Appendix B. Bayesian network overview.

Bayesian network overview

Supplement 1. R source code.

<h2>File List</h2><blockquote> <p> <a href="ModelAveraging.R">ModelAveraging.R</a>  - R code for model averaging<br> <a href="HighlyProbable.R">HighlyProbable.R</a>  - R code for identification of highly probable functional relationships<br> <a href="KendallsW.R">KendallsW.R</a>  - R code for implementation of Kendall's W</p> </blockquote><h2>Description</h2><blockquote> <p> Files contain R source code for the model averaging technique, ModelAveraging.R, and identification of highly probable functional relationships, HighlyProbable.R, as described in the paper, and implementation of Kendall's W as per Legendre (2005), KendallsW.R. </p></blockquote

Appendix A. Supplementary methods for data processing, modification of Bayesian network methods for ecological data, and analysis of networks.

Supplementary methods for data processing, modification of Bayesian network methods for ecological data, and analysis of networks

Appendix C. Supplementary figures showing detail networks for species and habitat, comparison of scores across data sets, and comparison of Bayesian networks with lasso regression analysis.

Supplementary figures showing detail networks for species and habitat, comparison of scores across data sets, and comparison of Bayesian networks with lasso regression analysis

Modelled median richness for threatened and restricted range butterflies in South Africa.

<p>Modelled median richness (Spatial Model 1) for (a) threatened and (b) restricted range butterfly species in South Africa at the 2 minute grid square scale. Higher richness is represented by darker shades of grey.</p

Modelled median total richness for South African butterflies at five grid square scales.

<p>Modelled median total richness (Spatial Model 1) for butterflies in South Africa at five grid square scales: a) 60 minutes, b) 30 minutes, c) 15 minutes, d) 5 minutes and e) 2 minutes. Higher richness is represented by darker shades of grey. In f), point localities of all butterfly distribution records (<i>n</i> = 326 530) in the atlas region (South Africa, Lesotho and Swaziland) which emanated from the SABCA project [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124327#pone.0124327.ref030" target="_blank">30</a>] are shown.</p

The relationship between butterfly richness and human population density in South Africa, at five spatial resolutions.

<p>Scatter plots of modelled median total butterfly richness (scaled and centred) and log human population density, at each of the five spatial resolutions, showing best fitting regression lines (mean ± standard error), for linear model 2 which was the best model in each case: a) 60 minutes, b) 30 minutes, c) 15 minutes, d) 5 minutes and e) 2 minutes.</p

Steps used for spatial distribution modelling and species richness determination, using Spatial Models 1.

<p>Species X reflects the focal species being modelled. The steps were carried out at five spatial resolutions. The steps were repeated using Spatial Model 2 (Step 4).</p><p>Steps used for spatial distribution modelling and species richness determination, using Spatial Models 1.</p

Model-averaged parameter estimates (estimates of fixed effects included in models with ΔAICc<i>_i</i> ≤2 with contributions to average weighted by <i>w</i>AICc<i>_i</i> of model), unconditional standard errors and 95% confidence intervals.

<p>Interactions are indicated by x.</p><p>Hatching date (1 =  1^st May) and date found (date nest discovered; 1 =  1^st May) were standardized before being input in models as fixed factors.</p><p>Model-averaged parameter estimates (estimates of fixed effects included in models with ΔAICc<i>_i</i> ≤2 with contributions to average weighted by <i>w</i>AICc<i>_i</i> of model), unconditional standard errors and 95% confidence intervals.</p

The effect of food supplementation on chick wing length.

<p>Variation in wing length (mean ±95% confidence limits) in relation to age for fed and control chicks in 2009 and 2010.</p