Understanding each pest's biology and its key period of activity is essential to a good pest management program. A practitioner of IPM needs to know each life stage of the pest and when it is present in the field. This knowledge is important to properly time monitoring activities and the implementation of management tactics. A lack of knowledge can lead one to begin scouting before a pest is present or after it has already caused damage to the crop. In either case, the cost of pest management is increased without any benefit to the farmer. This lack of knowledge can also lead to improper timing of a management tactic and ineffective control of the pest. Again, this adds to the cost of pest management.

To avoid these shortcomings, an IPM practitioner can use his/her experience and/or a predictive model to estimate when a key life stage of the pest will be present. Experience tells us that a pest will be present during a specific part of the grow season. For instance, a crop consultant may know that black cut worm clipping tends to occur around June 1 in most years or when the corn is at about the 4th leaf stage (V4). Although this is a good guideline, the timing in reality may vary by up to three weeks from year to year. To more accurately time monitoring and the implementation of pest management tactics, researchers use mathematical models that describe the relationship between temperature and the rate of a pest's development. These models have been primarily developed for insect pests and several crop species. Few models are available that predict weed or disease development in field crops.  In this section, you will find information about how simple mathematical models, termed Degree Day models, are derived and how they can be used in a pest management program.  Table 2 provides key degree day thresholds for several periods in field crop insect life cycles that are important in pest management.  In addition, charts of relative pest activity periods are provided to help anticipate when monitoring should be initiated or terminated (Tables 3 - 11).

Why Use Degree Days? For any pest species there is a key life stage or stages when pest populations should be monitored and control tactics implemented. For example, chemical control should be aimed at late instars of the alfalfa weevil. If the timing is off and the adults are accidentally killed, then important biological control agents that develop inside the adults are also killed, leading to continued outbreaks in the field and no advantage from the pesticide. If control is timed too early, then additional larvae may hatch and cause injury to the field after the insecticide has run out. Degree day models can be used to predict when alfalfa weevils reach late instars. Another example of how degree days can help improve the effectiveness of an insecticide is in the timing of stalk borer control efforts. If treatment for this pest is not timed to coincide with movement from grasses to corn, then insecticide applications will be ineffective. Once the pest has entered a corn seedling, it cannot be controlled by an insecticide application. The pesticide must be in place before the insect moves from its grass host to corn, but not too early so that the insecticide residue has declined to ineffective levels.

Degree days can also be used to increase effectiveness of pest monitoring by clearly defining the period when the harmful pest stages are beginning activity. For instance, there is no need to spend time scouting for corn rootworm adults, if adults haven't begun to emerge or the corn host is at a stage that does not attract the adults. Because of climatic variability, the timing of these events can vary by as much as five weeks between years or from one location in the state to another. It should be clear that pest monitoring and control activities cannot be based on calendar date, but are better timed using degree day models.

What is a Degree Day?

Insects, diseases, and plants depend on heat in their environment to drive metabolic processes because they cannot generate their own heat as do warm-blooded animals. The heat that drives metabolic processes in an organism indirectly affects its growth and developmental rate. The amount of heat available to drive an organism's growth and development can be measured by temperature. Temperature is a measure of heat in the organism's environment.

Because we know that pest development is tied to temperature, researchers have been able to establish mathematical equations that predict the rate of development at different temperatures. These relationships can be used to predict the rate of an insect or plant's development as temperatures fluctuate over time. There are several ways to use these equations to predict the developmental rate of an organism, but the simplest method is to calculate "growing degree days" or "heat units". A degree day is simply a measure or index of the amount of heat accumulated during a day to drive the metabolism or development of a cold blooded organism.

Researchers have developed a number of methods to calculate degree days, but the following equation is the simplest:

Essentially, a degree day is the difference between the average daily temperature and the Base Threshold of Development (Bt).

Example Calculation of DD

To help you understand how to use degree days, let's do an example calculation. An individual establishes a standard weather station to record daily maximum and minimum temperatures. On July 9, he or she reads a properly calibrated max/min. thermometer at 10:00 AM and finds that the maximum temperature in the last 24 hour period was 86^oF and the minimum was 64^oF. We know that the Base Threshold of Development is 50^oF for the pest of interest. On July 8, the Daily Degree Days accumulated were:

Let's investigate further why we can use degree days to predict an organism's stage and rate of development. To do so, let's again return to the mathematical relationship in Figure 1. This relationship gives us two pieces of information:

1. the relationship between temperature and rate of development of an organism
2. and the base threshold of development (Bt).

In Figure 1, the relationship between the organism's rate of development and temperature is linear (a straight line). It is essential that this relationship be linear for the concept of a degree day to work. It is not essential, however, that the relationship be linear to predict an organism's rate of development. In fact, the relationship usually is non-linear. For most organisms, however, it is approximately linear within the temperature range experienced during the period when a prediction is needed. The the equation that describes the relationship between temperature and the organism's rate of development is:

If we insert 86^oF into the equation for temperature, we predict that the organism's rate of development is 0.363 parts of its total development completed each day. If we add these parts up every day until they equal 1.0, we find it takes 3.11 days to complete the organism's life stage at 86^oF. But what if the average daily temperature is different each day? One way to deal with this is to predict the part of development completed each day by plugging in the average temperature for each day into the equation and then adding up the parts of development until they equal one. For instance, suppose that over a week's time, the average daily temperature for each day was 85, 83, 82, 80, 81, 78, and 79. Then on day one, 0.31 parts of the organism's developmental time in the life stage is completed, on day two 0.30 parts are completed, and on day three 0.29 parts are completed. By adding up these three numbers, we find it would take over 3.0 days for the organism to complete its development in this life stage. From this relationship we can see that the number of days it takes to complete a life stage can be predicted by measuring temperature, estimating the average daily temperature for each day, and then using the average daily temperature in the developmental equation.

This method, however, is cumbersome and requires keeping track of parts of development. Another more convenient method is to determine the number of degree days needed to complete each life stage of an organism. To do this we must first estimate the Base Threshold of Development (Bt). The Bt is the temperature at which an organism's developmental rate is zero or development stops. It can be calculated by setting the rate of development equal to zero in the equation and then solving for temperature:

This can also be expressed as, temperature = 0.452 ÷ 0.009 = 50.2^oF. Based on this calculation, at temperatures at or below 50.2^oF the insect will not development. This is the Base Threshold of Development for this life stage of the organism. In reality, each life stage has a different Bt, but in practice, a single average Bt is used for all life stages.

Now that we know how to calculate an organism's rate of development and its base threshold of development, we can calculate the number of degree days required to complete a life stage. Earlier we determined that it would require 3.11 days to complete the life stage at 86^oF. At 86^oF, we calculate that 35.8 degree days (DD) will be accumulated each day (86 - 50.2 = 35.8 DD). Because we know it takes 3.11 days to complete the life stage at 86^oF and that 35.8 DD are accumulated each day, we can multiply 3.11 days times 35.8 degree day per day to estimate the total number of degree days that must accumulate before the life stage can be completed. From this we can see that 111.3 DD are required to complete this life stage. Because the relationship between temperature and the rate of development is linear, you will also get the same number of degree days required to complete the life stage using any temperature. To illustrate that the degree days needed to complete a life stage is constant and independent of temperature, we will choose another temperature, 68^oF, and recalculate the degree day requirement. At 68^oF, the degree days per day accumulated is 68^oF - 50.2^oF = 17.8 DD. The rate of development is 0.16 or 6.25 days to complete development. If we multiply 17.8 DD per day times 6.25 days, we also get 111.3 DD. Because each insect and plant species is adapted to different environmental conditions, the Bt and development rate equations vary between species, as do the number of degree days needed to reach a life stage. Table 2 contains the degree day requirements for key events in the life cycle of several insects that are important in their management.

Using Degree Days in an IPM Program Degree day requirements are available for six major insect pests of field crops in Pennsylvania: the European corn borer, black cutworm, corn rootworm, alfalfa weevil, and seed corn maggot. With the exception of the black cutworm and seed corn maggot, degree day accumulations begin on January 1. The black cutworm degree day system requires that pheromone traps be monitored to identify the peak of the spring migratory flight and then accumulate degree days from this date. The degree days for seed corn maggot are accumulated from the date that a crop is plowed under.

Of these insects only the European corn borer is a pest during two generations. Using degree days, the period for first and second flights, the time to initiate scouting for first generation injury symptoms and control timing, and the time to scout for egg masses and to implement control for the second generation can be predicted. For this insect more sophisticated and accurate computer models are also available to predict these key periods.

The beginning of seedling corn clipping by black cutworm occurs 300 DD after peak moth capture in a pheromone trap. This can be used as a clue to begin scouting. Similarly, alfalfa weevil larvae reach the period of significant feeding at about 300 DD, and by 500 DD the majority of their feeding injury is complete. Stalk borer larvae develop first in grasses around field margins or in the field before moving into young corn plants. A scout can look for evidence of their presence in grasses between 1300 and 1400 DD. A treatment decision to protect young corn fields should be made between 1400 and 1700 DD. A preventative treatment can be applied to grassy areas at 575 to 750 DD. When green residue is plowed under before planting, a grower can wait 450 DD before planting to avoid infestation and damage by seed corn maggot. A post-emergence insecticide application to control corn rootworm larvae should be applied between 380 and 474 DD for optimal performance. Scouting for rootworm adults should begin when 1253 DD have accumulated and should stop when beetle numbers begin to drop.

In simple terms, an Economic Threshold (ET) is a guideline to help growers determine if pest numbers are high enough to justify implementing a management tactic. More specifically, an ET is the number of pests per some unit (i.e per square foot, per plant, per feet of row, etc.) that, if left uncontrolled, will soon increase to levels high enough to exceed the Economic Injury Level (EIL). So what is the EIL? The EIL is the number of pests who's feeding injury causes a crop loss, in dollars, exactly equal to the amount of money it would cost to control the pest. It is, in essence, the break-even point between the cost of implementing control and the economic loss caused by the pest, expressed in numbers of the pest per some unit. Although some people use the terms ET and EIL interchangeably, they are in fact different. Figure 2 shows the relationship between the economic threshold, the economic injury level, and fluctuation of a pest's population level over time. It can be seen that the EIL is always higher than the ET. The purpose of the ET is to give a grower time to implement a control tactic before the break-even point (EIL) is reached; thereby saving as many dollars as possible, while making sure that it is cost- effective to implement the management tactic. The ET is the signal to take action, and for this reason is sometimes called the Action Threshold (AT). Without sound economic thresholds, effective implementation of an IPM program would not be possible.

EIL's are fundamental to an IPM program, so it is important that an IPM practitioner understand how they are developed. The level of sophistication in economic thresholds varies. Some pest thresholds are single values that remain constant across all economic and environmental conditions, while others are dynamic and vary when the economic and/or environmental conditons change. Regardless of how elaborate the ET, its EIL is based on the relationship between crop yield, market value, control cost, the proportion of pests killed by a control tactic, the expected yield loss caused per pest, and the number of pests per some unit (i.e. number per plant). To calculate an EIL, the following information is needed:

• the cost of a control tactic (CC),
• the estimated market value of the crop (MV),
• the estimated yield of the crop (EY),
• the proportion of the pest population that will be killed by management (PC), and
• the yield loss caused by each pest (usually expressed as a proportional loss, (PL).

The following equation is used to estimate a cost:benefit ratio and the EIL for a pest:

The number of pests that cause a dollar loss that leads to a cost:benefit ratio of 1.0, is the EIL.

Both decision indices (cost:benefit ratio and EIL) are in effect one and the same, but calculation of the economic injury level requires one additional step. The decision rules, however, are slightly different. With the cost:benefit ratio, implementation of a management tactic is recommended when the cost:benefit ratio is less than or equal to 1.0. A cost:benefit ratio greater than 1.0 indicates that the cost of the management tactic is greater then the benefit derived from its implementation. The economic injury level is expressed as the number of insects that cause a crop loss, in dollars, exactly equal to the cost of implementing a management tactic. The economic injury level is the number of insects that lead to a cost:benefit ratio of 1.0 (i.e. the break-even point). Using an economic injury level approach, the grower implements control if the number of insects found in the field through scouting exceeded the economic threshold. Remember, the economic threshold is the number of insects, that if left uncontrolled, will in all probability increase to numbers higher than the economic injury level. It provides a time window to implement a control measure before economic loss occurs. For European corn borer the economic injury level varies with plant growth stage, crop market value, expected yield, cost of a control tactic, and the expected proportional of the population that will be killed by the control tactic. Tables 14 and 15 provide a template to calculate a cost:benefit ratio and the economic injury level for the first and second generations of the European corn borer.

Example Calculation

Based on the above equation let's work through an example calcuation of the Cost:Benefit ratio and economic injury level for the European corn borer. To help you understand this calculation two examples are provided: one with Table 14 and one with Table 15. Let's work through the example in Table 14. During a recent visit to a corn field, three hundred larvae are found on 100 corn plants at the 10th leaf stage (V10). Research has shown that we can expect only 20% of these larvae to survive and cause injury to the 100 plants. To calculate how many larvae will survive and cause injury to the plants, we multiply 300 by .20, which gives us 60 larvae per 100 plants (line 1). The next step is to convert the number per 100 plants to the number per plant. This is done by dividing 60 larvae by 100, which is 0.60 larvae per plant (line 2). Research has also shown that during the first generation, each larva per plant causes a 5.9% loss in yield. By multiplying the number of surviving larvae per plant (0.60) times 0.059 (5.9%), we find that the total loss per plant is 0.035 or 3.5% loss (line 3). By multiplying the total loss times the expected number of bushels per acre, we estimate that 4.73 bushels per acre will be lost to first generation European corn borer (line 4). In line 5, we multiply the number of bushels per acre lost times a crop value of $3.00 per bushel, which indicates that monetary loss per acre to European corn borer is $14.18. To calculate the amount of this monetary loss that can be prevented by an insecticide application, we multiply the number of dollars per acre lost times the proportion of the European corn borer population that will be killed by an insecticide application. For first generation European corn borer we can usually expect about 72% control with one insecticide application. Multiplying $14.18 per acre times 0.72 (72%), we find that we can protect only $10.21 per acre (line 6). In line 7, we subtract the cost of an insecticide application from the number of dollars saved implementing the management tactic. In this example, the cost of control is $15.00 per acre. Subtracting $15.00 per acre from $10.21 per acre shows that we would be $4.79 per acre worse off than doing nothing to control the pest (line 7). Dividing $15.00 per acre by $10.21 per acre gives a cost:benefit ratio of 1.47 (line 8). To estimate the economic injury level, simply multiply the number of larvae per plant (0.60) time the cost:benefit ratio (1.47). This gives an economic injury level of 0.88 larvae per plant. A similar approach is used for second generation, but one additional step is added because scouting must take place during the egg deposition period to allow time for control tactic implementation.

Estimating the economic threshold is not as easy. Most ETs are based on an understanding of an insect's biology and its population growth rate. Seldom are ETs mathematically calculated. More likely, they are based on observations and set at conservatively low levels to prevent missing an insect population that will cause economic loss to the farmer. None-the-less, they are good guidelines for making informed pest management decisions. Tables 12 - 23 provide economic threshold values for pests that attack field crops or assist with the calculation of economic injury levels.

An economic threshold for weeds is defined as the density of a weed population at which control is economically justified because of potential for yield reduction, quality loss, harvesting difficulties, or other problems that weeds may cause.Each acre of land has a specific amount of resources for the growth and development of plants. This amount varies from site to site and from year to year with differing environmental conditions. An area will support as much vegetation as possible with the available sunlight, water, nutrients, and space. If a weed-free crop is grown, the crop has all of the resources for its own use. If weeds are allowed to grow with the crop, however, they will use a portion of these resources and may cause losses great enough to justify control measures. Generally, removing an infestation of insects or disease from a crop does not necessarily lead to an infestation by more of these pests. However, if a species of weed is removed from an area, other species may invade unless the crop is sufficiently competitive to prevent its doing so.

Besides an economic yield loss, other concerns may determine when weed control is justified. For example, eastern black nightshade in soybeans or late-emerging grasses in corn may not reduce yield, but these weeds can clog equipment, causing harvest delays and creating a frustrating situation in which the farmer is prone to accidents. A few velvetleaf plants in corn may not be economically significant in that year's crop, but many farmers treat weeds to prevent seed production and subsequent soil infestation. Another problem involves the importance of aesthetics to tenant farmers and their landlords. If the landlord views a few weeds as an indication of poor management, the tenant farmer may be concerned with the possibility of losing the farm to a "tidier" neighbor as well as with potential yield loss. Some general assumptions about weed-crop interference can help make the appropriate management decision. Weed-crop competition studies indicate that if weeds are allowed to grow with most field crops under normal environmental conditions for no longer than 4 to 6 weeks after crop emergence and are then removed, and if the crop remains weed-free until harvest, then yield reduction is unlikely. In addition, if weeds are kept out of the field for 4 to 6 weeks after crop emergence, any weeds that later invade will not reduce yield significantly, although they may produce seeds, cause harvesting problems, or reduce crop quality.

Broadleaf weeds and grass weeds will compete with crops at different levels of intensity depending upon the competitiveness of the crop, tillage system, environmental conditions, and other weeds present. In general, broadleaf weeds are more damaging to a broadleaf crop, while grass weeds are more competitive in a grass crop. For example, cocklebur is more devastating in soybeans than corn because it competes for the exact same space and sunlight that soybeans do. It is also harder to control an infestation of broadleaf weeds in a broadleaf crop than it is to control a grass weed. The same theory applies to a grass crop like corn. Shattercane, which has a similar growth habit to corn, is very difficult to control in corn and competes for the same space and sunlight.

In almost every cropping situation, an economic threshold exists justifying the use of some form of weed control. Crop yield loss information has been determined for certain single weed species growing with the crop for the corn and soybean belt of the Midwest. However, not all weeds have been researched and few data exist for the more common situation - the effect of multiple weed species at various populations. Crop yield loss data is available for the northeastern U.S., including Pennsylvania. Because the competitive ability of different species can change under various conditions, determining yield loss information for several species growing together is often difficult. However, if we assume an additive relationship between the crop and multiple weed species, and base our economic threshold on the potential for yield reduction, an economic treatment threshold can be calculated.

Determining an Economic Treatment Threshold

An economic threshold may be important when considering whether or not a cultivation or post-emergence herbicide application is needed. The following guidelines are based solely on the effect of weeds on crop grain yield.

To calculate an economic treatment threshold for a particular field, first determine the expected yield level of the crop. Next, determine the relative densities of the various weed species in the field. Do this by identifying and recording all the weed species found. Determine the level of severity by counting the number of weeds per 10 ft. of row for large infestations or per 100 ft. of row for more scattered areas. Sample areas should represent no more than 5 acres, so sample enough areas to get an accurate count. Once the densities of the various weed species present have been determined, find the closest corresponding number on Table 21 or Table 23 for the different weed species and read the percent yield reduction from the top line of the chart. Sum up the percent yield reductions for all weeds and multiply this value by the expected yield. This is the percent yield reduction (bu/A) that should be expected without any control measure implemented. Next, determine the cost of control or treatment and enter that figure into your calculation. The treatment or control cost must include the cost of the herbicide and any adjuvants, fuel, equipment, and operator's time. Finally, calculate the expected dollars lost without treatment (bu/A loss X $/bu) and enter this figure. Subtract the cost of treatment from the dollars lost to obtain your net gain. If the net gain from the treatment exceeds the control cost, then treatment is justified.

If the weeds in the field are not in Table 21 then use Tables 22 & 23. Table 22 classifies common grass and broadleaf weeds into categories of relative competition with corn and soybeans. Categorization is based on Dr. Bill Curran's experience with these weed species. Table 23 provides estimates of percent grain yield reduction for each competition category and weed density by crop. These two tables can be used to estimate the economics of controlling weed populations in these crops. In general, weed densities that reduce crop yield greater than 10 percent are above the economic treatment threshold.

Caution: The values in Tables 21 and 23 are averages from several U.S. studies conducted in the North Central Region of the Midwest and northeastern U.S. The values assume that the weeds emerge with the crop and that the crop is planted in 30 inch rows. Time of weed emergence, variations in local environment (soil and weather), and degree of post-emergence weed control will impact weed-crop in ierference and economic threshold decisions. Failure to obtain 100 percent weed control must also be considered. This factor can be rather large if weeds are under stress from drought, cool weather, or if the weeds are "off label" with regards to size. Therefore, some judgement should be used in applying these principles. Also, keep in mind that quality loss, harvesting difficulties, aesthetics, or other problems associated with weeds are not considered in this economic treatment threshold calculation.