Incorporation of indices of annual climatic variation into growth models for Pinus radiata

Citation
P. Snowdon et al., Incorporation of indices of annual climatic variation into growth models for Pinus radiata, FOREST ECOL, 117(1-3), 1999, pp. 187-197
Citations number
36
Categorie Soggetti
Plant Sciences
Journal title
FOREST ECOLOGY AND MANAGEMENT
ISSN journal
03781127 → ACNP
Volume
117
Issue
1-3
Year of publication
1999
Pages
187 - 197
Database
ISI
SICI code
0378-1127(19990517)117:1-3<187:IOIOAC>2.0.ZU;2-8
Abstract
Data for Pinus radiata D. Don grown in the Australian Capital Territory (AC T) are used to show that annual indices of growth potential can be successf ully incorporated into Schumacher projection models of stand basal area gro wth. Significant reductions in the error mean squares of the models can be obtained by including a simple index such as annual rainfall, but best resu lts were obtained by incorporating estimates of photosynthesis simulated wi th a detailed process-based model: BIOMASS. In the ACT it was sufficient to estimate the growth index at a single location within the forest estate. R eductions in error mean squares due to the incorporation of temporal variab les were about twice as large as those obtained by incorporating spatial va riables such as geological substrate, site index or indices of soil develop ment. The gains due to the two classes of variables were approximately addi tive. The new models improve the descriptive power of the Schumacher model. Short-term predictions made with the models should be more accurate than t hose obtained with the traditional model and should be particularly useful for updating stand inventories. The new models would be most applicable to regions where there is substantial variation in climatic factors between gr owing seasons and where the object species is responsive to those factors. A key result is that the temporal variation in the growth indices need not be assessed at each sample plot used to calibrate the model nor each invent ory plot to which the model is applied. The temporal variation is regional in nature; consequently, it can be characterised by studies at a relatively few number of sites. This leads the way to new avenues for forest modellin g. (C) 1999 CSIRO Published by Elsevier Science B.V. All rights reserved.