Quantitative fatty acid signature analysis: a new tool to determine trophic interactions in soil food webs

定量脂肪酸特征分析：确定土壤食物网中营养相互作用的新工具

• 批准号: 321417827
• 负责人: Professorin Dr. Liliane Rueß
• 金额: --
• 依托单位: Arbeitsgruppe Ökologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/321417827?language=en
• 关键词: Quantitative; fatty; acid; signature; analysis

Soil food webs are important drivers for ecological key functions in soil systems such as carbon and nutrient cycling. However, food web models generelly lack quantitative data from empirical studies to describe these energy flows. This is mainly due to the shortage in high-throughput methods to assign the accurate dietary information in dominant food web members. The aim of the proposed project is to implement Quantitative Fatty Acid Signature Analysis (QFASA) as new tool to study cryptic belowground feeding relationships. This model approach, recently designed for marine ecosystems and vertebrate predators, will be adapted to soil ecosystems and invertebrate consumers. Over the last decade fatty acids have been established as biochemical marker molecules in soil food webs. Starting from this qualitative fatty acids profiling as prerequisite, the project will generate the major input factors for the QFASA model as a premise to its application in soil systems. Collembola as frequent soil decomposer are used as model organisms. Firstly, a lipid library for major resources is conducted and prey-on-prey simulations are run to reveal overlap in signatures of resource types. Secondly, calibration coefficients as weighting factors for specific fatty acids are developed to account for consumer metabolism using formulated diets in laboratory experiments. And thirdly, the QFASA model is validated in simulation studies with pseudoconsumers. The best-fit model finally is applied to field populations of Collembola to assign their diets at a deciduous forest, grassland, and arable site. In sum, the proposed project will found the base for the application of QFASA to a wide range of soil decomposers, for gathering quantitative data to describe food web interactions and energy flows under realistic conditions in the field.

土壤食物网是土壤系统中碳和养分循环等生态关键功能的重要驱动力。然而，食物网模型普遍缺乏定量的数据，从实证研究来描述这些能量流。这主要是由于缺乏高通量的方法来分配占主导地位的食物网成员的准确饮食信息。该项目的目的是实施定量脂肪酸特征分析（QFASA）作为研究地下摄食关系的新工具。这种模式的方法，最近设计的海洋生态系统和脊椎动物捕食者，将适应土壤生态系统和无脊椎动物消费者。在过去的十年中，脂肪酸已被确定为土壤食物网中的生化标记分子。从这个定性脂肪酸谱作为先决条件开始，该项目将产生QFASA模型的主要输入因子，作为其在土壤系统中应用的前提。弹尾目是常见的土壤分解者，被用作模式生物。首先，进行主要资源的脂质库，并进行捕食模拟，以揭示资源类型的签名中的重叠。其次，校准系数作为特定脂肪酸的加权因子，用于在实验室实验中使用配制饮食来解释消费者代谢。第三，在虚拟消费者的仿真研究中验证了QFASA模型的有效性。最后将最佳拟合模型应用于弹尾目野外种群，以分配其在落叶林、草地和耕地的饮食。总之，拟议的项目将为QFASA在广泛的土壤分解者中的应用奠定基础，以收集定量数据来描述该领域现实条件下的食物网相互作用和能量流动。