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Understanding freshwater ecosystem health from a microbial perspective

Understanding freshwater ecosystem health from a microbial perspective
从微生物角度了解淡水生态系统健康
批准号:
2890049
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

项目摘要

项目成果

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中文摘要
翻译
淡水环境面临压力,导致淡水物种、生态系统及其提供的服务减少。理解这些下降的原因是复杂的,因为通常存在多种相互作用的压力。此外,这些压力可能是零星的,例如以化学污染脉冲或极端天气事件的形式,这使得直接测量压力源事件成为一个挑战。了解生态系统状况和查明下降原因的一个既定办法是使用生物指示剂。这些标准通常以鱼类、大型无脊椎动物、硅藻或大型植物群落的组成为基础。然而,细菌,真菌和真核微生物群落在数量上以及物种和遗传多样性方面都占主导地位。这些社区在淡水生态系统健康的运作和维持方面发挥着重要作用。它们主要负责有机物的分解,是地球化学循环的关键驱动力,光合作用固定碳,并形成水生食物网的基础。然而,我们缺乏对淡水中微生物群落结构的了解,更重要的是,它们如何应对生态系统压力,如营养和有机污染物,以及气候和水文变化。由于这些群落的功能重要性,了解它们在淡水流域的组成和分布,以及探索它们揭示生态系统状况的能力是一个优先事项。DNA高通量测序(HTS)的进展意味着我们现在可以以前所未有的细节,低成本和高通量地研究整个微生物生态系统。该项目将应用环境署结构化淡水监测方案(河流监测网络)收集的淡水生物膜高温超导技术。该项目将利用来自RSN的现有数据,并进行现场采样和分子分析,以开发和改进方法,从而能够利用分子工具进行常规监管生物监测。此外,该项目还将探索基于DNA的新方法来识别淡水微生物,包括长读段DNA测序(PacBio或Nanopore)来识别整个社区。这些数据将以短读DNA测序方法(Illumina)为基准,该方法是由环境署正在开发评估淡水生态系统健康的新方法的工作产生的。该项目将解决以下关键研究问题:1.英格兰河流流域的淡水微生物群落(细菌、真菌和真核生物)是如何构成的?2.淡水微生物群落的不同组成部分如何在全国范围内对理化和空间驱动因素作出反应?3.如何使用新的统计和机器学习方法来确定可用于确定淡水生态系统状况和确定压力的生物指示类群?
英文摘要
Freshwater environments are exposed to stressors that contribute to the decline of freshwater species, ecosystems, and the services they provide. Understanding the causes of these declines is complex, as there are typically multiple, interacting pressures. Additionally, these pressures may be sporadic, for example in the form of pulses of chemical pollution or extreme weather events, which makes directly measuring stressor events a challenge. An established approach to understand both the condition of ecosystems and identify the causes of declines, is the use of bioindicators. These are typically based on the composition of fish, macroinvertebrate, diatom or macrophyte communities. However, bacterial, fungal, and eukaryotic microbial communities dominate freshwater biodiversity, both numerically and in terms of species and genetic diversity. These communities play fundamental roles in the functioning and maintenance of freshwater ecosystem health. They are primarily responsible for the decomposition of organic matter, are key drivers of biogeochemical cycles, photosynthetically fix carbon, and form the base of aquatic food webs. However, we lack an understanding of how microbial communities are structured within freshwaters and, critically, how they respond to ecosystem stressors such as nutrient and organic pollutants, and climatic and hydrological change. Due to the functional importance of these communities, it is a priority to understand more about their composition and distributions across freshwater catchments, as well as explore their ability reveal ecosystem condition.Advances in High Throughput Sequencing (HTS) of DNA mean that we now can characterise whole microbial ecosystems in unprecedented detail, at low cost and in high throughput. This project will apply HTS of freshwater biofilms collected by the Environment Agency's structured freshwater monitoring programme (the River Surveillance Network). The project will utilise both existing data from the RSN and perform field sampling and molecular analysis to develop and refine approaches to enable the utilisation of molecular tools for routine regulatory biomonitoring. In addition, this project will explore novel DNA-based approaches to characterise freshwater microbes, including long-read DNA sequencing (PacBio or Nanopore) to characterise whole communities. These data will be benchmarked against short-read DNA sequencing approaches (Illumina), generated by the Environment Agency's ongoing work into developing novel approaches for assessing freshwater ecosystem health. There will be opportunities to feed directly into regulatory policy.The project will address the following key research questions:1. How are freshwater microbial communities (bacterial, fungal, and eukaryotic) structured across river catchments in England?2. How do different components of the freshwater microbial community respond to physicochemical and spatial drivers at a national scale?3. How can novel statistical and machine learning approaches be used to identify bioindicator taxa that can be used determine freshwater ecosystem status and identify stressors?
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海外基金
横断山区淡水三肠目涡虫资源及分类学研究
  • 批准号:
    30670247
  • 项目类别:
    面上项目
  • 资助金额:
    27.0万元
  • 批准年份:
    2006
  • 负责人:
    陈广文
  • 依托单位: