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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