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Monitoring Insect Pests in Retail Stores by Trapping and Spatial

Analysis

Article in Journal of Economic Entomology · November 2000

DOI: 10.1603/0022-0493-93.5.1531 · Source: PubMed

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 STORED-PRODUCT AND QUARANTINE ENTOMOLOGY

Monitoring Insect Pests in Retail Stores by Trapping and Spatial

Analysis
RICHARD T. ARBOGAST, PAUL E. KENDRA, RICHARD W. MANKIN, AND
JEFFREY E. MCGOVERN1
Center for Medical, Agricultural, and Veterinary Entomology, ARS-USDA, P.O. Box 14565, Gainesville, FL 32604

J. Econ. Entomol. 93(5): 1531Ð1542 (2000)

ABSTRACT Stored-product insects are a perennial problem in retail stores, where they damage
and contaminate susceptible merchandise such as food products and animal feed. Historically, pest
management in these stores has relied heavily on chemical insecticides, but environmental and
health issues have dictated use of safer methods, and these require better monitoring. A monitoring
procedure that employs an array of moth and beetle traps combined with spatial (contour) analysis
of trap catch was tested in three department stores and two pet stores. The rate of capture increased
with the level of infestation but was essentially constant over 4- to 5-d trapping periods. Contour
analysis effectively located foci of infestation and reßected population changes produced by ap-
plications of the insect growth regulator (S)-hydroprene. The most abundant insects were Plodia
interpunctella (Hübner), Lasioderma serricorne (F.), Oryzaephilus mercator (Fauvel), Tribolium
castaneum (Herbst), and Cryptolestes pusillus (Schönherr). The results indicate that contour analysis
of trap counts provides a useful monitoring tool for management of storage pests in retail stores. It
identiÞes trouble spots and permits selection, timing, and precision targeting of control measures to
achieve maximum pest suppression with minimum pesticide risk. It permits managers and pest
control operators to visualize pest problems over an entire store, to monitor changes over time, and
to evaluate the effectiveness of control intervention. The contour maps themselves, along with
records of control applications and stock rotation, provide permanent documentation of pest
problems and the effectiveness of pest management procedures.

KEY WORDS stored-product insects, retail stores, insect trapping, insect monitoring, spatial
analysis, precision targeting

STORED-PRODUCT INSECTS ARE a perennial problem in tional or conventional chemical insecticides. Histori-
retail stores, where they damage and contaminate cally, retailers and pest control operators have relied
susceptible merchandise such as food products and heavily on chemical pesticides, but increasing aware-
animal feed. Their presence causes loss of customer ness of risk to environmental quality and human health
good will, guarantees the presence of potential aller- has made it necessary to seek safer methods. Early
gens (Brenner 1993, Brenner et al. 1991), and may detection and location of infestation through im-
result in citation by public health ofÞcials when the proved monitoring will reduce risk by permitting ap-
store sells groceries or includes a restaurant. These plication of pesticides only when and where they are
pests may be resident in stores or invade stores from needed. Improved monitoring will also provide a
nearby areas, but often they are introduced in prod- means to identify points of control failure and take
ucts delivered from infested warehouses. As their corrective action.
numbers increase, introduced insects disperse to in- Research over the last two or three decades has
vade other products in the store. Spillage from broken produced a variety of traps that are effective in de-
packages that has accumulated under display and stor- tecting insect pests (Burkholder 1984, Vick et al. 1990,
age shelves, among clutter in stock rooms, or in other Mullen 1992), but the value of these traps for making
inaccessible places also becomes infested and provides pest management decisions has been limited by our
a continuing source of infestation. ability to relate numbers of insects captured to num-
Effective management of the problem requires bers present, or to economic impact. Attempts to in-
good sanitation, inspection of incoming goods, fre- terpret trap catch in terms of population density have
quent rotation of stock, monitoring for pests, removal enjoyed only limited success (Arbogast and Mankin
of infested stock, and judicious application of biora- 1999). Wilkin and Fleurat-Lessard (1991) suggested
that in stored grain, it may in fact be impossible to
This article reports the results of research only. Mention of a make such an interpretation, and they proposed that
proprietary product does not constitute an endorsement or recom-
mendation by the USDA for its use.
a risk factor system be devised instead. Thus, there are
1
Acurid Retail Services LLC, 2170 Piedmont Road NE, Atlanta, GA currently two possible systems for interpreting the
30324. results of trapping. These can be termed representa-
1532 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 93, no. 5

tive and indicative (Arbogast and Mankin 1999). Rep- beetles using pitfall traps (Storgard FLI៮TeTRAK M2,
resentative interpretation makes the assumption that TRÉCÉ, Salinas, CA) baited with cigarette beetle and
the number of insects captured represents a popula- confused ßour beetle/red ßour beetle pheromone
tion density to which it can be converted mathemat- lures and with oat oil as a food attractant. The moth
ically, whereas indicative interpretation uses trap traps (7 by 10 by 1.5 cm) were attached to a wall, a
catch as an indicator of risk or action to be taken. shelf rack, or the underside of a shelf (at heights of
Wilkin (1990) recognized two sorts of risk (probabil- 1Ð2.5 m) by means of Velcro for easy removal and
ity that insects will be detected by a customer, and replacement when making counts. Most often, the
effect of further storage on quality) and presented a traps were concealed under shelves. Beetle traps were
scheme for interpreting trap catch in terms of action placed on the ßoor, either under a shelf or against a
to be taken. Pinniger (1991) outlined a scheme, based wall.
on action thresholds set by experience and the needs The data used in spatial analysis are topographical;
of industry, that can be adapted to different commer- that is, each data element consists of two independent
cial facilities and pests. location variables, and a dependent or functional vari-
Trapping and spatial analysis of numbers captured able (number of insects captured). Thus, a basic re-
(Arbogast et al. 1998, Brenner et al. 1998) provide a quirement for spatial analysis is that trap locations be
powerful tool for indicative interpretation. Pierce speciÞed on a two-dimensional coordinate system. We
(1994) used pheromone-baited traps and triangula- established a rectangular (x, y) coordinate system for
tion to locate hidden infestations of cigarette beetles, each store with the origin at one corner, and used it to
Lasioderma serricorne (F.), and pyralid moths in food lay out a grid of trap positions (Fig. 1). Trap positions
warehouses. He based his method on the inverse re- were Þrst laid out on a ßoor plan of the store, then
lationship between numbers captured and the prox- located in the store itself and labeled. To locate po-
imity of infestation. The current article reports studies sitions in the store, we used measurements and ref-
of moth and beetle infestations in department and pet erence to various physical features, such as doorways,
stores, primarily by contour analysis of numbers shelving, support columns, and ßoor tiles. We used 50
trapped at Þxed points, and examines the practical moth traps in each of two department stores (depart-
value of spatial analysis for management of insect pests ment stores 1 and 3) (Fig. 1 A and C) and 61 in the
in retail stores. third (department store 2) (Fig. 1B), which was
larger. Trapping was conducted: 8 Ð11 August 1997 in
store 1; 2Ð 6 September 1997 in store 2; and 4 Ð9 August
Materials and Methods
1997 in store 3. We used 25 traps in a second, follow-
The study included Þve retail stores in north-central up, trapping campaign (16 Ð20 September 1997) that
Florida: three department stores with grocery and pet was limited to the infested area (the pet department
departments, and two pet stores. At the time of our and adjacent areas) of store 3 (Fig. 1F). Ideally, traps
study, no chemical insecticides had been used to con- should be spaced evenly, but this is not a strict re-
trol stored-product insects in the department stores quirement and is impossible in retail stores because
for at least 3 mo. Instead, the pest control technician locations suitable for trap placement are not uniformly
had recommended improved stock rotation and better available. Also, to minimize the number of traps
sanitation in areas infested by the Indianmeal moth, needed, it is desirable to place more traps in areas
Plodia interpunctella (Hübner) (Lepidoptera: Pyrali- likely to support insect infestation than elsewhere.
dae), and had installed traps for moth detection. The Accordingly, we distributed traps throughout each
pet store managers had been given similar recommen- store with more in the pet and grocery departments
dations, and in November 1998, a program of Gentrol and fewer in departments such as hardware, electron-
applications was initiated in both stores. Gentrol is a ics, and clothing. The number of moths captured in
formulation of the IGR (S)-hydroprene (9% emulsi- each trap was recorded after 1 and 4 h and then daily
Þable concentrate). It was applied as an aqueous spray for 4 d.
at a concentration of 7.81 ml/liter (1 oz/gal of water), We used 40 moth traps and 40 beetle traps in each
mainly to ßoor-wall junctions, between pallets, under of the pet stores (Fig. 1 D and E). These were dis-
and behind display and storage racks, and inside hol- tributed throughout the stores, except for the check-
low rack supports. Application was repeated monthly out areas, with one moth trap and one beetle trap at
for 3 mo, using 3.79 liters (1 gal) of spray in each each location. Numbers of insects captured were re-
application, and a different section of the store was corded daily for 5 d. We ran two trapping campaigns
treated each time. After this initial treatment, appli- in pet store 1 (14 Ð19 September 1998 and 11Ð15 May
cations were done quarterly. No chemicals had been 1999) and one in pet store 2 (7Ð12 December 1998).
used in pet store 1 before November 1998, but Gentrol The x,y-coordinates of the trap positions and the
had been applied monthly for about a year in pet store corresponding numbers of insects captured were en-
2. tered in Surfer 6.02 (Keckler 1995) for contour anal-
The department stores were monitored only for ysis. This software posts observed trap catch to the
moths, but the pet stores were monitored for both appropriate coordinates on a ßoor plan of the store,
moths and beetles. Moths were monitored using pher- which has been entered as a base map, and then
omone-baited sticky traps (SP-Locator Moth Traps, creates a denser grid of trap catch values by interpo-
Agrisense-BCS Limited, Mid Glamorgan, UK) and lation, using one of several algorithms. We used radial
October 2000 ARBOGAST ET AL.: MONITORING INSECT PESTS IN RETAIL STORES 1533

Fig. 1. Floor plans of the retail stores in which the study was done. Areas sampled by trapping were as follows: 8,370
m2 (department store 1); 12,209 m2 (department store 2); 8,217 m2 (department store 3); 1,730 m2 (pet department and
surrounding area of department store 3); 2,073 m2 (pet store 1), and 1,984 m2 (pet store 2). There was a moth trap and a beetle
trap at each of the locations indicated by dots. Moth traps were attached to a wall, a shelf rack, or the underside of a shelf
at a height of 1Ð2.5 m above the ßoor. Beetle traps were placed on the ßoor, either under a shelf or against a wall. C, check-out
area; G, groceries; N, nursery (garden shop); O, ofÞce; P, pet supplies; S, stock room. Shaded areas indicate portions of the
stores not included in the trapping studies.

basis functions (with the multiquadric function), tour analysis was done for each set of observations and
which is a ßexible algorithm that provides good overall for most of the insect species detected, but mostly the
interpretation of most data sets (Keckler 1995). Con- Þnal observations (cumulative trap catch over the
1534 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 93, no. 5

Table 1. Assignment of indicator values to trap locations when the pest management threshold has been set at about 90% suppression
or the trap threshold set at four or more insects

Calculated Assigned
Cumulative Indicator
Trap No. captured cumulative cumulative
total value
location (ni ) frequency frequency
(ci ) (P)
(fi ) (f ⴕi)
12 54 54 0.196 0.196 1
19 25 79 0.287 0.287 1
18 19 98 0.356 0.356 1
7 17 115 0.418 0.418 1
5 14 129 0.469 0.520 1
6 14 143 0.520 0.520 1
21 12 155 0.564 0.564 1
11 10 165 0.600 0.600 1
15 9 174 0.633 0.665 1
33 9 183 0.665 0.665 1
2 8 191 0.695 0.724 1
8 8 199 0.724 0.724 1
22 7 206 0.749 0.800 1
32 7 213 0.775 0.800 1
36 7 220 0.800 0.800 1
17 6 226 0.822 0.822 1
3 4 230 0.836 0.895 1
9 4 234 0.851 0.895 1
23 4 238 0.865 0.895 1
27 4 242 0.880 0.895 1
31 4 246 0.895 0.895 1
4 3 249 0.905 0.927 0
29 3 252 0.916 0.927 0
37 3 255 0.927 0.927 0
14 2 257 0.935 0.925 0
20 2 259 0.942 0.925 0
25 2 261 0.949 0.925 0
26 2 263 0.956 0.925 0
28 2 265 0.964 0.925 0
30 2 267 0.971 0.925 0
35 2 269 0.978 0.925 0
38 2 271 0.985 0.925 0
1 1 272 0.989 1.000 0
16 1 273 0.993 1.000 0
24 1 274 0.996 1.000 0
34 1 275 1.000 1.000 0
10 0 275 1.000 1.000 0
13 0 275 1.000 1.000 0
39 0 275 1.000 1.000 0
40 0 275 1.000 1.000 0

Number of beetles captured by pitfall traps in pet store 1, 14 Ð19 September 1998. Columns 1 and 2 were sorted in descending order by number
captured. Cumulative totals (ci ) and calculated cumulative frequencies (fi ) were then calculated as follows:

ci ⫽ 再 ni
ni ⫹ c i ⫺ 1
i⫽1
i ⬎1 and f i ⫽ c i / ¥ n i , where i ⫽ 1 to 40 is the row number.

Assigned cumulative frequencies differed from calculated cumulative frequencies only when equal numbers of insects were captured in two
or more traps. In that case, the highest calculated cumulative frequency was assigned all traps. Indicator value ⫽ 1 when fi⬘ ⱕ0.895. Otherwise,
indicator value ⫽ 0.

trapping period) for the Indianmeal moth and for all equations at the bottom of Table 1. Traps that captured
beetles combined were used as illustrations. the same number of insects were grouped together, and
The utility of contour analysis can be enhanced by the highest cumulative frequency in the group was as-
assigning indicator variables, rather than raw trap counts, signed to all traps in the group (Table 1). The assigned
to trap locations (Brenner et al. 1998). We used an cumulative frequency (fi⬘) for any trap, thus indicates
indicator variable (P) obtained by converting trap catch the proportion of the total catch represented by the
to probability. The data manipulations required to assign combined catch of traps with an equal or greater number
values of P to trap locations were performed in an Excel of insects. It estimates the probability that any one trap
97 spreadsheet (Microsoft, Redmon, WA) and are illus- will capture an equal or greater number of insects, given
trated by the example in Table 1. Trap locations (des- the size and spatial distribution of the population.
ignated 1Ð40) and number of insects captured by each If we assume that the spatial distribution of trap
trap (ni) were sorted in descending order by numbers catch reßects the spatial distribution of the insect
captured. Cumulative totals (ci) and cumulative fre- population, we can then use the cumulative frequency
quencies (fi) were then calculated as indicated by the distributions derived from trap samples (Table 1) to
October 2000 ARBOGAST ET AL.: MONITORING INSECT PESTS IN RETAIL STORES 1535

Fig. 2. Spatial distribution of Indianmeal moths in department stores. Contours represent numbers captured in 50 (A, C)
or 61 (B) traps over a 4-d period.

deÞne areas in which action thresholds for pest man- basis of experience and pest management needs
agement are exceeded. A threshold can be either an (goals), were used to assign values of P to trap loca-
insect count typically associated with the maximum tions. This was done as follows: P ⫽ 0 when fi⬘ ⬎
tolerable level of damage or contamination (trap threshold and P ⫽ 1 when fi⬘ ⱕ threshold. Because P
threshold), or it can be a proportion of the pest pop- represents a probability, it can assume any value be-
ulation that must be suppressed (Brenner et al. 1998). tween 0 and 1(0 ⱕ P ⱕ 1) at various points in a store.
Thresholds, which in practice would be chosen on the Intermediate values in areas between trap locations
1536 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 93, no. 5

Fig. 3. Spatial distribution of Indianmeal moths in the pet department and adjacent areas of department store 3 during
follow-up trapping, ⬇5 wk after the Þrst trapping campaign. Contours represent cumulative numbers captured in 25 traps
after 1 h (A), 24 h (B), and 96 h (C).

were generated by interpolation during the contour- tolerable damage or some other factor, and this would
ing process (using radial basis functions in Surfer). have dictated a pest management goal of 90% sup-
Now consider an example in which our goal is to pression. In either case, for all traps with four or more
eliminate ⬇85% of the pest population represented by insects P ⫽ 1, and for all others P ⫽ 0 (Table 1).
the sample in Table 1. The target proportion (cumu- We ran contour analyses to map the spatial distri-
lative frequency fi) would be 0.85, which is most bution of P in the stores, using contour values of P ⫽
closely approximated in Table 1 by 0.851. This pro- 0.0, 0.5, and 1.0. The value of P (0 ⱕ P ⱕ 1) at each point
portion corresponds to the second of Þve traps that on these contour maps estimates the probability that
each captured four insects. All of these traps have an a trap placed at that point will capture a number of
assigned cumulative frequency (fi⬘) of 0.895, so we insects that equals or exceeds the trap threshold. The
choose 0.895 as a threshold for assigning values of 0 or contours also estimate areas occupied by various per-
one to P. This establishes our pest management goal at centages of the pest population; the percentages in
⬇90% pest suppression, and the trap threshold be- each case being determined by the threshold chosen
comes ⱖ4 insects. Conversely, we could have chosen to deÞne values of P and by the contour interval. In our
a trap threshold of ⱖ4 insects on the basis of maximum example (Table 1), we chose a threshold of 0.895, or

Table 2. Beetles captured by 40 pitfall traps in two pet stores during three, 5-d periods of trapping

Species Common name Family No. trapped % total

L. serricornea Cigarette bettle Anobiidae 147 44.3
S. paniceum Drugstore beetle Anobiidae 1 0.3
O. mercatora Merchant grain beetle Silvanidae 146 44.0
A. rectus Silvanidae 1 0.3
C. pusillus Flat grain beetle Laemophloeidae 11 3.3
Corticaria sp. Lathridiidae 1 0.3
T. castaneuma Red ßour beetle Tenebrionidae 19 5.7
T. parallelopipedum Lyctidae 1 0.3
S. oryzae Rice weevil Curculionidae 5 1.5

Storgard FLITeTRAK M2 traps baited with cigarette beetle and red ßour beetle/confused ßour beetle pheromone lures and with oat oil.
a
Count includes larvae and adults. Other counts are adults only.
October 2000 ARBOGAST ET AL.: MONITORING INSECT PESTS IN RETAIL STORES 1537

pet department, but the data were too sparse to iden-

tify foci of infestation. In department store 2 (Fig. 2B),
a single focus of infestation, associated with bagged
sunßower seeds in the pet department, became evi-
dent within 1 h. The number of captures, and the area
in which they occurred, increased steadily over the
next 4 d until the whole department was involved, but
the center remained Þxed on the sunßower seeds.
There were scattered captures elsewhere in the store,
but no additional foci could be identiÞed. The heaviest
infestation occurred in department store 3 (Fig. 2C),
where all but one capture occurred in or near the pet
department. The most intense focus of infestation oc-
curred in association with bagged birdseed on shelves
along one wall, and this was readily apparent within
the Þrst hour of trapping. After 4 d, two additional foci
appeared, one associated with birdseed and another
with items not susceptible to infestation, including cat
litter and ßea treatments. Follow-up trapping in the
Fig. 4. Mean number (⫾SE) of beetles or Indianmeal
pet department and adjacent areas (Fig. 3), showed
moths per trap captured in 40 traps in pet stores during a 5-d four well-deÞned foci of infestation that encompassed
period. There were two trapping campaigns in store 1, one shelves with birdseed, dog food, and nonsusceptible
before and another 6 mo after initiation of Gentrol treat- products (Arbogast and Mankin 1999). In all of the foci
ments. There was only one trapping campaign in store 2, of infestation, we found accumulations of infested pet
which had been treated before trapping began. When letters food and bird seed in the enclosed space between the
above any two bars within orders (beetles or moths) are not bottom shelves and the ßoor. Two of the foci were
the same, the difference between stores or trapping periods already apparent after 1 h (Fig. 3A), three after 1 d
is statistically signiÞcant (Wilcoxon signed rank test, P ⬍ (Fig. 3B), and all four after 4 d (Fig. 3C).
0.001).
Pet Stores. We found Indianmeal moths and nine
species of beetles (Table 2) in the two pet stores. Eight
⬇90% of the population, for assigning P a value of 1. of the species are commonly encountered in stored
Therefore, ⬇90% of the pest population is expected to products, and, of these, the most abundant were L.
occur inside contour 1.0 (Fig. 5C). Of the remaining serricorne, Oryzaephilus mercator (Fauvel), Tribolium
10%, ⬇5% is expected to occur between contours 0.0 castaneum (Herbst), and Cryptolestes pusillus (Schön-
and 0.5 and ⬇5% between contours 0.5 and 1.0. herr). Ahasverus rectus (Le Conte), Sitophilus oryzae
The average level of infestation in a store was ex- (L.), Stegobium paniceum (L.), and Corticaria sp. were
pressed as the mean number of beetles or moths cap- captured in smaller numbers. Most beetles captured
tured per trap during the trapping period (total cap- were adults, although we captured larvae of L. serri-
tured/number of traps). Beetles and moths were not corne, O. mercator, and T. castaneum. Trogoxylon par-
compared statistically with one another, but within allelopipedum (Melsheimer) is a wood borer com-
each group, pairwise comparisons were made be- monly intercepted from pallets by the Division of
tween stores and trapping periods, using the Wilcoxon Plant Industry, Florida Department of Agriculture and
signed ranks test in SigmaStat 2.0 (SPSS 1997). This Consumer Services (M. C. Thomas, personal commu-
nonparametric test was selected over a t-test because nication) and probably entered the store with a pallet.
the trap counts were not normally distributed. Beetle The numbers of beetles and moths captured in pet
and moth totals were accumulated from observation to store 1 were much lower after Gentrol treatments
observation, and regression analysis of the cumulative began than before (Fig. 4). Fewer beetles were cap-
totals versus time was used to examine rates of capture. tured in pet store 2 than in store 1, either before or
Regression analysis of cumulative numbers captured after treatment, but the number of moths captured in
in all traps versus time was done with SigmaStat, store 2 did not differ signiÞcantly from store 1 before
SigmaPlot 5.0 (SPSS 1998), and the REG Procedure of treatment. We have no pretreatment data for com-
SAS (SAS Institute 1988). parison in store 2, but it appears that a combination of
sanitation, stock rotation, and Gentrol applications
had prevented serious beetle infestation. There was a
Results and Discussion
serious moth infestation, but this was recently estab-
Department Stores. We found Indianmeal moths in lished and had been traced to dog food that arrived
all three department stores, but the level of infestation infested from the warehouse.
differed greatly among stores. The lightest infestation The spatial distribution of moths and beetles in the
occurred in department store 1 (Fig. 2A), where only pet stores is illustrated by the contour maps in Figs.
seven moths were captured over the 4-d period, three 5Ð7. In September 1998, there were two prominent
in the pet department and four in other parts of the foci of beetle infestation in pet store 1 (Fig. 5A). One
store. The pattern of capture suggested an origin in the (upper left in Þgure), associated with dry cat food, dry
1538 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 93, no. 5

Fig. 5. Spatial distribution of beetles in pet store 1. Contours in A and B represent numbers captured in 40 traps over
a 5-d period before and 6 mo after initiation of (S)-hydroprene applications. Contours in C and D represent corresponding
indicator values based on cumulative frequency thresholds of 0.895 (C) and 0.903 (D), which gave trap thresholds of ⱖ4 and
ⱖ2, respectively. The contours indicate the probability that the number captured in any trap will equal or exceed the trap
threshold.

dog food, and horse scratch feed along the back wall, 5B). A small focus on the back wall indicated a rem-
consisted mostly of merchant grain beetles. We found nant merchant grain beetle infestation, and the re-
adults and larvae on the ßoor under the bottom shelves maining two consisted mostly of cigarette beetles.
along with spilled food. The highest trap catch was There were two major concentrations of Indianmeal
near the horse feed, which may have been the source moths in September 1998, with lesser infestations in a
of infestation. The second focus (lower left in Þgure) back corner and in the stock room (Fig. 6A). There
consisted mostly of cigarette beetles, but the source of were fewer moths in May 1999 after Gentrol treat-
infestation was uncertain. Although there were seeds ments. The largest concentration was gone, but the
and hamster food in the affected area, the greatest others persisted (Fig. 6B).
numbers were captured near artiÞcial logs and aquar- Most of the beetles captured in pet store 2 were red
ium supplies. Peak numbers were much lower in May ßour beetles captured under shelves with canned cat
1999, about 6 mo after initiation of Gentrol treatment, food (Fig. 7A), but the source of infestation was not
and the beetles occurred mainly in three foci (Fig. determined. Moths were widespread (Fig. 7B) and
October 2000 ARBOGAST ET AL.: MONITORING INSECT PESTS IN RETAIL STORES 1539

Fig. 6. Spatial distribution of Indianmeal moths in pet store 1. Contours in A and B represent numbers captured in 40
traps over a 5-d period before, and 6 mo after initiation of (S)-hydroprene applications. Contours in C and D represent
corresponding indicator values based on cumulative frequency thresholds of 0.899 (C) and 0.758 (D), which gave trap
thresholds of ⱖ3 and ⱖ2, respectively. The contours indicate the probability that the number captured in any trap will exceed
the trap threshold.

there was a large focus of infestation in the stock room place. The resulting trap thresholds ranged from ⱖ2 to
associated with infested dog food that had been moved ⱖ4 insects, and the contours in Figs. 5 C and D, 6 C and
there to await disposal. D, and 7 C and D indicate the probability that the
In practice, as already noted, experience and pest number of insects captured by any trap will equal or
management goals would be used to determine trap exceed these thresholds. The 1.0 contours also esti-
thresholds, but for purposes of illustration, we hypo- mate the areas in which 76 Ð93% of the pest popula-
thetically set our goal at suppressing the pest popu- tions occur, depending on the cumulative frequency
lation by ⬇85%. With this goal, the assigned cumula- chosen for assigning indicator values. Thus, elimina-
tive frequencies (fi⬘) chosen for assigning values of tion of pests from these areas by control intervention
one or 0 to the indicator variable ranged from ⱕ 0.76 would be expected to achieve ⬇73Ð93% pest suppres-
to ⱕ 0.93. The average (⫾SE) was ⱕ0.87 ⫾ 0.03. This sion in the stores. If chemical control were used, the
range resulted from variation among cumulative fre- reduction in pesticide risk achieved by limiting appli-
quency distributions with pest species, time, and cation to these areas is obvious. Also, careful exami-
1540 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 93, no. 5

Fig. 7. Spatial distribution of beetles and Indianmeal moths in pet store 2. Contours in A and B represent numbers of
beetles and moths, respectively, captured in 40 traps over a 5-d period after ⬇1 yr of monthly (S)-hydroprene applications.
Contours in C and D represent corresponding indicator values based on cumulative frequency thresholds of 0.810 (C) and
0.932 (D), which gave trap thresholds of ⱖ3 and ⱖ4, respectively. The contours indicate the probability that the number
captured in any trap will exceed the trap threshold.

nation of heavily infested areas could suggest

nonchemical alternatives, such as cleaning up spills or
removing infested products.
Capture Rates. Capture rates were essentially con-
stant over the entire trapping period for both beetles
and moths in all samples, so the relationship between
days of trapping and cumulative numbers of insects
captured was described well by straight lines (Figs.
8 Ð9). Yet, there was some evidence that the rate of
capture may actually have decreased with time during
the Þrst day or two. All of the regression lines were
forced through the origin, because initially (time ⫽ 0)
there were no insects in any of the traps. When non-
zero intercepts were allowed, two of the three lines in
Fig. 8 and one in Fig. 9 had intercepts that differed Fig. 8. Cumulative trap catch of Indianmeal moths in de-
signiÞcantly from 0, which could indicate curvature of partment stores. Regression is through the origin. Numbers in
the lines near the origin. This implies that, in these parentheses following regression coefÞcients are standard er-
three instances, the rate of capture was highest im- rors. Department store 1: P ⬍ 0.01, R2 ⫽ 0.97, adjusted R2 ⫽ 0.96.
mediately after the traps were put out, but decreased Department store 2: P ⬍ 0.01, R2 ⫽ 0.82, adjusted R2 ⫽ 0.78.
with time and stabilized at a lower level. As would be Department store 3: P ⬍ 0.01, R2 ⫽ 0.98, adjusted R2 ⫽ 0.98.
October 2000 ARBOGAST ET AL.: MONITORING INSECT PESTS IN RETAIL STORES 1541

study, the moth traps regularly showed differences in

numbers captured, even when spaced only ⬇5 m
apart, enabling precise location of infestations. Part of
this precision probably stems from the limited range of
the SP-Locator pheromone dispensers. Previous stud-
ies with the SP-Locator system showed that the range
of these traps was ⬍4 m (Mankin et al. 1999). Traps of
such limited range are ideal for situations in which the
goal is not simply to detect, but also to pinpoint in-
festations.
In conclusion, contour analysis of trap counts obtained
from an array of well-placed traps yields a map of insect
infestation that provides a practical tool for monitoring
and management of storage pests in retail stores. This
tool identiÞes trouble spots, which we have referred to
as foci of infestation, and permits selection, timing, and
precision targeting of control measures to achieve max-
imum pest suppression, with minimum pesticide risk to
human health and the environment. A well-designed
trap array should cover as much as possible of the area
to be mapped, because partial coverage encourages ar-
tifact in the contour analysis. Spacing of traps within the
array should be as nearly uniform as possible to minimize
biasing the contour map by trap placement, although this
does not appear to be a serious problem. Successive
trapping campaigns, with a Þxed array of traps and com-
parison of sequential contour maps, will allow store man-
agers and pest control operators to visualize pest prob-
lems over an entire store at a glance and to monitor
changes that occur over time. Changes can be related to
time of delivery and placement of new products received
from warehouses. Sequential contour maps also indicate
the effectiveness of control measures, and along with
records of control applications and stock rotation, they
provide permanent documentation of pest problems and
their management. The length of the trapping period and
the frequency of observation can be varied according to
the needs and capabilities of the user.

Fig. 9. Cumulative trap catch of beetles and Indianmeal

moths in pet stores before and after initiation of monthly Acknowledgments
(S)-hydroprene treatments. Regression is through the origin.
Numbers in parentheses following regression coefÞcients are We are indebted to the retail store owners and managers
standard errors. (A) Numbers of beetles captured before and for making their facilities available and for their cooperation
⬇6 mo after treatments began in pet store 1. (Before: P ⬍ in the research. We are especially grateful to Betty Weaver
0.01, R2 ⫽ 1.00, adjusted R2 ⫽ 0.99. After: P ⬍ 0.01, R2 ⫽ 1.00, and Shahpar Chini, who assisted with many aspects of the
adjusted R2 ⫽ 0.99.) (B) Numbers of Indianmeal moths study; we appreciate their untiring efforts in setting up tests,
captured before and ⬇6 mo after treatments began in pet making observations, and tabulating data. We also thank
store 1. (Before: P ⬍ 0.01, R2 ⫽ 0.99, adjusted R2 ⫽ 0.99. After: Shahpar Chini for her skillful assistance in analyzing data and
P ⬍ 0.01, R2 ⫽ 0.99, Adjusted R2 ⫽ 0.98.) (C) Numbers of preparing Þgures, and for her many valuable suggestions.
beetles and Indianmeal moths captured after ⬇1 yr of Mike Thomas (Division of Plant Industry, Florida Depart-
monthly treatments in pet store 2. (Beetles: P ⬍ 0.01 R2 ⫽ ment of Agriculture and Consumer Services, Gainesville, FL)
0.97, adjusted R2 ⫽ 0.96. Moths: P ⬍ 0.01, R2 ⫽ 0.99, adjusted identiÞed specimens of T. parallelopipedum, A. rectus, and
R2 ⫽ 0.99.) Corticaria sp. We thank Rick Brenner and Nancy Epsky for
helpful discussion and suggestions. Finally, we would like to
express our appreciation to Judy Johnson, Susanne Dyby,
expected, the rate of capture was higher when the
and Don Silhacek for their critical review of an earlier
level of infestation was higher. version of the manuscript and for their helpful suggestions.
Trap Range and Precision Targeting. For spatial Research reported in this article was supported in part by
analysis, traps with a short range of attraction are funds from Pollution Prevention Project No. 1053, Strate-
desirable, because they more effectively resolve local gic Environmental Research and Development Program
components of an insect population and thus provide (SERDP), and from EPA-USDA-ARS Interagency Agree-
a sharper picture of spatial pattern. In the current ment No. DW12937600-01-0.
1542 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 93, no. 5

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