Staying ahead of pesticide resistance is crucial for maintaining effective pest management strategies. One major challenge is that pesticide resistance is often discovered after it has emerged. This means actions toward managing resistance are reactive, and don’t prevent the evolution of resistance in the first place.
Instead, a proactive approach would help reduce the rate of resistance evolving by identifying pests at greatest risk of developing resistance. This would help inform growers how best to target pests so as to minimise selection pressure on pests deemed ‘at risk’ of resistance evolution. Recent research has been working toward this goal through The Australian Grains Pest Innovation Program (AGPIP), an investment by GRDC and led in collaboration through the University of Melbourne and Cesar Australia.
Understanding the consequences of pesticide resistance
Australia, much like other regions worldwide, is experiencing a concerning escalation in the prevalence of pesticide-resistant insect species. Pests have an increased risk of resistance evolution when the “selection pressure,” is high. For example, when a pesticide is used at high rates or very frequently, it puts pressure on pests populations to evolve traits that allow them to survive pesticide exposure.
Three key questions for predicting resistance
To understand the risks of resistance evolution in different pests, we need to address three fundamental questions:
- How much selection pressure is being imposed on pest populations through pesticide usage?
- How does pesticide usage translate into resistance risk for specific pests?
- Where is the highest pesticide resistance risk?
However, obtaining accurate data to answer these key questions is challenging. This is largely due to the lack of available pesticide usage data in Australia. We need to be more creative if we want to get estimates of pesticide usage and translate this into risks of resistance evolution.
Measures of pesticide usage
AGPIP researchers Dr James Maino (Cesar Australia) and Dr Joshua Thia (The University of Melbourne) have tackled the issues of limited pesticide usage data in Australia through ‘data mining’. The idea is that other publicly available databases may contain information that is in some way related to pesticide usage in Australia. This may allow us to make a guess at how much pesticide is being used (the selection pressure).
Maino and Thia demonstrated that pesticide product registrations can be used to estimate pesticide usage. Pesticide product registrations are made publicly available by the APVMA (Australian Pesticides and Veterinary Medicines Authority). More highly registered pesticides were also found to be more frequently used in the field, as assessed through survey data obtained by Bayer Crop Science. Maino and Thia suggested that this link is driven by market demand and availability: as pesticides become more readily available and registered, they are more widely used. This may mean that pesticide product registrations might be a useful way to approximate the amount of selection pressure experienced by pests in Australia.
Assessing the risk of pesticide resistance
The next step in Thia and Maino’s work tested whether pesticide product registrations could be used to assess the risk of pesticide resistance evolution. Using a predictive modelling approach, Thia and Maino found that this expectation held true for arthropod pests in Australia. This may suggest that pesticide product registrations may in some way be associated with the relative selection pressure experienced by pests in the field.
Thia and Maino then extrapolated their predictive model to consider pests that are currently susceptible to pesticides. The logic was that pests with pesticide susceptibilities may be at risk of resistance if they also have a large number of pesticides registered against them. This provided an important step in translating the pesticide product registration (an estimate of selection pressure) into predictions for proactive management (by identifying risks).
Risk outputs: Identifying high-risk pests and chemical modes of action
Among a set of candidate pests and chemical modes of action, Thia and Maino identified some key concerns for Australian agriculture. The first was a high risk for diamondback moth for spinosyn resistance, and the second was a moderate risk for redlegged earth mites for neonicotinoid resistance.
Following the publication of Thia and Maino’s work, it became clear that spinosyn resistance in diamondback moth was indeed a real and growing issue. Reports from Western Australia have indicated potential sensitivity shifts to this chemical. Diamondback moths already have an arsenal of resistances in Australia, including organophosphate, pyrethroid, diamide and indoxacarb. Loss of spinosyn pesticides would further exacerbate the loss of chemical control options for this pest.
The moderate risk of neonicotinoid resistance in redlegged earth mites was also concerning. Neonicotinoid-based seed treatments are a widespread preventive control strategy in Australian canola. This undoubtedly places high selection pressure on redlegged earth mites, and Thia and Maino’s modelling work suggests strong consideration for alternate strategies that minimise overuse of this pesticide for redlegged earth mite control.
Progress, challenges, and the path forward
The next steps in this research involve curating the results into a publicly available platform to enhance accessibility for growers and agronomists. Additionally, there is the need to identify local risk factors to estimate resistance risks more accurately at specific locations.
Predicting pesticide resistance in agricultural arthropod pests is an exciting field with great potential. These risk predictions will play a crucial role in proactive resistance management and empowering growers and agronomists to make informed decisions. For example, through better planning of chemical rotations, use of recommended field rates, and alternate non-chemical control strategies. This will help safeguard agricultural productivity, mitigate resistance risk and keep growers’ pest control toolboxes fully stocked.
The research project and its associated publications were carried out by a team researchers including Joshua Thia, James Maino, Alicia Kelly, Ary A. Hoffman, and Paul A. Umina. The research is being undertaken as part of the Australian Grains Pest Innovation Program (AGPIP). AGPIP is a collaboration between the Pest & Environmental Adaptation Research Group at the University of Melbourne and Cesar Australia. The program is a co-investment by the Grains Research and Development Corporation (GRDC) and the University of Melbourne, together with in-kind contributions from all program partners.