By Alyssa Speiran, OMAFRA Horticulture Research Assistant
Did you know that insects can’t regulate their own body temperature? For an insect to grow and thrive, it must be under its own favourable conditions. That is where degree day modeling comes in.
A degree day is a period of 24 hours where the temperature remains within a lower and upper threshold for development (Figure 1). Individual insect species have varying thresholds, which is why insects will emerge and grow at different times. A common lower threshold for an insect is 10oC, while the common upper threshold is 35oC.
Consider bees: they emerge in spring and summer when it’s warm, meaning they have a higher threshold. On the other hand, mosquitos typically come out during summer nights when it cools down, which means they have a lower threshold.
Why Use Degree Day Models?
Degree day models depend on an insect’s growth being closely related to the temperature of where it’s found. These models are created to establish key timings in an insect’s development and predict important events such as egg hatch, crawler emergence or first flight.
It can be extremely difficult to observe some of these life stages in the field due to the size of these insects as well as labour it would take to monitor. For that reason, degree day models are key as they can be used as a tool for scouting or management. Critical life stages can also be very short lived, so timing is crucial. For instance, codling moth larvae can enter developing fruit within 24 hours after hatch.
Timing needs to be precise to target these critical life stages, especially with the movement toward reduced-risk insecticides with a limited application window. In summary, degree day models are a very useful tool in monitoring the life stages of an insect.
Benefits of Using Degree Day Models
The benefit of using degree day models is that they are useful in predicting and monitoring insect development to precisely time critical life events. The number of degree days for each pest with vary in different areas depending on temperature, moisture, and climate. Therefore, it’s important to look at weather data in each area annually to determine pest activity.
A biological fix point, or more commonly known as a biofix, is an event that is easily observed. An example of this is the first capture of a moth in a delta trap. The information gathered from these models can then be used to determine spray timings for targeted life stages.
Degree Day Models for Hard to Monitor Pests
Two examples of degree day models OMAFRA used this season for pest prediction were the Max/Min Method for both San Jose scale (SJS) and apple leafcurling midge (ALCM). The Max/Min Method uses the following formula for calculating degree day Celsius (DDC).
DDC = [(daily min. temperature + daily max. temperature) / 2] – min. base temperature
As pictured in Figure 2, double sided tape can be used to monitor for SJS crawlers. Degree day models signify when the double-sided tape can be applied to the trees. However, this method can be difficult to observe due to the very small size of the crawlers. Using a degree day model instead with a biofix of March 1st or based off first adult flight can help predict this critical crawler emergence period.
Delta traps with a pheromone lure can be used for a number of orchard pests, including ALCM. Each week, OMAFRA summer students would collect these liners from two orchards in Simcoe. As a result of high ALCM pressure, the liners tended to be consistently full of ALCM (Figure 3) and difficult to accurately predict trends. ALCM eggs are found tucked into the newest unfurled leaves of a growing terminal and can be difficult to detect with the untrained (or unmagnified) eye. However, targeting management for larvae once leaf curling has actually been observed often provides ineffective control. Degree day models are useful in this instance because they provide the predicted date for when egg laying and larval emergence occurs.
Predicted Dates of Emergence (2022)
The starting date (biofix) for each model was March 1st, 2022. These models used minimum base temperatures of 9°C and 10°C for ALCM and SJS, respectively. Degree days were accumulated in all 5 growing districts in the province, including stations in Harrow, London, Delhi, Grimsby, Clarksburg, and Oshawa (Table 1 and 2).
In addition, three apple orchards local to Simcoe used first generation SJS flight as a biofix, meaning that degree day accumulation began the first day the pest was caught using a pheromone trap. Past weather data for each location was used, along with 14-day forecasts that were updated regularly.
Table 1. Predicted dates of San Jose Scale crawler emergence in different regions across Ontario (March 1st, base 10°C)
1st Generation (278 DDC)
2nd Generation (806 DDC)
Table 2. Predicted dates of Apple Leafcurling Midge adult emergence in different regions across Ontario (March 1st, base 9°C)
1st Generation (132 DDC)1
2nd Generation (556 DDC)
3rd Generation (1160 DDC)
Insect species can have distinct generations, meaning that once the accumulated number reaches a certain point, it signifies a new generation. For SJS, the 1st generation key DDC timing is 278, while the 2nd generation key DDC timing is 806. The way that degree day models can identify spray timings are using these accumulated numbers.
- For example, insecticides effective against SJS such as Sivanto Prime or Closer should be applied at or around predicted crawler emergence (278 DDC and 806 DDC) whereas Movento should be applied just ahead of activity.
- Appropriate timings for ALCM are still being determined as this model was only recently developed. Currently, applying effective insecticides at peak adult emergence and egg laying per generation look to be the most efficacious.
Degree day timings have been determined for a number of other orchard pests such as oriental fruit moth. Similar to SJS and ALCM, it is important to consider control product when determining appropriate spray timing. For instance, Group 5 and 28 insecticides have an ideal timing of 805-833 DDC for the 2nd generation, and 1361-1389 DDC for the 3rd generation, whereas products belonging to Group 4 are best applied slightly earlier as 750-778 DDC and 1205-1333 for 2nd and 3rd generation, respectively.
It’s important to continue monitoring for pests using degree day models, where developed and visual observations. This is because the information gathered is crucial in determining and implementing appropriate timing for control strategies, making for more precise management and potential reduction in pesticide use.
Jones, V. & Brunner, J. (1993). Degree Day Models. WSU Tree Fruit. Retrieved from http://treefruit.wsu.edu/crop-protection/opm/dd-models/
Ontario Ministry of Agriculture, Food and Rural Affairs. (2009). Integrated Pest Management for Apples. Publication 310.
University of California Agriculture and Natural Resources [Photo]. (2016, June 21). Degree-days. Retrieved from http://ipm.ucanr.edu/WEATHER/ddconcepts.html
Wisconsin Vegetable Entomology. Degree-day modeling. Retrieved from https://vegento.russell.wisc.edu/ipm/degree-day-modeling/