Phylogenetic diversity
To quantify phylogenetic diversity in each time period in each region, we calculated the standardized effect size (SES) for Faith’s phylogenetic richness that accounts for differing sample sizes (SES for Faith’s PD, (Faith 1992)). Faith’s PD (hereafter PD) is the sum of the branch lengths of the phylogenetic tree linking all isolates for each subset (in this case the two time periods). As the number of isolates in each contrast differed (stable region 2005-2011: 11 isolates, stable region 2012-13: 5 isolates, treatment region 2005-2011: 10 isolates, treatment region 2012-14: 5 isolates) we calculated the standardized effect size (SES) by comparing the PD we observed to a null model that accounts for number of tips (i.e., how much phylogenetic diversity would we see for a given number of isolates by chance). We denote the standardized PD as SES.PD from here on; this was calculated across a subset of posterior phylogenetic trees from our previous Bayesian phylogenetic analyses (Fountain-Jones et al. 2019). To capture phylogenetic uncertainty in these estimates, we utilized the computational efficiency of the PhyloMeasures R package algorithm (Tsirogiannis & Sandel 2016) to calculate SES.PD and apply this across a 1000 tree subsample of posterior trees (Fountain-Jones et al.2019). Specifically, for each calculation of SES.PD we compared our observed PD to a uniform null model (i.e., isolate samples are taken with equal [uniform] probability). The code and data to perform these operations as well as the transmission tree analysis above can be found here: https://github.com/nfj1380/TransmissionTreeCode
Acknowledgments: This project was funded by the National Science Foundation Ecology of Infectious Diseases research program grants (DEB 1413925) and an Australian Research Council Discovery Project Grant (DP190102020). M.L.J.G. was supported by the Office of the Director, National Institutes of Health under award number NIH T32OD010993. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. SD is supported by the Fonds National de la Recherche Scientifique (FNRS, Belgium). GB acknowledges support from the Interne Fondsen KU Leuven / Internal Funds KU Leuven under grant agreement C14/18/094, and the Research Foundation – Flanders (‘Fonds voor Wetenschappelijk Onderzoek – Vlaanderen’, G0E1420N). MEC was funded by the National Science Foundation (DEB-1654609 and 2030509) and the CVM Research Office UMN Ag Experiment Station General Ag Research Funds. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Acknowledgments: This project was funded by the National Science Foundation Ecology of Infectious Diseases research program grants (DEB 1413925) and an Australian Research Council Discovery Project Grant (DP190102020). M.L.J.G. was supported by the Office of the Director, National Institutes of Health under award number NIH T32OD010993. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. SD is supported by the Fonds National de la Recherche Scientifique (FNRS, Belgium). GB acknowledges support from the Interne Fondsen KU Leuven / Internal Funds KU Leuven under grant agreement C14/18/094, and the Research Foundation – Flanders (‘Fonds voor Wetenschappelijk Onderzoek – Vlaanderen’, G0E1420N). MEC was funded by the National Science Foundation (DEB-1654609 and 2030509) and the CVM Research Office UMN Ag Experiment Station General Ag Research Funds. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
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