SAMPLING AND BIOSTATISTICS Effective Sampling Range of a Synthetic Protein-Based Attractant for Ceratitis capitata (Diptera: )

NANCY D. EPSKY,1 HERNA´ N R. ESPINOZA,2 PAUL E. KENDRA, ROBERT ABERNATHY,3 4 DAVID MIDGARDEN, AND ROBERT R. HEATH

USDAÐARS, Subtropical Horticulture Research Station, 13601 Old Cutler Road, Miami, FL 33158

J. Econ. Entomol. 103(5): 1886Ð1895 (2010); DOI: 10.1603/EC09286 ABSTRACT Studies were conducted in Honduras to determine effective sampling range of a female-targeted protein-based synthetic attractant for the Mediterranean fruit ßy, Ceratitis capitata (Wiedemann) (Diptera: Tephritidae). Multilure traps were baited with ammonium acetate, pu- trescine, and trimethylamine lures (three-component attractant) and sampled over eight consecutive weeks. Field design consisted of 38 traps (over 0.5 ha) placed in a combination of standard and high-density grids to facilitate geostatistical analysis, and tests were conducted in coffee (Coffea arabica L.), mango (Mangifera indica L.), and orthanique (Citrus sinensis ϫ Citrus reticulata). Effective sampling range, as determined from the range parameter obtained from experimental variograms that Þt a spherical model, was Ϸ30 m for ßies captured in tests in coffee or mango and Ϸ40 m for ßies captured in orthanique. For comparison, a releaseÐrecapture study was conducted in mango using wild (Þeld-collected) mixed sex C. capitata and an array of 20 baited traps spaced 10Ð50 m from the release point. Contour analysis was used to document spatial distribution of ßy recaptures and to estimate effective sampling range, deÞned by the area that encompassed 90% of the recaptures. With this approach, effective range of the three-component attractant was estimated to be Ϸ28 m, similar to results obtained from variogram analysis. Contour maps indicated that wind direction had a strong inßuence on sampling range, which was Ϸ15 m greater upwind compared with downwind from the release point. Geostatistical analysis of Þeld-captured in appropriately designed trapping grids may provide a supplement or alternative to releaseÐrecapture studies to estimate sampling ranges for semiochemical-based trapping systems.

KEY WORDS Mediterranean fruit ßy, spatial statistics, geostatistics, variogram, contour analysis

Detection and monitoring systems are critical com- laboratory- or factory-produced colonies, and result- ponents of control and eradication programs for pest ant data from these studies provide information tephritid fruit ßies worldwide (IAEA 2003). These needed for the sterile technique (Hendrichs et systems use attractants, including the parapheromone al. 2002). However, the behavior of sterile ßies may or trimedlure, which capture males of the Mediterranean may not be directly applicable to the behavior of fruit ßy, Ceratitis capitata (Wiedemann) (Diptera: Te- fertile laboratory-reared or wild ßies. In tests with phritidae), and protein-based baits and lures, which traps baited with trimedlure, Wong et al. (1982) found capture male and female C. capitata as well as other higher recapture of sterile C. capitata than wild C. tropical tephritid pest (IAEA 2003). ReleaseÐ capitata with a decrease in recapture of sterile ßies recapture studies traditionally have been used to de- with an increase in irradiation dosage, but no differ- termine aspects of fruit ßy dispersal (Severin and ences in distanceÐresponse curves. Fletcher and Hartung 1912) and trap sensitivity (Calkins et al. 1984, Economopoulos (1976) found that, in studies with Baker et al. 1986, Cunningham and Couey 1986, Lance protein-baited glass McPhail traps, there was wider and Gates 1994). These often use sterile ßies from dispersal of wild olive fruit ßies, Bactrocera oleae (Gmelin), than sterile ßies. Wild ßies used for releaseÐrecapture studies are This article reports the results of research only. Mention of a typically obtained from larval-infested fruit. Adults are proprietary product does not constitute an endorsement or recom- mendation by the USDA. given proteinÐsugar laboratory diet and are held for 1 Corresponding author, e-mail: [email protected]. various times to allow for sexual maturation and mat- 2 Fundacio´n Honduren˜ a de Investigacio´n Agrõ´cola, La Lima, ing before their release in the Þeld. With male C. Corte´s, Honduras. capitata, there is no difference in immature versus 3 Current address: Department of Chemistry and Biochemistry, University of Colorado, Boulder, CO 80309. mature response to trimedlure (Shelly and Pahio 4 Current address: USDAÐAPHISÐIS, Sao Paulo, Brazil 04709 110. 2002). However, female-targeted attractants are based October 2010 EPSKY ET AL.: SAMPLING RANGE FOR C. capitata 1887 on food needs, oviposition needs, or both so the phys- (two-component attractant; Epsky et al. 1995, Heath iological state and nutritional requirements of the ßy et al. 1995). Effective sampling range of the two-com- probably affect response to traps and lures (Rull and ponent attractant was 30 m for feral (fertile) females Prokopy 2000). Female tephritids are sexually imma- but only 20 m for sterile females. To date, there have ture at eclosion and require dietary protein for ovary been no published reports addressing effective sam- development and egg production (Wheeler 1996). pling range of ammonium acetate and putrescine in This protein requirement underlies the attraction of combination with trimethylamine (three-component females to ammonia (Christenson and Foote 1960, attractant, Heath et al. 1997) for capture of C. capitata. Bateman and Morton 1981), to diamines such as pu- Due to potential compromises with the use of labo- trescine and cadaverine (Kendra et al. 2008) and to ratory-reared fertile or sterile ßies in releaseÐrecap- liquid protein baits (e.g., torula yeast and Nulure). ture experiments, we conducted studies to estimate Olfactory response to ammonia, as measured by elec- sampling range of the three-component attractant troantennography (EAG), also is related to ovarian based on captures of wild C. capitata and data analysis development in females of the Caribbean fruit ßy, with a geostatistical (or spatial statistical) approach. suspensa (Loew), with peak EAG response There is increasing use of geostatistics for many to ammonia immediately preceding peak vitellogen- aspects of insect ecology (Liebhbold et al. 1993) and esis, i.e., synthesis of yolk protein (Kendra et al. 2005, insect pest management (Brenner et al. 1998). Trap 2006). Age and access to food have been shown to counts and trap locations within a trapping array are affect responses of C. capitata adults to protein baits used to determine underlying spatial patterns for use (Kouloussis et al. 2009) and adults of the apple maggot, in population prediction at unsampled locations or to Rhagoletis pomonella (Walsh), to host fruit-based and identify sources of infestation. In addition to local protein-based lures (Reynolds and Prokopy 1997). statistics and autocorrelation, spatial patterns also may Female Anastrepha ludens (Loew) have a lower pro- be characterized by variogram analysis, which plots tein requirement for egg production (Robacker 1991, variance against every pairwise distance sampled, and 1998; Cresoni-Pereira and Zulcoloto 2001) and are less these distances are grouped into lag classes. The shape responsive to protein baits than female Anastrepha of an experimental variogram, i.e., the variogram ob- obliqua (Macquart) (Dõ´az-Fleischer et al. 2009). Ster- tained from trap counts, provides estimates of several ile females have limited ovary development and lack spatial autocorrelation parameters. These include the mature eggs (Walder and Calkins 1992); thus, they nugget variance (C0), which is the error inherent in may be less responsive to protein-based baits than the measurement (experimental error or y-intercept ϩ fertile females. in the model); the sill (C0 C), which quantiÞes the An important aspect of trapping efÞciency is effec- spatial intensity pattern or traditional sample variation tive sampling range, strictly deÞned as the maximum (the model asymptote); and the range (A, also called distance from which an insect can reach an attractive effective range to distinguish it from the range pa- source in a given time (Wall and Perry 1987). Infor- rameter A0), which is the separation distance over mation about the effective sampling range of a speciÞc which the samples are autocorrelated (Robertson trapÐlure combination is valuable for determining ap- 2008) and indicates where the samples are spatially propriate coverage of traps for use in population de- inßuenced by the same underlying process (Liebhold limitation, mass trapping control strategies, or identi- et al. 1993, Fleischer et al. 1999, Fortin et al. 2002). Þcation of foci of infestation for precision targeting of Dungan et al. (2002) noted that spatial structure re- control measures (Mankin et al. 1999, Arbogast et al. ßects both the physical structure of a system, affected 2000). It also aids in determination of the minimal by factors such as topography, hydrology, and soil type distance between adjacent traps to avoid trap inter- and also the spatial characteristics of the processes ference (Wall and Perry 1978). Mature female R. that act upon it. These processes themselves have two pomonella responded to host tree models without components, the distance at which it can act (range of host-based lures that were up to 1.5 m away from point action or effective range), and the area that is affected. of release and to host tree models with host-based They use the example of allelopathic chemical release lures that were up to 2.5 m away from the point of affecting the surrounding lichen population; however, release (Green et al. 1994). Despite extensive use of it also may apply to chemical release from a baited protein-based, female-targeted attractants in current trap. Abiotic factors inßuencing spatial effect of a trapping programs for tropical tephritids (Heath et al. trapping system would include the volatility (release 2007, Thomas et al. 2008), there is little documentation rate) of the chemical attractant, as well as the envi- on effective sampling range for protein-based lures. ronmental conditions, such as ambient temperature, Delrio and Zu¨ mreog˘lu (1983), based on release/re- wind speed, and wind direction. Also affecting the capture studies with C. capitata, estimated a trapping trapping system are factors determined by the neu- range of 10 m for traps containing wicks saturated in rophysiology of the target insect, such as the binding buminal, a protein hydrolysate. For A. suspensa, Ken- afÞnity of the attractant chemicals to antennal olfac- dra et al. (2010) combined releaseÐrecapture tech- tory receptors and the threshold needed to elicit an niques with contour analysis of trap catch to estimate orientation response. effective sampling ranges for a liquid protein bait We conducted studies in Honduras to determine (torula yeast/borax) and for a protein-based synthetic whether the range parameter from an experimental lure containing ammonium acetate and putrescine variogram of Þeld-captured fruit ßies could be used to 1888 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 103, no. 5 estimate effective sampling range of the protein-based synthetic attractant. Trapping studies were conducted in coffee (Coffea arabica L.), mango (Mangifera indica L.), and orthanique (Citrus sinensis ϫ Citrus reticu- lata) farms with populations of C. capitata (Espinoza et al. 2007). For comparative purposes, we also con- ducted a releaseÐrecapture study using Þeld-collected C. capitata. Adult ßies were released (within 24 h of capture) from a single point in the center of a trap array in a mango orchard that was not in fruit during the spring 2008 studies because it had been heavily trimmed in the fall 2007 as part of orchard renovation activities. Contour analysis was performed to docu- ment spatial distribution of ßy recaptures and to pro- Fig. 1. Placement of traps in a coffee farm in Honduras vide an independent estimate of sampling range. for Þeld tests of sampling range of a synthetic food-based synthetic attractant. Design was a combination of a standard 5 by 5 trapping grid (open circles) and a high-density trap- Materials and Methods ping grid (closed circles). The entire trapping grid was Traps and Lures. All studies were conducted with placed at least 20 m from any edge of the coffee Þeld. The y-axis presents distance between traps within a row, and the Multilure traps (Better World Manufacturing Inc., x-axis presents distance between rows of coffee trees. Fresno, CA), which are plastic McPhail-type traps (17 cm in diameter at its widest point), each with a yellow base (7 cm in height) and a clear top (11 cm in height). male, male and total (female plus male) C. capitata Traps were baited with a three-component (ammo- were recorded along with the location of each trap. nium acetate, putrescine, and trimethylamine) syn- Sexual maturity of the captured ßies was not deter- thetic protein-based attractant (BioLure, Suterra mined. LLC, Bend, OR). To retain captured ßies, 300 ml of an The mean number (ßy per trap per week), standard aqueous solution of 0.01% of the surfactant Triton deviation and variance were determined for each site (Union Carbide, Danbury, CT) was added to the base and sample week. The coefÞcient of dispersion (CD) of each trap. Lures were replaced after 4 wk, and was determined from the variance/mean ratio (Taylor surfactant solution was added as needed to maintain a 1984) for female C. capitata and was used to determine level of 300 ml. Traps without retention ßuid were the index of dispersion [I␦ ϭ (N Ϫ 1) ϫ CD] to test used to collect live ßies for use in the release/recap- for departure from random distribution by exclusion ture experiment. from 95% conÞdence interval bounded by ␹2 with n Ϫ Field Test. Trapping studies were conducted in 1 degrees of freedom (Davis 1994). Experimental var- three sites with C. capitata hosts. One site was a coffee iogram parameters were produced using GS Plus farm (ÔBorbo´n,Õ Rene´ Martõ´nez Farm; 1,280-m altitude; (Gamma Design Software, LLC, Plainwell, MI). GS 14:09:23.79Њ N, 88:01:18.72Њ W) located in Marcala, Plus Þts the experimental variogram to one of four Departmento de La Paz, Honduras. Besides coffee, isotropic models: the spherical model, a modiÞed qua- this farm has only Inga sp. as shade trees and Citrus dratic function in which the range parameter speciÞes (seed trees of unknown cultivar). The second site was the distance at which pairs of points are no longer a mango orchard (ÔHadenÕ) that also was located in autocorrelated and the variogram has reached an as- Marcala but in the Comayagua Valley. The third site ymptote; the exponential and Gaussian models in was an orthanique orchard at Municipio Santa Cruz de which the range parameter is the distance at which the Yojoa, Department of Corte´s. Standard 5 by 5 trapping sill is within 5% of the asymptote; and the linear model, grids were installed at all sites, with the 25 traps placed which is a straight line variogram and the range pa- Ϸ12, 15, or 20 m apart in alternating rows that were rameter is deÞned as the distance for the last lag class. Ϸ12, 15, or 20 m apart in coffee (Fig. 1, open circles), The relationship between the effective range (A) and mango or orthanique, respectively. To prevent edge the range parameter (A0) for each model are spherical ϭ ϭ 0.5 ϭ effects, no traps were placed closer than 20 m from the A A0, gaussian A 3 A0, exponential A 3A0; and edge of the Þeld. A high-density trapping grid was linear in which there is no effective range because superimposed over the standard trapping grid by add- autocorrelation occurs across the entire range sam- ing 13 traps to the center of the plot so that the traps pled (Robertson 2008). Data from all lag classes (Ta- in the interior section of the grid were half the distance ble 1) were used in this analysis, because the purpose apart as spacing in the standard grid (Fig. 1, closed was to describe the spatial relationships not to esti- circles). The purpose of the high-density trapping grid mate values at unsampled locations (Midgarden et al. was to increase the number of pairs of traps in prox- 1993). imity to improve estimates of spatial autocorrelation Release and Recapture Study. A release and recap- (Tobin 2004). Studies were initiated 8 March 2007, 21 ture experiment with Þeld-collected wild C. capitata April 2008, and14 May 2008 in coffee, orthanique, and was conducted in 2008 in a mango (ÔHadenÕ) orchard mango, respectively. Traps were sampled weekly for (630-m altitude; 14:20:00.48Њ N, 87:40:06.58Њ W) lo- 8 wk. Captured ßies were sexed, and numbers of fe- cated in La Paz, Departmento de La Paz, Honduras. October 2010 EPSKY ET AL.: SAMPLING RANGE FOR C. capitata 1889

Table 1. Mean distance between pairs of Multilure traps baited with synthetic food based lures and number of pairs used to de- termine variogram model

Mean distance between No. pairs Lag pairs (m) distance Orthanique, Orthanique, Coffee Coffee mango mango 1 6.00 6.00 14 14 2 13.79 11.49 93 100 3 20.58 17.15 31 31 4 25.26 21.03 100 109 5 31.23 25.95 51 55 Fig. 2. Number of ßies (females plus males) captured per 6 37.81 31.49 97 104 7 44.41 37.01 31 31 trap per day in tests conducted for eight consecutive weeks 8 49.88 41.61 97 102 (sample week). Tests were conducted in Honduras. were captured in Multilure traps baited with ammonium acetate, putrescine and trimethylamine. Tests were con- ducted in shaded coffee (solid line, solid triangle), or- Trees in this orchard had been pruned severely in 2007 thanique (dotted line, asterisk), and mango (dashed line, as part of renovation practices, so no fruit was pro- open diamond), and there were 38 traps per test. duced in the 2008 season (H.R.E., unpublished data). Use of this Þeld insured that fruit would not be threat- ened by the C. capitata release and that only released determine an appropriate interpolation method (Ar- ßies would be captured. Traps, baited with the three- bogast et al. 2000, 2006), and two types of contour map component attractant, were set Ϸ10, 20, 30, 40, and were generated. Maps based on mean capture per trap 50 m from a central release point in the four cardinal gave a visual representation of the strict sampling directions, forming a 20 trap transect (Delrio and range (distance at which at least one ßy was cap- Zu¨ mreog˘lu 1983). Traps were placed initially in the tured). Maps based on cumulative frequency of cap- Þeld 48 h before the Þrst release, and traps were tures (i.e., cumulative percentages) provided a means checked to conÞrm no capture of nonreleased ßies of estimating effective sampling range. For the latter, immediately before the release. After sampling, traps data were transformed by Þrst sorting the traps in remained in the Þeld for 24 h and were checked descending order by number of ßies captured and immediately before the next release to conÞrm no then calculating cumulative totals and corresponding background capture of nonreleased ßies. Flies for re- cumulative frequencies (Arbogast et al. 2000). The lease were obtained by placing traps baited with the cumulative frequency indicates the proportion of the three-component attractant but without retention liq- total catch represented by the combined catch of traps uid in a peach, Prunus persica (L.) Batsch ÔDiamanteÕ with an equal or greater number of insects. Effective orchard (1,180-m altitude; 14:11:08.68Њ N, 88:01:39.04Њ sampling range was deÞned as the radius of a circular W) located Ϸ42 km from the release site. Traps were sampling area in which 90% of the recaptures occurred sampled after 24 h, and live ßies were transferred to (Kendra et al. 2010) and that distance was represented large plastic bags. Bags with ßies were kept in a cooler on contour maps as the level with a value of 0.9 cu- with ice for immediate transport to the release site. mulative frequency. Flies were counted and then released at the center of the mango orchard. Releases were replicated three Results times, with 122 ßies on 25 April, 130 ßies on 1 May, and 134 ßies on 8 May. Traps were checked after 6 d, and Average (ϮSD) numbers of total C. capitata cap- the number of ßies per trap was recorded. tured per trap per week over the 8-wk study period To evaluate sampling range, numbers of ßies cap- were 8.9 Ϯ 12.6, 4.0 Ϯ 4.6, and 2.2 Ϯ 3.3 ßies in coffee, tured were summed for all traps within each of Þve orthanique, and mango, respectively. Numbers cap- distance groups (10, 20, 30, 40, and 50 m from release tured were similar at all three sites for the Þrst 3 wk of point), and relative trapping efÞciency (percentage of the study but were higher in coffee for the last 5 wk ßies captured within each distance group) was used (Fig. 2). Females comprised 60.8 Ϯ 25.9% of the cap- for subsequent analysis (Epsky et al. 1999, Kendra et ture in coffee but increased to 76.9 Ϯ 29.6% in mango al. 2010). Effect of distance from release point on and 89.5 Ϯ 20.3% in orthanique. SigniÞcant departure relative trapping efÞciency was analyzed using one- from random distribution, as indicated by calculating way analysis of variance (ANOVA) (Proc GLM, SAS I␦, was used to determine distribution of C. capitata Institute 2000) followed by least signiÞcant difference captured at each location and each sample week. Ag- (LSD) mean separation (P ϭ 0.05). The need to trans- gregated distributions were found for all 8 wk for tests form the data was assessed before analysis to meet the conducted in coffee and orthanique but in only the assumption of equal variance (Box et al. 1978). Þrst 4 wk for tests in mango. In addition an estimate of sampling range was ob- Experimental variograms of total ßy captures were tained from contour analysis using Surfer 8.05 (Golden Þt by the spherical model for nine of the 24 wk sam- Software, Inc., Golden, CO). Kriging and radial basis pled (Table 2). Effective range estimated by vario- functions (multiquadric algorithm) were compared to grams from test models for the coffee and mango sites 1890 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 103, no. 5

Table 2. Effective sampling range as estimated from variogram models from total (females plus males) C. capitata per trap per week captured in field tests conducted in three fruit fly host sites in Honduras

Spatial range (m) Host Model n r2 (min.Ðmax.) Effective range (m) (mean Ϯ SD) Coffee Exponential 1 4.4 0.088 13.2 Gaussian 2 19.9 Ϯ 10.2 0.553Ð0.722 34.5 Spherical 5 32.6 Ϯ 4.8 0.453Ð0.691 32.6 Mango Gaussian 3 41.0 Ϯ 6.2 0.768Ð0.856 71.0 Linear 2 41.6 Ϯ 0.0 0.142Ð0.851 Nonea Spherical 3 29.4 Ϯ 25.4 0.204Ð0.780 29.4 Orthanique Exponential 2 64.3 Ϯ 6.0 0.721Ð0.740 192.2 Gaussian 5 32.3 Ϯ 4.6 0.823Ð0.930 56.0 Spherical 1 44.9 0.565 44.9

Multilure traps (38 traps over 0.5 ha) were baited with ammonium acetate, putrescine, and trimethylamine (three component BioLure). Effective range deÞned as range over which there is spatial autocorrelation equals spatial range for data Þtting spherical models; 30.5 times spatial range for data Þtting gaussian models; 3 times spatial range for data Þtting exponential models. a Cannot be estimated from linear models because range equals largest lag distance. was Ϸ 30 m. It increased to Ϸ40 m for the orthanique Ϸ50% of all captures (Fig. 4B). Effective sampling site, but this was from only 1 wk of the 8 wk sampled. range, as indicated by the contour level with value of When female and male captures were analyzed sep- 0.9 in Fig. 4B, also varied by direction from release arately, effective ranges were 33.6 Ϯ 4.1 (four of 24 point: north, 28 m; northeast, 30 m; east, 18 m; south- wk) and 31.0 Ϯ 18.0 (nine of 24 wk), respectively, over east, 16 m; south, 15 m; southwest, 38 m; west, 40 m; and all three sites. Effective range for total ßy capture from northwest, 42 m. Mean effective range of the three- the gaussian models increased from Ϸ35 m in coffee to component attractant was 28.4 Ϯ 11.1 m. Contour 56 m in orthanique and 71 m in mango. The estimates analysis based on interpolation with the multiquadric from the fruit tree sites and the effective range from algorithm gave a better Þt to the data compared with the exponential model in orthanique (192 m) are all interpolation with kriging. Contours based on cumu- extrapolations beyond the distance sampled (Ϸ42 m). lative frequency of captures damped out effects of The effective range for the exponential model in cof- isolated captures and were better indicators of overall fee was the smallest estimate (13 m) and effective trends. A spherical model was the best Þt of recapture range cannot be determined from the linear models in data from the releaseÐrecapture study, with an esti- mango. Thus, the best estimate of effective sampling mated range of 22.5 m (r2 ϭ 0.552). range is 30 m, the range obtained from the spherical models in coffee and mango. Discussion Release and Recapture Study. No C. capitata were captured in traps sampled before each release; so, all Sampling range traditionally has been determined ßies captured during the study were assumed to be with releaseÐrecapture studies by using laboratory- experimentally released ßies. Approximately 26% of the ßies released were recaptured after 6 d. Distance from the release point affected capture (F ϭ 36.52; df ϭ 4, 10; P Ͻ 0.0001), with most of the ßies recap- tured in traps located 10 m from the release point (Fig. 3). The next highest percentage recapture was in traps located 30 m from the release point, with intermediate capture in traps 20 and 40 m from the release point. The lowest capture was in traps located 50 m from the release point, and this represented ßies recaptured in the last release only. Figure 4 presents contour maps illustrating the spa- tial distribution of recaptures. Despite a symmetric arrangement of traps around the release point, the contour levels indicative of ßy dispersal were not distributed concentrically about that point. Captures were considerably higher north and west of the re- Ϯ lease point compared with captures south and east. Fig. 3. Relative trapping efÞciency (mean SE) of traps Strict sampling range, represented by the contour placed 10, 20, 30, 40, and 50 m in the four cardinal directions from the point of release of wild C. capitata in a releaseÐ level with a value of 1.0 in Fig. 4A, varied from 20 m recapture study conducted in a mango orchard in Honduras. east to 40 m west of the release point, with several Flies were captured in Multilure traps baited with ammo- isolated captures to the south. The area of highest nium acetate, putrescine and trimethylamine within6dof capture was located directly north of the release point, release (n ϭ 3). Bars topped with the same letter are not 10 m in the upwind direction. This area accounted for signiÞcantly different. October 2010 EPSKY ET AL.: SAMPLING RANGE FOR C. capitata 1891

ever, this single trap seemed to function as a “sink” that restricted ßy dispersal. This likely resulted in an un- derrepresentation of captures in more distant traps and thereby a reduction in the calculated efÞciency of traps beyond 10 m. Therefore the more reliable esti- mate of effective sampling range was 28 m, as deter- mined from contour analysis of the releaseÐrecapture data. The spherical variogram model from the releaseÐ recapture study gave a more conservative estimate of sampling range at 23 m. These estimates, which are for mixed-sex captures of C. capitata, are slightly lower than the sampling ranges of 30Ð35 m, obtained from the spherical variogram models from capture of fe- males, males and total ßies the Þeld tests in coffee and total ßies in mango, and 40 m obtained in the Þeld test in orthanique. Flies in the releaseÐrecapture study were not sexed either before release or after recap- ture. However, previous studies have documented fe- male-bias in traps baited with the three-component attractant (Epsky et al. 1999, Espinoza et al. 2007). Therefore, although there were probably more fe- males than males among the released ßies, there was little difference in effective trapping range for females versus male ßies as determined by capture in the Þeld tests. There were environmental/habitat differences among the sites and studies that may account for some of the differences in sampling range estimates. Dif- ferences in tree canopy, fruit phenology, availability of alternate food sources, ambient temperature and wind currents are a few of the factors that have been shown to affect fruit ßy response to traps (Aluja et al. 1993, Fig. 4. Contour maps illustrating mean spatial distribu- Rull and Prokopy 2000, Katsoyannos et al. 1998). The tion of wild C. capitata captured in a releaseÐrecapture study coffee trees presented a continuous canopy within a conducted in a mango orchard in Honduras. Flies were cap- row, and there were shade trees that further restricted tured in Multilure traps (closed circles) baited with ammo- air movement within that site. The canopies in the nium acetate, putrescine, and trimethylamine within6dof fruit tree sites were more open, and recent heavy release from a central release point (R). Prevailing daily trimming of the mango trees at the releaseÐrecapture winds were from the north. (A) Contour map based on mean ßy recaptures per trap (n ϭ 3). Strict sampling range is study site further increased the air movement. As indicated by the contour level labeled 1.0. (B) Contour map shown previously, wind direction can have a strong based on cumulative frequency of captures. Effective sam- inßuence on the odor plume emitted from food-baited pling range is indicated by the contour level labeled 0.9, traps, and this in turn affects the spatial distribution of which corresponds to the area in which 90% of the recaptures ßy captures (Kendra et al. 2010). In the release/re- occurred. capture test (Fig. 4), the majority of ßy captures were north and west of the release point, and effective sampling range was Ϸ15 m greater in the upwind reared insects and traps set along transects equidistant direction. This shift gave the appearance that the from the release point. Recaptured ßies are then source of insects was 10 m north of the actual release grouped into distance classes, and each class evaluated point. This pattern has important implications for con- in terms of percentage of capture (or relative trapping trol measures that use a precision targeting approach. efÞciency). In a previous releaseÐrecapture study In the absence of air currents, there is good correlation with laboratory-reared A. suspensa and a two-compo- between trap catch and distance from source (Arbo- nent attractant consisting of ammonium acetate and gast et al. 2003), facilitating accurate location of foci of putrescine, we found good agreement in sampling infestation with contour analysis. With Þeld trapping range values estimated from trapping efÞciency by studies, however, interpretation of contour maps distance groups and from contour analysis of ßy re- should incorporate knowledge of the environmental captures (Kendra et al. 2010). In this current test with variables, particularly wind currents, and their poten- C. capitata and the three-component attractant, most tial effects on the interpolated spatial distribution of a of the released ßies were recaptured in the trap just target population. Differences in both air temperature north of the release point, suggesting an effective and relative humidity due to differences in shading range of only 10 m (consistent with results reported and elevation among the sites may have affected sam- for buminal by Delrio and Zu¨ mreog˘lu 1983). How- pling range and trap performance. 1892 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 103, no. 5

Age structure of the ßy population may also inßu- ments (Papadopoulos et al. 2003). They found that ence sampling range. In A. suspensa releaseÐrecapture female aggregation patterns were more closely related studies with the two-component lure, in which equal to the host phenology than were the male aggregation numbers of mature and immature females were re- patterns and that aggregated patterns were obtained leased concurrently, the immature females dispersed only during time periods with high fruit ßy captures. farther and were recovered in higher numbers than Samples collected during the population buildup at the mature females (Kendra et al. 2010). Kouloussis et the beginning of the season or during population de- al. (2009) found that C. capitata captured in food- crease at the end of the season in that study had baited traps tended to be younger than ßies aspirated random spatial patterns. In our study in the coffee site, from fruiting host trees at the same site. Protein-based all samples were collected after the coffee had been traps were used for all estimates of sampling range in harvested but during the peak of the ßy population, our study, so the ßies released in the mango orchard and numbers decreased only slightly toward the end may have had an age structure similar to that of the of the study. Captures in mango were very low during ßies captured in the coffee farms. Fruit was present in the last 4 wk of the study, which corresponded with the mango and orthanique orchards at the time the the population decrease at the end of the season. Þeld trapping tests were conducted, but was not Aggregated patterns were found throughout our study present in the mango orchard during the releaseÐ in coffee and in the Þrst 4 wk of the study in mango, recapture study due to heavy trimming of the trees in corresponding with the results obtained by Papado- the previous year. Absence of fruit and the process of poulos et al. (2003). Aggregated patterns were found capturing and holding the ßies for 24 h may have throughout the study in orthanique although number inßuenced behavior of the released ßies, changing of ßies decreased throughout the study. Examination their dispersion pattern. However, the recapture of of contour maps of fruit ßy capture in the Þeld test sites 26% of released ßies was similar to recapture of 21% of (data not shown) found that most of the ßies in the released ßies of mixed sex, age and nutritional back- orthanique orchard were captured along the edges of ground in Þeld cage tests of Multilure traps baited with the Þeld that were closest to adjacent coffee Þelds. ammonium acetate and trimethlyamine (Kouloussis et Immigrating pests tend to move synchronously into a al. 2009). Additional studies are needed to estimate Þeld; thus, they have aggregated distributions (Nestel sampling range of synthetic protein-based lures for et al. 2004). Thus, the aggregated patterns observed different age cohorts of C. capitata under different throughout the sampling period were probably due to environmental conditions, in different seasons, and in the capture of ßies immigrating into the orchard rather different cropping systems. than capture of ßies that were produced within the Geostatistical analysis provides an alternative ap- orchard. populations were less effectively mod- proach for determining the sampling range of a trap- eled using spatial statistics at this site, probably be- ping system by using Þeld-captured insects. Midgar- cause ßies represented an immigrating population. den et al. (1993) used spatial analysis, speciÞcally Another limitation to using spatial statistics to deter- dispersion indices, and geostatistics to investigate the mine sampling range is that the use of a high-density spatial distribution of adults of the western corn root- trapping grid may directly affect the population level worm, Diabrotica virgifera virgifera LeConte, by using within the trapping area, thus decreasing the possi- counts obtained froma7by7trapping grid of unbaited bility of capturing ßies within in the area covered by sticky traps, with traps placed 15 m apart. They found the high-density trapping grid. In the center of the that traps placed within 30 m of each other were high density trapping grid, trap density was Ϸ100 traps autocorrelated and recommended that traps be per hectare, twice the density used to suppress the spaced at least 30 m apart to obtain independent sam- population by mass trapping. Population reduction ples. For Þeld tests that compare fruit ßy capture by due to trapping over the time period of the study may different trapping systems, traps are often placed have interfered with the use of spatial analysis to 20Ð30 m apart (Epsky et al. 1999, Broughton and de determine sampling range toward the end of the ex- Lima 2002), indicating that trap interference may be periment. occurring in these tests. The standard trapping grid Critical to the use of geostatistics for estimation of deploys Ϸ50 traps per ha, which is the density rec- sampling range is the placement of traps close together ommended for C. capitata mass trapping (Leza et al. to enhance trap interference and increase the number 2008), with traps placed in every tree (Ros et al. 2000) of pair distances for Þtting a model to the experimental or in at least every third tree (Alemany et al. 2006) in variogram. Size of Þelds available, spacing of the avail- citrus. Results from our study indicate that this spacing able trapping sites, and homogeneity of the cropping corresponds with the sampling range of trapping sys- system may affect the ability to use a geostatistical tems with the three-component attractant. Thus, traps approach, therefore grid design will need to be ad- should be placed Ͻ30 m apart for mass trapping or for justed to accommodate different Þeld situations. For thorough coverage of an area for detection. However, the trapping system used in our study, it is recom- traps should be placed Ͼ30 m apart to avoid trap mended that the traps be moved to a new site after 4 interference in trapping system comparison studies. wk, the time when new lures would be added to the Spatial autocorrelation has been used to assess dis- traps, to reduce the effect of the high density-mass persion patterns of C. capitata populations and to de- trapping in the center of the grid on the fruit ßy termine the effect of host phenology on adult move- population. This may not be necessary for less ef- October 2010 EPSKY ET AL.: SAMPLING RANGE FOR C. capitata 1893 fective traps. A combination of releaseÐrecapture (Diptera: Tephritidae) under a range of climatic condi- studies, ideally with recently Þeld-collected wild tions and populations levels in Western Australia. J. Econ. insects, and Þeld tests with appropriately designed Entomol. 95: 507Ð512. trapping grids are needed to compare the utility of Calkins, C. O., W. J. Schroeder, and D. L. Chambers. 1984. this approach for other trapping systems and/or for Probability of detecting Caribbean fruit ßy, Anastrepha other pest species. Due to the difÞculty in obtaining suspensa (Loew) (Diptera: Tephritidae), populations laboratory-reared insects that are physiologically with McPhail traps. J. Econ. Entomol. 77: 198Ð201. Christenson, L. E., and R. E. Foote. 1960. Biology of fruit equivalent to wild insects, these approaches may ßies. Annu. Rev. Entomol 5: 171Ð192. provide the information needed to determine real- Cresoni-Pereira, C., and F. S. Zulcoloto. 2001. Dietary self- istic sampling ranges of protein-based lures, such as selection and discrimination thresholds in wild Anas- the female-targeted synthetic lures used for pest trepha obliqua females (Diptera: Tephritidae). J. Insect tephritid fruit ßies. Physiol. 47: 1127Ð1132. Cunningham, R. R., and H. M. Couey. 1986. Mediterranean fruit ßy (Diptera: Tephritidae) distance/response curves Acknowledgments to trimedlure to measure trapping efÞciency. Environ. Entomol. 15: 71Ð74. We thank Rene´ Martinez for cooperation and support for Davis, P. M. 1994. Statistics for describing populations, pp. this study by providing access to his coffee farm. We also 34Ð54. In L. P. Pedigo and G. D. Buntin [eds.], Handbook thank the Þeld technicians Arnold Cribas and Carlos Hum- of sampling methods for in agriculture. CRC, berto Valle (FHIA, Honduras); David Nestel (Agricultural Boca Raton, FL. Research Organization, The Volcani Center, Beit-Dagan, Is- Delrio, G., and A. Zumreoglu. 1983. Attractability range rael), Terry Arbogast (USDAÐARS, Gainesville, FL), Nikos ¨ ˘ Papadopolous (University of Thessaly, Magnisia, Greece), and capture efÞciency of medßy traps, pp. 445Ð450. In R. and Yoav Gazit (Citrus Marketing Board of Israel, Beit-Da- Cavallora [ed.], Fruit Flies of Economic Importance: gan, Israel) for discussions and reviews of earlier versions of Proceedings of the CEC/IOBC International Symposium, this manuscript; and the anonymous reviewers for valuable 16Ð19 November 1982, Athens, Greece. insight and recommendations. Dı´az-Fleischer, F., J. Arrendo, S. Flores, P. Montoya, and M. Aluja. 2009. There is no magic fruit ßy trap: multiple biological factors inßuence the response of adult Anas- References Cited trepha ludens and Anastrepha obliqua (Diptera: Tephriti- dae) individuals to MultiLure traps baited with BioLure Alemany, A., M. A. Miranda, R. Alonso, and C. Martin Es- or NuLure. J. Econ. Entomol. 102: 86Ð94. corza. 2006. Changes in the spatial and temporal popu- Dungan, J. L., J. N. Perry, M.R.T. Dale, P. Legendre, S. lation density of the Mediterranean fruit ßy (Diptera: Citron-Pousty, M.-J. Fortin, A. Jakomulska, M. 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