What diameter?What height?Influence of measures of average tree size on area-based allometric volume relationshipsOACSTPCD
Volume is an important attribute used in many forest management decisions.Data from 83 fixed-area plots located in central New Brunswick,Canada,are used to examine how different measures of stand-level diameter and height influence volume prediction using a stand-level variant of Honer''s(1967)volume equation.When density was included in the models(Volume=f(Diameter,Height,Density))choice of diameter measure was more important than choice of height measure.When density was not included(Volume=f(Diameter,Height)),the opposite was true.For models with density included,moment-based estimators of stand diameter and height performed better than all other measures.For models without density,largest tree estimators of stand diameter and height performed better than other measures.The overall best equation used quadratic mean diameter,Lorey''s height,and density(root mean square error=5.26 m^3·ha^(-1);1.9%relative error).The best equation without density used mean diameter of the largest trees needed to calculate a stand density index of 400 and the mean height of the tallest 400 trees per ha(root mean square error=32.08 m^(3)·ha^(-1);11.8%relative error).The results of this study have some important implications for height subsampling and LiDAR-derived forest inventory analyses.
Yilin Wang;John A.Kershaw;Mark J.Ducey;Yuan Sun;James B.McCarter;
Integrated Forest Mensuration and Systems Analysis Laboratory,Faculty of Forestry and Environmental Management,University of New Brunswick,Fredericton,NB,CanadaDepartment of Natural Resources and the Environment,University of New Hampshire,Durham,NH,USACollege of Forestry,Nanjing Forestry University,Nanjing,210037,ChinaScientific Programmer,Rayonier,Yulee,FL,USA
林学
Allometric relationshipsStand structureVolume estimationStand-level attributes
《Forest Ecosystems》 2024 (001)
P.100-109 / 10
the Natural Sciences and Engineering Research Council of Canada(Discovery Grant RGPIN-2023-05879);the New Brunswick Innovation Foundation(Emerging Projects Grant EP-0000000033)。
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