Australian plantation forest managers face considerable and increasing challenges to maintain and develop their forest growth and yield planning systems. While increasing precision and detail on the current and future attributes of their plantation resource is required, there is ever increasing opportunity and complexity in using new data sources that are becoming available, especially from sensors (satellite, airborne or ground-based) and process-based modelling. Increased complexity in modern systems development requires specialist skills not usually available in forest companies. Because of these trends, existing industry growth and yield systems are a mix of old technologies and more modern additions, with their functionality constrained by legacy designs and limited capabilities.
This project offered the potential for growers to design and experience elements of a modern system akin to that available to grain growers and other agricultural sectors. This system would for the foreseeable future augment, rather than replace, existing growth and yield forecasting systems by incorporating process-based modelling capabilities and data from sensors. The project also aimed to evaluate cooperative business models that could develop and sustain delivery of these advanced technical services to the forest plantation industry.
Process-based modelling here refers to modelling that includes specific mathematical representation of ecosystem processes that lead to wood production, e.g. the use of light, water and nitrogen for carbon fixation.
The APSIM modelling framework was chosen as the process-based modelling framework for this project, because it is well-established in the agricultural sector nationally and internationally for research and commercial uses. APSIM simulates plant growth at the plot scale, and prior to this project it had been calibrated for Eucalyptus grandis plantations and related tropical and sub-tropical genotypes. During the project, model development added genotypes required for temperate eucalypt plantations in Australia (E. globulus and E. nitens) and pines in tropical-to-temperate regions (Pinus radiata, P. elliottii, P. caribaea, and hybrids). These models not only use climate variables as inputs, but also management variables of initial stocking, thinning, mortality, weeds, nitrogen fertilisation and irrigation.
The project demonstrated elements of a proposed workflow for merging remotely sensed data with process-based modelling and current inventory and empirical modelling.
Project number: VNC519-1920
