Author: Luis, Angela D.; O'Shea, Thomas J.; Hayman, David T. S.; Wood, James L. N.; Cunningham, Andrew A.; Gilbert, Amy T.; Mills, James N.; Webb, Colleen T.
Title: Network analysis of host–virus communities in bats and rodents reveals determinants of cross-species transmission Document date: 2015_8_24
ID: yqc8r3ll_25
Snippet: Because closely related species share traits, we tested for phylogenetic dependence by setting the error term for the GLS to the phylogenetic correlation matrix multiplied by an additional parameter, Pagel's k, that was estimated to determine the strength of phylogenetic dependence (Pagel 1999; Freckleton et al. 2002) . A k estimate of 1 indicates that the error structure of the model was directly proportional to the species shared branch lengths.....
Document: Because closely related species share traits, we tested for phylogenetic dependence by setting the error term for the GLS to the phylogenetic correlation matrix multiplied by an additional parameter, Pagel's k, that was estimated to determine the strength of phylogenetic dependence (Pagel 1999; Freckleton et al. 2002) . A k estimate of 1 indicates that the error structure of the model was directly proportional to the species shared branch lengths. A k of 0 indicates the error structure of the model was not related to the species shared branch lengths (i.e., phylogeny does not explain any additional variation). Note that phylogeny is not a covariate in this analysis, and may not be significant if the model covariates themselves have phylogenetic dependence. Models were ranked by their AICc (Akaike information criterion adjusting for finite sample sizes) values. Correlation coefficients (R) were Pearson's product moment correlation comparing observed values to model predictions.
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