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                                       Est.   S.E.    t      P    lmg (%)
                                 IA     0.069  0.039    1.775    0.088  14.0
                                 EL     0.188  0.069    2.722    0.011  12.6
                                 IS    − 0.111  0.048   − 2.299    0.030  14.9
                                 SR     0.588  0.127    4.637  < 0.001  20.1
                                 PC     0.159  0.070    2.268    0.031  11.6
                                Table 1.   Results for the AIC-based stepwise Generalized Linear Model predicting species richness on
                                islands based on: IA = island area; EL = maximum elevation of island; IS = island isolation from the
                                nearest source; SR = butterfly richness of the nearest source; PC = occurrence of Pleistocene connection.
                                Mean annual temperature and annual precipitation did not enter the model. Abbreviations: Est =  estimated
                                parameter; SE =  Standard Error; t =  t value; P =  P value; lmg =  percentage of explained variance attributed by
                                hierarchical partition of variance.

                                whether competition and interaction between species traits and island characteristics (mostly mediated by differ-
                                ences in dispersal tendency among species) play a primary role 3,10,15 .
                                   Genetic variation provides fundamental information to understand the historical and ecological dynamics
                                that shaped island populations and communities 6,16 . Past connections or long-term isolation are well-known
                                determinants of phylogeographic patterns, but they exert variable effects on different species, with highly
                                migratory species expected to show the least geographic variation due to frequent gene flow 16–18 . However, the
                                assumption that species lacking spatial genetic differentiation are the most vagile and widespread has rarely been
                                tested 6,16,19 .
                                   Following these premises, it is not surprising that, although numerous studies exposed the role of complex
                                phenomena in producing faunistic 20,21  and genetic community structures for selected insular taxa 19,22 , compre-
                                hensive studies aiming to disentangle large arrays of ecological-historical and deterministic-stochastic factors
                                over large taxonomic groups are uncommon 8,16,17 . In this study, we examined butterfly communities occurring on
                                the circum-Sicilian islands and compared them with populations from the southern Italian Peninsula, Sicily and
                                north Africa. Sicily and the surrounding islands represent a biogeographic crossroad with high species richness
                                and contrasting biodiversity 23–25 . These islands have different geological histories and locations with respect to
                                the two main faunistic sources (southern Europe and north Africa) and possess different environmental settings,
                                while the well-known taxonomy and distribution of the butterflies occurring in this region make them an excel-
                                lent model system. However, the sparse information about their genetic structure has impeded the link between
                                community composition and patterns of genetic differentiation. In this study we: i) model species richness over
                                the western Mediterranean islands, ii) examine the pattern of nestedness in the study area, iii) analyse the relative
                                importance of species dispersal tendency and frequency at source in determining their frequency on islands, iv)
                                we sequenced the COI gene to assess the genetic differentiation patterns for populations of 29 species and test
                                for a possible correlation between dispersal tendency and regional genetic variation, v) document the overall
                                genetic differentiation pattern for north Africa, circum-Sicilian islands, Sicily, and the Italian Peninsula, and vi)
                                categorize the species based on their island occupancy and genetic structure. This integrative approach aids the
                                recognition of the multiple processes generating species assemblages for an entire and diverse superfamily and
                                provides the information needed to prioritize conservation decisions in a key biogeographical contact zone.
                                Determinants for island species richness.  The AIC-based Generalized Linear Model (GLM) for
                                the richness of Western Mediterranean islands on the basis of ecological factors, returned a model with four
                                variables: island area (IA), isolation (IS), source richness (SR) and maximum elevation (EL). Isolation represented
                                the largest part (26.1%) of the total variance explained by the model (67.8%) (Supplementary Table S3). The Maltese
                                islands, Lampedusa, Lipari and Vulcano were richer in species than expected (Supplementary Fig. S1a), while
                                Pantelleria, Linosa, Stromboli and Marettimo had fewer species than expected. In the second GLM (including the
                                Pleistocene land connections (PC) as a variable) a six variable model best fitted the data (Supplementary Table
                                S4), adding mean island precipitation (PT) and PC to the previous model. In order to make this model directly
                                comparable with the first one, we excluded PT (results including this variable are shown in Supplementary Table S4).
                                This model increased the explained variance to 73.2% with PC having the lowest lmg value (Table 1). The differ-
                                ence in richness residuals between the model without the PC and the full model can provide an estimation of
                                the number of species that colonized the islands during the Last Glacial Maximum (LGM), due to land-bridge
                                connections, and survived until present (Table 2).

                                Community structure.  Various null models provided different evidence for the existence of a significantly
                                nested pattern of the butterfly communities on the 11 studied islands. The observed nestedness metric based on
                                overlap and decreasing fill (NODF) of the entire packed matrix (Fig. 1) was significantly higher than the mean
                                NODF obtained with the equiprobable rows and columns (EE) and proportional rows and columns total (CE)
                                null models (Table 3). However, the mean NODF for the fixed rows and columns (FF) null model was signifi-
                                cantly higher than the observed value, revealing an anti-nested pattern (Table 3). After dividing the matrix into

         Scientific RepoRts | 6:28828 | DOI: 10.1038/srep28828                                                 2
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