Fingerprinting macrophyte blue carbon by pyrolysis-GC-compound specific isotope analysis (Py-CSIA)

Document Type

Journal Article

Publication Title

Science of the Total Environment



PubMed ID





School of Science / Centre for Marine Ecosystems Research




Ministerio de Economía y Competitividad Marine Sciences Institution (projects RYC2019-027073-I, 20213AT014 funded by MCIN/AEI/10.13039/501100011033 MINECO pre-doctoral FPI fellowship BES-2017-079811 Project PAIDI2020, PY20_01073. co-funded with EU FEDER funds


Kaal, J., González-Pérez, J. A., San Emeterio, L. M., & Serrano, O. (2022). Fingerprinting macrophyte Blue Carbon by pyrolysis-GC-compound specific isotope analysis (Py-CSIA). Science of The Total Environment, 836, 155598. https://doi.org/10.1016/j.scitotenv.2022.155598


There is a need for tools to determine the origin of organic matter (OM) in Blue Carbon Ecosystems (BCE) and marine sediments to (1) facilitate the implementation of Blue Carbon strategies into carbon accounting and crediting schemes and (2) decipher changes in ecosystem condition over decadal to millennial time scales and thus to understand and predict the stability of BCE in a changing world. Pyrolysis-GC-compound specific isotope analysis (Py-CSIA) is applied for the first time in marine environments and BCE research. We studied Australian mangrove, tidal marsh and seagrass sediments, in addition to potential sources of OM (Avicennia, Posidonia, Zostera, Sarcocornia, Ecklonia and Ulva species and seagrass epiphytes), to identify precursors of different biomacromolecule constituents (lignin, polysaccharides and aliphatic structures). Firstly, the link between bulk δ13C and δ13C reconstructed from compound-specific δ13C showed that the pyrolysis approach allows for the isotopic screening of a representative portion of the OM. Secondly, for all samples, the C isotope fingerprint of the carbohydrate products (plant polysaccharides) was the heaviest (13C enriched), followed by lignin and aliphatic products. The differences in δ13C among macromolecules and the overlap in δ13C among putative sources reflect the limitations of bulk δ13C analyses for deciphering OM provenance. Thirdly, phanerogams specimen had the heaviest carbohydrate and lignin, confirming that seagrass-derived lignocellulose can be traced based on δ13C. Consistent differences for individual compounds were identified between seagrasses and between Avicennia and Sarcocornia using Py-CSIA. Fourth, ecosystem shifts (colonization of seagrass habitats by mangrove) on millenary time scales, hypothesized in previous studies on the basis of bulk δ13C and Py-GC–MS, were confirmed by Py-CSIA. We conclude that Py-CSIA is useful in Blue Carbon research to decipher OM sources in marine sediments, identify ecosystem transitions in palaeoenvironmental records, and to understand the role of different OM compounds in Blue Carbon storage.



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