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

生物多样性正在以前所未有的速度丧失，对生态系统的功能和服务造成了有害后果。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，农药通常同时存在，并可能与其他压力源相互作用，如增加细沉积物流入开放的农业土壤。这种多重压力相互作用可能导致复杂的非线性反应，即它们可能对生物体和生态系统功能产生比单一压力反应预测的更弱或更强的影响。因此，可靠的生态系统管理需要了解和预测多种压力的影响的能力。因此，辨别农药和细颗粒沉积物的影响以及确定潜在的联合影响是一项高度相关和及时的挑战。然而，测试的多个压力源的影响需要独立的压力，这是几乎不可能实现的相关领域的研究。此外，高分类分辨率有助于确定压力源的影响，但很少提供分类鉴定的困难。因此，需要新的实验和分析方法，在多重压力的研究，以提高压力的歧视。在我们的项目中，我们将进行创新的实验室和现场实验，研究氯虫苯甲酰胺作为模型农药和沉积细沉积物对河流无脊椎动物和相关生态系统功能（有机物分解）的单独和联合影响。第一个工作包（WP 1）将采用DNA元条形码和杂交富集的定量方法进行基于DNA的社区评估。虽然这两种方法都可用于合并样品的物种评估，但由于PCR偏倚，从所得测序数据推断生物量或丰度受到阻碍。因此，我们提出了一个独特的标签序列（简并碱基区，DBR）的整合，以估计模板分子的真实数量，从而生物量。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泥沙的应激反应。在WP 2中，我们将评估农药和细沉积物对四种无脊椎动物切碎机（有机物降解的关键类群）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社区和功能变化。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的相对重要性的应激反应，这是一个非常及时的主题功能生态学。通过整合环境基因组学，生态毒理学，生态学和生物信息学的学科，该项目旨在从描述到真正理解和预测多种应激源的影响。

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.