Manipulating the Abundance of Natural Enemies in Ornamental Landscapes with ﬂoral Resource Plants

Biological Control 33 (2005) 203–216 www.elsevier.com/locate/ybcon

Manipulating the abundance of natural enemies in ornamental landscapes with ﬂoral resource plants

Eric J. Rebek a,*, Cliﬀord S. Sadof a, Lawrence M. Hanks b

a Department of Entomology, Purdue University, 901 W. State Street, West Lafayette, IN 47907, USA b Department of Entomology, University of Illinois at Urbana-Champaign, 320 Morrill Hall, 505 S. Goodwin Ave., Urbana, IL 61801, USA

Received 5 November 2004; accepted 20 February 2005 Available online 23 March 2005

Abstract

We manipulated densities of floral resource plants to test the hypothesis that natural enemies would be more abundant in arti- ficial ornamental landscapes that contained high densities of floral resource plants than in landscapes without these plants. We established an experimental landscape consisting of 3 · 3 m plots that contained a central bed of Euonymus fortunei (Turcz.) and either a low or high density of four species of perennial flowering plants, or no flowering plants. The cultivars of perennials, Trifo- lium repens L., Euphorbia epithymoides L., Coreopsis verticillata L. var. ÔMoonbeam,Õ and Solidago canadensis L. var. ÔGolden Baby,Õ were chosen because their staggered bloom periods would provide nectar and pollen for natural enemies throughout the summer months. We used yellow sticky cards and a vacuum sampler to collect arthropods from experimental plots in 2000 to 2003. Natural enemies in general, and spiders and parasitic wasps specifically, were usually most abundant in euonymus beds surrounded by flowering plants. The number of parasitic wasps and total natural enemies on sticky cards was positively correlated with biomass of E. epithymoides within plots, and that of all flowering plants combined. Removal of inflorescences from plants in a subset of study plots did not affect patterns of natural enemy abundance or dispersion of natural enemies within the landscape, suggesting that vegetative characteristics of plants, rather than flowers, influenced the abundance of natural enemies. We conclude from these findings that the presence of floral resource plants in landscapes enhances the abundance of natural enemies. 2005 Elsevier Inc. All rights reserved.

Keywords: Conservation biological control; Habitat manipulation; Euonymus fortunei; Trifolium repens; Euphorbia epithymoides; Coreopsis verticillata; Solidago canadensis

1. Introduction ceous insects such as syrphids (Carreck and Williams, 1997; Hickman and Wratten, 1996; White et al., 1995), Conservation biological control encourages natural coccinellids (Freeman Long et al., 1998; Nalepa et al., enemies to suppress target pests through manipulation 1992; Pemberton and Vandenberg, 1993), and lacewings of environmental factors that influence natural enemy (Freeman Long et al., 1998). Some flowering plant spe- survival and effectiveness, including microclimate, avail- cies also are highly attractive to parasitic wasps (Bugg et ability of food for adults and alternative prey, and shel- al., 1989; Carreck and Williams, 1997; Jervis et al., 1993; ter from adverse environmental conditions (Ehler, 1998; Leius, 1960; Shahjahan, 1974; Tooker and Hanks, Landis et al., 2000; Rabb et al., 1976). Floral nectar and 2000a; Wa¨ckers, 2004), and can enhance parasitism pollen also are highly attractive to a diversity of preda- rates of herbivorous pests (Leius, 1967). Parasitoids may visit flowers to obtain nectar and/or pollen, which contain essential nutrients that can improve the survival * Corresponding author. Present address: Department of Entomol- ogy, Michigan State University, East Lansing, MI 48824, USA. Fax: and/or fecundity of adult wasps (Foster and Ruesink, +1 517 353 4354. 1984; Hougardy and Gre´goire, 2000; Idris and Grafius, E-mail address: [email protected] (E.J. Rebek). 1995, 1997; Leius, 1963; Shahjahan, 1974; Syme, 1975).

Although incorporation of flowering plants into agro- measured 3 · 3 m and consisted of a central 1-m2 bed ecosystems can enhance natural enemy populations of Euonymus fortunei (Turcz.) var. ÔColoratus,Õ container (Hickman and Wratten, 1996; Patt et al., 1997a; White grown and purchased from a local nursery, planted on et al., 1995), it may fail to promote biological control 22-cm centers (20 plants per bed). Prior to planting, of the target pest if flowering does not coincide with we inoculated euonymus plants in the greenhouse with the activity period of key natural enemies (Bowie et mobile, first-instar euonymus scales, Unaspis euonymi al., 1995), if corolla structure hinders feeding by adult (Comstock) (Homoptera: Diaspididae), by attaching natural enemies (Patt et al., 1997b), or if natural enemies scale-infested euonymus cuttings to each plant (see Sa- do not move from flowering plants to crop plants (Big- dof and Raupp, 1991). Euonymus plants were sur- ger and Chaney, 1998; Freeman Long et al., 1998). rounded by a 10-cm layer of composted wood mulch Although much attention has been given to the ben- that was amended each spring. All plants grew vigor- eficial effects of floral resource plants on natural enemies ously and it was necessary to trim them each autumn in agroecosystems (e.g., Altieri and Whitcomb, 1979; to maintain the original border with the wood mulch. Cowgill et al., 1995; Idris and Grafius, 1995; Zhao Study plots were arranged 3 m apart in four rows spaced et al., 1992), conservation biological control also holds 6 m apart. Ten blocks were used for long-term studies promise for managing pests in urban landscapes. Urban on abundance of natural enemies (N = 30 plots) while landscapes are often poor quality habitats for natural four blocks, separated from long-term plots by 6 m, enemies when they consist of matrices of pavement were used for short-term studies on abundance of natu- and turf, devoid of resources that are required by natural enemies and floral bloom phenology (N = 12 plots). ral enemies, and are subject to high temperatures, pollu- Areas between plots were seeded with Kentucky blue tion, dust, and pesticides (Dreistadt et al., 1990; Hanks grass, Poa pratensis L. and Denno, 1993; Luck and Dahlsten, 1975; Sperry Treatments were randomly assigned to plots in each et al., 2001). Despite these problems, natural enemies block by varying the density of floral resource plants can be favored in urban landscapes by simply increasing surrounding the beds of euonymus plants. Floral re- the diversity of plant species. A review by Barbosa and source plants were selected to provide natural enemies Benrey (1998) revealed plant architecture and diversity with floral resources from early spring through early can influence abundance and diversity of parasitoids. fall, and included: (1) flowering spurge, Euphorbia epith- For example, Shrewsbury and Raupp (2000) suggested ymoides L. (Euphorbiaceae) (formerly E. polychroma A. that rates of predation of azalea lace bug were greater Kern.), blooming from mid-April to mid-May, which in habitats in which plant communities were taxonomi- has exposed nectaries that are readily accessible to nat- cally and structurally diverse. Hanks and Denno (1993) ural enemies (Patt et al., 1997b); (2) coreopsis, Coreopsis found that densities of generalist natural enemies of a verticillata L. var. ÔMoonbeamÕ (Asteraceae), blooming scale insect, and predation rates, were greater on host from mid-June to late August, which produces abun- trees in more diverse woodlots than on trees in isolated dant pollen; (3) goldenrod, Solidago canadensis L. var. locations. Higher rates of predation in more diverse hab- ÔGolden BabyÕ (Asteraceae), blooming from late June itats resulted in lower densities of scales (Hanks and to mid-August, which is visited in abundance by a diver- Denno, 1993). Similarly, a greater diversity and abun- sity of natural enemies (Tooker and Hanks, 2000a); and dance of generalist predators in natural habitats appar- (4) white clover, Trifolium repens L. (Fabaceae), bloom- ently resulted in lower population densities of another ing from late May to mid-July, which is known to be scale species on conifers compared to populations in attractive to aphelinid parasitoids of scale insects (Too- managed landscapes (Tooker and Hanks, 2000b). ker and Hanks, 2000b). ‘‘No Flower’’ plots did not re- In this paper, we test the hypothesis that incorporating ceive flowering plants; ‘‘Low Flower Density’’ plots floral resource plants in ornamental landscapes will en- received one row of three plants spaced 0.3 m apart; hance the abundance of natural enemies. Effects of and ‘‘High Flower Density’’ plots received three rows manipulating flowering plant density on population den- (0.3 m apart) of three, five, and seven plants, respectively sities of herbivorous insects will be presented in another (Fig. 1). In plots with floral resource plants, four species paper. were randomly assigned to plot quadrants and they re- mained in their assigned position for the duration of the study. In accordance with the treatment design, 2. Materials and methods one and three rows of white clover were seeded into Low Flower Density and High Flower Density plots, 2.1. Study plots and plant species respectively (see Fig. 1). Euonymus fortunei var. ÔColora- tusÕ does not bloom, and so would not interfere with the Research plots were established in the summer of effects of floral resource plants on the abundance of nat- 1999 in a turf area adjacent to the Purdue University ural enemies. Average densities of euonymus scale were Nursery in West Lafayette, Indiana. Each study plot initially similar across all treatments (unpub. data). E.J. Rebek et al. / Biological Control 33 (2005) 203–216 205

and Mecoprop-P (128 g a.i./L) (Trimec Classic, PBI Gordon, Kansas City, MO USA) each spring.

2.2. Floral bloom phenology

To determine floral bloom phenology, we assessed flower abundance in the High Flower Density treatment in short-term study plots (N = 12) in 2002–2003. We sampled flower density in these plots weekly over the entire blooming period of each flowering plant species by blindly throwing a wire quadrat (600 cm2) into quadrants and counting the number of blooms within the quadrat. Two samples were taken per flowering plant species per plot in 2002, and three samples in 2003. For each sample date, we calculated mean floral abundance per flowering plant species.

2.3. Inﬂuence of ﬂoral resource plants on abundance of natural enemies

We monitored abundance of natural enemies in 2000–2003 by sampling study plots at monthly intervals during the growing season so as not to deplete plots of natural enemies. During each sampling period, arthropods were sampled by two methods: (1) with double- sided, 7.5- by 12.5-cm yellow sticky cards (Sensor Mon- itoring Cards, Whitmire Micro-Gen Research Labora- tories, St. Louis, MO USA) to capture flying insects and (2) a vacuum sampler to capture resting and less vagile arthropods (modified leaf blower, Model No. BG 75, Stihl, Virginia Beach, VA USA, fitted with a vacuum attachment and 250-mesh organdy bag secured over the vacuum tube with a rubber band). All study plots (N = 42) were sampled with sticky cards, but only long-term study plots (N = 30) were vacuum sampled. We vacuum sampled arthropods only on warm (P21 C), sunny days between 1000 and 1400 h when arthropods were most active. Each sample consisted of six, 10-s suctions of arbitrary locations within the bed of euonymus and each resource plant species. We sampled resource plants as they appeared, regardless of blooming period. Collection bags were immediately Fig. 1. Representative plot layout for the three treatments of floral placed in a chilled cooler to inhibit predation. In the lab- resource plants in 2000–2002. See text for description of experimental oratory, samples were frozen, then arthropods were design. sorted under a dissecting microscope, spiders were iden- tified to class, and predaceous and parasitic insects to order and family. Voucher specimens were deposited Plots were irrigated during periods of low precipita- in the Purdue University Entomology Research Collec- tion with an overhead sprinkler system (0.8-m height) tion. Vacuum samples were collected on 10 dates: 29 running between plot rows. Weeds growing within plots June and 19 September, 2000; 29 May, 26 June, 27 July, were usually pulled by hand, but several localized appli- and 21 August, 2001; 30 May, 20 June, 11 July, and 12 cations of glyphosate (480 g a.i./L; Round-up Pro; August, 2002. Monsanto, St. Louis, MO) were required each year to Sticky cards were placed in the field when several con- suppress weeds. We managed weeds growing in turf secutive days of sunny, warm weather (P21 C) were areas by mowing and suppressed broadleaf weeds by forecast. We placed two sticky cards within each euony- applying 2,4-D (240 g a.i./L), Dicamba (25 g a.i./L), mus bed, and two cards within each species of flowering 206 E.J. Rebek et al. / Biological Control 33 (2005) 203–216 plant when plants were present (No Flower plots ex- were placed in the field 13–15 May, 9–11 June, 21–23 cluded). Sticky cards were attached to bamboo plant July, and 18–20 August. Natural enemy counts were stakes 5 cm above the plant canopy and left in the field log10 (x + 1) transformed. No Flower, Flowers Re- for 48 h. Cards were then collected and covered with moved, and Flowers Intact plots were not replicated in plastic wrap to facilitate handling. We examined cards blocks. For each sampling period and method, we used under a dissecting microscope to count and classify nat- ANOVA for a completely randomized design (PROC ural enemies as described above. Sampling dates were GLM, SAS Institute, 1985) to analyze treatment differ- 13–15 June, 26–28 July, and 13–15 September, 2000; ences in abundance of natural enemies caught within 15–17 May, 18–20 June, 16–18 July, and 13–15 August, euonymus. We tested the dependent variable (abun- 2001; 22–24 May, 17–19 June, 8–10 July, and 6–8 Au- dance of natural enemies) with treatment as the indepen- gust, 2002. dent variable. Treatment means for each analysis were Natural enemy counts were log10 (x + 1) transformed separated by Fisher protected least significant difference to stabilize the variance among samples. For each sam- tests. For both sampling methods, we used paired t tests pling period and method, we used one-way analysis of (PROC TTEST, SAS Institute, 1985) to compare natu- variance (ANOVA) for a randomized complete block ral enemy abundance between Flowers Removed and design (PROC GLM, SAS Institute, 1985) to analyze Flowers Intact treatments for each floral resource plant. treatment differences in abundance of natural enemies To investigate the effect of resource plant biomass on collected from each euonymus bed. We tested the depen- abundance of natural enemies, we harvested above- dent variable (abundance of natural enemies) with treat- ground flowering plant material from the long-term ment and block as the independent variables. We plots at the end of the 2003 season and dried them at repeated this analysis for vacuum sample data using par- 70 C. Pearson correlation coefficients (PROC CORR, asitic wasps and spiders as separate dependent variables. SAS Institute, 1985) were used to compare data for Differences between means were tested with Fisher pro- dry weights of flowering plants with corresponding tected least significant difference tests. We used two-fac- log-transformed data for abundance of natural enemies tor ANOVA to test the dependent variable (abundance from 2003. Because late-season plant dry weights of natural enemies) with two independent variables encompass total growth over the entire 2003 season, (flowering plant species and treatment), as well as their we analyzed average arthropod abundance per plot for interaction. Differences between means were tested with each natural enemy group collected throughout the sea- Fisher protected least significant difference tests. How- son. For both sampling methods, dry weights were com- ever, May samples were confined to euphorbia and clo- pared with count data for both parasitic wasps and total ver because these were the only species having a natural enemies; for vacuum samples, dry weights were sufficient amount of above-ground plant material for also compared with spider abundance. All statistical sampling in late spring. Therefore, we compared May procedures were analyzed at a = 0.05. trap catches for euphorbia and clover using paired t tests (PROC TTEST, SAS Institute, 1985). 2.4. Influence of floral resources on spatial distribution of In 2003, we altered the experimental design of long- natural enemies term study plots to investigate the direct influence of floral resources on populations of natural enemies. The No We conducted a separate study in 2002–2003 to inves- Flower treatment was retained from earlier experiments, tigate spatial patterns of natural enemy abundance while plots with flowering plants were split into two new across the experimental landscape. We placed a yellow treatments: all flower buds were removed prior to bud sticky card at the perimeter of each plot in each of the break in ‘‘Flowers Removed’’ plots, whereas flowers four cardinal directions and in three locations (N =12 were allowed to bloom in ‘‘Flowers Intact’’ plots. We as- cards per plot): (1) at the interface between euonymus signed these treatments to plots in late April 2003 by and resource plants or mulch, (2) at the interface be- ranking all plots containing flowering resource plants tween resource plants or mulch and turf, and (3) 1 m by increasing order of percent plot area covered by into turf surrounding plot borders. The landscape was euphorbia (the only flowering plant species present at mapped in x- and y-coordinates (in meters) and the po- the time). Every other ranked plot was assigned to the sition of each sticky card sample (N = 504) was plotted Flowers Removed treatment to establish an even distri- and recorded. Thus, trap catch allowed us to gauge the bution of flowering plant densities across both overall distribution of natural enemies throughout the treatments. landscape. Samples were processed as described above. We used vacuum and sticky card samples in 2003 to Sampling was conducted on 12–14 June, 16–18 July, assess the effect of removing inflorescences from re- and 20–22 August, 2002; and 18–20 June and 29–31 source plants on total abundance of natural enemies July, 2003. by the methods already described. Vacuum samples Count data were square-root transformed to stabilize were taken 16 June, 25 July, and 22 August. Sticky cards the variance. For each sample date, we used two-factor E.J. Rebek et al. / Biological Control 33 (2005) 203–216 207

ANOVA to test the dependent variable (abundance of separation distance (h) no longer yield increases in vari- natural enemies) with two independent variables (treat- ogram value, and (2) the sill value, or the plateau ment and location), as well as their interaction. We reached by the variogram at the range value. interpret a significant treatment-by-location interaction To determine the spatial structure of untransformed as an indication that proximity to floral resource plants natural enemy counts on sticky cards located at each influences the distribution of natural enemies. x-, y-coordinate, we calculated omnidirectional vario- Geostatistics is a branch of applied statistics that esti- grams (Geovariances, 2002) for each sampling period mates and models spatial patterns using both values and and standardized each variogram value to 1. We deter- locations of a given data set (Liebhold and Sharov, mined that abundance data were isotropic based on 1998; Rossi et al., 1992). Traditionally used in geology analysis of variance maps (Geovariances, 2002). We and mining, geostatistics has been widely applied to eco- chose a 2-m lag distance with a lag tolerance of ±1 m logical data, including analysis of spatial autocorrela- and an angular tolerance of 90. Nugget effect and tion among insect count data (Gribko et al., 1995; spherical models were used to describe the structure of Tobin and Pitts, 2002; Wright et al., 2002). Data are each variogram and estimate the sill and range values. considered spatially autocorrelated when values are The nugget effect accounts for discontinuities that occur more similar for samples taken from locations in prox- at the origin of the variogram, and is modeled as: imity than for samples from locations that are separated 0ifh ¼ 0; by a greater distance (Liebhold and Sharov, 1998). A c0ðhÞ¼ ð2Þ variogram is a geostatistical tool that measures the sep- 1 otherwise: aration distance, or lag distance (h), at which data pairs Discontinuities arise because the variogram value at are no longer spatially autocorrelated. The variogram, h = 0 is strictly 0, but may be considerably larger than c(h), summarizes all possible data pairs over significant 0 at very small lag distances (Isaaks and Srivastava, lag distances (Liebhold and Sharov, 1998), and is equal 1989). The spherical model describes the basic structure to half the average squared difference between paired of the variogram and is calculated as: data values at the same separation distance (Isaaks ( 1:5 h 0:5ðh Þ3 if h 6 a; and Srivastava, 1989). The variogram is calculated as: cðhÞ¼ a a ð3Þ 1 otherwise; 1 X cðhÞ¼ ðv v Þ2; ð1Þ 2N i j where a is the range (Isaaks and Srivastava, 1989). To- ðhÞ ði;jÞjh ¼h i;j gether with the treatment-by-location interaction from ANOVA, we interpreted range as the distance at which where N is the number of data pairs in h, v is a value (h) i flowering plants cease to affect abundance of natural at location i, and v is a value at location j separated by h j enemies. We compared variograms for different years (see Isaaks and Srivastava, 1989 for further information to detect changes in response of natural enemies to floral on variogram models and the methods described below). resource plants in 2002 when flowers were intact and in To describe how the spatial continuity of a given var- 2003 when flowers had been removed from half of the iable changes with distance and direction, variogram long-term plots. values (y-axis) are plotted against all lag distances (x- axis). Because only a small number of data pairs fall ex- actly along h in any given direction, lag tolerance and angle tolerance values are chosen to increase the number 3. Results of data pairs used in construction of the variogram. A lag tolerance value of typically one-half the lag distance 3.1. Floral bloom phenology is incorporated to include data pairs that are separated by distances approaching h. Similarly, angular tolerance Euphorbia was the first resource plant to bloom, fol- manipulates positive and negative rotation about the lowed by clover, coreopsis, and goldenrod (Fig. 2). vector to include more data pairs. Because a large num- Overlap in flowering periods of the resource plant spe- ber of variograms can be calculated for all data pairs cies assured continuous availability of pollen and nectar separated by h in any given direction, it is common to for natural enemies from mid-April through late construct omnidirectional variograms. These vario- August. grams represent an approximate average of the various directional variograms, and are valid if spatial continu- 3.2. Influence of floral resource plants on abundance of ity is determined to be similar in all directions (i.e., it is natural enemies isotropic). Various models are then used to estimate the structure of the omnidirectional variogram. The basic Despite differences in the kinds of natural enemies variogram structure is then used to calculate: (1) the caught with each trapping method, parasitic Hymenop- range value, or distance at which further increases in tera as a whole were strongly dominant (Fig. 3). Sticky 208 E.J. Rebek et al. / Biological Control 33 (2005) 203–216

Fig. 2. Blooming period for four species of perennial flowering plants in high flower density treatment during (A) 2002 and (B) 2003. Euphorbia, E. polychroma L.; Clover, T. repens L.; Coreopsis, C. verticillata L. var. ÔMoonbeamÕ; and Goldenrod, S. canadensis L. var. ÔGolden Baby.Õ cards collected more individuals of vagile groups, including parasitic Hymenoptera, tachinids, syrphids, Fig. 3. Percentage of natural enemies of different taxonomic groups of and coccinellids, while vacuum samples yielded less vag- the total number of individuals collected using (A) sticky cards and (B) ile groups, especially spiders and ants, but also canthar- a vacuum sampler. Data are pooled across all plants, treatments, and ids and anthocorids. sample dates from 2000 to 2003. When significant differences were detected among treatments, mean abundance of natural enemies was collected from euonymus beds surrounded by flowering higher for plots with flowering plants than for No Flow- plants than those with only mulch (Fig. 6; September er plots. Natural enemies were occasionally more abun- 2000, F = 29.30, df = 2, 18, P < 0.0001; June 2001, dant on sticky cards placed in euonymus beds F = 4.99, df = 2, 18, P = 0.0188; July 2001, F = 20.87, surrounded by low and high densities of flowering plants df = 2, 18, P < 0.0001; and July 2002, F = 27.15, than on those placed in plots without flowering plants df =2,18,P < 0.0001). For samples collected from flo- (Fig. 4; June 2000, F = 29.71, df = 2, 26, P < 0.0001; ral resource plants, the abundance of natural enemies July 2000, F = 10.17, df = 2, 26, P = 0.0005; June differed significantly across plant species for all sample 2001, F = 19.63, df = 2, 26, P < 0.0001; and July 2001, dates (Table 2), including May of 2001 and 2002 (May F = 38.39, df = 2, 26, P < 0.0001). The number of natu- 2001, t = 10.20, df = 38, P < 0.0001; May 2002, ral enemies captured on sticky cards positioned within t = 7.60, df = 38, P < 0.0001). The abundance of natural plantings of flowering plants was significantly influenced enemies was more consistently associated with resource by treatment and plant species for nearly all sampling plant species in these vacuum samples than in sticky periods in 2000–2002 (Table 1), though patterns were card samples (Fig. 7). Clover yielded the greatest num- not consistent among plant species (Fig. 5). Trap catches ber of natural enemies in May, while both clover and from euphorbia and clover were never significantly dif- goldenrod did so in June and July; differences among ferent when compared in May 2001 and 2002 (Fig. 5). plant species were more variable in July and August Data from vacuum samples were similar to those for samples (Fig. 7). sticky cards. Where treatment was significantly different, Parasitic wasps and spiders were generally more natural enemies were more abundant in vacuum samples abundant in vacuum samples collected from euonymus E.J. Rebek et al. / Biological Control 33 (2005) 203–216 209

Table 1 Results of two-factor ANOVA for 2000–2002 sticky card samples from ﬂoral resource plants Eﬀects NdfF P June 2000 112 Treatment 1 21.10 <0.0001*** Flowering plant 3 34.43 <0.0001*** Trt · Plant 3 0.14 0.9370 Error 216

July 2000 112 Treatment 1 104.15 <0.0001*** Flowering plant 3 11.91 <0.0001*** Trt · Plant 3 1.42 0.2412 Error 216

September 2000 112 Treatment 1 6.86 0.0104* Flowering plant 3 110.23 <0.0001*** Trt · Plant 3 4.00 0.0101* Error 216

June 2001 112 Treatment 1 5.48 0.0215* Flowering plant 3 22.29 <0.0001*** Trt · Plant 3 1.38 0.2533 Error 216

July 2001 112 Treatment 1 9.72 0.0024** Flowering plant 3 4.69 0.0043** Trt · Plant 3 1.33 0.2701 Error 216

August 2001 111 Treatment 1 5.32 0.0020** Flowering plant 3 4.69 0.0043** Trt · Plant 3 1.43 0.2401 Error 216

October 2001 110 Treatment 1 0.17 0.6773 Fig. 4. Mean log10 (x + 1) number of natural enemies per plot (±SE) Flowering plant 3 16.68 <0.0001*** collected from euonymus beds on sticky cards in 2000–2002. Means Trt · Plant 3 0.10 0.9613 with different letters within months are significantly different (Fisher Error 216 Protected LSD, P 6 0.05). June 2002 112 Treatment 1 3.17 0.0784 beds with flowering plants than those with only mulch Flowering plant 3 14.81 <0.0001*** (Figs. 8 and 9; parasitic wasps: September 2000, F = Trt · Plant 3 2.55 0.0606 7.62, df =2,18,P = 0.0040; June 2001, F = 7.83, df =2, Error 216 18, P = 0.0036; July 2001, F = 5.62, df = 2, 18, P = July 2002 112 0.0134; August 2001, F = 5.98, df = 2, 18, P = 0.0108; Treatment 1 3.16 0.0787 July 2002, F = 16.04, df = 2, 18, P = 0.0001; and August Flowering plant 3 8.40 <0.0001*** 2002, F = 4.03, df = 2, 18, P = 0.0357; spiders: Septem- Trt · Plant 3 0.86 0.4629 Error 216 ber 2000, F = 10.11, df = 2, 18, P = 0.0011; July 2001, F = 14.28, df = 2, 18, P = 0.0002; and July 2002, F = August 2002 112 5.95, df = 2, 18, P < 0.0104). Treatment 1 2.79 0.0981 Removing flowers significantly influenced the abun- Flowering plant 3 1.65 0.1838 Trt · Plant 3 0.06 0.9803 dance of natural enemies collected in euonymus beds in Error 216 May 2003 sticky card samples (F = 4.65, df = 2, 27, The dependent variable is abundance of natural enemies. P = 0.0184) and August 2003 vacuum samples (F = * P < 0.05. 4.07, df =2,25, P = 0.0295) (Table 3). When assessed ** P < 0.01. separately for each resource plant species, removing *** P < 0.001. 210 E.J. Rebek et al. / Biological Control 33 (2005) 203–216

Fig. 5. Mean log (x + 1) number of natural enemies per plot (±SE) 10 Fig. 6. Mean log (x + 1) number of natural enemies per plot (±SE) collected from floral resource plants on sticky cards in 2000–2002. 10 collected from euonymus beds in vacuum samples in 2000–2002. Means with different letters within months are significantly different Means with different letters within months are significantly different (Fisher Protected LSD, P 6 0.05). (Fisher Protected LSD, P 6 0.05). inflorescences from resource plants had a negligible influ- of parasitic wasps (r = 0.494, P = 0.0268) and total nat- ence on natural enemy abundance. The treatment effect ural enemies (r = 0.558, P = 0.0106). was significant only for July vacuum samples in goldenrod (t = 4.83, df = 18, P < 0.0001), with 1.225 ± 0.044 3.3. Influence of floral resources on spatial distribution of versus 0.911 ± 0.048 natural enemies collected in Flowers natural enemies Intact and Flowers Removed treatments, respectively. Biomass of flowering plants was not correlated with The treatment-by-location interaction was highly sig- mean abundance of natural enemies in vacuum samples nificant for all sample dates except July 2003 (Table 4), collected from euonymus beds in 2003 (Pearson correla- which may indicate that the spatial location of floral re- tion, P > 0.05). In contrast, when natural enemies were source plants typically influenced the distribution of nat- sampled with sticky cards in euonymus beds, dry ural enemies in the landscape. Spatial variance in weights of euphorbia were positively correlated with natural enemy abundance, assessed with sticky cards, mean abundance of parasitic wasps (r = 0.508, showed similar structure for all sampling months in P = 0.0223) and total natural enemies (r = 0.604, 2002–2003 (Fig. 10). The range values were 16.1, 5.4, P = 0.0048), and combined dry weights of all resource 7.8, 6.6, and 7.6 m for June, July, and August 2002, plants were positively correlated with mean abundance and June and July 2003, respectively. With the exception E.J. Rebek et al. / Biological Control 33 (2005) 203–216 211

Table 2 Results of two-factor ANOVA for 2000–2002 vacuum samples from ﬂoral resource plants Eﬀects NdfF P June 2000 80 Treatment 1 13.41 0.0008*** Flowering plant 3 36.18 <0.0001*** Trt · Plant 3 2.08 0.1205 Error 152 September 2000 80 Treatment 1 1.83 0.1845 Flowering plant 3 15.87 <0.0001*** Trt · Plant 3 2.84 0.0516 Error 152 June 2001 80 Treatment 1 9.26 0.0044** Flowering plant 3 22.42 <0.0001*** Trt · Plant 3 0.55 0.6489 Error 152 July 2001 80 Treatment 1 6.25 0.0171* Flowering plant 3 5.06 0.0050** Trt · Plant 3 0.47 0.7040 Error 152 August 2001 57 Treatment 1 1.74 0.1990 Flowering plant 2 4.01 0.0316* Trt · Plant 2 0.01 0.9878 Error 114 June 2002 80 Treatment 1 5.98 0.0195* Flowering plant 3 34.90 <0.0001*** Trt · Plant 3 1.94 0.1410 Error 152 July 2002 74 Treatment 1 0.44 0.5109 Flowering plant 3 25.90 <0.0001*** Trt · Plant 3 0.80 0.5017

Error 152 Fig. 7. Mean log10 (x + 1) number of natural enemies per plot (±SE) collected from floral resource plants in vacuum samples in 2000–2002. August 2002 60 Means with different letters within months are significantly different Treatment 1 0.13 0.7225 (Fisher Protected LSD, P 6 0.05). Flowering plant 2 21.83 <0.0001*** Trt · Plant 2 0.44 0.6513 Error 114 containing mulch only (Figs. 4 and 6), supporting our The dependent variable is abundance of natural enemies. hypothesis that including floral resource plants in orna- * P < 0.05. ** P < 0.01. mental urban landscapes will enhance the abundance of *** P < 0.001. natural enemies. Plots with high densities of flowering plants occasionally harbored greater numbers of natural enemies than those planted with low densities. In most of June 2002, range values were fairly stable over time, cases, however, abundance of natural enemies appar- suggesting that the influence of flowering plants on the ently was favored by the mere presence of flowering distribution of natural enemies was similar throughout plants, regardless of planting density. Parasitoids were the study. the largest group of natural enemies (Fig. 3), and usually were most abundant in euonymus beds that contained flowering plants (Fig. 8). However, abundance of natu- 4. Discussion ral enemies, and most likely parasitoids, was generally not affected by our removing flowers from resource Natural enemies were more abundant in plots of plants in 2003 (Table 3). Parasitoids could have re- euonymus surrounded by flowering plants than in plots sponded to environmental factors other than the pres- 212 E.J. Rebek et al. / Biological Control 33 (2005) 203–216

Fig. 8. Mean log10 (x + 1) number of parasitic Hymenoptera per plot (±SE) collected from euonymus beds in vacuum samples in 2000–2002. Fig. 9. Mean log10 (x + 1) number of Araneae per plot (±SE) collected Means with different letters within months are significantly different from euonymus beds in vacuum samples in 2000–2002. Means with (Fisher Protected LSD, P 6 0.05). different letters within months are significantly different (Fisher Protected LSD, P 6 0.05). ence or absence of floral resources. For example, be- plants had dense canopies. Because spiders do not feed cause the landscape surrounding the research site is rel- on floral resources, the positive impact of flowering atively impoverished and affords little protection from plants on spider abundance is probably related to char- adverse climatic conditions, floral resource plants may acteristics of the vegetation such as increased plant have influenced parasitoid abundance by providing a structure, diversity, and/or complexity (Bell et al., favorable microclimate (Landis et al., 2000). Alterna- 2002; Coll and Bottrell, 1995; Kevan and Greco, 2001; tively, parasitoids may have learned to forage on re- Rieux et al., 1999; Schwab et al., 2002), or increased source plants that emitted non-floral plant volatiles prey abundance. The significant influence of resource and continued to be attracted to resource plants even plant treatments on abundance of spiders and parasit- after flowers were removed. Flowering plants also may oids, representing two different entomophagous func- have harbored aphids, which could provide honeydew tional groups, suggests that there is potential for or serve as hosts to some parasitoid species (Barbosa, controlling a wide variety of arthropod pests using this 1998). conservation biological control tactic. Spiders were occasionally most abundant in vacuum All of the flowering plant species in this study were samples of plots that contained floral resource plants either attractive to, or able to retain, predators and par- (Fig. 9), particularly during late summer when resource asitoids. However, the abundance of natural enemies did E.J. Rebek et al. / Biological Control 33 (2005) 203–216 213

Table 3 Table 4 Trap catch of natural enemies from sticky card and vacuum samples in Results of two-factor ANOVA for the 2002–2003 study of the euonymus beds in 2003 influence of floral resource plants on the spatial distribution of natural Treatment N Mean log-number of enemies natural enemies ± SEa Effects NdfF P Sticky card samples June 2002 504 May Treatment 2 18.47 <0.0001*** No Flower 10 0.687 ± 0.056a Location 2 6.42 0.0018** Flowers Intact 10 0.482 ± 0.041b Trt · Loc 4 3.31 0.0109* Flowers Removed 10 0.617 ± 0.047ab Error 369 June July 2002 504 No Flower 10 1.018 ± 0.038a Treatment 2 28.81 <0.0001*** Flowers Intact 9 0.937 ± 0.037a Location 2 29.81 <0.0001*** Flowers Removed 10 0.925 ± 0.044a Trt · Loc 4 2.63 0.0340* Error 369 July No Flower 10 0.547 ± 0.031a August 2002 504 Flowers Intact 10 0.677 ± 0.043a Treatment 2 28.81 <0.0001*** Flowers Removed 9 0.658 ± 0.064a Location 2 29.81 <0.0001*** Trt · Loc 4 2.63 0.0340* August Error 369 No Flower 10 0.640 ± 0.059a Flowers Intact 10 0.690 ± 0.021a June 2003 492 Flowers Removed 10 0.839 ± 0.090a Treatment 2 22.79 <0.0001*** Location 2 9.37 0.0001*** Vacuum samples Trt · Loc 4 4.70 0.0010** June Error 360 No Flower 10 0.790 ± 0.087a July 2003 501 Flowers Intact 10 0.625 ± 0.083a Treatment 2 10.69 <0.0001*** Flowers Removed 10 0.674 ± 0.072a Location 2 8.57 0.0002*** July Trt · Loc 4 0.64 0.6354 No Flower 10 0.793 ± 0.056a Error 369 Flowers Intact 10 0.908 ± 0.033a Sticky card samples were taken from all plots at the following loca- Flowers Removed 10 0.950 ± 0.088a tions: euonymus bed-plot interface, plot-turf interface, and in turf (see August text). The dependent variable is abundance of natural enemies. No Flower 10 0.866 ± 0.106b * P < 0.05. Flowers Intact 9 1.153 ± 0.039a ** P < 0.01. Flowers Removed 9 1.077 ± 0.050ab *** P < 0.001. a Means with different letters within months are significantly different (P 6 0.05). enemies were in Flowers Intact plots (Table 3). Perhaps removing flowers had the greatest effect on natural en- not necessarily correspond to the availability of floral re- emy abundance in August because of the greater mass sources. For example, a large number of natural enemies of flowers present. When we analyzed each flowering were collected from euphorbia through late summer and plant species separately for all sample dates, however, early fall (Figs. 7A and B), even though it usually only one instance showed a greater number of natural stopped blooming at the end of May (Fig. 2). With re- enemies associated with Flowers Intact than Flowers spect to flowering plant species, patterns of abundance Removed plots. Further, numbers of both parasitic were much clearer for vacuum samples (Fig. 7) than wasps and total natural enemies caught on sticky cards sticky card samples (Fig. 5). These results suggest that were positively correlated with total biomass of euphor- less vagile natural enemies (e.g., spiders) were more bia and all flowering plants combined. Similar vario- strongly influenced by regular changes in some quality gram structure and range values among most of the of each plant species; in contrast, the highly variable re- sample dates for 2002–2003 (Fig. 10) also suggest that sponse of flying natural enemies may relate to more sub- removing flowers from half the long-term study plots tle differences among flowering plant species over time. in 2003 had a negligible effect, if any, on dispersion of The flower removal study provided little evidence for natural enemies throughout the landscape. The large the influence of floral resources on the abundance of difference in range values between June 2002 and June natural enemies. In May 2003, more natural enemies 2003 is not likely due to effects of flower removal be- were captured on sticky cards placed in No Flower plots cause effects were also not observed between natural than in other treatments (Table 3). In August 2003 vac- enemies caught in sticky cards placed in plots with and uum samples, however, the highest number of natural without flowers in June 2003. However, the range values 214 E.J. Rebek et al. / Biological Control 33 (2005) 203–216

Our study clearly demonstrates that floral resource plants can be used to increase abundance of natural enemies in ornamental urban landscapes, though natural enemies may benefit more from the flowering plants themselves than the floral resources they provide. Enhancing natural enemy populations in managed habitats engenders a greater potential for successful biological control. With a few notable exceptions (see review by Landis et al., 2000), however, most studies to date have been unable to associate increased predation or parasitism rates with increased abundance of natural enemies. Future research should directly address the relationship between natural enemy abundance and effective regulation of arthropod pests.

Acknowledgments

We are grateful to the countless undergraduate research technicians who maintained our research plots and collected, sorted, and identiﬁed arthropods. We also thank R.J. OÕNeil, M. Dana, N. Dudareva, J. Holland, D. Richmond, and two anonymous reviewers for com- ments on previous versions of the manuscript. This material is based upon work supported by The Cooper- Fig. 10. Relative omnidirectional variograms for abundance of natural enemies trapped on yellow sticky cards from June 2002 through July ative State Research, Education, and Extension Service, 2003. Each variogram contains two structures (nugget eﬀect and U.S. Department of Agriculture, under Agreement Nos. spherical model), 15 lags of 2 m with a 50% tolerance, and an angular 99-35316-7850 and 2001-35316-11275. This is paper tolerance of 90. 2005-17600 of the Indiana Agriculture Research Program.

(ranging from 5.4 to 16.1 m) we obtained hint at potential interactions among flowering plant species located References within plots, and more importantly, between plots that are separated by 6 m or less of turf. Such interaction Altieri, M.A., Whitcomb, W.H., 1979. The potential use of weeds in could have confounded the results of analysis of vari- the manipulation of beneficial insects. HortScience 14, 12–18. ance for the flower removal study, thereby explaining Barbosa, P., 1998. Agroecosystems and conservation biological a general lack of significance among treatments in control. In: Barbosa, P. (Ed.), Conservation Biological Control. 2003. Yet, we were able to find significant effects of Academic Press, San Diego, CA, pp. 39–54. Barbosa, P., Benrey, B., 1998. The influence of plants on insect treatment and flowering plant species in the previous parasitoids: implications for conservation biological control. In: study in 2000–2002, despite the possibility of confound- Barbosa, P. (Ed.), Conservation Biological Control. Academic ing interactions between plots. Therefore, we conclude Press, San Diego, CA, pp. 55–82. that floral resources themselves had little impact on Bell, J.R., Johnson, P.J., Hambler, C., Haughton, A.J., Smith, H., the abundance of natural enemies. Feber, R.E., Tattersall, F.H., Hart, B.H., Manley, W., MacDon- ald, D.W., 2002. Manipulating the abundance of Lepthyphantes Geostatistical analysis demonstrated that the distri- tenuis (Araneae: Linyphiidae) by field margin management. Agric. bution of natural enemies was rather stable over time, Ecosyst. Environ. 93, 295–304. even when flowers were removed in 2003. Analysis of Bigger, D.S., Chaney, W.E., 1998. Effects of Iberis umbellata (Brass- variance determined a significant interaction between icaceae) on insect pests of cabbage and on potential biological treatment and trap location for all sample periods ex- control agents. Environ. Entomol. 27, 161–167. Bowie, M.H., Wratten, S.D., White, A.J., 1995. Agronomy and cept July 2003 (Table 4), suggesting that the spatial loca- phenology of ‘‘companion plants’’ of potential for enhancement of tion of flowering plants did not influence the insect biological control. N. Z. J. Crop Hortic. Sci. 23, 423–427. distribution of natural enemies for that sample period. Bugg, R.L., Ellis, R.T., Carlson, R.W., 1989. Ichneumonidae (Hyme- Indeed, compared to previous sample dates, the vario- noptera) using extrafloral nectar of faba bean (Vicia faba L., gram structure for July 2003 (Fig. 10) is relatively weak, Fabaceae) in Massachusetts. Biol. Agric. Hortic. 6, 107–114. Carreck, N.L., Williams, I.H., 1997. Observations on two commercial implying that the range value calculated for that sample flower mixtures as food sources for beneficial insects in the UK. J. date is simply an artifact of the model fitting procedure. Agric. Sci. 128, 397–403. E.J. Rebek et al. / Biological Control 33 (2005) 203–216 215

Coll, M., Bottrell, D.G., 1995. Predator–prey association in mono- and Luck, R.F., Dahlsten, D.L., 1975. Natural decline of a pine needle dicultures: effect of maize and bean vegetation. Agric. Ecosyst. scale (Chionaspis pinifoliae [Fitch]), outbreak at South Lake Tahoe, Environ. 54, 115–125. California following cessation of adult mosquito control with Cowgill, S.E., Wratten, S.D., Sotherton, N.W., 1995. The selective use malathion. Ecology, 893–904. of floral resources by the hoverfly Episyrphus balteatus (Diptera: Nalepa, C.A., Bambara, S.B., Burroughs, A.M., 1992. Pollen and Syrphidae) on farmland. Ann. Appl. Biol. 114, 223–231. nectar feeding by Chilocorus kuwanae (Silvestri) (Coleoptera: Dreistadt, S.H., Dahlsten, D.L., Frankie, G.W., 1990. Urban forests Coccinellidae). Proc. Entomol. Soc. Wash. 94, 596–597. and insect ecology. BioScience 40, 192–198. Patt, J.M., Hamilton, G.C., Lashomb, J.H., 1997a. Impact of strip- Ehler, L.E., 1998. Conservation biological control: past, present, and insectary intercropping with flowers on conservation biological future. In: Barbosa, P. (Ed.), Conservation Biological Control. control of the Colorado potato beetle. Adv. Hortic. Sci. 11, 175–181. Academic Press, San Diego, CA, pp. 1–8. Patt, J.M, Hamilton, G.C., Lashomb, J.H., 1997b. Foraging success of Foster, M.A., Ruesink, W.G., 1984. Influence of flowering weeds parasitoid wasps on flowers: interplay of insect morphology, floral associated with reduced tillage in corn on a black cutworm architecture and searching behavior. Entomol. Exp. Appl. 83, 21–30. (Lepidoptera: Noctuidae) parasitoid, Meteorus rubens (Nees von Pemberton, R.W., Vandenberg, N.J., 1993. Extrafloral nectar feeding Esenbeck). Environ. Entomol. 13, 664–668. by ladybird beetles (Coleoptera: Coccinellidae). Proc. Entomol. Freeman Long, R., Corbett, A., Lamb, C., Reberg-Horton, C., Soc. Wash. 95, 139–151. Chandler, J., Stimmann, M., 1998. Beneficial insects move from Rabb, R.L., Stinner, R.E., van den Bosch, R., 1976. Conservation and flowering plants to nearby crops. Calif. Agric. 52, 23–26. augmentation of natural enemies. In: Huffaker, C.B., Messenger, Geovariances, 2002. Isatis Software Manual, fourth ed. Geovariances, P.S. (Eds.), Theory and Practice of Biological Control. Academic Avon Cedex, France. Press, San Diego, CA, pp. 233–254. Gribko, L.S., Liebhold, A.M., Hohn, M.E., 1995. Model to predict Rieux, R., Simon, S., Defrance, H., 1999. Role of hedgerows and gypsy moth (Lepidoptera: Lymantriidae) defoliation using kriging ground cover management on arthropod populations in pear and logistic regression. Environ. Entomol. 24, 529–537. orchards. Agric. Ecosyst. Environ. 73, 119–127. Hanks, L.M., Denno, R.F., 1993. Natural enemies and plant water Rossi, R.E., Mulla, D.J., Journel, A.G., Franz, E.H., 1992. Geosta- relations influence the distribution of an armored scale insect. tistical tools for modeling and interpreting ecological spatial Ecology 74, 1081–1091. dependence. Ecol. Monogr. 62, 277–314. Hickman, J.M., Wratten, S.D., 1996. Use of Phacelia tanacetifolia Sadof, C.S., Raupp, M.J., 1991. Effect of variegation in Euonymus strips to enhance biological control of aphids by hoverfly larvae in japonica var. aureus on two phloem feeding insects, Unaspis cereal fields. J. Econ. Entomol. 89, 832–840. euonymi (Homoptera: Diaspididae) and Aphis fabae (Homoptera: Hougardy, E., Gre´goire, J.C., 2000. Spruce stands provide natural Aphididae). Environ. Entomol. 20, 83–89. food sources to adult hymenopteran parasitoids of bark beetles. SAS Institute, 1985. SAS UserÕs Guide, Statistics, version 5. SAS Entomol. Exp. Appl. 96, 253–263. Institute, Cary, NC. Idris, A.B., Grafius, E., 1995. Wildflowers as nectar sources for Schwab, A., Dubois, D., Fried, P.M., Edwards, P.J., 2002. Estimating Diadegma insulare (Hymenoptera: Ichneumonidae), a parasitoid of the biodiversity of hay meadows in north-eastern Switzerland on diamondback moth (Lepidoptera: Yponomeutidae). Environ. the basis of vegetation structure. Agric. Ecosyst. Environ. 93, 197– Entomol. 24, 1726–1735. 209. Idris, A.B., Grafius, E., 1997. Nectar-collecting behavior of Diadegma Shahjahan, M., 1974. Erigeron flowers as a food and attractive odor insulare (Hymenoptera: Ichneumonidae), a parasitoid of diamond- source for Peristenus pseudopallipes, a braconid parasitoid of the back moth (Lepidoptera: Plutellidae). Environ. Entomol. 26, 114– tarnished plant bug. Environ. Entomol. 3, 69–72. 120. Shrewsbury, P.M., Raupp, M.J., 2000. Evaluation of components of Isaaks, E.H., Srivastava, R.M., 1989. An Introduction to Applied vegetational texture for predicting azalea lace bug, Stephanitis Geostatistics. Oxford University Press, New York, NY. pyrioides (Heteroptera: Tingidae), abundance in managed land- Jervis, M.A., Kidd, N.A.C., Fitton, M.G., Huddleston, T., Dawah, scapes. Environ. Entomol. 29, 919–926. H.A., 1993. Flower-visiting by hymenopteran parasitoids. J. Nat. Sperry, C.E., Chaney, W.R., Shao, G., Sadof, C.S., 2001. Effects of Hist. 27, 67–105. tree density, tree species diversity, and percentage of hardscape on Kevan, P.G., Greco, C.F., 2001. Contrasting patch choice behavior by three insect pests of honeylocust. J. Arboric. 27, 263–271. immature ambush predators, a spider (Misumena vatia) and an Syme, P.D., 1975. The effects of flowers on the longevity and fecundity insect (Phymata americana). Ecol. Entomol. 26, 148–153. of two native parasites of the European pine shoot moth in Landis, D.A., Wratten, S.D., Gurr, G.M., 2000. Habitat management Ontario. Environ. Entomol. 4, 337–346. to conserve natural enemies of arthropod pests in agriculture. Tobin, P.C., Pitts, C.W., 2002. Geostatistical analysis and the impact Annu. Rev. Entomol. 45, 175–201. of moisture on the spatial and temporal distribution of larval Leius, K., 1960. Attractiveness of different foods and flowers to the Musca domestica (Diptera: Muscidae). Environ. Entomol. 31, 273– adults of some hymenopterous parasites. Can. Entomol. 92, 369– 280. 376. Tooker, J.F., Hanks, L.M., 2000a. Flowering plant hosts of adult Leius, K., 1963. Effects of pollens on fecundity and longevity of adult hymenopteran parasitoids of central Illinois. Ann. Entomol. Soc. Scambus buolianae (Htg.) (Hymenoptera: Ichneumonidae). Can. Am. 93, 580–588. Entomol. 95, 202–207. Tooker, J.F., Hanks, L.M., 2000b. Influence of plant community Leius, K., 1967. Influence of wild flowers on parasitism of tent structure on natural enemies of pine needle scale (Homoptera: caterpillar and codling moth. Can. Entomol. 99, 444–446. Diaspididae) in urban landscapes. Environ. Entomol. 29, 1305– Liebhold, A.M., Sharov, A.A., 1998. Testing for correlation in the 1311. presence of autocorrelation in insect count data. In: Baumga¨rtner, Wa¨ckers, F.L., 2004. Assessing the suitability of flowering herbs as J., Brandmayr, P., Manly, B. (Eds.), Population and Community parasitoid food sources: flower attractiveness and nectar accessi- Ecology for Insect Management and Conservation: Proceedings of bility. Biol. Control 29, 307–314. the Ecology and Population Dynamics Section of the 20th White, A.J., Wratten, S.D., Berry, N.A., Weigmann, U., 1995. International Congress of Entomology, Florence, Italy, 25–31 Habitat manipulation to enhance biological control of Brassica August, 1996. A.A. Balkema, Rotterdam, Netherlands, pp. 111– pests by hover flies (Diptera: Syrphidae). J. Econ. Entomol. 88, 117. 1171–1176. 216 E.J. Rebek et al. / Biological Control 33 (2005) 203–216

Wright, R.J., DeVries, T.A., Young, L.J., Jarvi, K.J., Seymour, R.C., Zhao, J.Z., Ayers, G.S., Graﬁus, E.J., Stehr, F.W., 1992. Eﬀects of 2002. Geostatistical analysis of the small-scale distribution of neighboring nectar-producing plants on populations of pest Lep- European corn borer (Lepidoptera: Crambidae) larvae and damage idoptera and their parasitoids in broccoli plantings. Great Lakes in whorl stage corn. Environ. Entomol. 31, 160–167. Entomol. 25, 253–258.