Appendix A. The environmental settings of the 59 plots on the Uncompahgre Plateau in western Colorado.

The environmental settings of the 59 plots on the Uncompahgre Plateau in western Colorado

Appendix B. The relationship between tree size class and age (years).

The relationship between tree size class and age (years)

Appendix C. Age-structure graphs for all 28 main, untreated (not mechanically cleared) woodland plots.

Age-structure graphs for all 28 main, untreated (not mechanically cleared) woodland plots

Response curves for <i>Pinus ponderosa</i> var. <i>ponderosa</i> and var. <i>scopulorum</i> in relation to key predictors.

<p>Single variable response curves estimating the probability of occurrence distributions for each ponderosa pine variety, using key predictor variables identified in the NPMR models.</p

Response curves for ponderosa pine haplotypes predicted by PRATIO.

<p>Single variable response curves estimating the probability of occurrence distributions for each haplotype (excluding haplotypes 9 and 10), predicted by the ratio of growing season precipitation to annual precipitation (PRATIO).</p

Reconstructed distribution of the potential climate niche for <i>P</i>. <i>p</i>. var. <i>ponderosa</i> (a) and var. <i>scopulorum</i> (b) during the last glacial maximum (~22,000 yr BP).

<p>Generalized contemporary distribution of ponderosa pine shown in thick gray lines.</p

Climate predictor variables used in nonparametric multiplicative regression (NPMR) analysis for ponderosa pine varieties and haplotypes.

<p>Climate predictor variables used in nonparametric multiplicative regression (NPMR) analysis for ponderosa pine varieties and haplotypes.</p

Relationship between seasonal temperature difference and precipitation balance defined for each ponderosa pine variety.

<p>Relationship between summer-winter mean temperature difference and summer-spring precipitation balance (ratio) derived from the ponderosa pine variety presence point locations (“x” symbols) and associated haplotype sampled locations (circles). A linear model and power model were fit to the 1961–1990 climate data associated with the <i>P</i>. <i>p</i>. var. <i>ponderosa</i> and var. <i>scopulorum</i> locations, respectively, to demonstrate the relative strength of these contrasting climate relationships. Three outlier locations were removed for var. <i>scopulorum</i> (Haplotype 2).</p

Mapped probability of occurrence predictions for ponderosa pine haplotypes.

<p>Probability of occurrence predictions derived from the NPMR models listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151811#pone.0151811.t002" target="_blank">Table 2</a> for each haplotype. Probability values are color-categorized using 10 equal-interval bins, with maximum probability values for each haplotype provided in the lower left of each map. Haplotypes 9 and 10 were not mapped due to small sample sizes and low Log<i>B</i> values. Point locations of sampled ponderosa pine haplotypes are shown in smaller maps. Generalized (green outline) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151811#pone.0151811.ref003" target="_blank">3</a>] and recently classified (gray shading) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151811#pone.0151811.ref044" target="_blank">44</a>] distributions of ponderosa pine are shown for context in each map.</p

Distribution of ponderosa pine in the western United States based on a recent, fine-scale analysis and classification available from the National Individual Tree Species Atlas (2015) [44] compared to a generalized mapped distribution by Little (1971) [3].

<p>Distribution of ponderosa pine in the western United States based on a recent, fine-scale analysis and classification available from the National Individual Tree Species Atlas (2015) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151811#pone.0151811.ref044" target="_blank">44</a>] compared to a generalized mapped distribution by Little (1971) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151811#pone.0151811.ref003" target="_blank">3</a>].</p