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，网络分析有望让我们更全面地了解大自然是如何运作的。众所周知，物种相互作用网络随着时间的推移而变化很大。然而，大多数理论和分析都假设网络结构是静态的，对采样效应的影响还没有很好的理解。因此，时间变化的驱动因素以及对相互作用的种群以及对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，我的目标是通过一个概念框架整合经验和理论方法来应对这些挑战。这个框架建立在这样的理念之上，即量化网络的(时间)变化是由不同类型的消费者对资源可获得性的反应造成的。通过使用相同的显式时间尺度并在比较中考虑抽样效应，促进了理论模型和经验数据之间的整合。我将开发一致的概念、理论和分析技术，以了解在多个时间尺度上(一天内、一年内和几年之间)物种相互作用网络中时间结构的动态和功能后果。我将把这个新框架应用于植物-传粉者数据，描述多个时间尺度上的网络动态，并测试消费者-资源过程在多大程度上可以解释相互作用模式和物种频率的数量变化。我将建立具有时间异步性的物种间间接相互作用的模型，并从理论上评估具有互惠和对立消费者的网络中的短期和长期影响。一个特定的模型将专注于传粉者连接的植物的每日时间动态以及对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解析描述进行评估。该项目将帮助开发和合成生态学的时间维度，并有助于使网络生态更具定量预测性，这最终是保护和生态系统服务管理中的明智决策所必需的。

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.