Data from: NOS: a software suite to compute node overlap and segregation in ecological networks

Investigating the structure of ecological networks can help unravel the mechanisms promoting and maintaining biodiversity. Recently, Strona and Veech (10.1111/2041-210X.12395) introduced a new metric (Ɲ ̅, pronounced ‘nos’), that allows assessment of structural patterns in networks ranging from complete node segregation to perfect nestedness, and that also provides a visual and quantitative assessment of the degree of network modularity. The Ɲ ̅ metric permits testing of a wide range of hypotheses regarding the tendency for species to share interacting partners by taking into account ecologically plausible species interactions based on constraints such as trophic levels and habitat preference. Here we introduce NOS, a software suite (including a web interface freely accessible at http://nos.alwaysdata.net, an executable program, and Python and R packages) that makes it possible to exploit the full potential of this method. Besides computing node overlap and segregation (Ɲ ̅), the software provides different functions to automatically identify a set of possible resource-consumer interactions in food webs based on trophic levels. As an example of application, we analyzed two well-resolved high-latitude marine food webs, showing that an explicit a priori consideration of trophic levels is fundamental for a proper assessment of food web structure.解析生态网络的结构，有助于揭示推动并维持生物多样性的内在机制。近期，Strona与Veech（DOI：10.1111/2041-210X.12395）提出了一种全新的度量指标（Ɲ ̅，发音为"nos"），该指标可用于评估从完全节点分离到完美嵌套性（nestedness）的各类网络结构模式，同时还能实现可视化与定量化的网络模块化程度（modularity）评估。该Ɲ ̅度量指标可通过纳入基于营养级（trophic levels）、生境偏好（habitat preference）等生态学合理约束的物种互作关系，检验关于物种共享互作伙伴倾向的一系列假说。本文介绍NOS，一款功能完备的软件套件，包含可免费访问的网页端界面（访问地址：http://nos.alwaysdata.net）、可执行程序，以及Python与R语言包，可充分发挥该方法的全部潜力。该软件除可计算节点重叠度（node overlap）与节点分离度（node segregation）（Ɲ ̅）之外，还提供多项功能，可基于营养级自动识别食物网（food webs）中一系列潜在的资源-消费者互作关系。作为应用示例，本研究分析了两个分辨率较高的高纬度海洋食物网，结果表明，明确的先验性营养级考量是准确评估食物网结构的核心前提。