plant community and soil type

AU - Ford, Hilary

AU - Garbutt, Angus

AU - Duggan-Edwards, Mollie

AU - Pages, Jordi F.

AU - Harvey, Rachel

AU - Ladd, Cai

AU - Skov, Martin W.

PY - 2019/1/25

Y1 - 2019/1/25

N2 - 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 sur- face 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.

AB - 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 sur- face 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.

U2 - 10.5194/bg-16-425-2019

DO - 10.5194/bg-16-425-2019

M3 - Article

VL - 16

SP - 425

EP - 436

JO - Biogeosciences

JF - Biogeosciences

SN - 1726-4170

IS - 2

ER -