College of Geographic Sciences, Hunan Normal University, Changsha 410081, China; College of Environmental Science and Engineering, Hunan University, Changsha 410082, China.
College of Geographic Sciences, Hunan Normal University, Changsha 410081, China.
Sci Total Environ. 2022 Sep 10;838(Pt 1):155946. doi: 10.1016/j.scitotenv.2022.155946. Epub 2022 May 13.
Organic matter (OM) tracing is critical for understanding the processes of soil redistribution and global carbon cycling. It effectively supports ecological management and global climate change prediction. Stable isotopes are generally more source-specific compared with other tracers and identify OM sources with a higher level of accuracy. Nevertheless, stable isotopes may be enriched or depleted by physical and biochemical processes such as selective migration of particles and OM mineralization in transport and sedimentary environments, making it difficult to establish links between the source and sink regions. Literature on OM source identification tends to assume a direct link between stable isotope sources and sinks, ignoring the non-conservatism of stable isotopes. There is further literature on understanding and modeling the processes that link the sources to sinks in terms of the non-conservatism of stable isotopes. The disagreement in response to the non-conservatism lies in the lack of comprehensive understanding of stable isotope fingerprinting systems and non-conservatism. The development of stable isotope fingerprinting technology is full of challenges. This review outlines the applicability of stable isotope tracers, identification mechanisms, and associated quantitative models, intending to improve the stable isotope fingerprinting system. We highlight the non-conservatism of stable isotopes in space and time caused by physical and biochemical processes. Additionally, a decision tree is established to determine the quantitative tools, evaluation indicators, and procedures related to non-conservatism. This decision tree clarifies the process from non-conservatism detection to threshold determination of statistical quantification, which can guide the end-users to better apply stable isotope to trace OM sources.
有机物质（OM）示踪对于理解土壤再分布和全球碳循环过程至关重要。它有效地支持生态管理和全球气候变化预测。与其他示踪剂相比，稳定同位素通常更具来源特异性，能够更准确地识别 OM 来源。然而，稳定同位素可能会受到物理和生化过程的富集或耗尽，例如颗粒的选择性迁移和 OM 在运输和沉积环境中的矿化，这使得难以建立源区和汇区之间的联系。关于 OM 源识别的文献倾向于假设稳定同位素源与汇之间存在直接联系，而忽略了稳定同位素的非保守性。还有一些文献是关于理解和模拟稳定同位素非保守性在源汇之间联系的过程。对非保守性的反应不一致，原因在于对稳定同位素指纹识别系统和非保守性缺乏全面的了解。稳定同位素指纹识别技术的发展充满了挑战。本综述概述了稳定同位素示踪剂的适用性、识别机制和相关的定量模型，旨在改进稳定同位素指纹识别系统。我们强调了物理和生化过程导致稳定同位素在空间和时间上的非保守性。此外，还建立了一个决策树来确定与非保守性相关的定量工具、评估指标和程序。该决策树阐明了从非保守性检测到统计量化阈值确定的过程，可为最终用户更好地应用稳定同位素来追踪 OM 来源提供指导。
