A Taper Equation for Loblolly Pine Using Penalized Spline Regression

Abstract Stem profile needs to be modeled with an accurate taper equation produce reliable tree volume assessments. We propose a semiparametric method where few priori functional form assumptions or parametric specification are required. compared the diameter and predictions of penalized spline regression (P-spline), P-spline extended additive dbh-class variable, six alternative equations including single, segmented, variable-exponent forms. used data from 147 loblolly pine (Pinus taeda L.) trees fit models make comparisons. Here we show that outperforms when predict outside bark in lower portion stem, up 40% height more valuable wood products (62% total volume) located. For volume, both perform equal better than best model, calibration, which could result possible savings on inventory costs by not requiring additional measurement. Our findings suggest assuming fixed imposes restrictions fail explain adequately proposed P-spline.