The Productivity and Wood Quality workstream focuses on realising the full potential of radiata pine using a whole-systems approach.
Our research is integrated with other research areas within the Resilient Forests programme by also contributing to investigations of the influence of genetic diversification and higher stand densities on disease risk, the impact of shorter rotations on market and wood quality risk, and the relationship between forest management and the microbiome.

Our aim is to enhance the productivity and wood quality of New Zealand’s radiata pine forests to provide greater resilience under future uncertainty. We want to answer these questions:

  • What is the impact of Genetics x Environment x Silviculture on growth and wood properties?
  • What does radiata pine’s microbiome look like and what role do the different organisms play?
  • How do we leverage maximum benefit from previous investment in trials?
  • What does resilient silviculture look like in practice?

In 2024-26 work under the Productivity and Wood Quality research area will:

  • quantify the extent and drivers of wood properties variation and their impacts on end-product performance
  • develop a spatially-explicit individual-tree growth simulator based on remote sensing phenotyping methods
  • examine plant-soil-microbial processes using an expanded microbiome platform
  • ensure ongoing data collection from key long-term research experiments, focused on enhancing wood quality and productivity.

The ultimate outputs of this research area will be:

  • quantitative information on the patterns of variation in wood properties within radiata pine and the implications of these patterns for end-product performance
  • new strategies to manage wood properties variation to improve outcomes for plantation grown timber
  • methods to delineate and characterise key attributes of individual trees from LiDAR data
  • new opportunities to manage forest productivity and resilience to abiotic and biotic threats through management of the microbiome.

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