SSF NOVEL TRACERS - Exploration of biogeochemical tracers (environmental and artificial DNA, organic carbon) for tracing subsurface stormflow

SSF NOVEL TRACERS - 探索用于追踪地下风暴流的生物地球化学示踪剂（环境和人工 DNA、有机碳）

• 批准号: 493884508
• 负责人: Professor Dr. Peter Chifflard
• 金额: --
• 依托单位: Institut für Geographie und Regionalforschung
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/493884508?language=en
• 关键词: SSF; NOVEL; TRACERS; Exploration; biogeochemical

Inferences of subsurface flow paths, sources and subsurface hydrological connectivity are limited by the various assumptions and sparse direct measurement opportunities. In response to the need for new tracers to detect source areas of subsurface stormflow (SSF), microbial community composition inferred via environmental DNA (eDNA) metabarcoding as well as the spatial differences of optical characteristics of water-soluble organic matter (WSOM; absorbance and fluorescence) in soils offers a so far little considered possibility. Depending on topographic and soil properties, specific habitats for soil microbial and macro-communities are formed, which can be mapped as spatial eDNA patterns and used to precisely locate and regionalize the source areas of SSF. Composition of eDNA is a found to be function of soil organic carbon composition which suggests a close connection of these. The application of artificial tracer DNA offers the possibility to carry out multiple tracer experiments with low technical effort and high information content with respect to subsurface flow paths. However, a rigorous assessment of the applicability of these novel tracers, also in combination, with respect to SSF has not yet been carried out. Thus, we propose to evaluate the potential of eDNA from natural communities as well as artificially applied tracer DNA and optical characteristics of WSOM as non-conservative tracers for SSF and subsurface connectivity in four contrasting catchments in the low and high mountain ranges (Sauerland, Ore Mountains, Black Forest, Alps). We will carry out soil sampling on 12 hillslopes in these catchments each with 10 soil profiles to detect spatial and dept-related distribution of eDNA and WSOM. In order to investigate the dept-dependent temporal variability of eDNA and WSOM we will take water samples of the subsurface runoff in different soil depths at one trenched hillslope in every catchment during natural rainfall-runoff events. During artificial irrigation experiments at two trenched hillslopes (low and high mountain) the SSF generation and flow paths will be studied in detail using self-designed and applied artificial DNA tracers. To analyze eDNA and WSOM in the lab we will use an array of state-of-the-art laboratory equipment and methods (TOC-Analyzer, Fluorescence Spectrometry, High-throughput amplicon sequencing and quantitative PCR). The use of multivariate statistical techniques (e.g., PCA, CCA, PARAFAC, Clusteranalysis, WGCNA)) will help to identify temporal and spatial patterns to identify source areas of SSF and to detect biochemical signatures of SSF as tracer for SSF.This systematically investigation of eDNA and WSOM at the hillslope scale in contrasting landscape will allow to assess these different biochemical tracers to trace SSF. Moreover, these investigations will create a unique comprehensive database for the derivation of biogeochemical signatures to identify source areas and flow pathways of SSF.

地下水流路径、水源和地下水文连通性的推断受到各种假设和稀疏的直接测量机会的限制。为了响应对新型示踪剂探测地下暴雨（SSF）源区的需求，通过环境DNA （eDNA）元条形码推断微生物群落组成以及土壤中水溶性有机物（WSOM；吸光度和荧光）光学特性的空间差异提供了迄今为止很少考虑的可能性。根据地形和土壤性质，形成特定的土壤微生物栖息地和宏观群落，并将其映射为空间eDNA模式，用于精确定位和区划土壤土壤养分来源区域。eDNA的组成是土壤有机碳组成的函数，表明两者之间存在密切联系。人工示踪剂DNA的应用为开展多种示踪剂实验提供了可能性，技术成本低，信息含量高。然而，还没有对这些新型示踪剂的适用性进行严格的评估，也没有对SSF进行组合。因此，我们建议评估来自自然群落的eDNA以及人工应用的示踪DNA和WSOM的光学特性作为低山脉和高山脉（Sauerland, Ore Mountains, Black Forest, Alps）四个不同流域的SSF和地下连通性的非保守示踪剂的潜力。我们将在这些集水区的12个山坡上进行土壤采样，每个山坡上有10个土壤剖面，以检测eDNA和WSOM的空间和深度分布。为了研究eDNA和WSOM随时间变化的深度依赖性，我们将在自然降雨-径流事件中，在每个集水区的一个沟槽山坡上采集不同土壤深度的地下径流水样。在两个沟状山坡（低山和高山）的人工灌溉试验中，将使用自行设计和应用的人工DNA示踪剂详细研究SSF的产生和流动路径。为了在实验室中分析eDNA和WSOM，我们将使用一系列最先进的实验室设备和方法（toc分析仪，荧光光谱法，高通量扩增子测序和定量PCR）。使用多元统计技术（如PCA， CCA， PARAFAC, Clusteranalysis， WGCNA）将有助于确定SSF的时空模式，以确定SSF的来源区域，并检测SSF的生化特征作为SSF的示踪剂。在对比景观的山坡尺度上对eDNA和WSOM的系统调查将允许评估这些不同的生化示踪剂来追踪SSF。此外，这些研究将创建一个独特的综合数据库，用于推导生物地球化学特征，以确定SSF的来源区域和流动路径。