Degrees of freedom

Are you tired of constant sampling? By helping you predict when insects will occur, degree-day monitoring will set you free.

As the Environmental Protection Agency (EPA) interprets and enacts the Food Quality Protection Act (FQPA), new regulations are restricting insecticide products and their usage. FQPA review is rapidly removing traditional, broad-spectrum and long-residual insecticides from turf and ornamental use. New chemistries are being developed with target specificity that demand accurate control timing. More than ever, you need to better time your applications to control common landscape pests.

Visual inspection and regular sampling are the best monitoring tools for determining pest presence and susceptibility to control. However, most management firms do not have clients who are willing to pay extra for such sampling. As a result, degree-day models and plant phenological indicators (biological events in plants that are determined, in some degree, by climatic conditions) have been proposed as alternative methods to predict insect and mite development. These methods have been proven to be excellent predictors for an array of ornamental and turf pests.

Degree-day modeling In academic terms, degree-day (DD) models are actually called "weather-mediated, predictive development models." They are developed by monitoring weather parameters, usually temperature (degree-days), and comparing them to insect development. Though these models can help determine when an insect should be susceptible to controls, they still do not answer the question of whether the pests are present or causing damage.

Degree-day models are published for a variety of ornamental and turf insect pests. However, models that are published in scientific literature may not be easy to use in the field. This is because many researchers attempt to determine the most precise temperature (called the base temperature or lower threshold) that corresponds to the development of each insect. Using these models may be the most accurate for a certain species, but its use by turf and ornamental managers can be time-consuming. Using a standard base temperature for all insects may cause you to miss your prediction by a day or two. However, in most cases, this is close enough to achieve adequate control of pests in your landscape.

Geographic location may also affect developmental rates. Therefore, you should keep local records of temperature and pest activity to better calibrate the published DD targets for your location.

Calculating degree-days to manage your landscape pests Animals (including insects) that cannot regulate their internal temperatures (often called "cold-blooded") depend on air and soil temperature. It determines their metabolism and rate of development. If this rate of development is determined, insect (and even plant) development can be predicted. Degree-days are simply a method of counting the heat units needed for an insect to reach a certain developmental stage.

Fortunately, most insects develop within a specific range of temperatures. If the temperature drops below a certain point (the lower threshold), insect development ceases. Above this lower threshold, the rate of development increases as the temperature increases. There is also an upper threshold temperature at which development begins to decline because of excessive heat. In nature, insects evolve in habitats where the lower threshold temperature is exceeded for a sufficient amount of time to complete their development. However, they rarely exist in locations where temperatures consistently exceed the upper threshold.

Several field crops and ornamental plants grow outside their native habitats. Corn plants shut down their development above 86F, but they grow where summer temperatures consistently exceed this. Unfortunately, most state crop reporting services base their DD models on corn DDs that have a relatively low upper threshold (86F) compared to insects (100 to 110F). Therefore, these models have limited applicability to turf and ornamental pests.

Several lower thresholds are common to many insects. Most soil-dwelling insects have lower thresholds of 40 to 45F, while many aboveground feeding insects (turfgrass surface feeders and most tree and shrub foliar pests) have a lower threshold of 50F. For most practical modeling, use a base temperature or lower threshold of 50F degree-days (DD50). It is considered satisfactory for most purposes.

Methods for calculating degree-days - Average temperature method. This is the easiest method to use (see the table below). You need nothing more than the daily highs and lows, the lower threshold that is applicable to your pest and the number of days. To use this method, calculate degree-day units for each day by subtracting the average daily temperature from the lower threshold. For example, using the graph to the left, for the first day (0 to 24), you would add the daily high temperature and the daily low temperature and divide this number by two to get the average daily temperature. Next, subtract the lower threshold temperature you are using (50F in this case) from the average daily temperature. The number you get is the DD units for day 1. Note that if your average daily temperature is at or below the lower threshold temperature, your DD units for that day are 0 - never use a negative number for degree-days. This means that no insect development that may have occurred during that day is counted. The table below illustrates the calculations for the 4 days in the graph to the left.

- Sine wave method. Many state reporting services and crop advisory companies use the sine wave calculation (see the graph on the next page). This method assumes that the rise and fall of daily temperatures approximates a mathematical sine wave pattern. It also allows for the accumulation of heat units when a small portion of a day was above the threshold while the average temperature was below the threshold. For example, if the maximum temperature on any given day was above 50F for part of the day, but the average temperature was below the lower threshold, the average method would allocate no degree-day units for that day. However, we know that the daytime temperature exceeded the lower threshold and therefore some insect development would occur.

Researchers primarily use the sine wave method; however, you can easily apply the mathematical formula using a computerized spreadsheet. This method more accurately assesses insect development by counting units when the actual temperature (not the average temperature) rises above the lower threshold.

- Small time-unit method. The small time-unit method uses a calculator to continuously monitor temperatures. This method measures temperature over time and uses that fraction of a day to calculate the DD. Many commercial weather stations have this capability, and it may be the most accurate method when applied correctly.

If you get your degree day information from a service, read the fine print on the reports. You need to know what thresholds were used (especially if an upper threshold is in effect) and the method of calculation (average, sine wave, etc.).

Determining degree-day targets for pests Several methods can determine DD-pest activity relationships. Most methods generally require special equipment and complicated calculations. However, the "experienced guess" and "trial and error" technique uses past experience (observations and records) to form a rough target DD. Then, modify this target yearly as you gather new information using actual DD calculations.

Let's say that you usually see pine needle scale crawlers in the third week of May, holly leaf miner adults in the first and second week of May, and lilac borers in your pheromone traps in the first three weeks of May. Your target DDs would then be 250 to 332, 143 to 261 and 143 to 332, respectively.

The next season you calculate the cumulative DDs, and you notice that the pine needle scale crawlers were active from 290 to 340 DDs. This indicates that the prediction should be shifted slightly to more DD units. In the following years, adjust the data as needed to fine-tune your degree-day modeling.

Using host plant phenology Several scientists have noted that certain plants "perform" specific, observable activities, including bud break, flowering and seed drop, each season. Many of these phenological events occur at the same time that specific insects or mites are undergoing a specific life-cycle event (egg hatch, adult emergence, etc.). Donald Orton was one of the first to publish an extensive listing of plant phenology associated with insect activity in his book, Coincide, The Orton System of Pest Management (Plantsmen's Publications, 1989). Subsequent to this publication, a landscape IPM group in the Philadelphia area (Southeast Pennsylvania IPM Research Group, began keeping records of plant phenology and insect pest activities. These reports were available to subscribers to this project, but they have been generally difficult to obtain by the general public. In 1997, Dr. Dan Herms, Ornamentals Research Entomologist (The Ohio State University, OARDC in Wooster, Ohio), began a long-term project whereby plant phenology, degree-day calculations and insect and mite events were recorded for 85 plants and 46 insects and mites. The early results of this study (1997-99 data) were published in the OSU/OARDC Special Circular 173: pp53-59 [available at:].

The beauty of plant phenology sequences is that anyone can develop them. Select plants in your area that are easy to observe. Observe them on a regular basis and keep a yearly journal of activity. By inserting observed insect observations, you can soon develop a sequence that fits your region. For example, you may discover that a particular plant's bloom coincides with the optimal application time for a certain pest.

Although commercial and agricultural growers frequently use degree-day modeling, its use in the turf and ornamental industry is not widespread. However, the application of DDs in landscape settings is not difficult. All you need to do is calculate the DDs in your area and determine what insects can be a problem.

In 1988, Warren Johnson of Cornell University produced one of the most comprehensive lists of insects and mites that attack trees and shrubs along with their associated DD activity periods. He did not use rigorous observations and model development. Instead, he took yearly notes of insect and mite activities and compared them to DD charts for those same years. He then recorded a range of DDs (base 50F).

Use this list as a reference, and compare it with your observations. Integrate it into a continual monitoring program, and note any discrepancies. Before long, you will be able to accurately predict insect occurrence and time your sampling and controls to effectively manage your landscapes and turf.

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