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. 2019 Sep 3;10:1060. doi: 10.3389/fpls.2019.01060

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Copyright © 2019 Li, Zhang and Fang

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Biplot from redundancy analysis (RDA) showing the association of genetic variation at the 14 nuclear microsatellite (nSSR) loci with geographic and climatic variables. Small red crosses at the center represent the 177 allelic variables. Eight eigenvectors corresponding to positive eigenvalues of the principal coordinates of neighbor matrix (PCNM) were used as geographic variables. Eight climatic variables include elevation, annual mean temperature (bio1), mean diurnal temperature range (bio2), temperature seasonality (bio4), mean temperature of driest quarter (bio9), annual precipitation (bio12), precipitation seasonality (bio15), and precipitation of warmest quarter (bio18). Orange and gray dots indicate individuals from highlands and lowlands, respectively. The proportion of total genetic variation explained by each axis is shown in parentheses.