Abstract
Ecologists have long been intrigued by the factors that control the pattern of biodiversity, i.e., the distribution and abundance of species. Previous studies have demonstrated that coexisting species partition their resources and/or that the compositional similarity between communities is determined by environmental factors, lending support to the niche-assembly model. However, no attempt has been made to test whether the relative amount of resources that reflects relative niche space controls relative species abundance in communities. Here, we demonstrate that the relative abundance of butterfly species in island communities is significantly related to the relative biomasses of their host plants but not to the geographic distance between communities. In the studied communities, the biomass of particular host plant species positively affected the abundance of the butterfly species that used them, and consequently, influenced the relative abundance of the butterfly communities. This indicated that the niche space of butterflies (i.e., the amount of resources) strongly influences butterfly biodiversity patterns. We present this field evidence of the niche-apportionment model that propose that the relative amount of niche space explains the pattern of the relative abundance of the species in communities.
Keywords: neutral theory, niche theory, relative species abundance
Biodiversity is often considered to be synonymous with species richness and relative species abundance (1). For more than half a century, ecologists have paid attention to the factors that determine the relative species abundance in ecological communities; i.e., the commonness and rarity of species (2). Host plants and their herbivore communities are good systems for examining how the diversity of herbivores is influenced by their resources; indeed, insect ecologists have focused considerable attention on the question of how host plant communities affect the species richness and composition of insects. Although a recent review (3) pointed out that little progress on this subject has been made since the 1980s, a number of important studies have demonstrated that a large number of plant species is frequently correlated with a large number of insect species (4–6). Experimental studies have also demonstrated a positive relationship between the diversity of plant species and the diversity of consumers (7–9). The abundance of resources also represents an important factor in the structuring of insect communities (10). A number of studies have demonstrated that resource abundance explains the variation in the abundance and species richness of herbivorous insects (11–14). However, these studies on host plant and herbivore communities have treated species richness and species composition as components of the diversity, and no studies have examined the relative abundance patterns of both host plants and herbivores.
On the other hand, recent theoretical arguments have focused on whether the neutral or niche theory better explains the patterns of relative species abundance. The neutral theory (1) of biodiversity based on a dispersal-assembly perspective assumes that the relative abundance of species in communities is determined by random dispersal and stochastic local extinction. Conversely, the niche-assembly view proposes that coexisting species should have different niches so that the abundance and diversity of species is determined by interspecific competition and the diversity of resources. Many studies have demonstrated that coexisting species partition their resources (15–17), which lends support to the niche-assembly model. However, recent studies have shown that the neutral theory can explain the biodiversity of several plant communities (1, 18), although other studies have refuted the theory (17, 19,20–21). An appropriate test that differentiates between the niche and neutral models is to assess the different predictions from the competing theories (17, 19). The neutral model predicts that the compositional similarity between communities will decrease as the distance between two points increases (17). In contrast, the niche-apportionment model predicts that the similarity of relative species abundance between communities will increase with an increase in the similarity of relative resource abundance. The relative contribution of distance and resource abundance to the similarity should be evaluated (22).
Previous studies supporting the niche theory have demonstrated that coexisting species partition their resources or that community composition is related to environmental conditions. However, these studies did not evaluate the relative abundance of available resources; consequently, the relationships between niche space and species abundance were not directly tested. Thus, to date, there has been no attempt to test whether the relative abundance of available resources, i.e., available niche space, affects the relative abundance of species. In this study, butterfly communities were examined because both the larval and adult stages of butterflies depend almost entirely on specific plants for their dietary requirements, and information as to which host plant a butterfly uses is generally available. In addition, we could estimate the host plant abundance using a high-resolution aerial photograph and field surveys. Therefore, using the host plant–butterfly system, we were able to directly test the relationship between fundamental niche space and relative species abundance.
Results
We examined butterfly species diversity on five of the Urato Islands, Japan (Fig. 1). Throughout the sampling period, a total of 39 species were identified and used in the study (see Materials and Methods: Mahanashi, 30; Hoh, 25; Katsura, 31; Nono, 34; Sabusawa, 35); these butterflies potentially use 58 host plant species [supporting information (SI) Fig. 3]. Of the butterfly species, nine are restricted to the use of a single host plant species, and, for eight species, the host plants are used by no other butterfly species. In this study, plant biomass was estimated as the weight of the edible parts of the plants. An analysis of the diversity and abundance of host plants and butterfly species was conducted for eight communities, of which two communities were classified on Katsura Island and three were classified on Sabusawa Island (the analysis of five communities, where each community corresponded to a single island, was also conducted, and the results are provided in SI Table 3 and SI Fig. 5). This community division was based on the observation that Katsura Island and Sabusawa Island support different vegetation types (Fig. 1; see also Materials and Methods).
Fig. 1.
Maps of the Urato Islands and vegetation classification. Eight communities were considered when the Katsura and Sabusawa Islands were divided into two and three areas, respectively, as shown by the black lines. 1, residential areas, roads, and other man-made structures; 2, rice fields; 3, other crop fields; 4, grasslands with vegetation <50-cm high; 5, grasslands dominated by Miscanthus sinensis and other tall grasses; 6, wetland vegetation mainly dominated by Phragmites communis; 7, bamboo or dwarf bamboo thickets; 8, Cryptomeria japonica plantations; 9, Pinus densiflora (P. thunbergii in part) forests; 10, Machilus thunbergii forests; 11, deciduous forests mainly dominated by Quercus serrata; 12, mixed secondary forest dominated by Juglans mandshurica var. sachalinensis, Celtis sinensis var. japonica, and Neolitsea sericea.
The number of butterfly species did not differ greatly among the communities (26–30 species), and there was no significant effect of host plant species richness on butterfly species richness (regression analysis, b = 0.0884, F1,6 = 1.151, P = 0.3247, R2 = 0.1615, SI Fig. 4a). Simple regression analysis indicated that the total host biomass densities significantly affect butterfly biomass densities (b = 0.01513, F1,6 = 31.95, P = 0.0013, R2 = 0.8419, SI Fig. 4b), but butterfly biomass densities were not observed to have any effect on butterfly species richness (b = −0.491, F1,6 = 1.142, P = 0.3264, R2 = 0.1599, SI Fig. 4c).
By using an extension of the Mantel test (23, 24), we examined whether the similarities of the relative abundance pattern of butterfly species between the communities (Butterfly matrix) are determined by the similarities of the relative abundance pattern of their host plant species (Resource matrix), by geographic distances (Distance matrix), or by both. There was a clear correlation between the matrices of Butterfly and Resource, but there was no significant correlation between the matrices of Resource and Distance (r = 0.3945, P = 0.103). The multiple regression of the Resource and Distance matrices on Butterfly matrix indicated that the relative abundance pattern of butterflies was highly significantly influenced by the relative abundance pattern of their host plants, but not by geographic distance (Table 1 and Fig. 2). It is possible that communities within islands were similar in the relative abundance of butterflies. When within- and between-islands factors were used as independent variables instead of the Distance matrix for the multiple regression, the Butterfly matrix was not significantly influenced by within-island effects (P = 0.3996).
Table 1.
Results of a multiple regression of the Resource and Distance matrices on the Butterfly matrix by using an extension of the Mantel test
| τAB.C | τAC.B | R2 | |
|---|---|---|---|
| Distance | 0.8052 | 0.1529 | 0.7654 |
| P < 0.0002 | P = 0.2258 | P < 0.0002 | |
| Log distance | 0.8121 | 0.1603 | 0.7685 |
| P < 0.0002 | P = 0.224 | P < 0.0002 |
τAB.C, regression coefficient of the Resource matrix on the Butterfly matrix. τAC. B, regression coefficient of the Distance matrix on the Butterfly matrix. The results for five-community analysis are shown in SI Table 3.
Fig. 2.
Relationship between the dissimilarities between butterfly communities and host plant communities (a), dissimilarities between butterfly communities and geographic distance (b), and dissimilarities between host plant communities and geographic distance (c). The r and P values shown in the figures were obtained by the Mantel test. Dissimilarities in relative species abundance of butterfly and relative resource abundance were calculated by using Odum's percentage difference method. The results for five-community analysis are shown in SI Fig. 5.
The effects of the biomass densities of host plant species on the density of each butterfly species that used them were examined. The results showed that in 23 (≈60%) of 39 butterfly species, the regression model that included the biomass of one or more host plant species as explanatory variables showed a lower Akaike information criterion (AIC) value than that obtained without the biomass, and the densities positively increased with increasing host plant biomass (Table 2). After controlling the error of multiple comparisons, one or more host plant species weakly (8 butterfly species, P < 0.2) or significantly (12 butterfly species, P < 0.05) affected the butterfly densities.
Table 2.
Effects of host plant biomass on the butterfly densities of each species
| Butterfly | Host plant |
|---|---|
| Graphium sarpedon nipponum | 5* (0.907) |
| Hestina persimilis japonica | — |
| Papilio xuthus | 2¶ (0.429) |
| Papilio macilentus | 3†, 2 (0.895) |
| Papilio bianor dehaanii | 2¶ (0.393) |
| Papilio machaon hippocrates | 6‡ (0.657) |
| Papilio protenor | 2 (0.294) |
| Atrophaneura alcinous | 1* (0.997) |
| Eurema hecabe | 12‡, 16, 17§, 18† (0.429) |
| Artogeia melete | 11† (0.830) |
| Colias erate poliographys | 10‡, 12‡, 15‡, 20§ (0.982) |
| Artogeia rapae crucivora | 11¶ (0.368) |
| Everes argiades | 31‡, 16, 29, 30 (0.967) |
| Rapala arata | 25‡, 16, 21, 30 (0.978) |
| Lycaena phlaeas daimio | — |
| Pseudozizeeria maha | — |
| Celastrina argiolus ladonides | 25, 22, 28¶, 30¶ (0.745) |
| Vanessa indica | 40† (0.894) |
| Limenitis camilla japonica | — |
| Sasakia charonda | — |
| Polygonia c-aureum | — |
| Hestina persimilis japonica | — |
| Neptis sappho intermedia | 14 (0.307) |
| Cynthia cardui | 38§ (0.509) |
| Kaniska canace | — |
| Libythea celtis | — |
| Lethe diana | 48 (0.267) |
| Mycalesis francisca perdiccas | — |
| Minois dryas bipunctata | 51* (0.999) |
| Lethe sicelis | 54¶, 48, 53, 55 (0.706) |
| Ypthima argus | — |
| Mycalesis gotama fulginia | — |
| Neope niphonica | 54 (0.476) |
| Parnara guttata | 55†, 46, 56 (0.840) |
| Polytremis pellucida | 53§, 48, 43, 55 (0.938) |
| Potanthus flavus | — |
| Thoressa varia | 53¶, 48 (0.578) |
| Daimio tethys | — |
| Isoteinon lamprospilus | 44¶, 47 (0.503) |
| Pelopidas jansonis | — |
The numbers below indicate host plant species and are also shown in SI Fig. 3. The host plant species that were included in the model that yielded the lowest AIC are shown. The symbol–indicates that no host plant species was selected in the model. Italicized numbers indicate host plants with a negative regression coefficient. Values in parentheses indicate the R2 of the regression. Significant values (P) were adjusted for controlling multiple comparisons by using the false discovery rate (FDR) procedure. 1, Aristolochia kaempferi; 2, Zanthoxylum ailanthoides; 3, Orixa japonica; 5, Neolitsea sericea; 6, Oenanthe javanica;10, Trifolium pratense; 11, Brassica rapa; 12, Medicago polymorpha; 14, Lespedeza buergeri; 15, Trifolium repens; 16, Lespedeza homoloba; 17, Albizia julibrissin; 18, Lespedeza juncea var. serpens; 20, Lotus corniculatus var. japonicus; 21, Deutzia crenata; 22, Vicia angstifolia; 25, Pueraria lobata; 28, Rosa wichuraiana; 29, Lathyrus japonicus; 31, Kummerowia stipulacea; 38, Cirsium nipponicum; 40, Boehmeria longispica; 43, Pleioblastus chino; 44, Spodiopogon sibiricus; 46, Carex doniana; 47, Miscanthus sinensis; 48, Sasamorpha borealis; 51, Calamagrostis arundinacea var. brachytricha; 53, Phyllostachys bambusoides; 54, Sasa nipponica; 55, Phyllostachys heterocycla; 56, Oryza sativa.
*, P < 0.001;
†, P < 0.01;
‡, P < 0.05;
§, P < 0.1;
¶, P < 0.2.
Discussion
The present results demonstrate that the relative abundance of resource biomass has a highly significant effect on the relative abundance of consumer species. The results indicate that the niche space of butterflies (i.e., the amount of their resources) strongly influences the abundance of butterflies and, consequently, butterfly biodiversity patterns. This was also supported by the results that the total biomass densities significantly affect the total biomass densities of all of the butterfly species and that the biomass of certain particular host plant species explains the abundance of the butterfly species that use them. The positive relationships between the total biomass and total butterfly biomass suggest that resource availability actually regulates butterfly abundance. However, butterfly species richness did not increase with increasing butterfly biomass densities. Thus, the increasing total biomass density of butterflies was attributable not to an increase in species richness but to an increase in the densities of certain species that was caused by large increases in the biomass of their host plants. For instance, several species (e.g., Graphium sarpedon nipponum, Papilio machaon hippocrates, Artogeia melete, and Colias erate poliographys) could be found at high densities in one or more communities, and the densities of these species were significantly affected by the biomass densities of their host plants (Table 2). In the present study, the species richness of butterflies was not related to that of their host plants, and this might be because the number of butterfly species did not differ greatly among the communities. Therefore, in the present communities, species richness was not useful for comparing communities; however, the relative abundance of species was an important aspect characterizing the biodiversity of butterfly communities. The relative amount of resources was a major factor that explained the biodiversity pattern of the butterfly communities.
The neutral theory predicts that the compositional similarity between butterfly communities will decrease as the distance between two communities increases because dispersal is a predominant factor determining community composition. Butterflies may be able to disperse to distant locations; however, the distances between the studied communities were not very large. A recent study showed that the similarity between communities begins to decrease at a distance of several hundred kilometers (25). Hence, there may have been an adequate number of migrants between communities regardless of distance. However, at present, there is no available data that demonstrates the relationship between the number of migrants and the distance between the studied communities. The distance effects should be examined to confirm that there might be no distance effects in the present communities. As expected, our studies demonstrated that geographic distance did not have a significant effect on butterfly diversity. In addition to the distance effect, the similarity between communities within islands might be larger than that between communities on different islands if migrations occur more frequently within islands. However, there was no evidence to suggest that communities within islands were more similar than those on different islands. Therefore, the present results do not support the neutral model at least for the studied spatial scale (<6 km).
In this study, one of the major factors that might have contributed to the significant effect of the relative abundance of host plant species on the relative abundance of butterfly species is the positive relationship between the abundance of each butterfly species and the biomass of its host plant species. For ≈60% of 39 butterfly species, the biomass densities of the host plants were observed to have positive effects on the densities of the butterfly species that used them, and for ≈30% of the species, the effects were significant. These positive effects of the host plant biomass found in many (but not all) of the butterfly species indicate a significant relationship between the relative biomass of host plants and relative abundance of butterflies. Two additional factors may have contributed to the results, particularly in the case of those species that did not exhibit high positive relations between butterfly densities and their host plant biomass. First, some species alter their host plant preference depending on the relative abundance of potential host plant species and the abundance of other (competitor) butterfly species that use the same host plants. For instance, weakly negative relations were observed between the densities of Papilio protenor and the host plant Zanthoxylum ailanthoides. This might be because the increasing biomass of Z. ailanthoides increased the densities of the competitors Papilio macilentus and Papilio bianor dehaanii, resulting in Papilio protenor changing its host plants. Second, unknown ecological or environmental factors associated with the relative abundance of host plant species might influence the relative abundance of butterflies. To examine the relative contribution of these factors, additional studies are required. For instance, to confirm the potential for host plant switches by butterflies, the actual resource selection by butterflies should be observed; this would be an interesting topic for future research.
Previous studies on butterflies and moths have demonstrated the relationship between lepidopteran species richness and plant species richness (26, 27). However, the local movements of adult butterflies might be influenced by nectar resources. Indeed, a study on butterfly communities in open successional fields demonstrated that butterfly species richness was explained by flower abundance (28). However, butterflies oviposit on specific host plants and their larvae depend on these plants. Hence, if adult butterflies do not frequently disperse from the natal island or community, the abundance of adult butterflies will be related to that of the juveniles that depend on the host plant abundance on that island. In this study, the locations of the sampling points were selected at random with regard to the locations of host plants and nectar plants. Thus, the estimated densities of butterflies are considered to reflect the butterflies indigenous to each island.
Most studies on plant–herbivore communities have focused on species richness and species composition as representative components of biodiversity; however, few studies have treated the effect and consequences of the relative abundance of species. Although species richness and species composition are significantly correlated to ecosystem functioning (29), differences in relative species abundance can affect ecosystem functioning. For instance, the portfolio effects of ecosystem stability could be considerably influenced by relative species abundance. Even if species richness does not change, large increase in particular species might decrease stability by the portfolio effects (29). In the present study, increasing the biomass of host plants promoted an increase in the densities of certain butterfly species, thus causing a change in relative species abundance. Thus, the present studies indicated that vegetation changes caused by differences in land use would largely affect butterfly community stability by changing the abundance of particular species.
There are several hypotheses explaining the relative abundance of species and diversity [reviewed by Tokeshi (16)]. Previous studies designed to test the neutral and niche theories have examined the relationships between community compositions and environmental gradients, and have provided no direct evidence for the effects of relative resource abundance on relative species abundance patterns. These results are field evidence of the niche-apportionment model that proposes that the relative amount of niche space explains the pattern of relative species abundance at the consumer level. The results clearly demonstrate that butterfly communities depend on available resource abundance. This implies that the conservation of butterfly diversity and that of plant diversity should consider not only the maintenance of species richness but also prevent the prevalence of a few dominant species.
Materials and Methods
Study Region and Butterfly Sampling.
The study was conducted on the Urato Islands in Matsushima Bay, Japan (Fig. 1). The diversity of butterfly species and their host plants was investigated on five islands: Mahanashi, Katsura, Sabusawa, Nono, and Hoh. The respective areas of these islands are 0.15, 0.76, 1.45, 0.56, and 0.15 km2. The locations of 4, 12, 22, 9, and 4 sampling points were randomly determined on Mahanashi, Katsura, Sabusawa, Nono, and Hoh, respectively, such that the number of sampling points per area was approximately the same (0.04–0.06 km2). A census of butterflies at all of the sampling locations was conducted three times, in August 2004 and in July and August 2005. To minimize the effect of the seasonal change in butterfly appearance, the census was conducted only in August and July. The number of individuals of each species observed and captured by sweep nets within 5 m either side of a 10-m line transect was recorded by two investigators during 12 min when weather conditions were suitable for butterfly activity.
The analysis of the diversity and abundance of host plants and butterfly species was conducted mainly at eight communities because these islands support different vegetation types (Fig. 1). At the five-community scale, each community corresponded to a single island, and the results for the 5 communities were shown in SI Table 3 and Fig. 5. At the eight-community scale, two and three communities were classified on Katsura Island and Sabusawa Island, respectively (Fig. 1). Sampling points 6, and 7, and 8, were included on Katura Island and Sabusawa Island, respectively. In the east of Katsura Island, a large area was occupied by deciduous forests and this was unique compared with the other areas on the island. On Nono Island, the northeast area includes vegetation types that are somewhat different than those found in other areas of the island; however, this area is a narrow peninsula and only one sampling point was included. Owing to the position of the randomly chosen sampling points, it was difficult to adequately divide Nono Island into two communities. Thus, Nono Island was not divided for the eight-community analysis. To remove the effects of different sampling effort on the different islands, 16 samplings were conducted on all of the islands, with the exception of Sabusawa where sampling was conducted once at all 22 sampling points. For instance, on Katsura, the sampling was conducted at all 12 sampling points and 4 random sampling points selected from the original 12. For the 8-community analysis, sampling was conducted twice on Mahanashi and Hoh islands in each census. Six to nine samplings were conducted in the communities. The numbers of individuals of each species per sampling point (100 m2) per sampling time were used as the butterfly densities for the analysis.
Throughout the sampling period, a total of 43 butterfly species were identified. Parantica sita niphonica and Dichorragia nesimachus were omitted from the analysis because P. sita niphonica does not reproduce on these islands, and the host plant of D. nesimachus could not be found. In addition, in the field, it was difficult to distinguish Limentis glorifira and Neope goschkevitschii from Limenitis camilla japonica and Neope niphonica, respectively. Therefore, the data for L. glorifira and N. goschkevitschii were combined with that of L. camilla japonica and N. niphonica, respectively. Thus, in total, 39 butterfly species were used in the study.
Estimation of Host Plant Biomass.
Investigations of the distribution of resources for butterflies on the Urato Islands were conducted from 2003 to 2005. In this study, we defined resources for butterflies as host plants for the juvenile stages; resource distribution was estimated by using the following procedure. The host plants used by each species of butterfly were selected by comparing the floral composition based on preliminary field investigations and the host plant records listed in Fukuda et al. (30). Species belonging to the Satyridae and Hesperiidae (with the exception of Daimio tethys) are, however, largely polyphagous, and few accurate records of host plant species are available. In these cases, only the plant species on which the larvae of a given butterfly were frequently recorded were classified as host plants. For butterflies that subsist on bambusoid plants, their host plants were defined as all of the bambusoid plant species distributed in the study area. This was necessary because the host plants recorded in the literature were not identified to the species level. In the case of Parnara guttata, known as a pest of rice, all of the plants belonging to the Poaceae and Cyperaceae were considered as host plants. This is because a relatively wide range of host plants has been recorded for this butterfly, although food plant preference at the species level remains undetermined (30).
Vegetation surveys were carried out by using the following procedures. We divided the vegetation and land use into the following 12 types according to the results of preliminary field surveys and an aerial digital photograph (one pixel = 10 cm × 10 cm) taken in July 2003: (1) residential areas, roads, and other man-made structures; (2) rice paddy fields; (3) other crop fields; (4) grasslands with vegetation <50-cm high, usually dominated by annual grasses such as Trifolium spp.; (5) grasslands dominated by Miscanthus sinensis and other perennial tall grasses; (6) wetland vegetation mainly dominated by Phragmites communis; (7) bamboo or dwarf bamboo thickets; (8) Cryptomeria japonica afforested areas; (9) Pinus densiflora (P. thunbergii, in part) forests; (10) Machilus thunbergii evergreen forests; (11) deciduous forests mainly dominated by Quercus serrata; and (12) mixed secondary forest dominated by Juglans mandshurica var. sachalinensis, Celtis sinensis var. japonica, and Neolitsea sericea (Fig. 1). We then established 8–26 quadrants of 10 m × 10 m for each vegetation or land-use type. Measurements were taken of the number of individuals of each plant species in a quadrant, the height of each tree individual, and the degree of cover by herbaceous plants. From these data, the average number of individuals per unit area for each size class of each tree species and the average degree of cover per unit area for each herbaceous plant were calculated for each vegetation or land-use type. In this study, we assumed that the leaves of each plant species were the edible parts for the larvae of butterflies and estimated the wet weights of leaves per individual for tree species and those per unit area for herbaceous plants. For each plant species, we measured the wet weights of leaves and counted the number of leaves per individual or per unit area. We then estimated the unit biomass of the edible parts based on the average weights per leaves and the average number of leaves per individual or unit area. The available resource biomass of a given plant species in each local community was estimated from the unit biomass and the area of vegetation and land-use types in which the plant species was distributed. Hence, in the analysis, the biomass of a given plant species was used as biomass density (unit biomass per unit area).
Analysis of Butterfly and Host Plant Diversity.
The relationships among the species richness of butterflies and host plants, the total biomass densities of butterflies and host plants, and the total biomass densities of butterfly species and species richness of butterflies were examined by using a linear regression analysis. The total biomass densities of butterflies were calculated as Σ di wi, where di is the densities of species i, and wi is the average weights of adult butterflies of species i. The total biomass densities of the host plants were calculated as the sum of the biomass densities of all of the 58 host plant species.
We tested the effects of resource and geographic distance on butterfly biodiversity by applying an extension of the Mantel test for estimating the regression coefficients of independent distance matrices (23, 24). We considered a multiple regression equation of the form: aij = τ0 + τAB.Cbij + τAC.Bcij, where bij is the dissimilarity matrix of the relative resource abundance between communities i and j (Resource matrix), cij is the geographic distance (Distance matrix, both linear and log-transformed were considered), and aij is the dissimilarity matrix of butterfly species diversity (Butterfly matrix). τAB.C and τAC.B are the regression coefficients, and the significances were tested by randomization. The geographic distances were measured between the centers of gravity of two communities. To measure the similarity of butterfly relative abundance and host plant resource distribution, we used Odum's percentage difference method (31). The dissimilarity between communities 1 and 2 is represented as follows:
 |
where x1i and x2i are the numbers of individuals of species i in community 1 and community 2, respectively. For butterfly species, the average numbers of individuals per sampling time per sampling point were used as x. When resource similarity was considered, x1i and x2i are the biomasses of host plant species i in community 1 and community 2, respectively. The biomass was divided by the area of the community. D values increase with decreasing similarity. The number of individuals and the biomass of host plant species were log transformed because the evaluation of dominant and rare species were equivalent (32).
Effects of Host Plant Biomass on Butterfly Density.
The effects of the biomass of the host plant on the density of each butterfly species were examined in eight communities. We used a linear regression in which the density of a butterfly species was a dependent variable, and the biomass density of its potential host plant species (SI Fig. 3) was used as an independent variable. If there was a high correlation coefficient between the biomass densities of the host plants, one of either host plant species was omitted in the analysis. We explored the set of predictors of the host plant species with a stepwise AIC procedure; independent variables were removed and added to the models to determine the set of predictors that yielded the lowest AIC by using the R software. Given the model with the lowest AIC, we obtained the significance of the regression coefficients. We conducted an analysis of 39 butterfly species, and thus, to control the errors of multiple comparison, we used the false discovery rate (FDR) procedure (33).
Supplementary Material
Acknowledgments
We thank I. Hanski, R. Butlin, T. Fukami, J. Urabe, A. Mizuno, T. Yoshida, J. Bridle, M. Tokeshi, A. Satake, and S. Chiba for valuable comments on the manuscript and K. Saito, Y. Nukatsuka, and other member of the laboratory of Evolutionary Biology for field assistance. M.K. was supported by Grant-in-Aid for Scientific Research 15370007 from the Japan Society for the Promotion of Science.
Abbreviation
- AIC
Akaike information criterion.
Footnotes
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/cgi/content/full/0701583104/DC1.
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