Daily and seasonal dynamics of ecological interaction networks: temporal structure and its functional consequences

由于大多数物种都参与了复杂的相互作用网络，网络分析有望更全面地了解自然界的运作方式。物种相互作用网络是已知的高度可变的随着时间的推移。然而，大多数理论和分析假设静态网络结构，和抽样效应的影响没有得到很好的理解。因此，时间变化的驱动因素和相互作用的种群和生物多样性和稳定性的功能后果在很大程度上是未知的。在这个项目中，我的目标是通过整合经验和理论方法，通过一个概念框架来应对这些挑战。这个框架的基础上的想法，（时间）变化的定量网络的结果从不同类型的消费者对资源的可用性的反应。通过使用相同的明确的时间尺度和比较中的抽样效应，促进了理论模型和经验数据之间的整合。我将发展一致的概念，理论和分析技术，以了解多个时间尺度上物种相互作用网络中时间结构的动态和功能后果（一天之内，一年之内和几年之内）。我将把这个新的框架应用于植物传粉者数据，在多个时间尺度上描述网络动态，并测试相互作用模式和物种频率的定量变化消费者-资源过程解释。我将建立物种之间的间接相互作用模型与时间的随机性和理论上评估短期和长期的影响，在网络与互惠和对立的消费者。一个具体的模型将集中在日常的时间动态的植物传粉者和植物物种共存的影响。该模型将通过对经验授粉网络的精细描述进行评估，该项目将有助于开发和综合生态学的时间维度，并有助于使网络生态学更具定量预测性，这最终是保护和生态系统服务管理中明智决策所需的。

Since most species are involved in complex networks of interactions, network analysis promises to allow a more complete understanding of how nature works. Species interaction networks are known to be highly variable over time. However, most theory and analysis assumes static network structure, and the influence of sampling effects is not well understood. Therefore, the drivers of temporal changes and the functional consequences for the interacting populations and for biodiversity and stability are largely unknown.In this project, I aim to tackle these challenges by integrating empirical and theoretical approaches through a conceptual framework. This framework builds on the idea that (temporal) variation in quantitative networks results from different types of consumer responses to resource availability. Integration between theoretical models and empirical data is facilitated by using the same explicit timescales and by accounting for sampling effects in comparisons. I will develop consistent concepts, theory and analytical techniques for understanding the dynamics and functional consequences of temporal structure in species interaction networks on multiple timescales (within a day, within a year and among years).I will apply this new framework for plant-pollinator data, describing network dynamics on multiple temporal scales and testing how far quantitative variation in interaction patterns and species frequencies can be explained by consumer-resource processes. I will build models of indirect interactions among species with temporal asynchrony and theoretically evaluate short- and long-term effects in networks with both mutualistic and antagonistic consumers. A specific model will focus on the daily temporal dynamics of plants linked by pollinators and the implications for plant species coexistence. This model will be evaluated with a finely resolved description of an empirical pollination network.This project will help develop and synthesize the temporal dimension of ecology and contribute to making network ecology more quantitatively predictive, which is ultimately needed for informed decisions in conservation and ecosystem service management.