Firstlevel

In the most basic and also the most widely practiced form of IPM, emphasis is on monitoring development and/or abundance of a single pest species at a single locale (e.g., a household, cow barn, greenhouse, cropped field, or woodlot) and using thresholds for deciding whether to take action.

FIGURE 1 Levels of IPM integration: main targets, ecological scales, and levels of ecological complexity.

Application of a pesticide is by far the most common form of action taken under first-level IPM. Integration occurs when abundance of natural enemies of the pest in question also is considered in the decision-making process and when selection among candidate pesticides involves explicit attention to minimizing harm to these and other beneficial organisms. This form of IPM has been characterized by some as "integrated pesticide management."

Monitoring Pest Development

Because the developmental rate of an arthropod is regulated largely by temperature, the monitoring of developmental rate for pest management purposes usually takes the form of measuring accumulation of heat units above a threshold temperature at which development begins. At temperatures above these fostering the maximal developmental rate, development may decrease. Such decrease has not been investigated for most pest arthropods and has not yet played a significant role in making pest management decisions.

The simplest and most prevalent approach to measuring accumulation of heat units above developmental threshold temperature involves use of degree-days (DD). For a specific date, the number of accumulated DD equals the average temperature of that date minus the developmental threshold temperature of the arthropod. Several procedures have been devised to estimate average daily temperature. The most common one, albeit somewhat crude, consists simply of averaging the maximum and the minimum ambient temperature of the day. To illustrate the DD approach, if the high and low temperature for a given day were 30 and 20°C, respectively, with a developmental threshold temperature of 10°C, then 15 DD would have accumulated on that day.

Pest development as monitored by DD accumulation may benefit decision making under first-level IPM in several ways, particularly for optimal timing of management activities. For example, ability to predict when a majority of pest adults is about to emerge from pupae is useful for optimal timing of deployment of traps for monitoring adults. Knowledge about when oviposition is likely to begin and peak can facilitate optimal timing of pesticide application against newly hatched larvae, which often is the stage most vulnerable to pesticide treatment. Sometimes this determination is made in conjunction with date of first capture of adults by traps, known as a "biofix" point for initiation of DD accumulation. The ability to forecast when a majority of larvae or nymphs is at a particular growth stage can aid in optimal timing of sampling their abundance and the abundance of their natural enemies.

Monitoring Pest Abundance

Ideally, an IPM practitioner would have available a precise count of the number of individuals of an insect pest species present in an area of concern; realistically, obtaining information on absolute densities of pests is prohibitively costly. Therefore, most practitioners rely on imprecise estimates of pest population density obtained by using one or more population sampling techniques. The intent is to capture a more or less consistent, if unknown, proportion of the pest population. Choice of appropriate sampling technique varies considerably according to pest species and developmental stage.

For sampling comparatively mobile individuals such as adults, traps using odor and/or visual stimuli are common tools. Odor stimuli usually consist of synthetic equivalents of either attractive sex odors (sex or aggregating pheromones) or attractive food or host odors. Visual stimuli normally rely on synthetic mimics of visually attractive sites where feeding, mating, or egg laying occurs.

For sampling less mobile individuals such as larvae, common techniques include visual searching of the target area accompanied by direct counts of detected pests, use of a sweep net (especially effective for sampling individuals on foliage of nonwoody plants), and use of a loose or framed cloth placed beneath vegetation that is shaken or tapped to dislodge pests. Sampling immobile individuals such as eggs or pupae usually is done by visual inspection.

To obtain an acceptably accurate and cost-effective estimate of the size of a pest population by means of one of these techniques, careful attention must be given to the program under which sampling is conducted. Effective sampling programs take into account the daily activity pattern of the target species as well as its characteristic spatial distribution (uniform, random, or clumped). Historically, most programs have incorporated sampling at several or numerous sites in a target area to acquire sufficient representation of the size of a pest population; then researchers have counted the sampled individuals of the target pest. New programs developed for some pests simplify these procedures. Sequential sampling is an approach that optimizes the number of sampling sites needed for classifying a pest population as below or above a density requiring action. Binomial sampling is an approach that classifies an individual species as either present or absent at a sampling site, thereby precluding the need to count all members of that species taken in a sample. Both these simplifying approaches require substantial species-specific background information for their development and use.

The emerging technologies of global positioning systems (GPS) and geographical information systems (GIS) offer unsurpassed capability of aiding in the mapping of site-specific variation in characteristics of areas under consideration for sampling. A GPS uses triangulation of signals from a constellation of satellites to identify the precise location (within a meter) of an area on the earth's surface. A GIS is a computer program for the mapping and spatial analysis of georeferenced information. GIS capabilities include assemblage, storage, manipulation, retrieval, and graphic display of information about attributes of precise locations identified through GPS. Such information can be exceptionally useful in forming associations between characteristics of a specific locale (e.g., terrain, soil, extent of vegetative growth, microclimate) and density of a population (Fig. 2). For pests, sampling can be directed toward specific sites in which densities are suspected to be highest.

FIGURE 2 Dispersal of Neoseiulus fallacis for biological control of spider mites in a strawberry field, 8 to 15 weeks following release of 100 adult females at each of 15 sites: squares, release sites; crosses, sample points. This distribution is due to ambulatory foliar movement and aerial dispersal (dominant winds from south and southwest). Data represented using GIS (GRASS v. 4.1). [From Coop, L. B., and Croft, B. A. (1995). Neoseiulus fallacis: Dispersal and biological conrol of Tetranychus urticae following minimal inoculation into a strawberry field. Exp. Appl. Acarol. 19, 31—43. Reproduced by permission from the authors and Chapman & Hall (now Kluwer Academic Publishers).]

FIGURE 2 Dispersal of Neoseiulus fallacis for biological control of spider mites in a strawberry field, 8 to 15 weeks following release of 100 adult females at each of 15 sites: squares, release sites; crosses, sample points. This distribution is due to ambulatory foliar movement and aerial dispersal (dominant winds from south and southwest). Data represented using GIS (GRASS v. 4.1). [From Coop, L. B., and Croft, B. A. (1995). Neoseiulus fallacis: Dispersal and biological conrol of Tetranychus urticae following minimal inoculation into a strawberry field. Exp. Appl. Acarol. 19, 31—43. Reproduced by permission from the authors and Chapman & Hall (now Kluwer Academic Publishers).]

FIGURE 3 Graphs depicting theoretical population fluctuations of two insect

Deciding Whether to Take Action

Several approaches have been developed for deciding whether an insect pest population has or has not reached a level requiring intervention, such as an insecticide application. For agricultural purposes, the approach used most often centers on the concept of "economic injury level" (EIL), formalized in 1959 by V. H. Stern, R. F. Smith, R. van den Bosch, and K. S. Hagen and defined by them as the "lowest pest population density that will cause economic damage." These entomologists also proposed a related concept, which they termed the "economic threshold" (ET), defined as the "pest density at which control measures should be applied to prevent an increasing pest population from reaching the economic injury level" (Fig. 3).

The decision-making concepts of EIL and ET have been fundamental to the development and implementation of first-level IPM, particularly for insect management in agriculture (but less pronouncedly for disease, vertebrate, and weed management). They have been especially useful when insect pest populations are expected to increase over time within a crop, can be sampled reliably, can be related in a predictable way to reduction in crop yield or quality, and can be controlled readily by taking immediate action (e.g., application of insecticide) to prevent further damage. They are less valuable when human comfort or aesthetics, rather than economic damage, is paramount. Even for agriculture, the concepts of EIL and ET cannot be applied rigidly because of inherent unpredictability of such factors as future weather (which can markedly affect rate of pest population growth and degree of crop susceptibility to a pest) and future value of the crop in the marketplace. Also, a type of action that may require considerable time before reducing pest density, such as application of a biocontrol technique, is likely to be less appropriate than an insecticide application within an EIL/ET framework.

A refinement of the concept of EIL, put forward by L. P. Pedigo and L. G. Higley, introduces the element of environmental quality into the decision-making process. Negative effects of insecticides on natural enemies of pests and

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