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Title of Journal: Ann Bot

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Abbravation: Annals of Botany

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Narnia

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DOI

10.1007/bf00144232

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0305-7364

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Crossvalidation of Nonlinear Growth Functions fo

Authors: ZHANG LIANJUN
Publish Date: 1997/03/01
Volume: 79, Issue: 3, Pages: 251-257
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Abstract

Six nonlinear growth functions were fitted to tree height–diameter data of ten conifer species collected in the inland Northwest of the United States The data sets represented a wide range of tree sizes especially largesized trees According to the model statistics the six growth functions fitted the data equally well but resulted in different asymptote estimates The model prediction performance was evaluated using Monte Carlo crossvalidation or data splitting for 25cm diameter classes All six growth functions yielded similar mean prediction errors for small and middlesized trees For largesized trees eg DBH diameter at breast height100 cm however five of the six growth functions except the Gompertz function overestimated tree heights for western white pine western larch Douglasfir subalpine fir and ponderosa pine but underestimated tree heights for western hemlock and Engelmann spruce Among these five functions the Korf/Lundqvist and Exponential functions produced larger overestimations The Schnute Weibull and Richards functions were superior in prediction performance to others The Gompertz function seemed always to underestimate tree heights for largesized trees

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