Journal of Biogeography (J. Biogeogr.) (2011) ORIGINAL Binary matrices and checkerboard ARTICLE distributions of birds in the Bismarck Archipelago Michael D. Collins1*, Daniel Simberloff 2 and Edward F. Connor3 1Department of Biology, Rhodes College, 2000 ABSTRACT North Parkway, Memphis, TN 38112, USA, Aim We examine a presence–absence matrix of the avifauna of the Bismarck 2Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Archipelago, for which the concept of competitively driven community assembly TN 37996, USA, 3Department of Biology, rules was formulated, to determine whether data support widespread competitive San Francisco State University, San Francisco, determination of geographical distributions. CA 94132, USA Location Bismarck Archipelago. Methods We obtained occurrences of 154 land and freshwater bird species on 31 islands. We calculated the observed number of checkerboards for all species pairs, for congeneric species pairs and for pairs of species within guilds, and employed randomization techniques to detect unusual co-occurrence patterns. Results Compared with random expectations, there are excesses of checkerboard pairs within both genera and defined guilds, but a detailed examination shows that competition is a cogent possible explanation in few instances. For many checkerboard pairs, species are not widely interspersed but are regionally allopatric, which probably reflects historical biogeography and dispersal limitation. Most congeneric and intraguild checkerboards include a species classified as a supertramp; when supertramps are omitted, there are 11 congeneric checkerboards and four intraguild but heterogeneric checkerboards. Main conclusions In isolation, presence–absence matrices provide limited insight into the role of competition in structuring bird communities of the Bismarcks. A major problem is disentangling historical geography and colonization history of the archipelago from the present-day ecology of the species. Examination of observed checkerboards from a geographically explicit perspective and with knowledge of colonization routes suggests that many checkerboards are likely to result, at least in part, from historical biogeography and supertramps. Although species may be forced into supertramp status by competition, other factors (e.g. habitat preference) may be causal, and biogeographical distributions alone cannot distinguish between causes. Keywords *Correspondence: Michael Collins, Department Assembly rules, Bismarck Archipelago, checkerboard distribution, competition, of Biology, Rhodes College, 2000 North Parkway, Memphis, TN 38112, USA. historical biogeography, island biogeography, presence–absence matrix, super- E-mail: [email protected] tramp. or larger groups of species (Simberloff & Connor, 1979). INTRODUCTION Inevitably, with the great interest in the role of interspecific Binary matrices of presence and absence of species on sites competition in determining species’ distributions, a burst of have been analysed for many years in biogeography and research on statistical analyses of such matrices began in the ecology, usually in comparisons of site similarity, but also in late 1970s and has continued to the present (Gilpin & comparisons of the similarity of sets of sites occupied by pairs Diamond, 1982, 1984; Colwell & Winkler, 1984; Gotelli & ª 2011 Blackwell Publishing Ltd http://wileyonlinelibrary.com/journal/jbi 1 doi:10.1111/j.1365-2699.2011.02506.x M. D. Collins et al. Graves, 1996; Gotelli et al., 1997; Sanderson et al., 1998, 2009; competition (Connor & Simberloff, 1979; Simberloff & Gotelli, 2000; Gotelli & McCabe, 2002; Miklo´s & Podani, 2004; Connor, 1981); for example, two species may have different Lehsten & Harmand, 2006; Sfenthourakis et al., 2006; Sim- habitat requirements, or they may simply be sister species that berloff & Collins, 2010). Much of the research focused on have recently speciated allopatrically. In the light of the new Diamond’s (1975) seven assembly rules, which implicitly availability of data on the distributions of the Bismarck discussed patterns in binary matrices, and tests of the rules as Archipelago birds, on which the original assembly rules were null hypotheses by Connor & Simberloff (1979). Although based, we explored the checkerboards and their interpretation Diamond (1975) deduced the assembly rules from data on 147 in this avifauna. species of land birds distributed among 50 islands in the Bismarck Archipelago near New Guinea, the subset of those MATERIALS AND METHODS data that we use for our analyses became available only with the publication of Mayr & Diamond (2001). Excluding migratory, transient and non-breeding species, and Our goal here was to use the data on avian distributions in species occurrences with questionable records, Mayr & the Bismarck Archipelago (Mayr & Diamond, 2001) to Diamond (2001) tabulate 154 land and freshwater bird species determine if they supported Diamond’s (1975) claim of on 31 islands in the Bismarcks (Fig. 1). If the pattern of ones widespread competitive determination of geographical distri- and zeros in a given binary matrix is hypothesized to be butions. We focused on the assembly rule that has received the affected by a particular force (in this instance, interspecific most attention, the fifth rule: ‘Some pairs of species never competition), then a test must compare this matrix with those coexist, either by themselves or as part of a larger combination’ constructed randomly, without this force operating, from the (Diamond, 1975, p. 344). These checkerboard distributions universe of all possible matrices for this particular biota and set have been taken as strong evidence for interspecific competi- of sites. With sites represented as columns in the matrix and tion (Diamond, 1975), although that inference is not always species as rows, a 1 in row i and column j means species i is well founded (Gotelli & Graves, 1996). The gist of the found in site j, and a 0 means it is absent. For a given matrix controversy over checkerboard distributions stems from two M, the universe of matrices with which it is compared is observations. First, depending on the numbers of species and usually taken to consist of all matrices with the same sets of islands in the matrix, as well as the species richnesses of the row and column sums as M. The column sum constraint islands and the number of occurrences of each species, one ensures that each site maintains the same number of species might have expected some checkerboard distributions even if that it actually has (so that such patterns as the species–area species colonized islands independently of one another (Con- relationship continue to hold), while the row sum constraint nor & Simberloff, 1979). Second, even if a particular check- ensures that each species continues to occupy the same erboard distribution is unlikely to have arisen by two species number of sites as it does in nature (so that widespread species having colonized islands independently, other possible expla- are still widespread, and narrowly distributed ones are still nations exist for such an exclusive arrangement in addition to narrowly distributed). Gotelli & Graves (1996) explain the Figure 1 Island groups in the Bismarck Archipelago used in the study of binary matrices and checkerboard distributions of birds. Island groups are separated by dis- persal barriers (dashed lines), which are determined by differences in avian species composition between island groups and by morphological differences in species occur- ring across barriers (from Mayr & Diamond, 2001). Islands: 1, Wuvulu; 2, Ninigo; 3, Hermits; 4, Anchorites; 5, Manus; 6, San Miguel; 7, Rambutyo; 8, Nauna; 9, St Matthias; 10, Emirau; 11, Tench; 12, Tingwon; 13, New Hanover; 14, Dyaul; 15, Tabar; 16, Lihir; 17, Tanga; 18, Feni; 19, New Ireland; 20, Duke of York; 21, Credner; 22, Vuatom; 23, Lolobau; 24, New Britain; 25, Witu, 26, Unea; 27, Sakar; 28, Umboi; 29, Tolokiwa; 30, Long; 31, Crown. 2 Journal of Biogeography ª 2011 Blackwell Publishing Ltd Bismarck Archipelago birds rationale for these conventions and discuss alternative views. Table 1 Guild memberships of bird genera in the Bismarck We used the method of Miklo´s & Podani (2004) to sample Archipelago for guilds specifically designated by Diamond (1975). matrices in this universe equiprobably, generating 1000 Number of randomized matrices in each simulation with 500,000 Guild Genera species attempted swaps between sampled matrices. Several statistics have been used to quantify co-occurrence Cuckoo-dove Macropygia, Reinwardtoena 4 patterns (Gotelli, 2000 and references therein). Here we focus Gleaning flycatcher Monarcha, Myiagra, Pachycephala 7 on the number of checkerboard distributions (CH, i.e. number Myzomela-sunbird Myzomela, Nectarinia 8 of exclusively distributed species pairs). We do not evaluate the Fruit pigeon Ducula, Ptilinopus 11 C-score [‘checkerboardedness’ index of the matrix as a whole (Stone & Roberts, 1990)], or the T-score [‘togetherness’ index, proposed as an index of congruence among species distribu- by inspection of the same sample of 1000 matrices, the tions in the matrix as a whole (Stone & Roberts, 1992)] expected number of checkerboards for each genus with two or because these metrics are counterintuitive and widely misun- more species, and in each guild for comparison with observed derstood (Stone & Roberts, 1992; Ulrich & Gotelli, 2007; numbers. Then we investigated the specific species involved in Gotelli & Ulrich, 2010).