COLLABORATIVE RESEARCH: Temporal stability of riverine communities in dendritic networks at multiple spatial scales

了解物种群落如何随时间变化是生态学的基本目标之一。理解自然系统如何运作的关键一步是回答两个问题：1）为什么有些社区比其他社区对干扰更敏感？（2）群落的敏感性是否可以根据其在景观中的位置来预测？这项研究旨在了解社区如何发展和维持河流。具体而言，该项目将探讨河流社区的敏感性如何受到环境特征的影响，这些特征决定了生物如何在景观中移动。这些环境特征的例子包括盛行的风流、森林碎片之间的联系、河流的形状和为河流供水的小溪（即，河流网络）中的一个分水岭。本计画以河川网路中之溪流无脊椎动物为模式系统。本研究主要包括三个方面的工作：1）利用现有资料分析河网形态对河流无脊椎动物群落变异性的影响。2)以实验的方式检验河网的结构如何影响无脊椎动物群落对干扰的反应。这项任务将使用实验流，实验性地诱导干扰，并遵循响应来完成。3)建立一个计算机模型，以探索考虑到不同形状的网络，不同类型的生物体和无法使用现有数据或实验探索的新干扰的情景。这项工作将直接告知科学家和管理人员河流系统对干扰的反应。该研究还将为探索新河流系统中的网络创建一个工具。这项研究将为研究生和本科生提供生态学和数学建模方面的培训。将群落稳定性与可变环境中的空间过程联系起来是生态学面临的最大挑战之一，对生物多样性的管理和保护具有重要意义。研究人员专注于控制河流生态系统中无脊椎动物群落的稳定性，因为他们发现树枝状河流网络中的位置可以影响当地的生物多样性和时间稳定性。因此，该项目解决了一个一般性问题：扩散网络中群落的位置如何与物种特征相互作用，从而影响群落聚集体和组成的稳定性？最终，这项工作将针对三个具体的问题：（1）在一个扩散网络中，位置如何影响社区的时间稳定性？(2)网络中不同位置的社区的弹性如何？(3)分散网络的局部稳定性和结构如何影响区域尺度的稳定性，即，在整个传播网络中这项工作将建立在现有的项目，包括河流网络的生态，社区的时间稳定性分析，河流网络建模，模型和现场数据之间的相互作用。该项目将采用几种技术来解决这个问题，包括归档的长期流监测数据的荟萃分析，现场实验和机械建模，以了解观察到的成分和聚集体稳定性背后的过程。 这将同时提供一个通用的理论基础，可以转移到其他环境和系统。

Understanding how communities of species change through time is one of the fundamental goals of ecology. A key step toward understanding how natural systems function is answering two questions: 1) Why are some communities more sensitive to disturbance than others? and 2) Can the sensitivity of a community be predicted based on its location in a landscape? This study seeks to understand how communities develop and are maintained in rivers. Specifically, the project will explore how sensitivity of river communities is affected by environmental features that dictate how organisms move about the landscape. Examples of these environmental features include prevailing wind currents, connections between forest fragments, and the shape of a river and the small streams feeding the river (i.e., river network) in a watershed. This project uses stream invertebrates in river networks as a model system. The work involves three major tasks: 1) To analyze how the shape of a river network affect the level of variability of stream invertebrate communities using existing data. 2) To experimentally test how the structure of river networks affects the response of invertebrate communities to disturbances. This task will be accomplished using experimental streams, experimentally inducing a disturbance, and following the response. 3) To produce a computer model to explore scenarios considering different shapes of networks, different types of organisms and novel disturbances that cannot be explored using existing data or experiments. This work will directly inform scientists and managers about the responses of river systems to disturbance. The study will also create a tool for exploration of networks in new river systems. This study will provide training for graduate and undergraduate students in ecology and mathematical modeling. Linking community stability to spatial processes in variable environments is one of ecology's remaining great challenges, with implications for the management and conservation of biodiversity. The researchers focus on controls over invertebrate community stability in riverine ecosystems because they have found that a site location in a dendritic stream network can influence both local biodiversity and temporal stability. Therefore, this project addresses the general question: How does location of a community within a dispersal network interact with species traits to affect aggregate and compositional community stability? Ultimately this work will be directed at three specific questions: (1) Within a dispersal network, how does location affect the temporal stability of communities? (2) How resilient are communities at different locations within a network? (3) How does local stability and structure of the dispersal network affect stability at the regional scale, i.e., across the entire dispersal network? The work will build on existing projects including the ecology of river networks, analysis of community temporal stability, river network modeling, and the interaction between models and field data. The project will employ several techniques to address the question, including a meta-analysis of archived long-term stream monitoring data, field experiments, and mechanistic modeling to achieve an understanding of processes behind observed compositional and aggregate stability. This will simultaneously provide a general theoretical underpinning that is transferable to other contexts and systems.