The study of mutualistic interaction networks has led to valuable insights into ecological and evolutionary processes. However, our understanding of network structure may depend upon the temporal scale at which we sample and analyze network data. To date, we lack a comprehensive assessment of the temporal scale‐dependence of network structure across a wide range of temporal scales and geographic locations. If network structure is temporally scale‐dependent, networks constructed over different temporal scales may provide very different perspectives on the structure and composition of species interactions. Furthermore, it remains unclear how various factors – including species richness, species turnover, link rewiring and sampling effort – act in concert to shape network structure across different temporal scales. To address these issues, we used a large database of temporally‐resolved plant–pollinator networks to investigate how temporal aggregation from the scale of one day to multiple years influences network structure. In addition, we used structural equation modeling to explore the direct and indirect effects of temporal scale, species richness, species turnover, link rewiring and sampling effort on network structural properties. We find that plant–pollinator network structure is strongly temporally‐scale dependent. This general pattern arises because the temporal scale determines the degree to which temporal dynamics (i.e. phenological turnover of species and links) are included in the network, in addition to how much sampling effort is put into constructing the network. Ultimately, the temporal scale‐dependence of our plant–pollinator networks appears to be mostly driven by species richness, which increases with sampling effort, and species turnover, which increases with temporal extent. In other words, after accounting for variation in species richness, network structure is increasingly shaped by its underlying temporal dynamics. Our results suggest that considering multiple temporal scales may be necessary to fully appreciate the causes and consequences of interaction network structure.

中文翻译：

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植物-授粉媒介网络的时间尺度依赖性

对相互影响的互动网络的研究已导致对生态和进化过程的宝贵见解。但是，我们对网络结构的理解可能取决于我们对网络数据进行采样和分析的时间尺度。迄今为止，我们还没有全面评估时间尺度的依存性，即网络结构在各种时间尺度和地理位置上的依赖性。如果网络结构是时间尺度相关的，则在不同时间尺度上构建的网络可能会对物种相互作用的结构和组成提供非常不同的观点。此外，目前尚不清楚各种因素如何协同作用，以形成跨不同时间尺度的网络结构，包括物种丰富度，物种更新，链接重新布线和采样工作。为了解决这些问题，我们使用了一个大型的时间分辨植物-授粉媒介数据库，研究了从一天到多年的时间聚集如何影响网络结构。此外，我们使用结构方程模型来探索时间尺度，物种丰富度，物种更新，链接重新布线和采样工作量对网络结构特性的直接和间接影响。我们发现植物-授粉媒介的网络结构在时间尺度上是高度依赖的。之所以出现这种一般模式，是因为时间尺度决定了网络中包含时间动态性（即物种和链接的物候转换）的程度，以及构建网络所需的采样工作量。最终，我们的植物-授粉媒介网络的时间尺度依赖性似乎主要是由物种丰富度驱动的，物种丰富度随采样努力而增加，而物种周转率则随时间范围而增加。换句话说，在考虑了物种丰富度的变化之后，网络结构越来越受到其潜在的时间动态的影响。我们的结果表明，考虑多个时间尺度可能是充分了解交互网络结构的原因和后果所必需的。