Needle Disease/Phytophthora

Red Needle Cast Overview

Conference Presenter: Mike Baker, Hancock Forest Management Ltd

Mike Baker describes the problems being caused by red needle cast and introduces the research programme.

Presentation:  09 Red Needle Cast Overview

Management of Red Needle Cast: Latest research on epidemiology and control

Conference Presenter: Stuart Fraser – Scion

Red needle cast (RNC) is now a widespread needle disease in New Zealand. It is caused by a fungal-like organism, Phytophora pluvialis,. Growth losses of up to 40% have been recorded after a disease impact, however it has been shown that trees recover and recurrence appear to be rare.

Control of RNC using copper: update

Researchers are working to develop a cost-effective aerial spray treatment for RNC. Understanding the life-cycle (epidemiology) of the disease is an essential precursor to chemical control in order to know the best time of chemical intervention.

Long-term monitoring of 50 forest sites in the North Island confirms that the disease generally expresses in winter; also spore release peaks towards the end of winter. There is variation between years, regions and sites, however, so RNC is a challenging disease to work with.

From a long-list of eleven possible RNC control chemicals, a series of trials confirmed that copper has most potential. Copper is well-known to the industry, as it is already used in Dothistroma control programmes.

Small-scale field trials using copper on RNC are underway in Kinleith Forest, thanks to collaboration with Hancock Forest Management. Operational copper sprays in February significantly reduced RNC severity and needle cast over the following winter.

Work has begun on a model to assess the costs and benefits of spray treatment, and this will be refined as more data becomes available, including on the longer-term growth impacts of RNC.  Decision support tools for growers who face the threat of RNC are not too far away.

Presentation:  10 Management of Red Needle Cast

Breeding for Disease Resistance. 

Conference Presenter:  Natalie Graham, Scion

Breeding trees with long-term and multiple disease resistance is a key aim of the Healthy Trees, Healthy Future programme.

Two well-established needle diseases – Dothistroma needle blight (DNB) and Cyclaneusma needle cast (CNC) – are together estimated to cost the NZ forest industry around $48 million annually in lost growth and spraying costs. Red needle cast (RNC) is now the third needle disease impacting seriously on radiata pine growth. Scion’s tree breeders aim to develop new radiata pine genotypes which are resistant to all three of these diseases.

Breeding for RNC resistance: update

Elite 2013/14 clones from the Radiata Pine Breeding Company (already selected for DNB and CNC resistance) are being used for the RNC breeding programme. Some 400 individuals from 63 families were inoculated with RNC and grown on in a fog chamber (emulating the type of conditions favouring the disease). The trees were then screened for RNC resistance.  The best 48 clones went out in a mini field trial in Kinleith Forest, and have been subjected to rigorous monitoring and foliage sampling. Researchers are using sophisticated techniques to better understand how RNC pathogens operate and interact with their host. Research at gene level will identify which host genes make for resistance to RNC; information which can then be used in future breeding and genomics programmes to develop genotypes with RNC resistance.

Red needle cast rankings

An early outcome is that provisional RNC resistance rankings now exist for RPBC’s clones. The best-ranked clones can be used for RPBCs crossing programmes once pollen becomes available, providing growers with early planting material likely to have enhanced RNC resistance.

Presentation:  11 Breeding for Disease Resistance

Remote Sensing and Red Needle Cast 

Conference Presenter:  Grant Pearse, Scion

Scion’s Geoinformatics team continue to work across a range of research programmes, including tree health and tree breeding.

Sentinel 2 imagery: update

The European Space Agency’s Sentinel 2 satellite has been identified as an excellent source of satellite imagery for forest management. The data is freely available at 10-metre resolution, has a 5-day revisit period, and high spectral resolution. It is therefore ideal for continuous monitoring of forests, for example identifying changes in canopy cover or colour over time. Major research effort continues into how to automate data capture and delivery in a form that is useful and can be used routinely by forest managers.

Detecting red needle cast using Sentinel 2 data has been achieved, although with only three years’ worth of data, it is still early days. Scientists can now identify the specific temporal colour changes that signify RNC, and have been able to monitor changes over consecutive seasons as the disease builds up, needles are cast, and then the trees recover.  This type of monitoring will greatly increase understanding of how the disease behaves at forest level over time.

Other aerial imagery

Research into using and interpreting UAV and LiDAR imagery to compliment Sentinel 2 images continues – UAV imagery is useful for fine-scale detection and mapping, even down to individual tree level. Use of oblique UAV imagery is also being explored, as this captures information in three dimensions such as relative tree heights and stem characteristics.

In addition, the Scion team has also been involved with using aerial imagery to monitor the trials to test copper as a way of controlling RNC.  The information gathered will be used in a new decision-support model currently being developed (see following section) to assist forest managers with decisions around RNC control.

Presentation:  12 Satellite RNC Monitoring

Red Needle Cast modelling for risk prediction and decision making

Conference Presenter:  Ralf Gommers, Scion

A powerful new model to assist forest managers faced with the threat of red needle cast (RNC) is at prototype stage.

The model is utilising the vast amount of existing data about RNC. This includes disease reports, lab and field trial data, and remote sensing data. By combining forestry-based data with other data sets – for example climate and site data – scientists have built a spatial model capable of predicting the risk of RNC outbreaks and severity in any given forest, and assisting with decisions on the cost-benefit of spraying trees.

For example, by combining climate data with 10 years’ of disease reports, it has been possible to quantify how location and climate impact on RNC incidence; similarly, by analysing data from breeding trials, the impact of genotype on susceptibility to RNC has been ranked.

The many different analyses have been combined in an integrated model which can now test scenarios for spraying decisions in forests in different locations. The model has the capacity to run forward in time and see the effect of adding one or two copper sprays with a given dose in a season.

Timeframe for model deployment

The timeframe for further development and launch of the model is as follows:

  1. Deploy for use within Scion (end-2018)
  2. Beta-testing with industry (mid-2019)
  3. Make accessible to industry (currently scoping options)
  4. Integrate more trials, forest growth models, cost-benefit analyses and disease impacts.

Presentation:  13 Disease Modelling