Pyrolyscience, Santiago de Compostela, Spain.
Instituto de Recursos Naturales y Agrobiología de Sevilla, Consejo Superior de Investigaciones Científicas (IRNAS-CSIC), MOSS Group, Seville, Spain.
Sci Total Environ. 2022 Aug 25;836:155598. doi: 10.1016/j.scitotenv.2022.155598. Epub 2022 Apr 29.
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 δC and δC reconstructed from compound-specific δC 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 (C enriched), followed by lignin and aliphatic products. The differences in δC among macromolecules and the overlap in δC among putative sources reflect the limitations of bulk δC analyses for deciphering OM provenance. Thirdly, phanerogams specimen had the heaviest carbohydrate and lignin, confirming that seagrass-derived lignocellulose can be traced based on δC. 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 δC 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.
需要有工具来确定蓝碳生态系统（BCE）和海洋沉积物中有机物（OM）的来源，以便 (1) 将蓝碳策略纳入碳核算和信用额度计划，以及 (2) 解析数十年至千年时间尺度上生态系统状况的变化，从而了解和预测变化世界中 BCE 的稳定性。热解气相色谱-化合物特定同位素分析（Py-CSIA）首次应用于海洋环境和 BCE 研究。我们研究了澳大利亚红树林、潮汐沼泽和海草沉积物，以及 OM 的潜在来源（黄槿、波西多尼亚、海草、盐角草、鹿角菜和石莼属物种和海草附生植物），以确定不同生物大分子成分（木质素、多糖和脂肪族结构）的前体。首先，总 δC 与化合物特异性 δC 重建之间的联系表明，热解方法允许对 OM 的代表性部分进行同位素筛选。其次，对于所有样品，碳水化合物产物（植物多糖）的 C 同位素指纹最重（C 富集），其次是木质素和脂肪族产物。大分子之间的 δC 差异以及假定来源之间的 δC 重叠反映了利用总 δC 分析来解析 OM 来源的局限性。第三，单子叶植物标本的碳水化合物和木质素最重，这证实了海草衍生的木质纤维素可以根据 δC 进行追踪。使用 Py-CSIA 确定了海草之间以及黄槿和盐角草之间个别化合物的一致差异。第四，根据基于总 δC 和 Py-GC-MS 的先前研究假设，在千年时间尺度上发生了生态系统变化（红树林对海草生境的殖民化），这一点通过 Py-CSIA 得到了证实。我们得出的结论是，Py-CSIA 在蓝碳研究中非常有用，可用于解析海洋沉积物中的 OM 来源、识别古环境记录中的生态系统转变，以及了解不同 OM 化合物在蓝碳储存中的作用。
