Ohlmann Marc, Garnier Jimmy, Vuillon Laurent
Laboratoire d'Écologie Alpine, LECA, CNRS Univ. Savoie Mont Blanc, Univ. Grenoble Alpes Grenoble France.
Laboratoire de Mathématiques, LAMA, CNRS Univ. Savoie Mont Blanc, Univ. Grenoble Alpes Chambéry France.
Ecol Evol. 2023 Aug 15;13(8):e10229. doi: 10.1002/ece3.10229. eCollection 2023 Aug.
Trophic networks describe interactions between species at a given location and time. Due to environmental changes, anthropogenic perturbations or sampling effects, trophic networks may vary in space and time. The collection of network time series or networks in different sites thus constitutes a metanetwork. We present here the R package , which will ease the representation, the exploration and analysis of trophic metanetwork data sets that are increasingly available. Our main methodological advance consists in suitable layout algorithm for trophic networks, which is based on trophic levels and dimension reduction in a graph diffusion kernel. In particular, it highlights relevant features of trophic networks (trophic levels, energetic channels). In addition, we developed tools to handle, compare visually and quantitatively and aggregate those networks. Static and dynamic visualisation functions have been developed to represent large networks. We apply our package workflow to several trophic network data sets.
营养网络描述了特定地点和时间物种之间的相互作用。由于环境变化、人为干扰或采样效应,营养网络可能会随时间和空间而变化。因此,不同地点的网络时间序列或网络集合构成了一个元网络。我们在此展示R包,它将便于对日益可用的营养元网络数据集进行表示、探索和分析。我们主要的方法进展在于一种适用于营养网络的布局算法,该算法基于营养级和图扩散核中的降维。特别是,它突出了营养网络的相关特征(营养级、能量通道)。此外,我们还开发了用于处理、直观比较和定量比较以及汇总这些网络的工具。已经开发了静态和动态可视化函数来表示大型网络。我们将我们的包工作流程应用于几个营养网络数据集。