Track Policies

Understanding and evaluating uncertainties in models predicting future growth, yield and wood properties

Presentations and posters dealing with all aspects of uncertainty relating to model predictions.  This could include uncertainties relating from error (e.g. sampling error, or model errors), changing future conditions (e.g. a range of possible increases in temperature) or uncertainties arising due to "unpredictable" events such as insect attacks or fire.

Directors
  • David Drew, Stellenbosch University
Checked Open Submissions Checked Peer Reviewed

The nexus between models of tree growth, wood formation and product properties

Papers and posters exploring all approaches to predicting variability in wood properties in forest trees, ranging from tree-level (e.g. effects on form), branching models through to detailed, cell-level models of wood formation.  Research that explores linkages between models of growth and wood properties is of particular interest.

Directors
  • David Drew, Stellenbosch University
Checked Open Submissions Checked Peer Reviewed

Model application, integration and accessibility for forest management, planning and product development

Presentations and posters looking at how forest growth and wood properties models can be integrated, and applied to real forest management and wood product development problems, through software tools, for example.  Presentations that explore approaches to making modelling research accessible to resource managers will be of particular interest.  Also, research looking at model accessibility for small growers in applicable regions is very welcome.

Directors
  • David Drew, Stellenbosch University
Checked Open Submissions Checked Peer Reviewed

The cutting edge in forest measurements and models

Presentations and posters looking at novel approaches that are being taken both empirically, e.g. using new statistical techniques or developments, as well as mechanistically, e.g. new process-based frameworks.  Work that looks at new ways ogenerating data to support models, or cutting edge plant physiological or mathematical research into model approaches, including insights from other fields, will be of particular interest.  For example, the use of machine learning or artificial intelligence approaches as a new frontier in self-evolving models.

Directors
  • David Drew, Stellenbosch University
Checked Open Submissions Checked Peer Reviewed

General poster session

For papers submitted as posters

Checked Open Submissions Checked Peer Reviewed


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