as.one.mode: Conversion of a network matrix In bipartite: Visualising Bipartite Networks and Calculating Some (Ecological) Indices

Description

This helper function converts a bipartite matrix into a one-mode matrix.

Usage

 `1` ```as.one.mode(web, fill = 0, project="full", weighted=TRUE) ```

Arguments

 `web` A matrix with lower trophic level species as rows, higher trophic level species as columns and number of interactions as entries. `fill` What shall unobserved combinations be represented as in the one-mode matrix (see below)? Defaults to 0. Set to NA if links not possible for bipartite networks should be masked (i.e. those within a level). `project` There are different ways to convert a two-mode (bipartite) network into one-mode networks. The most common is to focus on one set (e.g. the n pollinators) and compute a n x n matrix with entries between species that pollinate the same plant (“higher”). Similarly, one can compute a k x k matrix for the k plant species (“lower”). Or, finally and the default, one can compute an (n+k) x (n+k) matrix in which only the observed interactions are present (“full”). This is in fact a near-trivial, symmetric matrix with 0s between species of the same trophic level. `weighted` Logical; shall the strength of links be included in the one-mode output? Defaults to TRUE, but can be set to FALSE to turn a weighted two-mode into a binary one-mode network.

Details

In bipartite (or: two-mode) networks, participants are of different types (e.g. pollinators and plants, actors and parties in social research). Hence, a party cannot connect to another party except through actors. A pollinator interacts with another pollinator only through the host plant.

Much network theory, however, is based on one-mode networks, where all participants are listed in one vector, i.e. plants and pollinators alike, actors together with events. This function here transforms the more condensed bipartite representation into a one-mode-representation, filling the unobserved type of interactions (i.e. plants with plants and pollinators with pollinators) with 0 (unless you specify it differently in fill).

The lower trophic level (e.g. plants or rows) is listed first, then the higher trophic level (e.g. pollinators or columns). Hence, pollinator 2 becomes species number r+2, where r is the number of rows of the network matrix.

The benefit of this conversion is access to the wonderful R-package Social Network Analysis (sna), with its many one-mode indices (such as `betweenness`, `closeness`, `centralization`, `degree`, `kpath.census` and so forth). Furthermore, `gplot` in that package also provides cool network depictions well worth checking out.

With respect to bipartite, `as.one.mode` is employed in the function `nodespec`, which itself uses the sna-function `geodist`.

Value

A matrix of dimension (n+k) x (n+k), where n and k are the dimensions of the input web. Both dimensions are given the names of the original web (first the lower, then the higher trophic level).

Author(s)

Carsten F. Dormann [email protected]

Function `projecting_tm` in package tnet provide smarter ways of converting two-modes into one-modes. This function can be accessed after transforming the web-matrix into an edge list using `web2edges`.

Examples

 ```1 2 3``` ```data(Safariland) image(Safariland) image(as.one.mode(Safariland)) ```

Example output

```Loading required package: vegan
This is vegan 2.4-3
network: Classes for Relational Data
Version 1.13.0 created on 2015-08-31.
copyright (c) 2005, Carter T. Butts, University of California-Irvine
Mark S. Handcock, University of California -- Los Angeles
David R. Hunter, Penn State University
Martina Morris, University of Washington
Skye Bender-deMoll, University of Washington
For citation information, type citation("network").
Type help("network-package") to get started.

sna: Tools for Social Network Analysis
Version 2.4 created on 2016-07-23.
copyright (c) 2005, Carter T. Butts, University of California-Irvine
For citation information, type citation("sna").
Type help(package="sna") to get started.

This is bipartite 2.08
For citation see: citation("bipartite").
Have a nice time plotting and analysing two-mode networks.

Attaching package: 'bipartite'

The following object is masked from 'package:vegan':

nullmodel
```

bipartite documentation built on July 13, 2018, 1:04 a.m.