4.7 Article

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

Journal

BIOGEOSCIENCES
Volume 16, Issue 2, Pages 425-436

Publisher

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/bg-16-425-2019

Keywords

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Funding

  1. Natural Environment Research Council (Bangor University) [CBESS: NE/J015644/1, NE/J015350/1]
  2. Biotechnology and Biological Sciences Research Council (BBSRC) as part of the UK's Living with Environmental Change (LWEC) programme
  3. Welsh Government
  4. Higher Education Funding Council for Wales through the Ser Cymru National Research Network for Low Carbon, Energy and Environment
  5. NERC [NE/J015350/1, ceh020015] Funding Source: UKRI

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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 (similar to 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.

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