Sample Size and Selection

In 1996, approximately 23,000 cargo aircraft arrived in Miami, Florida, from foreign origins (APHIS-PPQ, unpublished), which equates to about 60 arrivals per day. To detect an infestation (= approach) rate as low as 1% with a 95% level of confidence, a sample size of 730 aircraft was selected, and two aircraft were randomly selected and inspected each day of the study period. The study was conducted over a 12-month period from 1 September 1998 to 31 August 1999. This duration would enable seasonal effects involving rainfall and temperature to be detected, at least for the most frequently sampled regions and countries.

To select samples, each day was divided into 96 quarter-hour increments. The increments were sequentially numbered with midnight to 12:14 AM being increment number one, 12:15 to 12:29 AM being increment number two, and so on. Daily, a random number table was used to select two numbers from one to 96 that corresponded to particular quarter-hour increments. The first foreign cargo aircraft scheduled to arrive during or after the selected increment was designated as a sample.

Sample Inspection Process

The regular workforce of approximately 150 APHIS-PPQ officers in Miami was specially trained and equipped to assist with this study. (Most APHIS-PPQ officers have subsequently been transferred into the newly created Department of Homeland Security, although duties relating to aircraft inspections remain unchanged.) When a sample aircraft arrived, the assigned officer immediately inspected the cockpit and galley areas for live hitchhiking organisms (i.e., insects, snails, slugs, and weed seeds). Unconsumed fresh fruits found in these areas were bagged in plastic to be examined later for commodity-associated insects and diseases. Flight crew members were asked to provide the exact time when the aircraft departed from the foreign airport from which it was arriving. The officer remained at the aircraft location throughout the cargo offloading process, during which time all surfaces of palletized cargo were inspected for hitchhiking organisms. When offloading was completed, the officer intensively examined the floors, walls, other surfaces, and air space within all cargo compartments for hitchhiking pests.

During and after the inspection, the officer recorded all pertinent information concerning the aircraft and the inspection on a specially designed data form to which were attached the cargo manifest and the U.S. Customs general declaration.

Identification of Specimens

All live specimens found associated with sampled aircraft were submitted to APHIS-PPQ local specialists for immediate identification. All determinations were made to the lowest taxon possible. When local specialists were unable to perform specific identifications, specimens were forwarded to national specialists located in Washington, DC, Beltsville, MD, Columbus, OH, and Miami, FL, depending on the type of organism intercepted. Specimens could not always be identified to the species or generic level because of the poor condition of material, lack of specialists or scientific knowledge for certain taxonomic groups, and taxonomic keys based on a single sex.

Following identification, specimens were categorized as either quarantine-significant (QS) or non-quarantine-significant (NQS). QS taxa are defined as species of plant-feeding insects, mites, or mollusks, plant-infecting pathogens, or weed seeds that are not known to occur, or are not widely distributed, in the United States. Specimens belonging to plant-feeding groups, but identified only to the family or generic level, are also placed in this category because they could potentially represent QS taxa. NQS taxa are species that are widely distributed in the United States and/or are categorized by APHIS-PPQ as not likely to pose a significant threat to U.S. agriculture, forests, and ornamentals.

We did not classify the relative risk levels of QS taxa. Instead, individual interceptions were simply grouped into one of the two categories outlined above, a practice that is widely used within APHIS-PPQ when making quarantine decisions.

Data Collection and Analysis

All data relating to the sampled aircraft were collected from specially designed data forms completed by the officers, or from official federal documents associated with the aircraft. Selected data were compiled into a local database. In addition, all data on QS taxa were recorded in the national Port Information Network (PIN) database which contains all pest interception reports since 1985. References to new records in this study imply that a given QS taxon did not appear in PIN in association with (1) aircraft as an entity, apart from any transported cargo, and/or (2) a particular U.S. port of entry, e.g., Miami.

Countries were grouped into one of the following regions for purposes of calculating regional approach rates: Central America, South America, West Indies, Europe, and Other. Trinidad was considered to be part of South America, not the West Indies, in keeping with other federal practices. Mexico was included among Central American countries. Canada and Taiwan were grouped in the artificial category “Other”.

A comparison of data for aircraft loaded during daylight hours versus those for aircraft loaded at night was made to determine if bright lights necessary for nighttime cargo operations attracted nocturnal fliers, thus increasing approach rates. The comparison was difficult because the precise time during which aircraft are loaded at the point of origin is not recorded by airline personnel. Aircraft logbooks, however, consistently reflect the time at which aircraft depart. Our experience at Miami International Airport has shown that commercial aircraft nearly always depart immediately after cargo loading is complete. Time of departure was therefore used as a close approximation of the time when cargo was loaded. Aircraft with departure times between 7:00 AM and 7:00 PM were considered to be loaded during daylight hours, while those departing between 7:00 PM and 7:00 AM were considered to be night-loaded. Efforts were focused on cargo aircraft arriving from Central America since approach rates from this region were substantially higher than those observed from any other. Departure times for seven aircraft from this region were not available. Temporal analyses also were performed on the Auchenorrhyncha, Noctuidae and Scarabaeidae found. These three groups were repeatedly intercepted during the study and are either primarily nocturnal or generally attracted to lights. Each was examined to determine if time of loading had any effect on their presence as hitchhikers.

To determine if certain types of cargo were more attractive to hitchhiking organisms, the commodities being transported were divided into two broad categories, regulated and non-regulated, with the approach rates of each examined. Regulated cargoes are agricultural in nature and are generally inspected on arrival by APHIS-PPQ. Plants or plant products make up the bulk of these items. Non-regulated cargoes are miscellaneous items not considered to be derived from agricultural sources.

Investigations into potential aspects of seasonality were restricted to Central America since aircraft arriving from that region experienced a far greater approach rate than did aircraft from any other region. Central America has essentially two seasons, wet and dry (Alfaro 2000). The onset of the wet season varies slightly from year to year but begins around May and lasts for approximately six months. For the purposes of our analyses, we considered the wet season to be from 1 May through 31 October, and the dry season to be from 1 November through 30 April. Aircraft were grouped into one these two categories and the approach rate for each was examined.

The G-test of independence (Sokal & Rohlf 1981) was used to determine if the presence of QS organisms in sampled cargo aircraft varied independently of or was correlated with (1) the time of departure from foreign origins, (2) the nature of the cargo loaded aboard and (3) the season of departure. For the time and season of departure, only the data pertaining to aircraft originating in Central America were included in the G-test. Regarding the nature of cargo, sampled aircraft from all geographic regions were included. In all cases, G values were adjusted by Williams’ correction for 2 × 2 contingency tables (Sokal & Rohlf 1981) and then compared with the critical value of chi square at the 5% significance level and 1 degree of freedom.

Approach Rates by Region and Country

Aircraft were sampled from 38 countries during the study, with QS organisms detected in aircraft arriving from 17 of these. The overall pest approach rate for foreign cargo aircraft arriving at Miami International Airport was 10.4% (Table 1). The approach rate for Central America (23.2%) was substantially greater than rates observed for any other region. Aircraft from all sampled countries in Central America contained QS organisms. Approach rates for individual countries within Central America varied slightly, with Costa Rica, El Salvador, Guatemala, and Honduras all greater than 23%. Mexico and Panama were approximately 10 percentage points lower. The approach rate for Nicaragua was substantially greater (50%), although this figure might be less reliable than others for the region due to the comparatively smaller sample size. The mean approach rate of more than 23% was at least four times that seen from any other region.

Approach rates for South American countries ranged from 0 to 15.9%, with a mean of 5.8%. Aircraft from six of the ten sampled countries contained QS pests. Small sample sizes for Argentina (7), Bolivia (4), and Uruguay (1) produced questionable approach rates for these countries. Ecuador had the highest approach rate for the region, followed by Trinidad. Rates observed for Peru and Colombia were noticeably lower. The approach rate for Argentina was also quite high, although the sample size (7) was relatively small. More aircraft were sampled from Colombia (155) than from any other country during the study, reflecting the tremendous volume of goods it exports to Miami. Most of those aircraft transported perishable cut flowers that could be attractive to phytophagous pests but, despite that, the observed approach rate almost equaled the mean rate for the region. Large numbers of aircraft from Brazil, Chile, and Venezuela were sampled, but very few were infested.

Approach rates for countries within the West Indies also varied considerably, ranging from 0 to 18%. Infested aircraft originated from just three countries in the region-Jamaica, Haiti, and the Dominican Republic. The approach rate for Haiti (18%) was more than twice that of any other country in the region, albeit from a comparatively small sample size of 11. In contrast, Bahamas and the Dominican Republic, the two countries in the region with the largest number of sampled aircraft, had lesser approach rates of 0 and 2.9%, respectively.

We made no inferences about approach rates for other regions because sample sizes were usually small. The lone infested aircraft from France can be called into question. The scarab beetle found on board belonged to a genus (Dyscinetus) known only from the Western Hemisphere (Endrödi 1985). More likely, this insect actually entered the aircraft during a fueling stopover in Canada. In general, more data are necessary to better understand the risks associated with cargo aircraft from these areas.

Diversity of Intercepted Taxa

Various QS organisms were intercepted from infested aircraft samples. In total, 151 insects from 33 families in five orders were represented, along with one plant pathogen (citrus canker in aircraft stores from Argentina) (Table 2). All insect specimens were adults except two. A larva of Crocidosema aporema (Walsingham) was found in the emptied hold of an aircraft from Guatemala and likely originated from boxes of beans on board. In the second case, a tettigoniid nymph was found aboard an aircraft transporting fruits and live plants from Costa Rica.

Lepidoptera comprised the largest single component of captured specimens, followed closely by Coleoptera (Fig. 1). These findings generally agree with those of Frank & McCoy (1992), who noted that the two most numerous orders of nonindigenous organisms reported new to Florida since 1971 were Lepidoptera and Coleoptera. Conspicuous by their absence were interceptions of Diptera and Hymenoptera. Members of these orders might be comparatively less attracted to light, QS groups such as leafminers and gall midges tend to be difficult to detect due to their small size, and relatively few QS taxa occur in these orders.

A sizable number of organisms intercepted during the study represented new records for APHIS-PPQ. These are denoted with superscripts in the list of taxa (Table 2). Of the 151 pests identified from infested aircraft, 32 (21%) belonged to taxa that had not previously been intercepted in cargo or passenger aircraft at U.S. ports of entry. Moreover, 13 (9%) of them had never been intercepted in conjunction with any pathway of entry.

Pests Per Infested Aircraft

Officers intercepted 151 QS organisms from the 73 infested aircraft. Some of these aircraft contained multiple organisms. The data indicate an inverse curvilinear relationship between the number of infested aircraft and the number of QS taxa per infested aircraft (Fig. 2). Accordingly, 59% of the infested aircraft had only one QS taxon, while 41% contained more than one, including one aircraft with 18. No other aircraft had more than seven QS pests.

Some infested aircraft harbored multiple individuals of the same taxon. For example, one aircraft sample contained a male and female of Tomarus(Coleoptera: Scarabaeidae). In such situations, the risk of establishment would presumably increase due to the presence of potential mating pairs.

Diurnal Patterns

Approach rates for all insect groups combined were not significantly different (G-test for independence; p > 0.05) for day versus night loading (Table 3). This apparent lack of correlation between time of loading and the presence of QS organisms suggests that APHIS-PPQ should continue to monitor cargo aircraft throughout the day.

Approach rates for the three primarily nocturnal groups also were not significantly different (G-test for independence; p > 0.05) for day versus night loading (Table 4). The daylight condition during which loading took place was independent of Noctuidae, Scarabaeidae, and Auchenorrhyncha later being found aboard the aircraft. These results are somewhat surprising because these groups are generally attracted to lights. In explanation, some actual loading times might have differed substantially from recorded departure times. Also, some nocturnal hitchhikers might have entered aircraft during nighttime loading operations and subsequently made several round trips before being detected and incorrectly associated with day-loaded aircraft.

Nature of Cargo

Demonstrating that higher approach rates result when cargo aircraft transport particular types of cargo might enable APHIS-PPQ managers to assign greater priority to inspection of those aircraft. Analysis of the data (Table 5), however, showed that approach rates for cargo aircraft were not dependent on whether regulated or non-regulated cargo was being transported (G-test for independence; p > 0.05). These results point to the need to inspect all foreign cargo aircraft arriving at Miami International Airport, regardless of the type of cargo being transported. Despite these results, though, it is conceivable that particular commodities, regulated and non-regulated alike, might serve to attract specific kinds of hitchhiking pests both before and during the cargo aircraft loading process. We note that 65% of the cargo aircraft sampled contained regulated agricultural material.

Seasonality Patterns

Monthly approach rates for aircraft from all origins were consistently greater in the spring and summer, with additional isolated peaks of 10% or greater in October and December (Fig. 3). QS organisms arrived at Miami International Airport via foreign cargo aircraft during all months of the year.

A pattern of seasonality emerged for Central America, but not for other regions. The infestation pattern for Central America (Fig. 4) resembled that for all regions combined (Fig. 3). Distinct peaks occurred in October and May, with the infestation percentage from April through August remaining at a generally high level. Unlike the pattern for all regions, however, the peak in October was as great as that in May. Approach rates for cargo aircraft arriving from Central America were significantly greater during the wet season there (about 29% from May through October) than during the dry season (about 16% from November through April) (G-test for independence; p < 0.05) (Table 6). Despite this seasonal difference, rates during the dry season were not low enough, in our opinion, to warrant deployment of personnel away from this pathway. Only in September and November did the percentage of infestation fall below 10 (Fig. 4). Additionally, there were two distinct peaks in January and April.

The pattern of total numbers of QS organisms per month (Fig. 5) largely resembled that for the percentage of infested aircraft per month (Fig. 3). The results for June, however, differed markedly. The percentage of infested aircraft for June was only moderate (Fig. 3), but the number of pests was exceptionally large (Fig. 5). This difference is attributable to an unusually large number of intercepted organisms (18) aboard a single aircraft from El Salvador (see Fig. 2).

We recognize that oceanographic and atmospheric factors, combined with latitude, influence when the wet and dry seasons begin and end annually in Central America (Alfaro 2000). Given these, it would be beneficial to gather multiple years of data for this region to improve understanding of any seasonality patterns. To obtain a similar understanding for the West Indies, much greater numbers of cargo aircraft would have to be sampled annually from a larger number of island countries. It might be more difficult to elucidate seasonal patterns for South America due to its wide spectrum of topography, vegetation, latitudes, and bodies of water.