* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Insect herbivory in an experimental agroecosystem: the relative
Island restoration wikipedia , lookup
Biogeography wikipedia , lookup
Plant defense against herbivory wikipedia , lookup
Wildlife crossing wikipedia , lookup
Extinction debt wikipedia , lookup
Restoration ecology wikipedia , lookup
Occupancy–abundance relationship wikipedia , lookup
Biodiversity action plan wikipedia , lookup
Overexploitation wikipedia , lookup
Renewable resource wikipedia , lookup
Wildlife corridor wikipedia , lookup
Source–sink dynamics wikipedia , lookup
Reconciliation ecology wikipedia , lookup
Mission blue butterfly habitat conservation wikipedia , lookup
Habitat destruction wikipedia , lookup
Habitat conservation wikipedia , lookup
Biological Dynamics of Forest Fragments Project wikipedia , lookup
Oikos 118: 14771486, 2009 doi: 10.1111/j.1600-0706.2009.17720.x, # 2009 The Authors. Journal compilation # 2009 Oikos Subject Editor: Daniel Gruner. Accepted 6 April 2009 Insect herbivory in an experimental agroecosystem: the relative importance of habitat area, fragmentation, and the matrix Kyle J. Haynes and Thomas O. Crist K. J. Haynes ([email protected]), Dept of Biology, Univ. of Louisiana, PO Box 42451, Lafayette, LA 70504, USA. T. O. Crist, Dept of Zoology, Miami Univ., Oxford, OH 45056, USA. Habitat area, fragmentation, and the surrounding matrix influence levels of herbivory in various ecosystems, but the relative importance of these effects has rarely been assessed. We compared levels of herbivory and densities of dominant arthropod herbivores (the hemipteran insects Agallia constricta, Empoasca fabae, Therioaphis trifolii, Lygus lineolaris and Halticus bractatus) among experimental plots that varied in the area and fragmentation of clover habitat and the composition of the matrix (bare ground or grass) surrounding clover habitat. To assess levels of herbivory, we compared clover biomass within herbivore exclosures to the biomass accessible to herbivores. The area and fragmentation of clover habitat, as well as matrix composition, significantly influenced the collective densities of herbivores, although each species exhibited unique responses to habitat structure. Herbivory was strongest in plots with large (64 m2) as compared to small (16 m2) amounts of clover habitat. The difference in clover biomass between the inside and outside of exclosures increased significantly with increasing density of Empoasca fabae but was unrelated to the densities of the other herbivores, suggesting that Empoasca fabae was an exceptionally important herbivore in this system. This study supports the view that herbivore densities and herbivory generally increase with increasing area of plant monocultures, but emphasizes that levels of herbivory may be driven primarily by one or a few key herbivore species. There is a large body of literature on the effects of the area and fragmentation of a focal habitat type and composition of the surrounding matrix on the distributions and abundances of species (Moilanen and Hanski 1998, Debinski and Holt 2000, Tscharntke et al. 2002, Cronin 2003). The effects of these factors on levels of herbivory have received a smaller, but still considerable, amount of attention (Thies et al. 2003, Östergård and Ehrlén 2005, Valladares et al. 2006). However, few studies have evaluated the relative importance of habitat area, fragmentation, and matrix composition to levels of herbivory (but see Diekötter et al. 2007). If one or a few herbivore species are responsible for most of the herbivory in a given community, the feeding specialization of these key species may determine the manner and strength with which habitat area, fragmentation and matrix composition affect levels of herbivory. Positive, negative, and neutral density responses to habitat area are frequently observed (Connor et al. 2000, Matter 2000, Zaviezo et al. 2006), but species with strong preferences for a focal habitat type are more likely to display positive densityarea relationships in the preferred habitat type than are habitat-generalist species (Hambäck et al. 2007). The fragmentation of a focal habitat type is generally thought to adversely affect populations but, in fact, positive effects of habitat fragmentation may be more likely for species that use multiple habitat types (Law and Dickman 1998). Fragmentation of a focal habitat type may have positive effects on a habitat generalist by increasing the extent to which complementary resources in the matrix occur within the organism’s dispersal range (Law and Dickman 1998, Fahrig 2003). Finally, whereas habitat specialists may respond more strongly to the area and fragmentation of a focal habitat type, habitat generalists may be more sensitive to the composition of the matrix (Brotons et al. 2003, Steffan-Dewenter 2003). For example, Haynes et al. (2007) found that (adult) densities of the polyphagous grasshopper Melanoplus femurrubrum in a focal habitat type (clover) were more strongly influenced by the availability of complementary resources in the matrix than by the area and fragmentation of the focal habitat. Assessing the relative importance of different attributes of habitat structure and composition to herbivory presents particular challenges. The habitat attributes of interest often covary in natural landscapes, hindering a researcher’s ability to isolate their independent effects. For example, Fahrig’s (2003) review revealed that most studies examining the effects of habitat area and fragmentation on population or community dynamics confounded the effects of these two factors. Furthermore, plant size or quality may covary with landscape features (e.g. matrix composition; Haynes and Cronin 2004), making it difficult to isolate the effects of herbivory from the effects of other factors on measures of plant growth (e.g. biomass, leaf area). One approach to 1477 evaluating the relative importance of different habitat attributes to herbivory is to combine observational data on herbivore densities and plant growth with experimental manipulations of both the habitat attributes and herbivore densities. In this study, we examine the relative importance of habitat area, habitat fragmentation, and matrix composition in determining levels of herbivory. We created a model agroecosystem consisting of replicated plots containing subplots of the forage-crop plant red clover Trifolium pratense. We manipulated the area and fragmentation of clover habitat and composition of the matrix (grass or bareground) according to a factorial design. Unlike many previous experimental studies (Fahrig 2003), our design manipulated habitat area independently of habitat fragmentation. In the experimental plots, we recorded the densities of the five numerically dominant herbivores: Agallia constricta, Empoasca fabae, Therioaphis trifolii, Lygus lineolaris and Halticus bractatus. To quantify levels of herbivory, we placed small herbivore exclosures in the experimental plots. We also examined the impacts of each herbivore species on clover biomass based on regressions of paired exclosure-control differences in clover biomass and herbivore abundance. Since clover represents the preferred habitat for all of the dominant herbivore species (Methods), we expected that densities and herbivory would increase with the area of clover habitat. We also expected that habitat-generalist species would have higher densities in clover habitat bordered by the grass matrix because it may provide complementary resources. Furthermore, we expected fragmentation to positively affect habitat generalists. Effects of habitat fragmentation on specialist herbivores may be positive or negative, because although dispersal mortality and densities of habitat-generalist predators may increase with fragmentation, parasitoids often are less effective in fragmented landscapes (Kruess and Tscharntke 1994, Tscharntke and Brandl 2004). Methods Study system The focal plant in this study was the herbaceous, perennial red clover Trifolium pratense. Red clover is an important forage crop worldwide, both in intensely managed cultivation and extensively managed pastures (Guretzky et al. 2005), and is commonly grown in clover/grass polycultures (Heath et al. 1973). The dominant herbivores of clover at our study site were all Hemiptera. They consisted of the leafhoppers Agallia constricta and Empoasca fabae (Cicadellidae), the aphid Therioaphis trifolii (Aphididae), the plant bug Lygus lineolaris (Mirididae), and the fleahopper Halticus bractatus (Mirididae). Therioaphis trifolii is only known to feed on legumes (e.g. alfalfa, clovers; Milne 1998, Nair et al. 2003). The remaining herbivore species are known to feed on a wide variety of herbaceous plants (Osborn 1928, Henry 1983, Young 1986, USDA 2002), but were found in much higher densities on clover than grass in our system (Haynes unpubl.). 1478 Experimental plots We conducted the experiment in the summer of 2006 in a 2-ha field at Miami Univ. Ecology Research Center near Oxford, OH. Two years earlier (in 2004), we created replicated 14 14 m plots, each containing four patches (or subplots) of red clover. The clover subplots varied in fragmentation (continuous or isolated by 2 m), habitat area (4 or 16 m2), and matrix type (grass or bare ground) according to a fully factorial design (Fig. 1). Each combination of fragmentation, area, and matrix was originally replicated in four separate plots, and arranged in a completely randomized design. However, we excluded two plots from the experiment due to clover mortality in the spring of 2006, leaving two treatment combinations (large clover area/bare-ground matrix/fragmented and small clover area/grass matrix/continuous) with three replicate plots. We established the clover subplots and grass matrix by sowing the plots with seeds of red clover Trifolium pratense and orchard grass Dactylis glomerata. We maintained bare-ground matrix within experimental plots and in the 8-m strips between plots by applying herbicide at monthly intervals. We kept the grass matrix free of forbs by applying 2,4-D herbicide annually in early summer (June). We mowed the grass monthly to minimize variation in the height of vegetation among plots because the structural complexity of matrix habitats may influence rates of movement into and out of focal patches (Kareiva 1985, Lawrence and Bach 1989). Finally, we regularly weeded all clover habitat. Herbivory experiment To quantify the effects of herbivores on clover biomass, we placed small exclosures in one randomly selected subplot per plot. Within each selected subplot, we placed the exclosure at a stratified random location. An exclosure consisted of fine-mesh (0.25 mm) polyester ‘no-see-um’ netting sewn to fit over a small (0.25w 0.4l 0.5h m) frame constructed of PVC tubing. We pushed the legs of the frame 5 cm into the soil. We prevented insects from entering the exclosures by anchoring the base of the netting firmly against the ground using iron rods. To kill any insects that may have been inside the exclosures, we sprayed 0.15 l of an aqueous solution containing organic pyrethrin Figure 1. Aerial view of the field containing 36 14 14 m experimental plots. Photo credits: Beth Dickman. pesticide through the netting onto the clover inside. Because the pesticide was diluted in water (1:500 dilution), we sprayed an equivalent amount of water onto an equivalent area of clover within the same subplot, which was used as a control. We assigned each control area to a stratified random location. Experiments testing for potential effects of the exclosures or pesticide on clover are described in the following section. The exclosures were in place for a 6-week period in 2006 while insects were at peak abundance (mid July to late August). After six weeks, we compared clover biomass inside the exclosures to clover biomass at control locations. We clipped the clover biomass at these two locations using a rectangular quadrat (0.2 0.35 m) to standardize the area sampled. The plant material was dried at 608C for 48 h and then weighed. We evaluated effects of herbivore exclusion on clover biomass using a profile ANOVA (Tabachnick and Fidell 2000). This procedure, which is comparable to repeated measures ANOVA, allows for the two clover biomass measurements (exclosure and control) taken from each plot to be non-independent. Clover biomass measures taken from the same plot could potentially be more similar than measures taken in different plots due to differences in abiotic conditions (e.g. soil quality). We also used the profile ANOVA to test whether the effect of herbivore exclusion on clover biomass was dependent on clover habitat area, habitat fragmentation or matrix composition. In addition, we tested whether clover biomass at control locations was influenced by the plot treatments using a three-way ANOVA. The clover biomass data were squareroot transformed prior to these analyses to homogenize variances and improve normality of residuals. We also removed a linear spatial trend in the control-location biomass data that we found by performing a regression against the x and y spatial positions of the plots (Crist et al. 2006). We did not use detrended data in the profile ANOVA, however, because this would preclude direct comparison of differences in biomass inside and outside of exclosures within each plot. We measured the densities of the herbivore species in the clover habitat of each experimental plot in mid July and late August. For each plot, we collected insects from the subplot containing the herbivore exclosure using a D-vac insect vacuum. Within each of these subplots, we placed the 0.08 m2 sampling head of the D-vac over the clover at four stratified random locations. The suction samples were transferred to plastic bags and placed in a freezer until all insects were dead. We then counted the insects using a stereoscopic dissecting microscope. To evaluate the relationships between the densities of individual herbivore species and the level of herbivore damage to clover, we performed multiple regression analysis using the densities of each herbivore species as predictor variables and the difference in clover biomass between the exclosure and control location (exclosure biomass control biomass) as the response variable. In addition, we examined the collective effects of the herbivores on clover biomass by performing a linear regression with total herbivore density as the predictor variable. We also evaluated the effects of the area and fragmentation of clover habitat and matrix composition on the densities of the five herbivore species using MANOVA. Following significant results from a MANOVA, we evaluated the effects of habitat area, fragmentation, and matrix composition on the individual herbivore species using univariate ANOVA (Quinn and Keough 2002). We analyzed the July and August data separately because the effects of herbivores on clover biomass could potentially shift over time. To protect against inflated type I error due to conducting two non-independent tests (on July and August densities), we set the significance level for MANOVA and multiple regression analyses to a 0.025 (0.05/2). To minimize heterogeneity of variance and to normalize residuals, the densities of each insect species were squareroot transformed prior to the analyses. As with the clover biomass data, we removed linear spatial trends in the densities of three herbivore species (Halticus bractatus in July and August, Empoasca fabae in July, and Therioaphis trifolii in July) prior to fitting the MANOVA and ANOVA models. Insect dispersal or spatially correlated environmental conditions (e.g. soil quality) could potentially have lead to non-independence of the insect density or clover biomass measurements taken from neighboring plots. We tested for spatial autocorrelation of the residuals from the ANOVA and regression models (Ver Hoef and Cressie 1993) using the nonparametric spatial correlation function (Bjørnstad and Falck 2001), which revealed that none of the residuals exhibited significant spatial autocorrelation at any lag distance between plots. Exclosure and pesticide effects on clover Based on a previous field study (Cronin 2007) using insect cages similar to ours, we did not expect the exclosures to affect clover biomass. Nonetheless, we conducted a separate but concurrent experiment to examine exclosure effects on plant biomass. We built ‘leaky’ exclosures, which allowed insects to access the clover inside. These ‘leaky’ exclosures were identical to the exclosures used in the herbivory experiment except that there were two large rectangular holes in the netting on opposite sides of the exclosure. The holes were 10 cm wide and extended from the soil to a height of 20 cm. We placed ten ‘leaky exclosures’ in a small secondary field (0.2 ha) of red clover 1 km from the experimental plots. Exclosures and paired control locations were arrayed along a linear transect. Exclosure-control pairs were spaced 2 m apart. We placed each exclosure 1 m to the left or right of the transect (at random) and located the paired control on the opposite side (also 1 m from the transect). After six weeks, we sampled clover biomass at each location using methods described previously. We tested whether clover biomass differed between the exclosures and controls using a paired t-test. Prior to this analysis, the clover biomass data were ln-transformed. We also experimentally tested whether clover sprayed with the aqueous pesticide solution differed from clover sprayed with water, as a check on the direct effects of pyrethrins on clover growth. We established 20 herbivore exclosures in the secondary clover field. We sprayed half of the exclosures with the pesticide solution and other half with an equivalent amount of water. The treatments were assigned to the exclosures at random and clover biomass was 1479 Results Herbivory experiment We found a significant interactive effect of clover habitat area and matrix composition on clover biomass at control locations (Table 1). In plots with 64 m2 of clover habitat, biomass was relatively constant across the combinations of fragmentation and matrix composition (Fig. 2). On the other hand, clover biomass in plots with 16 m2 of habitat was substantially higher in plots with bare-ground matrix than in plots with grass matrix. Clover biomass was significantly higher inside the experimental exclosures compared to control locations with no exclosure (Table 2, Fig. 3). In addition, the effect of the exclosures on clover biomass differed according to clover habitat area. In plots with 16 m2 of clover habitat, clover biomass did not differ strongly between exclosures and controls. In plots with 64 m2 of clover habitat, however, clover biomass was 1.4 times higher inside the exclosures. Thus herbivores had strong effects on clover biomass in larger patches of clover. Herbivory effects on clover biomass were unrelated to matrix composition and habitat fragmentation. Based on a multiple regression analysis, the differences in biomass between the exclosures and controls (exclosure biomass control biomass) were not significantly related to the July densities of any of the herbivore species (Table 3). However, there was a positive relationship between the difference in biomass and the density of Empoasca fabae in August (Table 3, Fig. 4). The August densities of all other insect species were unrelated to the difference in biomass between exclosures and controls. For the August data, a regression model including all of the herbivore species explained 26.6% of the variation in the biomass differential among plots (based on the r2 value). Despite the apparent effects of Empoasca fabae on clover biomass, we found no relationship between total herbivore density and the biomass differential in July (biomass differential 1.121 (density)0.564.823, n 30, p 0.585, r2 0.011) or August (biomass differential10.102 (density)0.5 43.323, n 30, p0.287, r2 0.04). Table 1. ANOVA results on the effects of habitat area, habitat fragmentation and matrix composition on clover biomass in control locations. Significant results at the a 0.05 level are shown in bold. Source DF F p Area Matrix Fragmentation AreaMatrix AreaFragmentation MatrixFragmentation AreaMatrixFragmentation Error 1 1 1 1 1 1 1 22 0.054 3.026 1.068 9.544 0.094 0.090 0.439 0.819 0.096 0.313 0.005 0.763 0.767 0.514 1480 20 Sq. root (clover biomass [g m-2]) measured after six weeks. We assessed whether clover biomass differed between exclosures sprayed with pesticide solution or water with ANOVA. Clover biomass was lntransformed prior to this analysis. 16 Bare, continuous Bare, fragmented Grass, continuous Grass, fragmented 1 1, 2 12 1, 2 2 8 4 0 Large Small Habitat area Figure 2. Effects of habitat area, habitat fragmentation, and matrix composition on clover biomass in control locations (means1 SE). Means labeled by different numbers respresent significant differences at the a0.05 level (Tukey’s HSD tests evaluated differences among all area and matrix combinations). In July, the densities of herbivore species were collectively influenced by all three main effects, clover area, clover fragmentation, and matrix composition (Appendix 1). Three of the five herbivore species displayed a trend towards higher density in the plots with greater clover area (Halticus bractatus, Lygus lineolaris, Empoasca fabae ; Fig. 5), though this trend was significant only for Halticus bractatus (Appendix 2). Densities of this species were 3.2 times greater in plots with 64 compared to 16 m2 of clover habitat. Conversely, Therioaphis trifolii density was 3.5 times higher in the latter plots. Matrix composition significantly affected the densities of both Therioaphis trifolii and Agallia constricta (Appendix 2). Therioaphis trifolii densities were 5.8 times higher in clover habitat embedded within the bare-ground matrix. Agallia constricta exhibited the opposite response; densities were twice as high in clover habitat within the grass matrix. Finally, fragmentation did not significantly affect the July densities of any single herbivore species. In August, herbivore densities were not collectively influenced by any of the experimental factors (Appendix 1). With regard to the effect of clover habitat area, however, all of the herbivore species individually exhibited the same trends that were observed in July. Table 2. Results from a profile ANOVA on effects of herbivore exclosure, habitat area, matrix composition, and habitat fragmentation on clover biomass. Significant results at the a 0.05 level are shown in bold. Source DF F p Exclosure ExclosureArea ExclosureMatrix ExclosureFragmentation ExclosureAreaMatrix ExclosureAreaFragmentation ExclosureMatrixFragmentation ExclosureAreaMatrixFragmentation Error 1 1 1 1 1 1 1 1 22 7.178 5.256 1.036 0.028 1.862 0.512 0.828 0.168 0.014 0.032 0.320 0.868 0.186 0.482 0.373 0.686 210 300 Biomass differential (residuals) Bare, continuous Biomass differential (g m-2) Bare, fragmented Grass, continuous 140 Grass, fragmented 70 0 200 100 0 -100 -200 -300 -400 0 -70 1 2 3 4 5 6 7 Square root (no. m-2) Large Small Habitat area Figure 3. Differences in clover biomass between herbivore exclosures and control locations (biomass inside exclosures control biomass, means1 SE). Results from a profile ANOVA (Table 2) showed that the effect of herbivore exclusion on biomass was greater in plots with 64 m2 of clover habitat than in plots with 16 m2 of clover habitat. Exclosure and pesticide effects on clover Our experimental test for enclosure effects on clover biomass revealed no difference between controls and the ‘leaky’ exclosures (0.00890.427 g m 2, mean difference of ln(g m 2) 995% CI, t9 0.466, p 0.652), which allowed insects to move freely in or out of the exclosures. In addition, clover biomass did not differ between exclosures sprayed with pesticide solution (82.498.4 g m 2, mean9 1 SE) and exclosures sprayed with water (79.696.1 g m2; F1,18 0.003, p0.955). Figure 4. Relationship between the density of Empoasca fabae and the effect of herbivores on clover biomass. The effect of herbivores on clover biomass was measured as the difference in clover biomass between herbivore exclosures and control locations (biomass inside exclosure control biomass). To indicate the effect of Empoasca fabae alone on clover biomass, the residuals from a model including all of the herbivores except Empoasca fabae were regressed against the density of Empoasca fabae (biomass differential [residuals] 38.26(Empoasca fabae density)0.5 114.21, n30, r2 0.219). exclosures and controls to differences in the intensity of herbivory. Thus, herbivory was much stronger in plots with greater clover area. Similar findings of insect herbivory increasing with increasing patch area have been reported in other systems (e.g. understory herbs, forest fragments; Östergård and Ehrlén 2005, Valladares et al. 2006). Unlike clover area, the fragmentation of clover habitat and composition of the matrix had no effects on herbivory. Habitat-structure effects on herbivore densities and herbivory Discussion Our study shows that herbivore damage to red clover was influenced by the area of clover habitat. We found a substantial difference in clover biomass between exclosures and open controls in plots with 64 m2 of clover habitat, but no such difference in biomass in plots with 16 m2 of clover habitat. Because we found no exclosure effects on clover biomass, we attribute differences in clover biomass between The strong effect of habitat area on herbivory may be partly explained by the collective effects of habitat area on herbivore densities. Densities of three of the five herbivore species (Halticus bractatus, Lygus lineolaris and Empoasca fabae) increased with increasing clover area, whereas two herbivore species (Therioaphis trifolii and Agallia constricta) exhibited negative responses to increasing clover area (these responses were statistically significant only for Halticus Table 3. Results from multiple regression analyses examining the relationships between the densities of each herbivore species in July and August and the clover biomass differential (biomass inside exclosure biomass outside exclosure). Densities were square-root transformed. Significant results at the a0.05 level are shown in bold. Herbivore species Agallia constricta Empoasca fabae Therioaphis trifolii Lygus lineolaris Halticus bractatus July August Coefficient t p Coefficient t p 3.990 2.434 0.843 10.841 14.733 0.400 0.303 0.119 0.507 1.124 0.693 0.764 0.906 0.617 0.272 5.490 39.112 10.791 8.444 5.545 1.153 2.634 1.148 0.468 0.679 0.735 0.015 0.260 0.644 0.504 July: r2 0.101. August: r2 0.266. 1481 Bare, continuous Bare, fragmented Grass, continuous Grass, fragmented Agallia constricta 120 Grass > Bare (p < 0.001) 50 40 30 20 10 0 80 40 0 Empoasca fabae 30 30 20 20 10 10 Density (no. m-2) 0 2500 2000 1500 1000 500 0 0 Therioaphis trifolii Small > Large (p = 0.005) Bare > Grass (p= 0.002) 50 40 30 20 10 0 Lygus lineolaris 25 20 15 10 5 0 10 8 6 4 2 0 Halticus bractatus 50 40 30 20 10 0 Large > Small (p = 0.001) Large Small 100 80 60 40 20 0 Large Small Habitat area Habitat area July August Figure 5. Effects of habitat area, habitat fragmentation, and matrix composition on the densities of Agallia constricta, Empoasca fabae, Therioaphis trifolii, Lygus lineolaris and Halticus bractatus (means1 SE). After finding that the densities of the herbivore species were collectively influenced by the experimental factors in July, but not August (based on MANOVAs), the July data was further analyzed by performing separate ANOVAs for each herbivore species (Quinn and Keough 2002). Significant results at the a0.05 level are listed in the figure. bractatus and Therioaphis trifolii). Positive densityarea relationships in herbivorous insects are traditionally thought to result from increased rates of immigration into and (or) decreased rates of emigration out of large host-plant patches in order to maximize feeding efficiency (the resource concentration hypothesis; Root 1973). Given that all of the herbivore species appeared to strongly prefer the clover habitat over the grass matrix (all exhibited much higher densities in clover; Haynes unpubl.), this hypothesis may explain the positive responses of Halticus bractatus, Lygus lineolaris and Empoasca fabae to increasing clover area. Even among habitat-specialist species, however, negative density area relationships, like we report for Therioaphis trifolii and Agallia constricta, are not atypical. In a meta-analysis, Hambäck and Englund (2005) found that various aphid, leafhopper and planthopper species exhibited densityarea relationships ranging from slightly negative to slightly positive. Negative densityarea relationships, they showed, 1482 are likely for species exhibiting area-dependent immigration and perimeter-dependent emigration (Hambäck and Englund 2005). An alternative explanation for the negative responses of Therioaphis trifolii and Agallia constricta to increasing clover area is that predation pressure on these species was higher in plots with large clover subplots. Reductions in habitat area are often expected to have stronger adverse effects on predators than on their prey (Holt et al. 1999, Tscharntke and Brandl 2004). One major consequence of this effect is that reducing the area of habitat could potentially lead to outbreaks of herbivores and plant destruction (With et al. 2002). If predation was responsible for the negative densityarea relationships of Therioaphis trifolii and Agallia constricta, this effect was not sufficient to have a cascading influence on clover biomass. For herbivores that forage in multiple habitat types, densities may often be elevated in patches of the focal habitat type that border matrix habitat types that provide supplementary or complementary resources (Dunning et al. 1992, Haynes et al. 2007). Consistent with this hypothesis, we found that Agallia constricta, a polyphagous leafhopper which feeds on both forbs and grasses, exhibited higher densities in clover habitat embedded within grass matrix compared to bare-ground matrix. The more-specialized, legume-feeding aphid, Therioaphis trifolii, showed the opposite response to matrix composition; densities were higher in clover within bare-ground matrix. The higher densities of aphids in clover habitat embedded within bareground matrix may be the result of a reluctance to move over bare ground. The planthopper Prokelisia crocea, a monophagous herbivore of the grass Spartina pectinata, displays a similar distributional pattern. The planthopper reaches higher densities in host-plant patches bordered by mudflats than in patches bordered by non-host grasses because the rate of emigration from patches in mudflats is much lower (Haynes and Cronin 2003, Cronin 2007, Reeve et al. 2008). Despite the effects of matrix composition on herbivore densities in our system, matrix composition did not influence levels of herbivory. The lack of effects of matrix composition on herbivory may be explained by the fact that neither Agallia constricta nor Therioaphis trifolii appeared to strongly affect clover biomass. Like matrix composition, habitat fragmentation did not affect levels of herbivory. The collective densities of herbivore species were influenced by habitat fragmentation, but no single species was strongly affected by this factor. The lack of clear fragmentation effects may be partially explained by the fact that the scale of fragmentation in this study was likely small relative to the dispersal abilities of three of the five herbivore species. The leafhoppers Agallia constricta and Empoasca fabae and the plant bug Lygus lineolaris are sufficiently mobile that the fragmentation of clover habitat probably did little to improve access to resources in the matrix (Fleischer et al. 1988, Hoffman and Hogg 1992, B. Schroeder pers. comm.). For Halticus bractatus, however, it is conceivable that fragmentation increased the ability to forage both in clover and the matrix since a large percentage of adult females are wingless (Day 1991). Similarly, most Theroaphis trifolii adults were wingless in July and August (92% and 100% of captured adults). Thus, rates of movement of this habitat-specialist herbivore among clover subplots were likely substantially reduced by the fragmentation of clover habitat. Competition between clover and matrix vegetation Our results also showed that clover biomass was influenced by an interactive effect of clover habitat area and composition of the matrix. Clover biomass was highest in plots with less clover area and bare-ground matrix. Given that we did not see interactive effects of area and matrix on herbivore densities, this effect was probably not a result of herbivory. It is more likely that the observed differences in clover biomass resulted because of competition between clover plants and grass in the matrix, particularly along clover-matrix edges. In plots with bare-ground matrix, clover plants near the edges of subplots may have exhibited increased growth due to reduced competition for water or nutrients. Because clover plants in small (4 m2) clover subplots were closer to clover-matrix edges, on average, than in large clover subplots (16 m2), the lack of competitors at the cloverbare-ground boundary would likely be more beneficial to clover in small clover subplots. A review by Haynes and Cronin (2004) found that matrix composition often influences the quality (e.g. plant size, tissue nitrogen content) of focal patches of vegetation by altering competition between plants in the patch and the matrix or by altering nutrient subsidies across the patch edge. Species-specific impacts of herbivores The density of only one herbivore species, Empoasca fabae, was significantly related to the difference in clover biomass between exclosures and controls. The biomass differential (exclosure biomass control biomass) increased with increasing density of Empoasca fabae in August, explaining approximately one fifth of the variation in the biomass differential among plots (Fig. 3). This greater importance of Empoasca fabae is likely due to the feeding habits of this species. Unlike many other hemipterans which are sheath feeders (stylet tips are sealed into a plant’s vascular cell using a sheath composed of hardened saliva), Empoasca spp. feed by rupturing plant cells with a unique form of stylet movement, secreting saliva, and then sipping the contents of damaged cells (reviewed by Backus et al. 2005). Consequently, Empoasca fabae and its congeners are especially likely to cause hopperburn, a type of damage that results in tip-wilting, leaf yellowing, and plant stunting (reduced growth). Stunting caused by Empoasca fabae is a major cause of reduced yield in legume forage crops in North America (Backus et al. 2005). Empoasca fabae was likely the most damaging herbivore in our clover agroecosystem, but spatial variation in levels of herbivory can not be understood solely on the basis of the spatial distribution of this species. Although our experiment revealed that the effects of herbivores on clover biomass were much stronger in plots with more clover area, densities of Empoasca fabae were only slightly higher in these plots. One possible explanation for the disproportionately high reduction in clover biomass in plots with large clover subplots is that increased clover habitat area had positive effects on the densities of three of the five dominant herbivores (Empoasca fabae, Lygus lineolaris and Halticus bractatus) in both July and August. Densities of Halticus bractatus, for example, were 1.9 and 3.2 times higher in large than in small clover subplots in July and August, respectively. Furthermore, although the multivariate response of all five herbivore species in August to habitat area was not significant, the consistently positive effects of clover habitat area on the densities of Empoasca fabae, Lygus lineolaris and Halticus bractatus likely explains the importance of habitat area in influencing levels of herbivory. Conclusions Our findings support the view that the area of a focal habitat (e.g. crop) is an important factor influencing herbivore densities and herbivore damage (Root 1973) as well as the concept that the practice of planting in large monocultures may ensure continued high losses of crop 1483 productivity to herbivores (Russell 1989, Daily 1997, Altieri 1999, Landis et al. 2000, Tscharntke et al. 2005). Given the small size of our experimental plots, however, how well our conclusions apply to agricultural landscapes is an important question. Monotonically increasing or decreasing density-area relationships have frequently been reported for herbivorous insects (MacGarvin 1982, Nowicki et al. 2007, but see Hambäck and Englund 2005), suggesting that herbivore densityarea relationships and levels of herbivory may remain more or less constant across a wide range of spatial scales. In contrast, matrix composition may often be more important in influencing herbivory within small experimental fields than in larger agricultural fields. Cross-edge foraging of matrix-dwelling or habitat-generalist herbivores and natural enemies into agricultural fields results in greater impacts on community structure near the field margin than in the field interior (Clough et al. 2005, Rand et al. 2006). Therefore, herbivore impacts in large fields, with their low edge-to-area ratios, may be less dependent on composition of the surrounding matrix. Finally, given that colonization rates typically decrease with increasing distance between source and recipient habitats (Hanski 1999), habitat fragmentation may be more important to community structure and herbivory at larger scales. By documenting considerable asymmetry in the impacts of different herbivore species on plant biomass, this study suggests that the effects of landscape features on herbivory may differ among systems supporting different suites of herbivores. The relative importance of habitat area, fragmentation, and matrix composition to herbivory in a given system could depend on how the distributions of a few key herbivore species, rather than overall herbivore densities, are influenced by these factors. This notion suggests that the relative importance of different landscape attributes to herbivory may be difficult to predict without a detailed understanding of the ecological impacts of the species in a given system (Rosenlew and Roslin 2008). Acknowledgements Special thanks to Candace Crist for sewing the herbivore exclosures and to Tim Diekötter for assisting with pilot studies. Laura Douglas, Sam Evans, Rodney Kolb, Brad Schroeder and Dave Stasek provided valuable help in the field. Daniel Gruner provided useful comments on earlier drafts of this manuscript. Funding for this project was provided by Miami Univ. and a Miami Univ. Postdoctoral Research Scholarship. References Altieri, M. A. 1999. The ecological role of biodiversity in agroecosystems. Agric. Ecosyst. Environ. 74: 1931. Backus, E. A. et al. 2005. Mechanisms of hopperburn: an overview of insect taxonomy, behavior and physiology. Annu. Rev. Entomol. 50: 125151. Brotons, L. et al. 2003. Are fragments islands? Landscape context and density-area relationships in boreal forest birds. Am. Nat. 162: 343357. Bjørnstad, O. N. and Falck, W. 2001. Nonparametric spatial covariance functions: estimation and testing. Environ. Ecol. Stat. 8: 5370. 1484 Clough, Y. et al. 2005. Spider diversity in cereal fields: comparing factors at local, landscape and regional scales. J. Biogeogr. 32: 20072014. Connor, E. F. et al. 2000. Individualsarea relationships: the relationship between animal population density and area. Ecology 81: 734748. Crist, T. O. et al. 2006. Spatial variation in insect community and species responses to habitat loss and plant community composition. Oecologia 147: 510521. Cronin, J. T. 2003. Matrix heterogeneity and hostparasitoid interactions in space. Ecology 84: 15061516. Cronin, J. T. 2007. From population sources to sieves: the matrix alters hostparasitoid sourcesink structure. Ecology 88: 29662976. Daily, G. C. et al. 1997. Ecosystem services: benefits supplied to human societies by natural ecosystems. Iss. Ecol. no. 2. Ecol. Soc. Am. Day, W. H. 1991. The peculiar sex ratio and dimorphism of the garden fleahopper, Halticus bractatus (Hemiptera, Miridae). Entomol. News 102: 113117. Debinski, D. M. and Holt, R. D. 2000. A survey and overview of habitat fragmentation experiments. Conserv. Biol. 14: 342 355. Diekötter, T. et al. 2007. Direct and indirect effects of habitat area and matrix composition on species interactions among flowervisiting insects. Oikos 116: 15881598. Dunning, J. B. et al. 1992. Ecological processes that affect populations in complex landscapes. Oikos 65: 169175. Fahrig, L. 2003. Effects of habitat fragmentation on biodiversity. Annu. Rev. Ecol. Evol. Syst. 34: 487515. Fleischer, S. J. et al. 1988. Dispersal of Lygus lineolaris (Heteroptera, Miridae) adults through cotton following nursery host destruction. Environ. Entomol. 17: 533541. Guretzky, J. A. et al. 2005. Species diversity and functional composition of pastures that vary in landscape position and grazing management. Crop Sci. 45: 282289. Hambäck, P. A. and Englund, G. 2005. Patch area, population density and the scaling of migration rates: the resource concentration hypothesis revisited. Ecol. Lett. 8: 10571065. Hambäck, P. A. et al. 2007. Habitat specialization, body size, and family identity explain lepidopteran densityarea relationships in a cross-continental comparison. Proc. Natl Acad. Sci. USA 104: 83688373. Hanski, I. 1999. Metapopulation ecology. Oxford Univ. Press. Haynes, K. J. and Cronin, J. T. 2003. Matrix composition affects the spatial ecology of a prairie planthopper. Ecology 84: 28562866. Haynes, K. J. and Cronin, J. T. 2004. Confounding of patch quality and matrix effects in herbivore movement studies. Landscape Ecol. 19: 119124. Haynes, K. J. et al. 2007. Resource complementation and the response of an insect herbivore to habitat area and fragmentation. Oecologia 153: 511520. Heath, M. E. et al. 1973. Forages: the science of grassland agriculture (3rd ed.). Iowa State Univ. Press. Henry, T. J. 1983. The garden fleahopper genus Halticus (Hemiptera, Miridae) resurrection of an old name and key to species of the western hemisphere. Proc. Entomol. Soc. Wash. 85: 607611. Hoffman, G. D. and Hogg, D. B. 1992. Effect of alfalfa water stress on potato leafhopper (Homoptera, Cicadellidae) plant preference and oviposition rate. Ann. Entomol. Soc. Am. 85: 506516. Holt, R. D. et al. 1999. Trophic rank and the speciesarea relationship. Ecology 80: 14951504. Kareiva, P. 1985. Finding and losing host plants by Phyllotreta: patch size and surrounding habitat. Ecology 66: 18091816. Kruess, A. and Tscharntke, T. 1994. Habitat fragmentation, species loss, and biological control. Science 264: 15811584. Landis, D. A. et al. 2000. Habitat management to conserve natural enemies of arthropod pests in agriculture. Annu. Rev. Entomol. 45: 175201. Law, B. S. and Dickman, C. R. 1998. The use of habitat mosaics by terrestrial vertebrate fauna: implications for conservation and management. Biodiv. Conserv. 7: 323333. Lawrence, W. S. and Bach, C. E. 1989. Chrysomelid beetle movements in relation to host-plant size and surrounding nonhost vegetatation. Ecology 70: 16791690. Matter, S. F. 2000. The importance of the relationship between population density and habitat area. Oikos 89: 613619. MacGarvin, M. 1982. Speciesarea relationships of insects on host plants: herbivores on rosebay willowherb. J. Anim. Ecol. 51: 207223. Milne, W. M. 1998. Suitability of clovers (Trifolium species and cultivars) as hosts of spotted clover aphid, a biotype of Therioaphis trifolii (Monell) (Hemiptera: Aphididae). Aust. J. Exp. Agric. 38: 241245. Moilanen, A. and Hanski, I. 1998. Metapopulation dynamics: effects of habitat quality and landscape structure. Ecology 79: 25032515. Nair, R. M. et al. 2003. Evaluating pasture legumes for resistance to aphids. Aust. J. Exp. Agric. 43: 13451349. Nowicki, P. 2007. From metapopulation theory to conservation recommendations: lessons from spatial occurrence and abundance patterns of Maculinea butterflies. Biol. Conserv. 140: 119129. Osborn, H. 1928. The leafhoppers of Ohio. Ohio Biol. Surv. Bull. 14. .Östergård, H. and Ehrlén, J. 2005. Among population variation in specialist and generalist seed predation the importance of host plant distribution, alternative hosts and environmental variation. Oikos 111: 3946. Quinn, G. P. and Keough, M. J. 2002. Experimental design and data analysis for biologists. Cambridge Univ. Press. Rand, T. A. et al. 2006. Spillover edge effects: the dispersal of agriculturally subsidized insect natural enemies into adjacent natural habitats. Ecol. Lett. 9: 603614. Reeve, J. D. et al. 2008. Diffusion models for animals in complex landscapes: incorporating heterogeneity among substrates, individuals and edge behaviours. J. Anim. Ecol. 77: 898 904. Root, R. B. 1973. Organization of plantarthropod association in simple and diverse habitats fauna of collards (Brassica oleracea). Ecol. Monogr. 43: 95120. Rosenlew, H. and Roslin, T. 2008. Habitat fragmentation and the functional efficiency of temperate dung beetles. Oikos 117: 16591666. Russell, E. P. 1989. Enemies hypothesis: a review of the effect of vegetational diversity on predatory insects and parasitoids. Environ. Entomol. 18: 590599. Steffan-Dewenter, I. 2003. Importance of habitat area and landscape context for species richness of bees and wasps in fragmented orchard meadows. Conserv. Biol. 17: 1036 1044. Tabachnick, B. G. and Fidell, L. S. 2000. Using multivariate statistics. Allyn and Bacon. Thies, C. et al. 2003. Effects of landscape context on herbivory and parasitism at different spatial scales. Oikos 101: 1825. Tscharntke, T. and Brandl, R. 2004. Plantinsect interactions in fragmented landscapes. Annu. Rev. Entomol. 49: 405430. Tscharntke, T. et al. 2002. Contribution of small habitat fragments to conservation of insect communities of grasslandcropland landscapes. Ecol. Appl. 12: 354363. Tscharntke, T. et al. 2005. Landscape perspectives on agricultural intensification and biodiversityecosystem service management. Ecol. Lett. 8: 857874. USDA (US Dept Agric.) 2002. Crop profiles for potatoes in Maryland. (/<www.cfmx1.ent.ncsu.edu/cropprofiles/wservices/ cpdisplay.cfm?filenameMdpotato/>). Valladares, G. et al. 2006. Habitat fragmentation effects on trophic processes of insectplant food webs. Conserv. Biol. 20: 212217. Ver Hoef, J. M. and Cressie, N. 1993. Spatial statistics: analysis of experiments. In: Scheiner, S. M. and Gurevitch, J. (eds), Design and analysis of ecological experiments. Chapman and Hall, pp. 319341. With, K. A. et al. 2002. Threshold effects of landscape structure on biological control in agroecosystems. Ecol. Appl. 12: 52 65. Young, O. P. 1986. Host plants of the tarnished plant bug, Lygus lineolaris (Heteroptera, Miridae). Ann. Entomol. Soc. Am. 79: 747762. Zaviezo, T. et al. 2006. Effects of habitat loss, habitat fragmentation, and isolation on the density, species richness, and distribution of ladybeetles in manipulated alfalfa landscapes. Ecol. Entomol. 31: 646656. 1485 1486 Appendix 1 Results from MANOVAs on the effects of habitat area, matrix composition, and habitat fragmentation on the collective densities of the five herbivore species. Densities were square-root transformed. Significant results at the a0.025 level are shown in boldface. Source July Wilk’s l Area Matrix Fragmentation AreaMatrix AreaFragmentation Matrix Fragmentation AreaMatrixFragmentation 0.351 0.318 0.500 0.787 0.799 0.815 0.642 August DF 5, 5, 5, 5, 5, 5, 5, 18 18 18 18 18 18 18 F p Wilk’s l 6.657 7.724 3.593 0.974 0.903 0.818 2.004 0.001 B0.001 0.020 0.460 0.501 0.553 0.127 0.539 0.696 0.649 0.693 0.874 0.744 0.801 DF 5, 5, 5, 5, 5, 5, 5, 18 18 18 18 18 18 18 F p 3.084 1.571 1.946 1.598 0.519 1.238 0.896 0.035 0.218 0.136 0.211 0.759 0.332 0.505 Appendix 2 Results from univariate ANOVAs examining effects of habitat area (A), matrix composition (M), and habitat fragmentation (F) on the densities of each herbivore species in July. Densities were square-root transformed. Significant results at the a 0.025 level are shown in boldface. Source A M F A M A F MF A MF DF 1, 1, 1, 1, 1, 1, 1, 22 22 22 22 22 22 22 Agallia constricta Empoasca fabae Therioaphis trifolii Lygus lineolaris Halticus bractatus F p F p F p F p F p 0.424 24.393 3.457 0.057 2.232 2.145 0.015 0.522 B0.001 0.076 0.813 0.149 0.157 0.903 0.362 0.864 0.274 1.391 3.171 1.504 0.010 0.643 0.363 0.606 0.251 0.089 0.233 0.922 9.486 12.941 0.847 2.651 0.435 0.026 0.642 0.005 0.002 0.367 0.118 0.516 0.873 0.432 2.736 0.035 2.490 0.377 0.914 0.824 4.287 0.112 0.854 0.129 0.546 0.350 0.374 0.050 13.143 0.021 0.224 0.734 0.615 0.045 3.726 0.001 0.886 0.641 0.401 0.441 0.835 0.067