Differences from the null model at the level of individual interaction strengths, species-level metrics or network-level metrics, indicates the presence of resource selection. By holding basic characteristics of the observed data constant in the null model (e.g. number of species and number of individuals of each species), the null model represents the network patterns that could be observed, given the limitations of the observed data, in the absence of any resource selection. Underlying it is the hypothesis that consumers show no active preferences, such that they will ‘consume’ resources in proportion to the relative abundance of those resources (i.e. if Resource A is twice as abundant as Resource B, they will interact twice as often with A than B Vaughan et al., 2018). The null model used in econullnetr was developed in the context of testing for prey preferences by predators (Agusti et al. Species are referred to as ‘consumers’ or ‘resources’, with the former term used when selecting which species (resources) to interact with: whilst often this involves actual consumption (e.g. predation), this need not be the case e.g. in a social network. For simplicity, terms are used in the broadest sense: nodes in the network are referred to as ‘species’, although in reality they could represent different taxonomic levels or other entities such as functional groups ‘individuals’ are the individual organisms that were sampled, with each species represented by one or (usually) more individuals. This document provides an illustrated introduction to how to use the package and how it can be combined with other packages. In particular, null models can distinguish features of the network that cannot be explained by ‘neutral’ mechanisms, such as the relative abundance of different organisms or sampling effects.Ī range of R packages is available for network analysis and the econullnetr package complements them. Null models can help to analyse these networks, looking at such characteristics as which species (nodes) interact with one another, the strength of individual interactions (link strengths) and the role of individual species in the network (e.g. specialist v. Many of these networks are bipartite, such as pollinators and flowers, seed dispersers and plants, and parasitoids and their hosts, whilst others are more complex, such as food webs with several trophic levels. Networks of species interactions are regularly plotted and analysed in ecology.
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