The Myrtle Rust Risk Prediction platform is here! A massive inter-agency effort has resulted in the first digital tool that allows for the prediction of myrtle rust risk on a site-by-site basis.
This platform is freely available to all—tangata whenua, the nursery industry, conservation groups, myrtle rust researchers and the public—to help determine the risk for myrtle rust based on local weather conditions.
The model was built using all available knowledge about the ideal climate conditions for myrtle rust. For example, research has shown that cool temperatures and high altitude extends myrtle rust’s “latent period”, the time between infection of a host plant and the production of new spores.
This means that in cooler parts of the country, myrtle rust remains inactive within host plants over the winter. However, in warmer areas, the infection cycle may continue through winter, increasing the spore load in the environment and increasing the risk of damage to host plants come spring.
Pinpointing when latency ends and activity begins has helped fine-tune regional understanding of differences in myrtle rust risk.
The Myrtle Rust Risk Prediction platform, launched in early October, provides open access to the information generated by these climate risk models.
The platform also includes convenient access to the NIWA myrtle rust risk maps, which give a broader national overview of risk regions.
Stakeholders will be able to determine for themselves when and where to expect myrtle rust. This will empower end users to make adjustments to their management activities, whether through surveillance, access restriction in infected areas, or application of preventative treatments.
Funding for the development of the Myrtle Rust Risk Prediction platform was provided by Ngā Rākau Taketake (NRT) and data used to inform the model were obtained from the MBIE Beyond Myrtle Rust (BMR) programme and from myrtle rust research funded by Biosecurity New Zealand (MPI). Continued upkeep, maintenance and free access is funded by NRT and BMR. Models and weather information are provided by Plant & Food Research, NIWA and HortPlus. The platform is designed, built and maintained by HortPlus.