Response of freshwater invertebrates to natural environmental and agricultural stressor gradients across larger scales

农用化学品，特别是农药，已被证明是许多敏感物种在当地消失的重要原因，例如，在世界不同农业地区的淡水生态系统中，高达42%的无脊椎动物。大多数研究都集中在个体和种群水平上，这限制了科学家对生态风险的适当评估和对社区影响的预测能力。人们提倡以特质为基础的方法来建立机制的特质-压力源关系，以便进行社区预测和压力源之间的区分，这与淡水管理者特别相关。各种各样的研究仔细研究了栖息地中相似的环境条件是否会导致淡水无脊椎动物群落的可预测特征组成。结果表明，可预测性往往依赖于上下文。在许多特质与环境关系的研究中，有一个事实没有得到充分的考虑，这可能部分解释了情境依赖性，那就是特质不是彼此独立出现的，而是经常相互关联的。我们将研究在何种程度上，根据性状谱来解释这些相互关系可以提高性状-环境关系在更大尺度（这里定义为大陆和洲际尺度）上的一致性，从而提高对群落结构的预测。在工作包（WP） 1中，我们将使用性状数据库提取来自全球不同地区（即欧洲、北美、澳大利亚、新西兰和玻利维亚）的分类群库的性状概况和类群。随后，我们将比较这些性状概况组和相关的性状状态跨区域和区域内。在WP 2中，我们将首先确定用于预测农药胁迫的最重要的响应性状和性状谱组（在WP 1中建立），同时考虑其他农业胁迫源和不同的溪流类型。然后，我们将评估具有最高可预测性的农药胁迫反应性状在多大程度上满足胁迫特异性标准。最后，我们将仔细研究它们在农业多重应激源背景下对农药应激的特异性，包括额外的应激源，如过度的营养负荷。总体而言，我们的项目将介绍基于性状的方法的效用和局限性，例如，关于性状-环境关系跨区域的可转移性，以及在农业多重压力背景下的应用。

Agrochemicals, especially pesticides, have been shown to be important contributors to the local loss of many sensitive species, for instance, up to 42% of invertebrates in freshwater ecosystems of different agricultural regions of the world. Most research has focused on pesticide effects on the individual and population level, which constrains the ability of scientists to appropriately assess the ecological risks and predict community-level effects. Trait-based approaches have been advocated to establish mechanistic trait-stressor relationships that allow for community prediction and for discrimination between stressors, which is of particular relevance for freshwater managers. Various studies scrutinised whether similar environmental conditions in a habitat lead to a predictable trait composition of freshwater invertebrate communities. The results show that the predictability is often context-dependent. One fact that has insufficiently been considered in many studies on trait-environment relationships and that may explain part of the context-dependency, is that traits do not occur independently of one another, but they are often intercorrelated. We will examine to which extent accounting for these intercorrelations in terms of trait profiles improves the consistency of trait-environment relationship across larger scales, defined here as continental and intercontinental scale, and consequently improves prediction of community structure. In Work Package (WP) 1 we will extract trait profiles and groups for the taxa pools from different global regions, namely Europe, North America, Australia, New Zealand and Bolivia using trait databases. Subsequently, we will compare these trait profile groups and associated trait states across and within the regions. In WP 2 we will first identify the most important response traits and trait profile groups (established in WP 1) for predicting pesticide stress, also accounting for other agricultural stressors and different stream types. Afterwards, we will evaluate to which extent criteria for stressor-specificity are met by the response traits with the highest predictability for pesticide stress. Finally, we will scrutinise their specificity for pesticide stress in an agricultural multiple stressor context including additional stressors such as excessive nutrient loading. Overall, our project will inform on the utility and limitations of trait-based approaches, for instance, regarding the transferability of trait-environment relationships across regions and for use in agricultural multiple stress contexts.