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Bwbgwal Journal gthe Linnean SociGty (1996), 57: 917-926. With 2 figures Biogeography of milkweed buttedies (Nymphalidae: Danainae) and mimetic patterns on tropical Pacific archipelagos ROBERT DUDLEY's3 AND GREGORY H. ADLER213 'Department ofzoology, Universip ofTaa.s, Austin, Ix 78712, USA. *Department ofBwbgy and Mkrobwlogy, Universip of Wuconsin-Oshkosh, Oshkosh, WZ 54901 USA 3Smithsonian Tiopical Research Institute, P.O. Box 2072, Balboa, Republic ofPanama Received 43anq 1995, acccptulfkpublicatton 9 May 1995 Distributions of danaine butterfly species and associated mimetic patterns were compared among fAeen archipelagos of the tropical Pacific Ocean, and withim five major archipelagos (the Bmarcks, Fiji, East and West Solomon Islands, and Vanuatu). Using both simple and stepwise linear regression analysis, variation in the total number of danaine species and number of mimetic patterns was assessed with respect to island size, isolation and elevation. Relative to interarchipelago distributions, the distribution of danaine species and number of mimetic patterns on islands within archipelagos exhibited less dependence upon interisland distance and island area. Geographical features influencing the number of mimetic patterns were similar to those of danaines as a whole. Analysis of residuals from stepwise linear regression suggested that factors influencing danaine distributions were Merent from those for nondanaine butterflies. Thin result is consistent with the hypothesis of enhancement of danaine species establishment through Miillenan mimicry, although other factors such as host plant availability and simiiar habitat use may also be important. 01996 The b e a n Society of London ADDITIONAL KEY WORDS: -archipelagos - buttefies - danaines - mimicry - Pacific Ocean.. C0"TS Introduction . . . Material and methods Results.. . . . Discussion . . . . Acknowledgements . References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317 318 319 321 325 326 INTRODUCTION The milkweed butterflies (Nymphalidae: Danainae) comprise a phylogenetically well-defined clade with its centre of diversity in the tropical Indo-Pacific (Ackery 8z Vane-Wright, 1984). Milkweed butterflies are particularly interesting because most if not all species are unpalatable to vertebrate predators. Thus, if any similarity in wing patterns and/or behaviour exists between two danaine species, both will potentially 00244066/96/040317 t 10 $18.00/0 317 (a1996 The Linnean Society of London 318 R DUDLEY AND G.H.ADLER derive selective Miillerian advantage in sympatry. The sequestration of cardiac glycosides and/or acquisition of pyrrolizidine alkaloids by danaines, and the high degree of wing pattern similarity among many danaine species, have led Ackery & Vane-Wright (1984)to synthesize hypotheses of distinct mimetic patterns in different faunal regions. Each of these patterns can potentially act as a template for Mullerian mimicry. Although the likelihood of Miillerian mimicry among danaine species is high, selective advantages of resemblance have rarely if ever been .demonstrated for individual species in ecological as distinct from laboratory contexts. One means of examining this hypothesis is to determine if danaine species distributions in specific geographical regions are randomly composed, or whether additional ecological factors promote presence or absence of particular species. Such factors may operate at Werent spatial scales, and it is of particular interest to determine the scale at which phenomena such as mimicry become important in influencing species distributions. The numerous archipelagos of the tropical Pacific Ocean provide an excellent opportunity to implement such an analysis, as these island groups contain numerous danaine species and represent distinct and isolated butterfly assemblages. As part of a larger study examining butterfly distributions in the tropical Pacific (see Adler & Dudley, 1994), this paper assesses the intra- and interarchipelago biogeography of milkweed butterflies and of their mimetic patterns. Although various examples exist of remarkable phenotypic convergence among heterogeneric danaine species (Ackery & Vane-Wright, 1984), the possibility that such similarities have arisen for reasons other than mimicry (see e.g. Bernardi, 1963) cannot be evaluated statistically. However, the present study shows that the distribution of tropical Pacific danaine butterflies and mimetic patterns relative to that of all nondanaine butterfly species is influenced by factors supplemental to geographical features that otherwise explain most variance in species distributions. This finding does not unequivocally confirm the hypothesis that Miillerian mimicry acts to promote species establishment, but does suggest that a more highly resolved assessment of species distributions and habitat overlap will demonstrate positive associations between species of the same mimetic pattern. MATERIAL AND METHODS The. 15 distinct archipelagos containing danaines in the tropical Pacific were considered in an interarchipelago analysis (archipelago definitions follow Adler, 1992). Nine geographical features characterizing each archipelago were used in the analysis: total land area, area of largest island, distance to the nearest continental area, the nearest larger land mass and the nearest land mass,greatest elevation, and numbers of islands > 1000, > 500, and > 100km2;(see Adler & Dudley, 1994). Australia, New Guinea, Asia, and large landbridge islands of the Philippines and Sunda Shelf were considered continental (or source) areas. Five major archipelagos (Bismarcks, Eastern and Western Solomon Islands, Vanuatu, and Fiji) were evaluated in detail to assess intra-archipelago distributions of danaine species. For individual islands in the intra-archipelago analysis, the following data were determined from a variety of geographical sources: distance from the largest island within the archipelago, distance from the nearest larger island, area, and maximum BIOGEOGRAPHY OF PACIFIC MILKWEED BVITERFLIES 319 elevation. Derrick (1965) was particularly useful for geographical data on the Fijian Islands, while UNEP/IUCN (1988) was helpful in determining elevational and areal data for some of the smaller coral atolls. Jared Diamond (in Zitt.) provided geographical data for the Bismarcks. Distributional data for resident milkweed butterfly species, as well as definitions and inclusion of particular species within mimetic patterns followed Ackery & VaneWright (1984). For each island or archipelago, the total number of danaine species and the number of resident mimetic patterns were used in statistical analysis. Ackery & Vane-Wright (1984) considered the Solomon Islands to be subdivided into two regions (eastern and western), each with a different set of mimetic patterns. This convention was also followed in the present analysis. The monarch butterfly Danaus plexippus was excluded from analysis because of likely anthropogenic introductions (see e.g. Scudder, 1875; Vane-Wright, 1993). For both intra- and interarchipelago analyses, simple log-log and stepwise linear regressions were used to determine the importance of aforementioned geographical features in explaining variation in species and pattern distributions. In both analyses, the numbers of danaine species and mimetic patterns were included as dependent variables in separate regressions, and the geographical variables (nine for inter- and four for intra-archipelago analyses) were included as independent variables. Each archipelago (in interarchipelago regressions) and each separate island (in intraarchipelago regressions) represented a single observation. For stepwise regressions, a variable was added to the model if the corresponding Pvalue was less than 0.05, and was excluded if P > 0.10. In the interarchipelago analysis, residual from stepwise linear regressions on geographical variables were determined for the following categories: the total number of danaine butterflies, the number of mimetic patterns, the number of nymphalid butterfly species less danaines, and the total of all nondanaine butterfly species (see Adler & Dudley, 1994). Residuals were then crosscorrelated to assess possible differences in danaine and mimetic pattern distributions relative to those of nymphalids and the entire butterfly fauna of the tropical Pacific. RESULTS On average, five danaine species were present per archipelago in the tropical Pacific region (range 1-1 7, excluding archipelagos lacking danaines). The average number of distinct mimetic patterns per archipelago was three (range 1-7). Within archipelagos, distributions of both species and patterns were highly variable, as were geographical data characterizing islands that comprised each archipelago (Table 1). Bivariate log-log regressions suggested that the principal determinant of danaine species abundance within and among archipelagos was island area (Table 2). By contrast, distance and elevation effects were less pronounced. Only one of the five archipelagos (Fiji) showed a significant relationship between number of species and distance from largest island within the archipelago, to be contrasted with the highly significant interarchipelago regression of total danaine species on distance. Fiji was, of the five archipelagos considered in detail, characterized by the greatest mean distance to the presumed source island within the archipelago (see Table 1). A significant relationship between species number and distance to nearest larger island R.DUDLEY AND G.H.ADLER 320 TABLE1. For the entire study area and for five tropical Pacific archipelagos, the number of archipelagos or islane included in the analysis ( n),mean number (range) of danaine species and mimetic patterns per archipelago or island, mean area (range) among or within archipelagos, mean distance (range) from the continental land mass or largest island, and the mean elevation (range) per archipelago or island Group tl No. species No. patterns Interarchipelago 15 5.3 (1-17) 3.1 (1-7) Birmarcks 10 8.8 (2-16) 3.1 (2-5) Eastern Solomons 10 4.6 (1-9) 2.1 (1-3) Area (kmp) Distance 9700 (25-49730) 4747 (31-35742) 869 (5-4306) 1239 (13-5279) 439 (2-1 0384) 438 (1-3937) 2478 (51-5370) 149 (19-381) 116 (1-206) 186 (5-521) 255 (10-1155) 206 (3-605) (km) Elevation (m) ~~ Western Solornons 21 7.6 (1-14) 3 (14) Fiji 41 2.7 (1-5) 2 (1-3) VanUatU 27 4.7 (1-10) 3.1 (1-6) 1221 (42743) 1011 (1-2439) 409 (761281) 811 (342743) 831 (41242) 730 (2-1890) was found only for the Western Solomons. Interestingly, this correlation was positive and therefore opposite to that predicted by standard island biogeography relating colonization to distance from source. The effects of elevation on species number (Table 1) was not significant in the interarchipelagocomparison, but was significant for three of five intra-archipelago comparisons. Relative to danaine species as a whole, the number of mimetic patterns within archipelagos showed less dependence on area, with only two of the five intraarchipelago regressions significant (Table 3). However, this areal regression was highly significant in the interarchipelago comparison. Mimetic pattern abundance and distance to continental land mass or largest island were significantly (and negatively) correlated only in the interarchipelago comparison. Within the Western Solomons, distance to nearest larger island was correlated significantly (and positively) with the number of mimetic patterns. Effects of island elevation were sigdicant in four of the five intra-archipelago comparisons (see Table 3). Corroboratingthe bivariate analysis, stepwise linear regressions demonstrated that area was the primary factor in explaining interarchipelago variation in danaine and mimetic pattern distributions (Table 4). In the intra-archipelago comparisons, however, the relationship to area was less pronounced. In two of the five archipelagos (Eastern Solomons and Fiji), elevation and distance to largest island, respectively, were the strongest geographical predictors of danaine species distributions. Only in the Western Solomons and Vanuatu did island area significantly explain variance in distribution of mimetic patterns; elevation and distance to largest island were implicated in the other archipelagos. In general, those geographical factors other than area, elevation, and distance (see Material and methods) were of minimal importance for interarchipelago distributions of both danaine species and their mimetic patterns (Table 4). Utilizing standardized residuals from stepwise linear regressions on area, elevation and distance to continental land, an interarchipelago comparison showed no relationship between residuals for all danaines versus those for all non-danaine butterfly species, whereas residuals derived for non-danaine nymphalids were positively related to residuals for all non-danaine butterflies (Fig. 1). These results BIOGEOGRAPHY OF PACIFIC MILKWEED BWITERFLIES 32 1 suggest that factors influencing the distribution of milkweed butterflies are Herent from effects that influence distribution of non-danaine nymphalids across archipelagos. Residuals from stepwise regressions on aforementioned geographical factors were also calculated for the number of danaine species within the largest mimetic pattern found on each archipelago. Across all archipelagos, these latter residuals were strongly correlated with those for all danaine species (Fig. 2), suggesting that species membership in the largest mimicry pattern does not promote archipelago establishment beyond that indicated for danaine butterflies as a whole. DISCUSSION A primary problem in biogeographical studies is adequacy of distributional information. In this regard, the milkweed butterflies of the tropical Pacific are wellstudied (Ackery & Vane-Wright, 1984). Carpenter (1953), for example, presented detailed distributional data for the major danaine genus Euploeu in the tropical Pacific, while D'Abrera (1990) treated comprehensively the entire Melanesian TABLE 2. Bivariate log-log regressions of number of danaine species on area, distance to nearest larger archipelago (interarchipelago analysis) or island, distance to continental land mass (interarchipelagoanalysis) or to largest island, and elevation among fifteen archipelagos and within five archipelagos. n is the number of archipelagos or islands in a regression, c is the intercept, and z is the slope Independmt vatiable: a m Group n C Interarchipelago 15 -0.67 Bismarcks 10 0.38 Eastern Solomons 10 0.22 Western Solomons 21 0.06 Fiji 41 0.25 Vanuatu 27 0.13 Indcpmdmt variable: distance to continental land mass or to kqmt Group n c 15 2.29 Interarchipelago 10 1.04 Bismarcks Eastern Solomons 10 0.63 21 0.55 Western Solomons 41 0.78 Fiji 27 0.48 Vanuatu Independent variable: distance to tlcMcst k n p amhipelup or island Group n C Interarchipelago 15 -0.50 10 1.03 Bismarcks Eastern Solomons 10 0.56 21 0.26 Western Solomons 41 0.44 Fiji 27 0.29 Vanuatu IfidGPendet vatiable: elevation Group Interarchipelago Bismarcks Eastern Solomons Western Solomons Fiji Vanuatu n 15 10 10 21 41 27 c -0.22 -0.35 -0.53 -0.36 0.10 0.17 2 0.37 0.18 0.18 0.31 0.10 0.22 ? R 0.81 0.66 0.69 0.76 0.32 0.60 0.01 0.04 0.03 0.01 0.06 0.01 islands z ? R -0.55 -0.10 -0.04 -0.20 -0.35 0.04 0.68 0.18 0.01 0.27 0.14 0.05 0.01 0.64 0.78 0.49 0.03 0.79 z 1.79 -0.11 -0.003 0.40 -0.04 0.20 z 0.26 0.41 0.46 0.41 0.13 0.15 ? 0.39 0.04 0.0001 0.47 0.009 0.10 R 0.02 0.62 0.99 0.01 0.57 0.11 ? R 0.22 0.29 0.58 0.25 0.12 0.08 0.77 0.14 0.01 0.02 0.03 0.16 R DUDLEY AND G. H. ADLER 322 butterfly fauna. Reasonable confidence may therefore be placed on the interarchipelago data set; deviations by several species com the total species count will have little effect on the overall statistical analysis. Danaines (as well as ithomiine butterflies; see Beccaloni & Gaston, 1995) are also much more apparent to human collectors than are other butterflies, but this effect is unlikely to influence the residuals analyses (Figs 1, 2) for interarchipelago distributions. Similarly, danaines and unpalatable butterflies generally are known to possess tougher bodies and greater longevities, although neither of these qualities are likely to change results of the interarchipelago analyses. By contrast, it is likely that existing knowledge of species distributions within tropical Pacific archipelagos is much less complete. Small islands within archipelagos are generally much less fiequently visited than are main islands, and presence of isolated transients may also confound characterization of resident populations. The distributional data presented by Ackery & Vane-Wright (1984) refer primarily to major islands within archipelagos. Such islands may well act as metapopulation sources for smaller islands that transiently and over variable time scales are colonized by individual danaines. In the absence of continuous sampling for species presence TABLE 3. Bivariate log-log regressions of mimetic patterns on area, distance to nearest larger archipelago (interarchipelago analysis) or island, distance to continental land mass (interarchipelago anal+) or to largest island, and elevation among fifteen archipelagos and within five archipelagos. n is the number of archipelagos or islands in a regression, e is the intercept, and z is the slope IndcpmdsntVfniab&:maO Group Interarchipelago Bipmarch Eastern Solomons Western Solomons Fiji VanUatU n c 15 10 10 21 41 27 -0.37 0.28 0.06 -0.01 0.22 -0.05 Z 0.24 0.07 0.11 0.185 0.04 0.22 va7iabb: &taw to CmJinnrkrl land mass m to lalpi kka?kis Group n c 2 InterarChipelagO 15 1.15 -0.34 Bismarch 10 0.70 -0.12 Eastern Solomom 10 0.54 -0.15 Western Solomons 21 0.29 0.14 Fiji 41 0.50 -0.10 VanUatU 27 0.48 0.04 Ifui+dmt vlniabk: &taw to Mamst kngeradiphgo O r k W Group n c Z Interarchipelago 15 1.05 -0.26 Bumarch 10 0.47 -0.004 Eastern Solomom 10 0.37 -0.09 Western Solomom 21 0.14 0.22 Fiji 41 0.33 -0.04 VanUatU zndcpmdsntvarwblc:slcvation Group Interarchipelago BismardLs Eastern Solomom Western Solomom Fiji Vanuatu 27 0.11 0.20 ? R 0.78 0.59 0.55 0.69 0.20 0.60 0.01 0.07 0.10 0.01 0.23 0.01 ? R 0.62 0.51 0.52 0.03 0.09 0.05 0.01 0.16 0.15 0.51 0.07 0.79 ? - 0.22 0.m1 0.83 0.33 0.02 0.10 R 0.08 0.97 0.45 0.01 0.46 0.11 n C Z ? Fc 15 10 10 21 41 27 0.17 4.36 -0.59 -0.26 0.16 -0.19 0.16 -0.28 0.36 0.45 0.05 0.22 0.19 0.66 0.63 0.21 0.05 0.16 0.11 0.01 0.01 0.04 0.19 0.04 BIOGEOGRAPHY OF PACIFIC MILKWEED BUTTERFLJES 323 TABLE 4. Stepwise linear regressions of loglo number of danaine species or mimetic patterns among and within tropical Pacific archipelagos No. danaine species Group Interarchipelago n 15 Bismarck Eastern Solomons Western Solomons Fiji Vanuatu No. mimetic pattens Group Interarchipelago Bismarck Eastern Solomons Western Solomons Fiji Vanuatu P R 0.79 F 23.2 0.01 10 10 21 41 27 Regression model 1.02t0.21 log,, area-0.52 log,, distance to continental land 0.09t0.27 log,, area -0.49*0.45 log,, elevation 4.019tO.33 loglo area 0.78-0.19 log,, distance to largest island 0.13-0.22 log,, area 0.64 0.48 0.56 0.14 0.33 10.9 6.5 22.9 5.6 12 0.03 0.05 0.01 0.05 0.01 n 15 10 10 21 41 27 Regression model -0.37+0.24 log,, area -0.36t0.29 log,, elevation -0.67+0.40 log,, elevation -0.04t0.20 log,, area 0.51-0.11 log,, distance to largest island -0.05+0.22 log,, area 12 F R 0.61 0.61 0.60 0.69 0.13 0.33 20.6 9.4 10.6 16.8 5.2 11.6 0.01 0.03 0.03 0.01 0.05 0.01 on small islands, the distributional data synthesized by Ackery & Vane-Wright (1984) should be regarded as sufficient for an initial biogeographical analysis. Additional geographical surveys, particularly of smaller islands, would advantageously supplement existing distributional information for tropical Pacific butterflies. The primary result for the distribution of danaine species is the reduced influence of island area and distance within archipelagos, in contrast to the significant effects of these variables on interarchipelago distributions (Table 2). Geographical factors influencing interarchipelago distributions of danaine species also differed somewhat from those for all butterflies. For the latter category (n = 26 archipelagos), distance to the nearest land entered a stepwise regression model first, followed by total land area (Adler & Dudley, 1994). For danaines (n = 15 archipelagos), area entered the regression model first, followed by distance to continental land (Table 4). In part, failure to observe intra-archipelago areal effects on danaine distributions may reflect - . -2.54 -2.5 -2 - 21 -lmn - . - t 1.5 2 ; - - - - 1.4 1, 0 -1.5 -1 -.5 I 0 .5 1 L standardized residuals, non-danaine butterflies Figure 1. Residuals from stepwise linear interarchipelagoregressions (Table 4) for danaine species (0)and non-danaine nymphalids (0)versus residuals for all butterfly species. Data for the latter two categories were taken from Adler & Dudley (1994).The regression between residuals for non-danaine nyrnphalids and for all non-danaine buttedies was highly significant (y = 0.87X,8 = 0.76, P = O.OOOl), whereas the comparable regression for danaine species was not significant (? = 0.02, P = 0.65). R.DUDLEY AND G.H.ADLER 324 standardized residuals, all danaines Figure 2. Residuals from stepwise linear interarchipelago regressions for the number of danaine species in the largest mimicry pattern versus residualsfor all danaine species. The significant correlation between these two sets of residuals (y = 0.64x, ? = 0.92, P = O.OOOl), suggests that danaine species in the largest mimicry pattern behave as a random subset of all danaines in the context of interarchipelago distribution. a sampling bias. Only major islands greater than 1 km2were included in the intraarchipelago analysis; variance in area among archipelagos was substantially greater than that within archipelagos (Table 1). Many archipelagos, however, are comprised of up to 300 smaller islands (e.g. the Fijian archipelago),some of which are only a few hectares in area and have not been evaluated biotically. Had the entire range of island sizes within archipelagos been included, much stronger species-area regressions would probably have been obtained. The significant effects of elevation on some intra-archipelago distributions of danaine species and patterns (Tables 2 and 3) may in part reflect the exclusion of high elevation species (altitudinal range > 1000m) from the numerous low-lying islands found within most archipelagos (see Table 1). In the interarchipelago comparison, effects of distance on danaine species and pattern distributions are not surprisingly significant (Tables 2 and 3) in light of the mean interarchipelago distance of approximately 2550km (Table 1). As with area, however, the effects of distance on intra-archipelago distributions are much less pronounced. Within four of the five archipelagos studied, distance to nearest larger or to the largest island is not a statistically significant factor influencing species numbers in a multivariate analysis (see Table 4), even though the mean interisland distance for these four archipelagos ranges from approximately 100 to 200 km (Table 1). Similarly, only in Fiji is the distribution of mimetic patterns significantly dependent on the distance to the nearest larger island (Table 4). Reduced effects of isolation on intra-archipelago distribution have been previously reported for birds in the Solomon Islands (Diamond & Mayr, 1976), but it is nonetheless surprising for buttexflies that distance effects are of so little consequence. In birds, for example, airspeeds and capacity for long-range powered flight is substantially higher. Apparently for danaine butterflies, a combination of powered flight and ambient air motions is sufficient within several hundred kilometers to overcome over time the distributional effects of distance on species numbers. It is clear that long distance dispersal over oceans is possible in many butterflies (Williams,1930; Holzapfel & BIOGEOGRAPHY OF PACIFIC MILKWEED BUTTERFLIES 325 Harrell, 1968; Fox, 1978; Farrow, 1984), including danaines (see e.g. Urquhart & Urquhart, 1976, 1979). The distribution of danaine mimetic patterns generally showed dependence on geographical features similar to that for danaine species. In part, this effect may simply reflect definition of individual mimetic groups as non-overlapping subsets of all danaine butterflies, although the extent to which such discrete categories are perceived by potential predators is unclear. Existing criteria for assigning species to mimicry groups rely not on quantitative similarity of wing shape, colour and flight behaviour, but rather on qualitative human synthesis of visual features. Furthermore, the actual predators of the tropical Pacific danaine fauna are unknown, as are the character and range of sensory modalities actually utilized during predation. It is likely, however, that birds and lizards are the principal predators of butterflies. Given their presumed unpalatability and overall morphological similarity, all danaines can potentially act as Miillerian co-mimics (Ackery & Vane-Wright, 1984). It is therefore appropriate to evaluate not only aforementioned mimetic patterns but also all danaine species as a single mimetic pattern in any analysis of the potential consequences of mimicry. This conclusion is supported by the finding that, within the mimetic pattern containing the greatest number of species on each archipelago, there is no enhancement of species presence beyond that established for the total count of danaine butterflies (Fig. 2). A quantitative assessment of wing colour and shape in danaines would usefully evaluate the correspondence of particular species to emergent groupings that potentially confer mimetic advantage. Danaine butterflies appear to be distributed differently from non-danaine species in an interarchipelago comparison (Fig. l), suggesting that factors supplemental to geographical features are acting to influence danaine distributions. Such factors that would differentially promote species establishment may include danaine longevity and toughness, shared host plants, similar use of habitat, and/or selective advantages associated with Miillerian mimicry. This last effect would potentially act to promote species establishment either within particular mimetic patterns or for danaine butterflies generally. The finding that danaine distributions differ from those of butterflies in general does not unequivocally demonstrate that Miillerian mimicry acts to promote species establishment, but it does suggest that a more highly resolved assessment of species distributions and habitat overlap will demonstrate positive associations among species of the same mimetic pattern or of overall morphological similarity. At present, data are unavailable to examine in detail the hypothesis that species establishment is promoted by common habitat or hostplant use. Given the marked differences in distribution between danaines and butterflies as a whole, it is possible that selective advantages of mimicry conferred to individuals may occur through predator generalization of all danaine species (Ackery & Vane-Wright, 1984).Membership in specific mimicry groups, however, may be more important in determining local abundance on particular islands or archipelagos, which may also vary in quantity and character of insectivorous predators. Field observations and population data are therefore necessary to evaluate the contributions of the aforementioned ecological factors to danaine species distributions. ACKNOWLEDGEMENTS We thank the Smithsonian Tropical Research Institute for logistical support and R.DUDLEY AND G. H.ADLER 326 J. Diamond for providing geographical data for the Bismarcks. E. Pianka kindly commented on the manuscript. The constructive comments of R.I.Vane-Wright and an anonymous reviewer are gratemy appreciated. REFERENCES RI. 1984. MiMuacd B u f t q k . London: British Museum (Natural Hktory). Mler CH. 1992. Endemism in birds of tropical Pacific islands. EnolulioMly bhgv 6: 296-306. Mlcr CH,Dudley R. 1994. Butterfly biogeography and endemism on tropical Pacific islands. Biological30unralof thc Linncmz 51: 151-162. Beccdoni OW, Cuton 1995. Predicting the species richness of Neotropical forest butterflies: Ithomiinae (Lepidoptera: Nymphalidae) as indicators. Bwlogical ConcnVatiOn 71: 77-86. Bernardi G. 1963. Quelques aspectes zoogkographiques du mimetisme chez les kpidopteres. h c + s ofthc Intrmakbnal C W ~ S of+b,Wdi@m D.C.(16) 41 161-166. Carpenter GDH. 1953. The genus Euplom (Lep. Danaidae) in Micronesia, Melanesia, Polynesia and Australia. A zoo-geographical study. Trmrracrimu ofthc .Zwrogicol sonc3)ofLondon 28: 1-184. D’AbB. 1990. B+ 4th AlLckolirm Z@n. Third [Revised] Edition. Melbourne and London: Hill House. Derrick RA. 1965. 77ze Fjii Iskmdr. Suva: Government Press. DirmondJM, Mayr E. 1976. Species-area relation for brds of the Solomon Archipelago. Zh+s ofthcNahna1 A c h y ofscimus USA 73: 262-266. Famow RA. 1984. Detection of transoceanic migration of insects to a remote island in the Coral Sea, Willis Island. Aurlralianjwrnal ofh‘colag9 9: 253-272. Fox q.1978. The transoceanic migration of Lepidoptera to New Zealand - A history and hypothesis on colonisation. Nm ,+lurid &i%mwhgki 6: 368-380. ~ot8pM EP, HurcllJC.1968. Transoceanic dispersal studies of insects. Pat@ Insscts 10: 115-153. Scudder SH. 1875. The introduction of Drmaida pruipplrs into the Pacific islands. P y h I: 81-84. UNEP/IUCN. 1988. cwol Re& of thc WwU. Volume 3 Central and Western Pacific. Nairobi/Gland United Nations Environment Programme. Urqdmrt FA, UrquIurt NR. 1976. A study of the peninsula Florida populations of the Monarch butterfly (h [email protected] Danaidae).J o d ofthc LcpidoptmictZ’ So&& 30: 73-87. UrquIurt FA, UrquIurt N R 1979. Aberrant autumnal migration of the eastern population of the Monarch butterfly (Dmrarcrp.pLw&us, Lepidoptera: Danaidae) as it relates to the Occurrence of strong westerly winds. ccmadianEnlanologisl I l l : 1281-1286. Vane-Wri&t RI. 1993. The Columbus hypothesis: an explanationfor the dramatic 19th century range expansion of the monarch butterfly. In: Malcolm SB, Zalucki M, eds. Biohgy and C o n s k 4th Monarch Bnt&t&. Los Angeles: Los Angeles County Museum, 179-187. Willhum CB. 1930. 7hM&&m gB+. London: Oliver and Tweed. Ackery PR,Vaxne-Wdght w.