Presented by David Drew, CSIRO, Wednesday 9 October, 2013.
This webinar will be presenting a new prototype model (e-Cambium) that uses information about site, management regime and daily weather data to predict variation in wood density and stiffness as well as stem radial growth. It can be operated at varied levels of detail (potentially linking to the CaBala model if desired), depending on how much site information is available. The model performed well in initial calibration and validation studies, predicting 80% of the variation in mean wood density of samples taken from 16 varied sites in Australia and New Zealand using a single parameter set.
Simulations can be performed at multiple positions in the tree, making it possible to reconstruct wood properties in 3 dimensions within one or more logs. The tool also provides a basic overview of expected board grades, based on calibrations obtained in previous FWPA studies. Although the prototype software offers relatively basic functionality, a range of customization options are envisaged in future Developments. The tool is expected to be of use in understanding broad-scale resource quality variability, as well as assessing the potential wood quality implications of changes in management regimes or under hypothetical future climate scenarios.
Presenter:
Dr David Drew is employed as a research scientist in the Forest Systems research group at CSIRO, based in Hobart, Tasmania. He has been involved in wood quality research for more than 13 years, initially working closely with the forestry industry in South Africa, and then, since 2005, in Australia. He completed a PhD on wood properties modeling in 2008, before taking a postdoctoral fellowship at CSIRO, working with Dr Geoff Downes, focused on understanding the dynamics of annual growth in diverse forest species. He was appointed to his current role in 2011, in which he is involved in research on forest growth, carbon sequestration and wood quality variability in a range of forest types and species.
View report for project PNC196-1011 here.
