Among the input variables, vegetation type explained the largest proportion (11.29%) of the variation, followed by bulk density (BD), soil organic carbon, and BD and vegetation type interactions.
In this study, most traits were affected by additive, dominance and imprinting effects with additive effects explaining most of the variation, followed by dominance and imprinting effects.
For this model, power coefficient variation follows the similar trend for all Reynolds number, increasing from 0° to 60° and then decreasing up to 120° then repeats from 120° to 230° and from 240° to 330°.
This commonly used hierarchical model effectively assumes that the between-sample variation follows a gamma distribution while the sequencing process leads to a Poisson distribution.
The seasonal variation follows the TGD's seasonal impounding and releasing of water.
Finally, summer precipitation variation follows the general trends observed for winter and spring, however, exhibiting wider seasonal variation range.
Figure 3 shows an example of a color scheme, in which the color variation follows a linear scale.
A more sophisticated model assumes the within-specimen (technical) variation follows a Poisson distribution and the between-specimen mean values follow a gamma distribution.
Although morphologically indistinguishable, except by detailed multivariate analysis (Nevo 1985; Nevo, Tchernov, et al. 1988), size variation follows as: 2 n = 52 (54)→58→60 (Nevo, Beiles, et al. 1986).
