Estimated scaling exponent of Eq. 2 by EEMT.

<p>Least-squares regression by EEMT (MJ m^-2 yr^-1) [on the x-axis] versus the estimated scaling exponent ± 95% <i>ci</i> for diameter to height proportionality [Eq. 3, on the y-axis] (vertical black lines). There was no significant difference between the first four EEMT groups. There was a trend of declining as EEMT increased.</p

Study Area locations and plot design.

<p>(A) Location of the three study areas, (B) Surface models showing topographic variability and plot location, and (C) sampling plot layouts. Shaded relief in left panel via US Geological Survey, The National Map.</p

Location, climate, geology, and generalized forest types (Ponderosa Pine = PP, Mixed-Conifer = MC, White-fir dominated = WF, Spruce and Fir = SF, and Aspen Disclimax = AD) of the three study areas (see S2 File for a cross-walk of forest type descriptions).

<p>Weather data are from the Western Regional Climate Center [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157582#pone.0157582.ref004" target="_blank">4</a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157582#pone.0157582.ref005" target="_blank">5</a>] and Liu et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157582#pone.0157582.ref046" target="_blank">46</a>]; forest type details are given the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157582#pone.0157582.s002" target="_blank">S2 File</a>.</p

Scaling exponent values for Eq. 4 by tree condition classes.

<p>Least-squares regression of , estimated scaling exponent ± the 95% <i>ci</i> [Eq. 2, on the y-axis] (vertical black lines) tree condition [on the x-axis]. Trees with the most vigorous growth forms resulted in power law models with scaling exponents slightly above and not significantly different from the MST predicted 2/3 scaling (horizontal dashed black line). Trees in lower condition classes were significantly below MST-predicted scaling, as was the average of all trees.</p

Least squares regressions of age, bole diameter, and height for dated trees from the Pinaleño (n = 368).

<p>(A) For diameter to height the correlation is fairly strong (r² = 0.652); (B) diameter to age have a very weak correlation (r² = 0.274) with wide heteroscedasticity; (C) similarly height has almost no correlation with increasing age (r² = 0.152).</p

Estimated scaling exponent for Eq. 4 based increasing on tree age.

<p>The estimated scaling exponent ± 95% <i>ci</i> for diameter to height proportionality [Eq. 3, on the y-axis] of tree age. As trees increased in age there was a general decline in the estimated value for the proportionate scaling of , though the difference was not significant at the 95% <i>ci</i> (vertical black lines).</p

Qualitative tree condition categories with least-squares regression: (Eq. 4); these models do not differentiate between species or location.

<p>The is graphically shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157582#pone.0157582.g002" target="_blank">Fig 2</a>; ** denotes significantly greater than α_1r at 95% <i>ci</i>; * denotes significantly less than α_1r at 95% <i>ci</i>.</p

Demographics registered users’ research area (A), occupation (B), and genders (C).

Demographics registered users’ research area (A), occupation (B), and genders (C).</p

Publications.

Peer-reviewed research citing the use of resources from the iPlant Collaborative (2008–2017) and CyVerse (2017-Present). Also see https://cyverse.org/publications for the latest update. (PDF)</p

Glossary.

Frequently used abbreviations and acronyms with descriptions. (PDF)</p