title: Development of a Compatible Taper Function and Stand-Level Merchantable Volume Model for Chinese Fir Plantations.
abstract: Chinese fir (Cunninghamia lanceolata [Lamb.] Hook) is one of the most important plantation tree species in China with good timber quality and fast growth. It covers an area of 8.54 million hectare, which corresponds to 21% of the total plantation area and 32% of total plantation volume in China. With the increasing market demand, an accurate estimation and prediction of merchantable volume at tree- and stand-level is becoming important for plantation owners. Although there are many studies on the total tree volume estimation from allometric models, these allometric models cannot predict tree- and stand-level merchantable volume at any merchantable height, and the stand-level merchantable volume model was not seen yet in Chinese fir plantations. This study aimed to develop (1) a compatible taper function for tree-level merchantable volume estimation, and (2) a stand-level merchantable volume model for Chinese fir plantations. This "taper function system" consisted in a taper function, a merchantable volume equation and a total tree volume equation. 46 Chinese fir trees were felled to develop the taper function in Shitai County, Anhui province, China. A second-order continuous autoregressive error structure corrected the inherent serial autocorrelation of different observations in one tree. The taper function and volume equations were fitted simultaneously after autocorrelation correction. The compatible taper function fitted well to our data and had very good performances in diameter and total tree volume prediction. The stand-level merchantable volume equation based on the ratio approach was developed using basal area, dominant height, quadratic mean diameter and top diameter (ranging from 0 to 30 cm) as independent variables. At last, a total stand-level volume table using stand basal area and dominant height as variables was proposed for local forest managers to simplify the stand volume estimation.
authors.affiliation: Chair of Forest Inventory and Remote Sensing, Georg-August-Universität Göttingen, Göttingen, Germany.
authors.forename: Xiaolu
authors.initials: X
authors.lastname: Tang
authors.affiliation: Chair of Forest Inventory and Remote Sensing, Georg-August-Universität Göttingen, Göttingen, Germany.
authors.forename: César
authors.initials: C
authors.lastname: Pérez-Cruzado
authors.affiliation: Chair of Forest Inventory and Remote Sensing, Georg-August-Universität Göttingen, Göttingen, Germany.
authors.forename: Lutz
authors.initials: L
authors.lastname: Fehrmann
authors.affiliation: Departamento de Ingeniería Agroforestal, Universidad de Santiago de Compostela, Lugo, Spain.
authors.forename: Juan Gabriel
authors.initials: JG
authors.lastname: Álvarez-González
authors.affiliation: Department of Forest Management and Statistics, Institute of Forest Resource Information techniques, Chinese Academy of Forestry, Beijing, PR of China.
authors.forename: Yuanchang
authors.initials: Y
authors.lastname: Lu
authors.affiliation: Chair of Forest Inventory and Remote Sensing, Georg-August-Universität Göttingen, Göttingen, Germany.
authors.forename: Christoph
authors.initials: C
authors.lastname: Kleinn
mesh_terms: D002681:China; D032486:Cunninghamia / Q000254:growth & development*; D016468:Forestry / Q000379:methods*; D008962:Models, Theoretical; D014197:Trees / Q000254:growth & development*