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. 2020 Jun 22;8(6):940. doi: 10.3390/microorganisms8060940

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© 2020 by the authors.

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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Correlation coefficients between forest environmental factors and genetic parallelism or phenotype. Posterior parameter estimates from Bayesian generalized linear hurdle Poisson models of parallel SVs in response to Jaccard’s distance of environmental factors (a). Posterior parameter estimates from a generalized linear model with a Bernoulli distribution (logit link function) of Jaccard’s distance between environmental conditions associated with NWT phenotype (b). Jaccard distance of environmental variables are calculated as the difference between Monterey Co. and Sonoma Co. First model (top panels) includes minimum temperature of the coldest month (bio 6), precipitation of the coldest quarter (bio19), N. densiflorus and U. californica stem density (LIDE.UMCA), precipitation during Spring (Springppt), Elevation, and a hurdle probability (hu). Second model (bottom panels) includes the same parameters, except solar radiation during August (sun radiation Aug) replaces minimum temperature during the coldest month. Bayes factor comparing both models was not significant (1.66).