Utilizing environmental genomics to study multiple agricultural stressor impacts on stream invertebrates and ecosystem functions

生物多样性正以前所未有的速度丧失，对生态系统功能和服务造成不利影响。河流生态系统尤其受到这种损失的影响。包括农药在内的农业压力因素是生物多样性丧失的最相关原因之一。然而，农药通常同时发生，并可能与其他压力因素相互作用，如开放农业土壤中增加的细沉积物流入。这种多重压力源相互作用可能导致复杂的非线性反应，即它们对生物体和生态系统功能的影响可能比单一压力源反应预测的更弱或更强。因此，可靠的生态系统管理需要理解和预测多种压力源影响的能力。因此，识别农药和细沉积物的影响以及识别潜在的联合影响是一项高度相关和及时的挑战。然而，多重压力源效应的测试需要压力源的独立性，这在相关领域的研究中几乎是不可能实现的。此外，高分类学分辨率有助于识别压力源影响，但由于分类学鉴定的困难，很少能获得。因此，在多应激源研究中需要新的实验和分析方法来提高应激源的识别能力。在我们的项目中，我们将进行创新的实验室和现场实验，研究氯虫腈作为模式农药和沉积细沉积物对河流无脊椎动物的单独和联合影响以及相关的生态系统功能（有机物分解）。第一个工作包（WP1）将采用DNA元条形码和杂交富集技术对基于DNA的群落进行定量评估。虽然这两种方法都可以用于汇总样本的物种评估，但由于PCR偏差，从结果测序数据推断生物量或丰度受到阻碍。因此，我们建议整合一个独特的标记序列（退化碱基区，DBR）来估计模板分子的真实数量，从而估计生物量。利用改进的定量工具，我们将评估河流无脊椎动物对农药和细沉积物的应激反应。在WP2中，我们将评估农药和细沉积物对四种无脊椎碎纸机（有机物降解的关键分类群）基因表达（转录组学）变化的单独和联合影响。我们将测试生理应激反应是否可以转化为观察到的群落和功能变化。此外，通过进行生物相互作用实验，我们将量化生物相互作用对应激源反应的相对重要性，这是功能生态学中一个非常及时的主题。通过整合环境基因组学、生态毒理学、生态学和生物信息学等学科，该项目旨在从描述到真正理解和预测多种应激源效应。

Biodiversity loss is proceeding at unprecedented rates with detrimental consequences for ecosystem functions and services. Stream ecosystems are especially impacted by this loss. Agricultural stressors, including pesticides, rank amongst the most relevant causes of biodiversity loss. However, pesticides usually co-occur and may interact with other stressors such as increased fine sediment influx from open agricultural soils. Such multiple stressor interactions can lead to complex non-linear responses, i.e. they can result in weaker or stronger effects on organisms and ecosystem functions than predicted from single stressor responses. Therefore, reliable ecosystem management requires understanding and the ability to predict the effects of multiple stressors. Discerning effects from pesticides and fine sediment as well as identifying potential joint effects is therefore a highly relevant and timely challenge. However, testing for multiple stressor effects requires independence of the stressors, which is almost impossible to achieve in correlative field studies. Furthermore, high taxonomic resolution facilitates the identification of stressor impacts, yet is rarely available given the difficulty of taxonomic identification. Therefore, new experimental and analytical approaches are needed in multiple stressor research to improve stressor discrimination. In our project, we will conduct innovative lab and field experiments to study individual and joint effects of chlorantraniliprole as a model pesticide and deposited fine sediment on stream invertebrates and associated ecosystem functions (organic matter decomposition). The first Work Package (WP1) will feature a quantitative approach to DNA-based community assessment using DNA metabarcoding and hybrid enrichment. While both approaches can be used for species assessment of pooled samples, inferring biomass or abundances from the resulting sequencing data is hampered due to PCR bias. We therefore propose the integration of a unique tagging sequence (degenerate base region, DBR) to estimate the true number of template molecules and thereby biomass. With the improved quantitative tools we will assess stressor responses of stream invertebrates to pesticide and fine sediment. In WP2 we will assess individual and joint impacts of the pesticide and fine sediment on changes in gene expression (transcriptomics) in four invertebrate shredders, key taxa in organic matter degradation. We will test if physiological stress responses can be translated to observed community and functional changes. Furthermore, by performing biotic interaction experiments we will quantify the relative importance of biotic interactions for the stressor responses, which is a very timely topic in functional ecology. Through integrating the disciplines of environmental genomics, ecotoxicology, ecology and bioinformatics this project seeks to move forward from describing to truly understanding and predicting multiple stressor effects.