econullnetr: an R package using null models to analyse the structure of 1 ecological networks and identify resource selection

Vaughan, Ian ORCID: https://orcid.org/0000-0002-7263-3822, Gotelli, Nicholas, Memmott, Jane, Pearson, Caitlin, Woodward, Guy and Symondson, William ORCID: https://orcid.org/0000-0002-3343-4679 2018. econullnetr: an R package using null models to analyse the structure of 1 ecological networks and identify resource selection. Methods in Ecology and Evolution 9 (3) , pp. 728-733. 10.1111/2041-210X.12907

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Abstract

1.Network analysis is increasingly widespread in ecology, with frequent questions asking which nodes (typically species) interact with one another and how strong are the interactions. Null models are a way of addressing these questions, helping to distinguish patterns driven by neutral mechanisms or sampling effects (e.g. relative abundance of different taxa, sampling completeness) from deterministic biological mechanisms (e.g. resource selection and avoidance), but few “off the shelf” tools are available. 2.We present econullnetr, an r package combining null modelling and plotting functions for networks, with data-export tools to facilitate its use alongside existing network analysis packages. It models resource choices made by individual consumers, enabling it to capture individual-level heterogeneity and generalising to a wider range of data types and scenarios than models applied directly to network matrices. The outputs can be analysed from the level of individual links to whole networks. 3.We describe the main functions and provide two short examples, along with the results of a benchmarking exercise to provide guidance about the statistical power and error rates. Our hope is that econullnetr provides a basis for more widespread use of null modelling to assist ecological network interpretation.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Biosciences
Publisher:	Wiley
ISSN:	2041-210X
Date of First Compliant Deposit:	29 September 2017
Date of Acceptance:	16 September 2017
Last Modified:	21 Nov 2024 07:30
URI:	https://orca.cardiff.ac.uk/id/eprint/105057

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