Macroecological signals of species interactions in the Danish avifauna Nicholas J. Gotellia,1, Gary R. Gravesb, and Carsten Rahbekc aDepartment of Biology, University of Vermont, Burlington, VT 05405; bDepartment of Vertebrate Zoology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013; and cCenter for Macroecology, Evolution and Climate, Department of Biology, University of Copenhagen, DK-2100 Copenhagen ?, Denmark Communicated by Thomas W. Schoener, University of California, Davis, CA, December 21, 2009 (received for review August 6, 2009) The role of intraspeci?c and interspeci?c interactions in structuring biotic communities at?ne spatial scales iswell documented, but the signature of species interactions at coarser spatial scales is unclear. We present evidence that species interactions may be a signi?cant factor in mediating the regional assembly of the Danish avifauna. Because >95% of breeding species (n = 197) are migratory, we hypothesized that dispersal limitation would not be important and that breeding distributionswould largely re?ect resource avail- abilityandautecologicalhabitatpreferences. Instead,wedetecteda striking pattern of spatial segregation between ecologically similar species at two spatial scaleswith a suite of nullmodels that factored in the spatial distribution of habitats in Denmark as well as popula- tion size and biomass of each species. Habitat utilization analyses indicated that community-wide patterns of spatial segregation could not be attributed to the patchy distribution of habitat or to gross differences in habitat utilization among ecologically similar species. We hypothesize that, when habitat patch size is limited, conspeci?c attraction in concert with interspeci?c territoriality may result in spatially segregated distributions of ecologically sim- ilar speciesat larger spatial scales. In theDanishavifauna, theeffects of species interactions on community assembly appear pervasive and can be discerned at grain sizes up to four orders of magnitude larger than those of individual territories. These results suggest that species interactions shouldbe incorporated into species distribution modeling algorithms designed to predict species occupancy pat- terns based on environmental variables. null models | assembly rules | interspeci?c territoriality | conspeci?c social attraction | allee affect The study of species interactions has been at the forefront ofecological research for 75 years (1?4), but the range of spatial scales at which interactions may be discerned in natural com- munities is imperfectly known. Species interactions affect the ?ne- grained spacing of individuals in a wide range of organisms including plants (5, 6), marine invertebrates (7?9), social insects (10), ?sh (11), lizards (12), and mammals (13). The evidence is particularly good for birds, where aggressive interactions may result in interspeci?c territoriality in which individuals defend territories against both conspeci?c and heterospeci?c individuals (14?16). At what point along the spatial continuum from individ- ual territories to continental landscapes does the signature of species interactions cease to be visible? Interspeci?c competition can have a pervasive in?uence on the distribution, abundance, and foraging behavior of birds on small islands (17?19), and it has been hypothesized that local competition among species could ?scale up? to generate competitively driven distributional patterns on larger islands (20). However, interspeci?c competition has a more subtle and ecologically limited effect in mainland avifaunas (14?16, 21). The extent to which interspeci?c competition in?uences the geographic distribution of species in continental landscapes hasnever been resolved.Because large-scale ?eld experiments on avian communities are unfeasible, evidence of interspeci?c competition has been sought in binary presence/ absence matrices of species occurrences on islands (20, 22) and in continental mainland regions (23). Inferences of community assembly rules fromstatistical analyses of presence/absencedata are controversial. Even with the use of sophisticated null-model anal- yses, it is not possible inmost systems todiscriminate spatial patterns generated by species interactions from those caused by historical effects, dispersal barriers, and especially those resulting from hab- itat selection, the intrinsic preferences that species show for par- ticular habitats (24). Large-scale distributional signals of species interactions, if they exist in continental avifaunas, originate at the scale of individual territories. Although habitat selection manifests itself at awide rangeof grain sizes (24, 25), theeffects of intraspeci?c and interspeci?c interactions in continental landscapes previously have been detected only at small grain sizes (14?16, 21, 24, 26?29). In this paper, we present evidence that both intraspeci?c and interspeci?c interactions may in?uence the large-scale spatial dis- tribution of breeding birds in Denmark. Denmark consists of the JyllandPeninsula andan archipelago of land-bridge islands, most of which are visible from the mainland. The contemporary breeding avifauna (197 species) is largely migratory, and only a handful of species (<5%) can be classi?ed as sedentary residents, although juveniles of even these species dis- perse widely (30). A majority of migratory species also have breeding populations in Sweden andNorway that transitDenmark during migration. Thus, the breeding distribution of birds in Denmark largely re?ects resource availability, habitat selection, and the outcome of species interactions, rather than dispersal limitation, historical contingency, or evolutionary processes (none of the species in this assemblage are endemic to Denmark). To disentangle the effects of species interactions from those of habitat selection in the Danish avifauna, we analyzed the breeding distributions of birds at two spatial grains?from a gridded matrix of 5-km ? 5-km cells (n = 2003) and a larger-scale aggregation of 10-km ? 10-km cells (n = 620) (Fig. 1 and Fig. S1). Cells of the smaller grain size (25 km2) are roughly equivalent in area to the breeding territories of the largest raptors (e.g.,Bubo bubo) but are three to four orders of magnitude larger than the breeding terri- tories of songbirds, which numerically dominate the Danish avi- fauna. We then quanti?ed the areas of principal terrestrial and aquatic habitats occurring in each cell at the two spatial scales (Table S1). These complementary databases were used to analyze the co-occurrence patterns of species and the observed and expected values of habitat utilization and electivity at two nested levels of assemblage organization: (i) foraging guilds within the avifauna and (ii) sets of congeneric or closely related specieswithin foraging guilds. This hierarchical framework groups species into guilds of ecologically similar species, with congeneric species within foraging guilds exhibiting the greatest similarity in foraging behavior and morphology. Author contributions: N.J.G., G.R.G., and C.R. designed research; N.J.G. and C.R. analyzed data; and N.J.G., G.R.G., and C.R. wrote the paper. The authors declare no con?ict of interest. 1To whom correspondence should be addressed. E-mail: ngotelli@uvm.edu. This article contains supporting information online at www.pnas.org/cgi/content/full/ 0914089107/DCSupplemental. 5030?5035 | PNAS | March 16, 2010 | vol. 107 | no. 11 www.pnas.org/cgi/doi/10.1073/pnas.0914089107 We crossed this spatial and guild classi?cation with analyses of four null models of species co-occurrence: a standard ??xed-?xed? null model (which preserves row and column sums of the observed binary presence/absence matrix) and three additional models that used information on habitat availability, population sizes, and biomass tomodifymarginal probability distributions (Table S1, S2, and S3 and Figs. S2 and S3). Finally, we conducted null-model analyses of habitat utilization and electivity (31, 32) at both grain sizes for the foraging and congeneric guilds. The resulting suite of 24 sets of null-model analyses (two guild categories ? two grain sizes ? six null models) permits us to address two fundamental questions about the distributional patterns of Danish breeding birds: (i) Do species in foraging and congeneric guilds exhibit nonrandom patterns of spatial aggregation or segregation? (ii) Can nonrandom distributional patterns at different spatial scales be accounted for by the availability and selection of habitat? Results Co-Occurrence Patterns Within Foraging Guilds. Species within most foraging guilds exhibited segregated distributions (Fig. 2, Left and Table S4). Summed across all of the foraging guilds, null models, and spatial grain sizes (24 guilds ? 2 grain sizes ? 4 null models = 192 analyses), 69.8% of tests indicated statistically signi?cant segregated distributions, 18.2% showed randomdistributions, and 12.0% indicated statistically signi?cant aggregated distributions. In a comparisonof patterns at the two grain sizes, a greater fraction of tests indicated segregated distributions in 100-km2 cells (74 segregated, 6 aggregated) than in 25-km2 cells (60 segregated, 18 aggregated). In a comparison of the different null models, com- bining results from both scales of resolution, all four indicated relatively high frequencies of segregated patterns: ?xed-?xed model (29 segregated, 0 aggregated); habitat model (33 segre- gated, 9 aggregated), population model (36 segregated, 6 aggre- gated); and biomass model (36 segregated, 7 aggregated). The habitat model showed the greatest difference in patterns between 100-km2 cells (22 segregated, 1 aggregated) and 25-km2 cells (11 segregated, 8 aggregated). Four foraging guilds exhibited segregated distributional pat- terns at both spatial grains over all models, whereas 11 guilds exhibited amixture of segregated and randomdistributions (Table S4). Eight guilds exhibited a mixture of segregated, aggregated, and random distributions, but only the dabbling ducks showed a strong pattern of aggregation (three of four models at both grain sizes). Of particular interest, the eight foraging guilds composed almost entirely of territorial songbirds (openland insectivores, terrestrial and low-stratum ?ycatchers, thrushes, marsh warblers, foliage gleaners, tit-like birds, corvids, passerine seedeaters) showed strongly segregated distributions in 25-km2 cells (20 seg- Fig. 1. Species richness ofDanish breedingbirds (Left) and spatial variation inhabitat diversity (HD) (Right) of grid cells at agrain sizeof 5km?5km (25km2). The HD score is the product of relative grid cell area and the probability that two points randomly chosenwithin a grid cell represent different habitat types (54). The HD score was used to parameterize null models of random species colonization independently. Species richness ranged from 1 to 109 species per cell (16, 60). The best-?tting power function was S = 27.93681(HD)0.1916, r2 = 0.1171. See Fig. S1 for comparable ?gures at the 10-km ? 10-km (100-km2) grain size. Fig. 2. Summary of null-model analyses of species co-occurrence in ecological guilds of Danish birds (Tables S4 and S5). Gotelli et al. PNAS | March 16, 2010 | vol. 107 | no. 11 | 5031 EC OL OG Y regated, 6 random, 5 aggregated) and 100-km2 cells (24 segre- gated, 7 random, 1 aggregated). Co-Occurrence Patterns Within Congeneric Guilds. Segregated pat- terns of distributional overlap in congeneric guilds of territorial songbirds provided further con?rmation of patterns observed in foraging guilds (Fig. 2, Left and Table S5). Summed across con- generic guilds and both spatial grains (eight guilds ? four null models ? two grain sizes = 64 analyses), 62.5% of tests indicated statistically signi?cant segregated distributions, 28.1% showed random distributions, and 9.4% indicated statistically signi?cant aggregated distributions. A greater fraction of tests indicated segregated distributions in 100-km2 cells (21 segregated, 1 aggre- gated) than in 25-km2 cells (18 segregated, 5 aggregated). All null models indicated relatively high frequencies of segregated pat- terns: 8 segregated and 1 aggregated for the ?xed-?xed model; 10 segregated and 2 aggregated for the habitat model; 11 segre- gated and 1 aggregated for the population model; and 10 segre- gated and 2 aggregated for the biomass model. Summing across spatial grain sizes, four congeneric guilds exhibited a mixture of segregated and random distributions; the remaining four guilds showed a mixture of segregated, random, and aggregated distributions (Table S5).Overlap patterns in Sylvia (2 segregated, 4 random, 2 aggregated) and Phylloscopus (1 seg- regated, 5 random, 2 aggregated) were equivocal. The remaining six guilds showed strong patterns of spatial segregation: Anthus (6 segregated, 1 random, 1 aggregated); Acrocephalus (6 segre- gated, 2 random, 0 aggregated); Parus (5 segregated, 2 random, 1 aggregated); Corvus (8 segregated, 0 random, 0 aggregated); Carduelis (6 segregated, 2 random, 0 aggregated); and Turdus (6 segregated, 2 random, 0 aggregated). Habitat Utilization and Electivity Within Foraging Guilds. All foraging guilds showed signi?cantly high overlap in habitat utilization at both spatial grain sizes (48/48 tests; Table S6). Similar patterns of high overlap were observed in habitat electivity analyses of 25-km2 cells (17/24 tests) and 100-km2 cells (15/24 tests). Species within foraging guilds never exhibited mutually exclusive patterns of habitat utilization and electivity. These analyses suggest that the pervasive spatial patterns of segregation indicated by the four co- occurrence null models (Fig. 2) were not caused by checkerboard distributions of habitats or by gross differences among species in habitat preferences. Habitat Utilization and Electivity Within Congeneric Guilds. Con- generic guilds are composed of species that might be expected, a priori, to exhibit the greatest degree of niche overlap based on phylogenetic similarity and niche conservatism. Congeneric guilds showed signi?cantly high overlap in habitat utilization at both spatial grain sizes (16/16 tests; Table S7). Similar patterns of high overlap were observed in habitat electivity in 25-km2 cells (six of eight tests) and in 100-km2 cells (six of eight tests). The one exception was observed in Sylvia (?ve species), which exhibited high overlap in habitat utilization but mutually exclu- sive patterns of habitat electivity at both spatial grains. This result suggests that species of sylviid warblers occupy cells with a similar spectrum of common habitats but may differ from one another in their occupancy of grid cells containing uncommon habitats (i.e., shrublands and deciduous woodlands). Discussion We began the analyses with the expectation that the breeding dis- tribution of birds inDenmarkwould be linked in a simpleway to the availability of preferred habitat at the scale of analysis (Fig. 1) (33). The signi?cant aggregation of dabbling ducks in grid cells con- taining marsh and freshwater lakes, for example, was consistent with this expectation. We were surprised, however, to discover a pervasivepatternof spatial segregationof species belonging towell- de?ned foraging and congeneric guilds (Fig. 2), especially among species of territorial songbirds. Because terrestrial habitat diversity is high within 25-km2 grid cells (9.6 of a possible 10 habitats), there is little evidence that segregated patterns of spatial overlap among widely distributed territorial species are caused by checkerboard distributions of distinctive habitat types or re?ect strong differences among species in habitat preferences (Fig. 3). A lack of habitat sorting also was con?rmed by the pattern of high overlap in habitat utilization and electivity among species belonging to the same foraging and congeneric guilds (Tables S6 and S7). The one exception was observed in Sylvia warblers, which exhibited sig- ni?cantly less overlap in habitat electivity. Although these ?ndings do not rule out the possibility that subtle habitat preferences in?uence the pattern of spatial segregation among other guilds at coarser spatial scales, they do suggest that behavioral factors other than simple habitat selectionmay in?uence the spatial distributions of species at grain sizes several orders of magnitude larger than the areas of individual territories. Conspeci?c and heterospeci?c attraction often result in clumped or aggregated distributions of breeding birds, most notably among colonial species such as herons, gulls, and swallows (34, 35). The occurrence of conspeci?c and heterospeci?c attraction among songbirds that defend relatively large territories (0.1?10 ha) is arguably more intriguing because the adaptive advantages of aggregated distributions for highly territorial species are less appa- rent. Because heterospeci?c attraction would yield a signi?cant excess of aggregated distributions among pairs of species (36), the opposite ofwhatwe observed, itmay be excluded as the basis for the pervasive community-wide patterns of spatial segregation. Although logistical and ethical constraints prevented us from conducting large-scale ?eld experiments, we hypothesize that the underlying cause of spatial segregation in territorial species at larger scales of resolution stems primarily from conspeci?c attraction. Several ?eld studies have shown that patch suitability is enhanced by the presence of conspeci?cs, which can lead to local abundance peaks higher than expected from the distribution of habitat resources (34). The bene?ts of local aggregative behavior in territorial birds, including mate acquisition and public infor- mation sharing, are examples of Allee effects (37, 38), broadly de?ned as the positive relationship between ?tness and the num- ber of conspeci?cs. Allee effects, which often are manifest at low population densities, may result in conspeci?c aggregations at spatial scales larger than those of individual territories. Although conspeci?c attraction may explain local aggregations of species at the grain sizes analyzed in this study, it cannot explain the excess frequency of interspeci?c segregation observed inmany foraging and congeneric guilds of Danish birds. Interspeci?c ter- ritoriality has been documented in a number of territorial song- birds in Eurasia (21, 39?41), even among some pairs of distantly related species (42). However, spatially segregated territories Fig. 3. Summary of null-model analyses of niche overlap in habitat uti- lization and electivity in ecological guilds of Danish birds (Tables S6 and S7). 5032 | www.pnas.org/cgi/doi/10.1073/pnas.0914089107 Gotelli et al. occur most frequently within pairs of closely related, ecologically similar species that occupy structurally simple habitats (15, 21, 28). When interspeci?c territoriality occurs in heterogeneous or structurally diverse environments, behaviorally dominant species usually exclude less aggressive species from the more productive end of successional gradients, leading to local habitat segregation (14). It should be noted that similar patterns of habitat segregation commonly arise in the absence of competition through the mechanism of habitat selection in heterogeneous environments (24, 43?45). Although habitat patch size may be another deter- mining factor for species occupancy, the minimum patch size for most northern European songbirds is relatively small (<1 ha) (46). In theDanish avifauna, migratory species arrive to nearly empty habitat each spring. Annual mortality rates of migratory songbirds are relatively high (30), and a substantial fraction of arriving individuals are na?ve yearlings with no prior breeding experience. Priority effects may come into play if several males of one species establish contiguous territories in a habitat patch before males of other species arrive. Conspeci?c attraction then might permit one species to dominate numerically a habitat patch so that it becomes less attractive to arriving heterospeci?cs, which either fail to establish territories or rapidly emigrate to other patches of similar habitat that support larger numbers of their own species. It thus is plausible that conspeci?c attraction combined with interspeci?c territoriality could result in mutually exclusive distributions of species at relatively large spatial scales. Interspeci?c territoriality alone would be unlikely to result in spatial segregation at the grain sizes studied here. Themechanismdescribed abovewould bemore likely to occur amongmigratory than resident species, at low rather than high population densities, and in patchy environments where patch size is relatively small. In summary, our analyses suggest that conspeci?c and heterospeci?c interactions can ?scale up? to pro- duce behaviorally driven assembly patterns at relatively large spatial grains. The next generation of coarse-grained macro- ecological studies may need to incorporate species interactions that occur at small spatial scales. Our results also suggest that a failure to incorporate mechanisms of species interactions may account for the mixed results of current species distribution modeling efforts that use only environmental variables to predict species occupancy (47, 48). Methods Geography. The deglaciation of Denmark was completed 16,000?15,500 years ago (ybp) (49), and transformation of the region into the Jylland Peninsula (i.e., mainland) and an archipelago of nearby land-bridge islands took place ? 8,500 ybp through the rising of the Litorina Sea (50). Present-day Denmark (?43,100 km2) presents an ideal geographic template for co-occurrence analysis of avian species at the regional scale. There are no major geographic barriers to avian dispersal (the highest point in Denmark is 173 m above sea level), and there is no evidence of in situ speciation (there are no endemic avian species or subspecies). The larger islands of Sj?lland (7,016 km2), Fyn (2,977 km2), Lolland (1,241 km2), Falster (514 km2), Mors (363 km2), Als (314 km2), Langeland (284 km2), M?n (217 km2), R?m? (129 km2), Sams? (114 km2), Amager (90 km2), ?r? (88 km2), T?singe (70 km2), and Fan? (56 km2) were retained in our analyses. Islands with land and freshwater areas totaling <25 km2 and those occurring >20 km from Jylland or the principal land-bridge islands were omitted from the analyses. Distributional Data. The breeding distribution of the Danish avifauna was mappedat the resolutionof 5-km? 5-kmcells (25 km2), following theUniversal Transverse Mercator coordinate system, by 750 observers during the period 1993?1996 (51) (see SI Text for additional sampling details). After small and distant islands and cells with<25 ha of land area were excluded from the data set, a total of 2,003 cells were available for analysis. We aggregated 5-km ? 5-km cells (both complete and marginal) to create 10-km ? 10-km cells (100 km2). At each grain size, we converted the distributional breeding records to a binary presence/absence (0,1) matrix in which rows represent species and columns represent cells. The matrix of 25-km2 cells supported 197 breeding species. Three species recorded during the 1993?1996 censuses (Ciconia cico- nia, Tetrao tetrix, and Sylvia nisoria) no longer breed inDenmark. Two colonial species (Rissa tridactyla and Alca torda) that occurred in marginal coastal cells at the 25-km2 grain size were omitted from the matrix when scaling it up to 100-km2 cells (n = 620). Edge effects of peripheral cells were incorporated by taking account of the area of each cell and its habitat diversity, both of which are reduced in peripheral cells. Habitat. The Danish environment has experienced several millennia of intensive human disturbance (52) culminating in a contemporary terrestrial landscape characterized by ?ne-grained patchworks of heath, hedgerow, shrubland, and woodland embedded in a matrix of pasture, meadow, and cropland. Habitats within 25-km2 cells were previously classi?ed into 12 dis- tinctive categories de?ned and quanti?ed based on remote sensing of 25-m ? 25-m pixels (53): open salinewater, open freshwater, urban and unvegetated ground, seasonally tilled cropland, grazed ormowngrassland,marshland and bog, grassy heathland, mixed grassy and shrubby heathland, shrubby heathland, shrubby woodland, deciduous woodland, and coniferous wood- land (Table S1). Cells typically contained a majority of the habitat categories present in Denmark (10.6 ? 1.0 of 12 possible habitats). We constructed a quantitative index of habitat heterogeneity (Fig. 1) based on the percent area of the common habitat categories occurringwithin 25-km2 cells. Habitat types covering <1% (25 ha) of the cell area were omitted from the diversity index for that cell. We estimated habitat heterogeneity (HH) as: HH ? 1:0? ? 12 i?1  p2i  where pi is the proportion of the total area measured within each cell that is occupied by habitat i. This index measures the probability that two random points chosen within a cell represent two different habitats (54). HH can range from a minimum of 0.0 (if only a single habitat type is present) to a maximum of 0.917 (if all 12 habitats are equally common). At the 100-km2 grain size, we recalibrated the HH values of 13 cells (<3% of the total) from 0.00 to 0.01 so that relative probability weights could be calculated. We then multiplied HH by the cell area minus the area of open saline water to create an index of habitat diversity (HD). To minimize numerical round-off error in the HD index (which ranged from 0.01 to 83.77), 60 values <1.0 were rescaled to 1.0. Recalibration was unnecessary at the 25-km2 grain size. Indices of Species-Speci?c Colonization Potential. The ability of a species to colonize isolated patches of habitat is in?uenced by many factors including population size and dispersal behavior (53, 55). We did not attempt to model dispersal behavior per se, because the spatial scales of annual migration and natal dispersal distances of European birds are large relative to the grain size of census cells (30). Parasitism, disease, and predation also may in?uence the occupancy of habitat patches, but comprehensive data on these potentially important factors were unavailable. We constructed two indices of colonization potential, one based on the estimated size of breeding populations in Denmark (51) and a second based on the biomass of each species (body mass ? Danish population size). We estimated body mass as the midpoint of the mean values recorded for males and females, respectively (Table S2). Interspeci?c variation in avian body mass correlates with longevity (56), which in turn may be linked with a species? ability to resist local extinction through a series of failed repro- ductive seasons (57). Species with high biomass values in Denmark thus may exhibit enhanced abilities to colonize and persist in suitable patches of habitat. The total breeding avifauna is estimated at 1.643 ? 107 pairs ranging from <10 pairs (27 species) to 2,228,000 pairs (Turdus merula) per species. The three most abundant species (Alauda arvensis, Turdus merula, and Fringilla coelebs) constituted 32.5% of the total individuals, but 71 species (36%) had breeding populations >10,000 pairs (Table S2). Narrowly distributed species exhibit a strong range size?abundance relationship, but the correlation is weaker for geographically widespread species in Denmark (58). Estimates of Danish population biomass ranged from <100 g (seven species) to 6.3 ? 108 g (Phasianus colchicus). Analysis of Ecological Guilds. We categorized the Danish breeding avifauna into two types of ecological guilds. First, we grouped 194 of 197 species into 33 mutually exclusive foraging guilds, which pool mixtures of congeneric and more distantly related species that use a similar spectrum of resources. We also analyzed a subset of eight narrowly de?ned congeneric guilds composed of closely related species (Table S2). To maintain statistical power in guild analyses, we focused on guilds that contained four or more species (171 species in 24 foraging guilds, and 40 species in eight congeneric guilds). For all analyses, the spatial domain included only those cells that contained at Gotelli et al. PNAS | March 16, 2010 | vol. 107 | no. 11 | 5033 EC OL OG Y least one guild member. This restriction guards against spurious patterns of aggregation that might arise from including empty cells that are not bio- logically suitable for any of the species in the guild. Quanti?cation of Species Co-Occurrence Patterns. Weused the C-score (59) as a quantitative index of species co-occurrence. The C-score is de?ned as (Ri ? S) ? (Rj ? S) where Ri and Rj represent the total number of occurrences of species i and j, respectively, and S is the number of shared occurrences. The average C-score, calculated over all unique species pairs within an ecological guild, summarizes the pattern of co-occurrence as a single metric. The larger the C-score, the fewer incidents of co-occurrence among pairs of species. How- ever, the C-score, like most indices of segregation or aggregation, is affected both by the number of shared occurrences and by the total number of occurrences of each species. For this reason, comparison with an appropriate suite of null models is essential. Randomization Tests. We compared the C-score observed for ecological guilds of breeding birds with scores generated by four different null models ranging in complexity from a simple constrained randomization of the binary pres- ence/absence matrix to models that incorporated measures of habitat het- erogeneity, population size, and biomass (for model details, SI Text). For each model, we created null avifaunal assemblages (n = 1,000) and calculated the C-score for each. We then compared the C-score observed for ecological guilds with the distribution of simulated C-scores to estimate the one-tailed probability. Each set of simulations was initialized with a new random number seed taken from the system clock, and all null-model analyses were conducted in EcoSim Version 7.2 (60). Analyses of Habitat Niche Overlap. Weused a nullmodel based on the ?habitat utilization matrix? (33) to determine whether species? co-occurrence patterns were associated with the coarse-grained distribution of habitats. For each species, we determined the total area of each of the 12 habitat categories in cells that it occupied. We then constructed a habitat utilization matrix in which each row represents a species, each column represents a habitat cat- egory, and the entries are the summed areas of the habitat categories in each occupied cell. The habitat areas thenwere converted to percentages for each species. For each unique species pair ij, we calculated habitat niche overlap Oij using Pianka?s (31) overlap index as: Oij ? Oji ? ? n k?1 p ik p jk ??????????????????????????????????????? ? n k?1 p 2ik ? n k?1 p jk 2 q where pik is the proportional occupancy of cells containing habitat k by species i. If Oij = 0.0, then species i and j occur in cells that do not share any habitat categories. In contrast, high index values indicate that species occur in cells that contain similar proportions of the various habitat categories. We then calculated the average pairwise overlap for all unique species pairs in the matrix. Habitat utilization matrices were calculated at both spatial scales for foraging and congeneric guilds. Note that the spatial scales of our analyses are relatively large compared with the scale at which avian habitat selection occurs. The metrics describe overlap in the habitat dis- tributions of occupied sites, which is not necessarily identical with overlap in habitat utilization. We compared the average pairwise overlap in real assemblages of species with thefrequencydistributionofoverlapvaluesobserved innull assemblages. Thenull distributionwas created by reshuf?ing the overlap valueswithin each row of the original species ? habitat utilization matrix to generate a null distribution (1,000 randomizations) that would be expected if habitat uti- lization was independent among species. We then calculated the probability that the observed niche overlap was drawn from this distribution (61). 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MacArthur RH, Wilson EO (1967) The Theory of Island Biogeography (Princeton Univ Press, Princeton, NJ). 56. Bonner JT (1965) Size and Cycle: An Essay on the Structure of Biology (Princeton Univ Press, Princeton, NJ). 57. Tracy CR, George TL (1992) On the determinants of extinction. Am Nat 139:102?122. 58. Borregaard MK, Rahbek C (2006) Prevalence of intraspeci?c relationships between range size and abundance in Danish birds. Divers Distrib 12:417?422. 59. Stone L, Roberts A (1990) The checkerboard score and species distributions. Oecologia 85:74?79. 60. Gotelli NJ, Entsminger GL. EcoSim: Null models software for ecology. Version 7. (Acquired Intelligence & Kesey-Bear Inc) (2004) http://garyentsminger.com/ecosim.htm. 61. Winemiller KO, Pianka ER (1990) Organization in natural assemblages of desert lizards and tropical ?shes. Ecol Monogr 60:27?55. 62. Gotelli NJ, Graves GR (1996) Null Models in Ecology (Smithsonian Institution Press, Washington, D.C.). 63. Lawlor LR (1980) Overlap, similarity, and competition coef?cients. Ecology 61: 245?251. Gotelli et al. PNAS | March 16, 2010 | vol. 107 | no. 11 | 5035 EC OL OG Y Supporting Information Gotelli et al. 10.1073/pnas.0914089107 Null-Model Algorithms Null-model analysis has been controversial, in part because the results depend on the assumptions of the speci?c null-model test, which often are dif?cult to evaluate (1, 2). Most null-model analyses have been based on a modi?ed version of Connor and Simberloff ? s (3) original strategy of preserving observed row and column sums in the matrix. Although this algorithm originally was criticized as allegedly being too conservative (4), extensive benchmark tests with arti?cial matrices suggest it has good stat- istical properties (5?7). However, to ensure our analyses were robust and not unduly in?uenced by the performance of a single test, we used a suite of four null-model algorithms. These models all use the C-score (8) as the index for measuring species segre- gation or aggregation. Related indices, such as Stone and Robert ? s togetherness index (9) could be used also, although these indices have not yet been subject to benchmark testing. Fixed-Fixed Model. The ?xed-?xed model creates null matrices in which the row and column totals of thematrix are preserved (5). In the absence of additional biological or geographic information, the ?xed row and column sums account for observed heterogeneity in site suitability and differences among species in colonization po- tential (3). To create such amatrix, we used an algorithm (5) which swaps the elements of randomly chosen 2 ? 2 submatrices of the form [01 | 10] or [10 | 01]. Although the pattern of ones and zeros is randomized, each null community has the same number of species (column totals) and occupied cells (row totals) as the real avifaunal community. We created each matrix with a total of 30,000 con- secutive swaps or mn swaps (where m = the number of rows in the matrix and n = the number of columns), whichever was larger. These numbers ensured that, in each randomly generated matrix, every swappable submatrix was reshuf?ed at least once. A unique, independent swap sequence was used for each of the 1,000 null matrices. The ?xed-?xed model, when used with the C-score, has been subjected to extensive benchmark testing with arti?cial ma- trices that contain speci?ed amounts of randomness and structure (5?7). The swapping algorithm that we have used to create null matrices is slightly less likely to detect segregation of species than is a more recent algorithm that samples all matrices with the same row and column totals equiprobably (10). However, this bias is small for large matrices of the size we have analyzed here (11). Habitat Model. A potential weakness of the ?xed-?xed model is that it does not directly simulate a random colonization process. To address this de?ciency, we used amodel in which the row totals of the matrix (the occurrence frequency of species) were ?xed, but the column totals (the number of species per cell) were not. Most importantly, species were assigned randomly and independently to cells with the probability of occurrence set proportional to the measured index of habitat diversity (HD) for each cell. Population Model. To re?ect the natural differences in habitat diversity among cells and colonization potential among species, we constructed a population-null model in which the total number of species occurrences in thematrix was preserved, but where row and column total were allowed to vary randomly (5). The probability of an occurrence of species i in cell j was proportional to both the total breeding population size of species i in Denmark and the HD value of cell j. Thus, for the placement of the ?rst species occur- rence in the matrix, the cell most likely to be chosen would occur at the intersection of the row with the largest sum (species with largest population) and column with the largest sum (grid cell with the highest HD value). The least likely cell to be chosen would be the one with the smallest row and smallest column sum. Biomass Model. The biomassmodel was identical to the population model,except thatbiomass(totalbiomassofbreedingindividuals in Denmark)was substituted for population size. The rational for this model is that total biomass re?ects the total energy that has been sequestered by the species in Denmark, integrating the effects of bothpopulation size andbody size.Because it is dif?cult to validate or parameterize null models for entire assemblages, our strategy was to test a suite of null models applied to different spatial scales and different levels of assemblage organization. Consistent results thatemergefromsuchabatteryof testsyieldrobust?ndings thatare insensitive to theassumptionsandrestrictions thatmayapply toany particular null model or data partition. Body masses were compiled from the Handbook of the Birds of Europe, the Middle East, and North Africa (12?20), with a pref- erence for data from Danish, Dutch, and northern German populations. A priori guild assignments were made by C. Rahbek and J. Fjelds? before co-occurrence analyses were performed. Census Data for Danish Avifauna Species occurrence records for the 197 breeding birds of Denmark were derived from data in the Danish atlas of breeding birds in Denmark, 1993?1996 (21). Denmark was divided into 2,169 atlas- cells (5 km ? 5 km). More than 99% of the cells were surveyed for breeding birds: 1,465 were well surveyed, 640 were reasonably well surveyed, 50 were incompletely surveyed, and only 14 cells were not surveyed. Atlas surveys were conducted by ca. 750 observers. The total number of observations (cells ? species occurrences) equaled 141,865.Each cell was visited 5?10 times each year for a quantitative census of all breeding species. Field work was conducted between February and August during each of the 4 years (1993?1996). Data derived from the atlas surveys were supplemented with information from census records from 2,500 large nature reserves, ongoing single-species surveys, and monitoring or research pro- grams on rare and/or endangered species, wildfowl, and raptors. Incidental information on rare breeding species also was included from published maps on occurrences of Danish breeding birds. The occurrence of each species in a cell was categorized as (i) con?rmed breeding (e.g., observation of adults feeding chicks, occurrence of freshly used nests, and/or adult birds carrying food or excrement); (ii) probable breeding (e.g., territorial singing males observed in the breeding season, individuals observed de- fending territories, engaging in courtship, building nests, or car- rying nesting materials); and (iii) presence observed (e.g., birds were observed in the breeding season butwith no other evidence of breeding). In our analyses, we used only records from the ?rst two categories to designate species occurrences. 1. Gotelli NJ, Graves GR (1996) Null Models in Ecology (Smithsonian Institution Press, Washington, DC). 2. Ladau J (2008) Validation of null model tests using Neyman-Pearson hypothesis testing theory. Theoretical Ecology 1:241?248. 3. Connor EF, Simberloff D (1979) The assembly of species communities: Chance or competition? Ecology 60:1132?1140. 4. Diamond JM, Gilpin ME (1982) Examination of the ?null? model of Connor and Simberloff for species co-occurrences on islands. Oecologia 52:64?74. 5. Gotelli NJ (2000) Null model analysis of species co-occurrence patterns. Ecology 81: 2606?2621. 6. Ulrich W, Gotelli NJ (2007) Null model analysis of species nestedness patterns. Ecology 88:1824?1831. Gotelli et al. www.pnas.org/cgi/content/short/0914089107 1 of 3 7. Gotelli NJ, Ulrich W (2010) The empirical Bayes approach as a tool to identify non- random species associations. Oecologia 162:463?477. 8. Stone L, Roberts A (1990) The checkerboard score and species distributions. Oecologia 85:74?79. 9. Stone L, Roberts A (1992) Competitive exclusion, or species aggregation? An aid in deciding. Oecologia 91:419?424. 10. Mikl?s I, Podani J (2004) Randomization of presence ?absence matrices: Comments and new algorithms. Ecology 85:86?92. 11. Lehsten V, Harmand P (2006) Null models for species co-occurrence patterns: Assessing bias and minimum iteration number for the sequential swap. Ecography 29:786?792. 12. Cramp S, Perrins CM (1994) Handbook of the Birds of Europe, the Middle East and North Africa: The Birds of the Western Palearctic. Buntings and New World Warblers (Oxford Univ Press, Oxford, U.K.), Vol 9. 13. Cramp S, Perrins CM (1994) Handbook of the Birds of Europe, the Middle East and North Africa: The Birds of the Western Palearctic. Crows to Finches (Oxford Univ Press, Oxford, U.K.), Vol 8. 14. Cramp S, Perrins CM (1993) Handbook of the Birds of Europe, the Middle East and North Africa: The Birds of the Western Palearctic. Flycatchers to Shrikes (Oxford Univ Press, Oxford, U.K.), Vol 7. 15. Cramp S (1992) Handbook of the Birds of Europe, the Middle East and North Africa: The Birds of the Western Palearctic. Warblers (Oxford Univ Press, Oxford, U.K.), Vol 6. 16. Cramp S (1988) Handbook of the Birds of Europe, the Middle East and North Africa: The Birds of the Western Palearctic. Tyrant Flycatchers to Thrushes (Oxford Univ Press, Oxford, U.K.), Vol V. 17. Cramp S (1985) Handbook of the Birds of Europe, the Middle East and North Africa: The Birds of the Western Palearctic. Terns to Woodpeckers (Oxford Univ Press, Oxford, U.K.), Vol 4. 18. Cramp S, Simmons KEL (1983) Handbook of the Birds of Europe, the Middle East and North America: The Birds of the Western Palearctic. Waders to Gulls (Oxford Univ Press, Oxford, U.K.), Vol 3. 19. Cramp S, Simmons KEL (1980) Handbook of the Birds of Europe, the Middle East and North Africa: The Birds of the Western Palearctic Hawks to Bustards (Oxford Univ Press, Oxford, U.K.), Vol 2. 20. Cramp S, Simmons KEL (1977) Handbook of the Birds of Europe, the Middle East and North Africa: The Birds of the Western Palearctic. Ostrich to Ducks (Oxford Univ Press, Oxford, U.K.), Vol 1. 21. Grell MB (1998) Fuglenes Danmark (Gads Forlag, Copenhagen, Denmark). Fig. S1. Species richness and habitat diversity (100-km2 grain size). Species richness of Danish breeding birds and spatial variation in habitat diversity (HD) of grid cells at a grain size of 10 km ? 10 km (100 km2). The HD score is the product of relative grid cell area and the probability that two points randomly chosen within a grid cell represent different habitat types (1). The HD score was used to parameterize null models of random species colonization independently. Species richness ranged from 10 to 117 species per cell (average = 81.45). The best-?tting power function was S = 48.17259(HD)0.1468, r2 = 0.4233. 1. Grell MB (1998) Fuglenes Danmark (Gads Forlag, Copenhagen, Denmark). Gotelli et al. www.pnas.org/cgi/content/short/0914089107 2 of 3 Fig. S2. Individual body mass. Distribution of body masses of the Danish avifauna (n = 197 species). Other Supporting Information Table S1 (DOC) Table S2 (DOC) Table S3 (DOC) Table S4 (DOC) Table S5 (DOC) Table S6 (DOC) Table S7 (DOC) Fig. S3. Population biomass. Distribution of population biomass (individual body mass ? population size) for the Danish avifauna (n = 197 species). Gotelli et al. www.pnas.org/cgi/content/short/0914089107 3 of 3 1 Table S1. Habitat categories. Percent coverage and distribution of habitat types among 5 km ? 5 km cells in Denmark. Habitat Categories % cover in cells % cells with > 25 ha of habitat open saline water 20.3 40.7 open fresh water 0.8 10.3 urban and unvegetated ground 7.7 93.8 Seasonally tilled cropland 38.0 95.8 grazed or mown grassland 19.0 97.0 marshland and bog 0.8 21.1 grassy heathland 2.6 67.5 mixed grassy and shrubby heathland 0.5 12.6 shrubby heathland 0.8 21.2 shrubby woodland 1.6 49.5 deciduous woodland 3.6 69.6 coniferous woodland 4.3 60.6 1 Table S2. Macroecological traits of the Danish avifauna. Rows represent breeding species included in the analysis. 25 km2 = number of grid-cell o ccurrences at the 5 x 5 km2 spatial grain (n = 2003 grid cells total; 100km 2 = number of grid cell o ccurrences at the 10 x 10 km2 spatial grain (n = 620 grid cells total). Territoriality = territorial or colonial stat us. Body mass = adult body mass in grams (averages given for sexually dimorphic species). N = est imated number of breeding pairs in Denmark. Foraging gu ild and congeneric guild assignments were made a priori by C. Rahbek and J. Fjelds?. Common English Name Scientific Name 25 km2 100 km2 Territoriality Body Mass N Foraging Guild Congeneric Guild Little Grebe Tachybaptus ruficollis 646 387 territorial 190 1750 aquatic pursuers Great Crested Grebe Podiceps cristatus 563 321 territorial 875 4000 aquatic pursuers Red-necked Grebe Podiceps griseigena 501 302 territorial 850 1750 aquatic pursuers Horned Grebe Podiceps auritus 2 2 territorial 394 <10 aquatic pursuers Eared Grebe Podiceps nigricollis 54 41 territorial 290 275 aquatic pursuers Great Cormorant Phalacrocorax carbo 42 47 colonial 2110 38500 aquatic pursuers Eurasian Bittern Botaurus stellaris 68 56 territorial 1225 175 wading birds Gray Heron Ardea cinerea 226 199 colonial 1432.5 6735 wading birds Black Stork Ciconia nigra 1 1 territorial 3000 <10 wading birds White Stork Ciconia ciconia 8 7 territorial 3447.5 <10 wading birds Eurasian Spoonbill Platalea leucorodia 2 2 colonial 1260 <10 wading birds Mute Swan Cygnus olor 925 484 territorial 10750 5000 grazing waterfowl Graylag Goose Anser anser 435 267 territorial 3465 3750 grazing waterfowl 2 Canada Goose Branta canadensis 26 25 territorial 4635 38 grazing waterfowl Barnacle Goose Branta leucopsis 4 5 territorial 1585 17 grazing waterfowl Common Shelduck Tadorna tadorna 1131 533 territorial 1152.5 2500 dabbling ducks Eurasian Wigeon Anas penelope 7 9 territorial 642.5 10 grazing waterfowl Gadwall Anas strepera 78 71 territorial 750 275 dabbling ducks Green-winged Teal Anas crecca 177 147 territorial 355 300 dabbling ducks Mallard Anas platyrhynchos 1747 603 territorial 1030 20000 dabbling ducks Northern Pintail Anas acuta 45 46 territorial 807.5 163 dabbling ducks Garganey Anas querquedula 97 86 territorial 327.5 275 dabbling ducks Northern Shoveler Anas clypeata 221 182 territorial 652.5 900 dabbling ducks Common Pochard Aythya ferina 214 159 territorial 870 500 diving ducks Tufted Duck Aythya fuligula 358 249 territorial 657.5 900 diving ducks Common Eider Somateria mollissima 110 119 territorial 2067.5 22000 diving ducks Common Goldeneye Bucephala clangula 20 14 territorial 825 63 diving ducks Red-breasted Merganser Mergus serrator 276 200 territorial 1092.5 2500 aquatic pursuers Common Merganser Mergus merganser 35 24 territorial 1435 50 aquatic pursuers Honey Buzzard Pernis apivorus 268 169 territorial 625 650 diurnal raptors Red Kite Milvus milvus 39 32 territorial 1015 26 diurnal raptors White-tailed Eagle Haliaeetus albicilla 3 3 territorial 4792.5 <10 diurnal raptors Marsh Harrier Circus aeruginosus 391 250 territorial 585 650 diurnal raptors Northern Harrier Circus cyaneus 7 7 territorial 438.5 <10 diurnal raptors Montagu's Harrier Circus pygargus 33 23 territorial 315 43 diurnal raptors Northern Goshawk Accipiter gentilis 594 331 territorial 925 675 diurnal raptors Eurasian Sparrowhawk Accipiter nisus 1140 507 territorial 205 3750 diurnal raptors Common Buzzard Buteo buteo 1498 524 territorial 805 5000 diurnal raptors Osprey Pandion haliaetus 10 10 territorial 1530 <10 diurnal raptors Eurasian Kestrel Falco tinnunculus 1215 529 territorial 115 2050 diurnal raptors Eurasian Hobby Falco subbuteo 3 3 territorial 210 <10 diurnal raptors 3 Black Grouse Tetrao tetrix 1 1 territorial 1080 <10 gallinaceous birds Gray Partridge Perdix perdix 1464 547 territorial 385 25000 gallinaceous birds Common Quail Coturnix coturnix 113 91 territorial 100 38 gallinaceous birds Ring-necked Pheasant Phasianus colchicus 1790 590 territorial 1125 280000 gallinaceous birds Water Rail Rallus aquaticus 400 282 territorial 115.5 3500 Rails Spotted Crake Porzana porzana 24 21 territorial 83 35 Rails Corncrake Crex crex 12 12 territorial 155 <10 Rails Common Moorhen Gallinula chloropus 1329 550 territorial 350 50000 Rails Eurasian Coot Fulica atra 1604 588 territorial 775 20000 Rails Common Crane Grus grus 9 8 territorial 5275 10 wading birds Eurasian Oystercatcher Haematopus ostralegus 758 420 territorial 525 7500 plovers Black-winged Stilt Himantopus himantopus 1 1 territorial 205 <10 plovers Pied Avocet Recurvirostra avosetta 182 141 territorial 245 5000 plovers Little Ringed Plover Charadrius dubius 227 173 territorial 38.5 300 plovers Common Ringed Plover Charadrius hiaticula 485 317 territorial 64.5 2000 plovers Snowy Plover Charadrius alexandrinus 11 10 territorial 47.5 55 plovers European Golden Plover Pluvialis apricaria 5 5 territorial 175 <10 plovers Northern Lapwing Vanellus vanellus 1805 597 territorial 217.5 40000 plovers Dunlin Calidris alpina 69 64 territorial 47 450 scolopacids Ruff Philomachus pugnax 41 34 territorial 140 400 scolopacids Common Snipe Gallinago gallinago 662 385 territorial 105 2750 scolopacids Eurasian Woodcock Scolopax rusticola 321 207 territorial 295 1750 scolopacids Black-tailed Godwit Limosa limosa 49 38 territorial 332.5 700 scolopacids Whimbrel Numenius arquata 115 82 territorial 987.5 300 scolopacids Common Redshank Tringa totanus 583 338 territorial 121.5 12500 scolopacids Green Sandpiper Tringa ochropus 34 28 territorial 80.5 55 scolopacids Wood Sandpiper Tringa glareola 25 19 territorial 67.5 73 scolopacids Common Sandpiper Actitis hypoleucos 4 4 territorial 48 <10 scolopacids 4 Ruddy Turnstone Arenaria interpres 1 7 territorial 110.5 40 scolopacids Mediterranean Gull Larus melanocephalus 1 1 colonial 275 <10 Gulls Black-headed Gull Larus ridibundus 386 276 colonial 280 150000 Gulls Common Gull Larus canus 240 193 colonial 387.5 27500 Gulls Lesser Black-backed Gull Larus fuscus 26 41 colonial 715 4400 Gulls Herring Gull Larus argentatus 171 160 colonial 957.5 56500 Gulls Great Black-backed Gull Larus marinus 75 86 territorial 1600 1550 Gulls Black-legged Kittiwake Rissa tridactyla 3 0 colonial 307.5 625 Gulls Gull-billed Tern Gelochelidon nilotica 5 5 colonial 217.5 14 Terns Sandwich Tern Sterna sandvicensis 18 26 colonial 275 4500 Terns Common Tern Sterna hirundo 92 86 colonial 125 1000 Terns Arctic Tern Sterna paradisaea 157 142 colonial 109.5 8500 Terns Little Tern Sterna albifrons 61 65 colonial 57 500 Terns Black Tern Chlidonis niger 13 11 colonial 63 100 Terns Razorbill Alca torda 1 0 colonial 722.5 610 Black Guillemot Cepphus grylle 6 17 colonial 377.5 1089 Stock Dove Columba oenas 255 178 territorial 302.5 900 columbids Common Wood Pigeon Columba palumbus 1939 608 territorial 510 291000 columbids Eurasian Collared Dove Streptopelia decaocto 1482 563 territorial 195 48500 columbids European Turtle Dove Streptopelia turtur 32 19 territorial 153.5 118 columbids Common Cuckoo Cuculus canorus 1755 594 territorial 110 22050 Barn Owl Tyto alba 38 32 territorial 365 63 Owls Eurasian Eagle Owl Bubo bubo 28 24 territorial 2220 33 Owls Little Owl Athene noctua 110 79 territorial 167.5 188 Owls Tawny Owl Strix aluco 889 395 territorial 462.5 4500 Owls Long-eared Owl Asio otus 644 381 territorial 257.5 1750 Owls Short-eared Owl Asio flammeus 14 15 territorial 295 <10 Owls European Nightjar Caprimulgus europaeus 114 77 territorial 85 550 5 Common Swift Apus apus 599 337 territorial 39.5 100000 aerial insectivores Common Kingfisher Alcedo atthis 160 111 territorial 39 300 Eurasian Hoopoe Upupa epops 1 1 territorial 66.5 <10 Eurasian Wryneck Jynx torquilla 99 81 territorial 37.5 88 woodpeckers European Green Woodpecker Picus viridis 451 218 territorial 191 775 woodpeckers Black Woodpecker Dryocopus martius 149 96 territorial 275 225 woodpeckers Great Spotted Woodpecker Dendrocopos major 1518 552 territorial 74 100000 woodpeckers Lesser Spotted Woodpecker Dendrocopos minor 37 31 territorial 20 85 woodpeckers Crested Lark Galerida cristata 38 33 territorial 44.65 63 open-land insectivores Wood Lark Lullula arborea 145 95 territorial 30 300 open-land insectivores Eurasian Skylark Alauda arvensis 1984 614 territorial 36.4 1360000 open-land insectivores Sand Martin Riparia riparia 693 418 territorial 13.15 30000 aerial insectivores Barn Swallow Hirundo rustica 1920 608 territorial 19.05 385000 aerial insectivores Common House Martin Delichon urbica 1629 585 territorial 18.6 93500 aerial insectivores Tawny Pipit Anthus campestris 6 6 territorial 24.5 23 open-land insectivores Anthus Tree Pipit Anthus trivialis 1275 494 territorial 21.5 67000 open-land insectivores Anthus Meadow Pipit Anthus pratensis 1130 546 territorial 19.25 40000 open-land insectivores Anthus Water Pipit Anthus spinoletta 12 18 territorial 23.5 123 open-land insectivores Anthus Yellow Wagtail Motacilla flava 350 236 territorial 17 8900 open-land insectivores Gray Wagtail Motacilla cinerea 326 179 territorial 17.4 475 White Wagtail Motacilla alba 1893 611 territorial 20.8 111000 open-land insectivores White-throated Dipper Cinclus cinclus 11 10 territorial 63.8 <10 Winter Wren Troglodytes troglodytes 1915 604 territorial 8.9 404000 terrestrial and low flycatching feeders Dunnock Prunella modularis 1728 596 territorial 19 101000 terrestrial and low flycatching feeders European Robin Erithacus rubecula 1807 594 territorial 16.7 285000 terrestrial and low flycatching feeders Thrush Nightingale Luscinia luscinia 1084 448 territorial 25 68000 terrestrial and low flycatching feeders Common Nightingale Luscinia svecica 4 2 territorial 20.3 <10 terrestrial and low flycatching feeders 6 Black Redstart Phoenicurus ochruros 454 294 territorial 16.2 875 terrestrial and low flycatching feeders Common Redstart Phoenicurus phoenicurus 1146 504 territorial 15.5 36000 terrestrial and low flycatching feeders Whinchat Saxicola rubetra 895 431 territorial 16.5 14000 terrestrial and low flycatching feeders Eurasian Stonechat Saxicola torquata 15 13 territorial 15.2 <10 terrestrial and low flycatching feeders Northern Wheatear Oenanthe oenanthe 253 198 territorial 23.8 2900 terrestrial and low flycatching feeders Common Blackbird Turdus merula 1977 610 territorial 96 2282000 thrushes Turdus Fieldfare Turdus pilaris 352 220 territorial 104.5 3500 thrushes Turdus Song Thrush Turdus philomelos 1821 595 territorial 68.5 259000 thrushes Turdus Redwing Turdus iliacus 2 2 territorial 62.5 <10 thrushes Turdus Mistle Thrush Turdus viscivorus 997 445 territorial 119 28000 thrushes Turdus Grasshopper Warbler Locustella naevia 413 271 territorial 13.3 1000 marsh warblers River Warbler Locustella fluviatilis 11 10 territorial 18.8 <10 marsh warblers Savi's Warbler Locustella luscinioides 22 19 territorial 15.65 25 marsh warblers Sedge Warbler Acrocephalus schoenobaenus 484 326 territorial 11.9 3900 marsh warblers Acrocephalus Marsh Warbler Acrocephalus palustris 1198 514 territorial 12 30000 marsh warblers Acrocephalus Eurasian Reed Warbler Acrocephalus scirpaceus 1304 563 territorial 11.8 53000 marsh warblers Acrocephalus Great Reed Warbler Acrocephalus arundinaceus 15 15 territorial 30.35 20 marsh warblers Acrocephalus Icterine Warbler Hippolais icterina 1560 587 territorial 13.3 64000 foliage gleaners Barred Warbler Sylvia nisoria 3 3 territorial 24.35 <10 foliage gleaners Sylvia Lesser Whitethroat Sylvia curruca 1704 598 territorial 11.6 160000 foliage gleaners Sylvia Greater Whitethroat Sylvia communis 1920 610 territorial 14.5 358000 foliage gleaners Sylvia Garden Warbler Sylvia borin 1732 588 territorial 18.25 216000 foliage gleaners Sylvia Eurasian Blackcap Sylvia atricapilla 1778 588 territorial 18.95 284000 foliage gleaners Sylvia Green Warbler Phylloscopus trochiloides 3 4 territorial 7.8 <10 foliage gleaners Phylloscopus Wood Warbler Phylloscopus sibilatrix 629 372 territorial 10.6 16000 foliage gleaners Phylloscopus Chiffchaff Phylloscopus collybita 1778 587 territorial 8.4 240000 foliage gleaners Phylloscopus Willow Warbler Phylloscopus trochilus 1910 607 territorial 9.35 603000 foliage gleaners Phylloscopus 7 Red-breasted Flycatcher Ficedula parva 11 11 territorial 11 <10 Eurasian Pied Flycatcher Ficedula hypoleuca 646 372 territorial 13.65 16200 Spotted Flycatcher Muscicapa striata 1033 489 territorial 14.9 19000 Goldcrest Regulus regulus 1462 560 territorial 5.8 168000 tit-like birds Firecrest Regulus ignicapillus 27 25 territorial 5 15 tit-like birds Bearded Tit Panurus biarmicus 81 67 territorial 14.4 1500 Long-tailed Tit Aegithalos caudatus 579 333 territorial 9 9700 tit-like birds Marsh Tit Parus palustris 1073 453 territorial 11.9 27000 tit-like birds Parus Willow Tit Parus montanus 38 22 territorial 11.15 200 tit-like birds Parus Crested Tit Parus cristatus 854 354 territorial 11.15 26000 tit-like birds Parus Coal Tit Parus ater 1417 543 territorial 10.1 178000 tit-like birds Parus Blue Tit Parus caeruleus 1839 597 territorial 10.85 245000 tit-like birds Parus Great Tit Parus major 1943 607 territorial 18.45 745000 tit-like birds Parus Eurasian Nuthatch Sitta europaea 948 409 territorial 23.9 35200 tit-like birds Eurasian Treecreeper Certhia familiaris 863 403 territorial 9.1 33000 tit-like birds Short-toed Treecreeper Certhia brachydactyla 200 123 territorial 8.6 1250 tit-like birds Eurasian Penduline Tit Remiz pendulinus 87 71 territorial 10 150 Eurasian Golden Oriole Oriolus oriolus 63 53 territorial 71 88 Red-backed Shrike Lanius collurio 557 355 territorial 30.25 1750 Great Gray Shrike Lanius excubitor 18 15 territorial 67 23 Eurasian Jay Garrulus glandarius 1315 522 territorial 167.55 56000 omnivorous corvids Eurasian Magpie Pica pica 1656 556 territorial 217.5 249000 omnivorous corvids Spotted Nutcracker Nucifraga caryocatactes 20 18 territorial 193 30 omnivorous corvids Western Jackdaw Corvus monedula 1308 529 territorial 234.5 82500 omnivorous corvids Corvus Rook Corvus frugilegus 533 296 territorial 462.5 45000 omnivorous corvids Corvus Carrion Crow Corvus corone 1767 604 territorial 506 160000 omnivorous corvids Corvus Northern Raven Corvus corax 461 255 territorial 1200.5 550 omnivorous corvids Corvus Common Starling Sturnus vulgaris 1909 605 territorial 80.5 660000 8 House Sparrow Passer domesticus 1845 592 territorial 30.35 944000 Eurasian Tree Sparrow Passer montanus 1816 587 territorial 21.7 482000 Common Chaffinch Fringilla coelebs 1969 610 territorial 22.2 1700000 foliage gleaners Brambling Fringilla montifringilla 3 3 territorial 23.25 <10 foliage gleaners European Serin Serinus serinus 18 18 territorial 11.95 <10 passerine seedeaters European Greenfinch Carduelis chloris 1855 597 territorial 25.1 489000 passerine seedeaters Carduelis European Goldfinch Carduelis carduelis 1249 524 territorial 16.75 34600 passerine seedeaters Carduelis Eurasian Siskin Carduelis spinus 314 227 territorial 13 1000 passerine seedeaters Carduelis Common Linnet Carduelis cannabina 1863 611 territorial 18.75 283000 passerine seedeaters Carduelis Common Redpoll Carduelis flammea 831 413 territorial 13.1 15000 passerine seedeaters Carduelis Red Crossbill Loxia curvirostra 424 257 territorial 40.75 2000 Parrot Crossbill Loxia pytyopsittacus 1 1 territorial 51.55 <10 Scarlet Rosefinch Carpodacus erythrinus 98 87 territorial 22.95 225 Eurasian Bullfinch Pyrrhula pyrrhula 1023 463 territorial 31.05 45000 Hawfinch Coccothraustes coccothraustes 577 338 territorial 54.7 13900 passerine seedeaters Yellowhammer Emberiza citrinella 1947 601 territorial 31.65 567000 Reed Bunting Emberiza schoeniclus 1539 588 territorial 18.8 49900 Corn Bunting Miliaria calandra 1200 466 territorial 47.65 31000 1 Table S3. Null models. Classification of row and column constraints and weighting factors used in each of 4 null model algorithms. Constraints are applied to a binary presence-absence matrix in which rows are species, columns are cells, and entr ies are the presence (1) or absence (0) of a particular species in a particular cell. Model Rows Sums (species) Columns Sums (cells) Weighting factor Fixed-fixed Fixed Fixed None Habitat Fixed Allowed to vary Habitat diversity Population Allowed to vary Allowed to vary Habitat diversity and population size Biomass Allowed to vary Allowed to vary Habitat diversity and biomass 1 Table S4. Co-occurrence analyses of congeneric guilds. Entries as in Table S4. ? Entries in italics indicate three models for which it was not possible to generate 1000 randomizations because the constraints were very difficult to achieve, and the simulati on usually aborted after thousands of unsuccessful trials. These p-values we re estimated from the standardized effect size, based on 10 successful replications of each model. Ecological Guild Fixed- Fixed Model 5 ? 5 Fixed- Fixed Model 10 ? 10 Habitat Model 5 ? 5 Habitat Model 10 ? 10 Population Model 5 ? 5 Population Model 10 ? 10 Biomass Model 5 ? 5 Biomass Model 10 ? 10 Anthus (4) 0.326 0.995 < 0.001 < 0.001 0.001 < 0.001 0.001 < 0.001 Acrocephalus (4) 0.578 0.142 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 Sylvia (5) 0.017 0.020 0.605 0.430 0.981 0.942 0.951 0.808 Phylloscopus (4) 0.189 0.712 > 0.999 ? < 0 .00 1 0.779 0.213 0.976 0.283 Parus (6) < 0.001 < 0.001 > 0.999 < 0.001 0.569 < 0.001 0.783 < 0.001 Corvus (4) < 0.001 < 0.001 < 0.001 ? < 0 .00 1 < 0.001 < 0.001 < 0.001 < 0.001 Carduelis (5) < 0.001 0.245 0.164 ? < 0 .00 1 < 0.001 < 0.001 < 0.001 < 0.001 Turdus (5) 0.002 0.191 0.089 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 SEGREG ATED 5 3 3 7 5 6 5 6 RANDOM 3 4 3 1 2 2 1 2 AGGREG A TED 0 1 2 0 1 0 2 0 1 Table S5. Co-occurrence analyses of foraging guilds. Each entry represents the probability value for a one-tailed test of the null hypothesis that species co- occurrence patterns are random. Tan-shaded cells i ndicate statistically significant segregation. Yellow- shaded cells indicate statistically significant aggregation. No shading indicates a non-significant pattern (p > 0.05 for both tails of the distribution. Number of species in each guild is given in parentheses. Foraging Guild Fixed- Fixed Model 5 ? 5 Fixed- Fixed Model 10 ? 10 Habitat Model 5 ? 5 Habitat Model 10 ? 10 Population Model 5 ? 5 Population Model 10 ? 10 Biomass Model 5 ? 5 Biomass Model 10 ? 10 aquatic pursuers (8) 0.042 < 0.001 < 0.001 < 0.001 < 0.001 0.006 < 0.001 < 0.001 wading birds (6) 0.145 0.423 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 grazing waterfowl (5) 0.372 0.567 < 0.001 < 0.001 0.049 0.001 0.049 0.003 dabbling ducks (7) < 0.001 < 0.001 > 0.999 > 0.999 > 0.999 > 0.999 > 0.999 > 0.999 diving ducks (4) < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 diurnal raptors (12) < 0.001 <0.001 > 0.999 < 0.001 0.997 0.164 > 0.999 0.001 gallinaceous birds (4) < 0.001 0.291 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 rails (5) 0.131 < 0.001 0.933 < 0.001 0.788 < 0.001 0.002 < 0.001 plovers (8) < 0.001 < 0.001 > 0.999 < 0.001 > 0.999 0.037 0.960 < 0.001 sandpipers (11) < 0.001 0.013 < 0.001 < 0.001 < 0.001 0.001 0.626 0.261 gulls (7) < 0.001 < 0.001 < 0.001 < 0.001 0.007 < 0.001 0.256 0.991 terns (6) 0.833 0.210 < 0.001 < 0.001 0.002 < 0.001 < 0.001 < 0.001 pigeons (4) 0.031 0.020 0.022 < 0.001 < 0.001 0.002 < 0.001 < 0.001 owls (6) 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 woodpeckers (5) 0.079 0.926 0.761 > 0.999 0.104 0.327 0.001 0.001 aerial insectivores (4) 0.109 0.214 0.976 < 0.001 > 0.999 < 0.001 > 0.999 < 0.001 openland insectivores (9) 0.009 0.780 0.021 < 0.001 0.033 < 0.001 < 0.001 < 0.001 terrestrial & low strata flycatchers (10) < 0.001 < 0.001 0.306 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 thrushes(5) 0.002 0.191 0.089 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 marsh warblers (7) 0.755 0.941 0.953 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 foliage gleaners (12) < 0.001 0.627 > 0.999 0.024 < 0.001 0.975 0.967 0.918 tit-like birds (12) < 0.001 < 0.001 > 0.999 < 0.001 0.569 < 0.001 0.783 < 0.001 corvids (7) < 0.001 0.642 0.740 < 0.001 0.001 < 0.001 0.001 < 0.001 passerine seedeaters (7) < 0.001 0.887 > 0.999 < 0.001 0.259 < 0.001 < 0.001 < 0.001 SEGREG ATED 17 12 11 22 16 20 16 20 RANDOM 7 12 5 0 4 2 3 2 AGGREG A TED 0 0 8 2 4 2 5 2 1 Table S6. Habitat utilization and el ectivity in congeneric guilds. Each row represents a different guild. Entries as in Ta ble S6 except that tan shading indicates significantly lower niche overlap than expected by chance. Congeneric Guild Grain size Utilization Overlap Electivity Overlap Anthus (4) 5 ? 5 0.657 0.711 10 ? 10 0.772 0.724 Acrocephalus (4) 5 ? 5 0.973 0.902 10 ? 10 0.982 0.951 Sylvia (5) 5 ? 5 0.911 0.836 10 ? 10 0.893 0.810 Phylloscopus (7) 5 ? 5 0.743 0.811 10 ? 10 0.830 0.825 Parus (6) 5 ? 5 0.986 0.939 10 ? 10 0.968 0.933 Corvus (4) 5 ? 5 0.994 0.966 10 ? 10 0.976 0.976 Carduelis (5) 5 ? 5 0.992 0.968 10 ? 10 0.990 0.984 Turdus (5) 5 ? 5 0.978 0.880 10 ? 10 0.925 0.926 1 Table S7. Habitat utilization and electivity in foraging guilds. Cell entries represent the average pairwise values of niche overlap for species in ecological guilds (number of species in parentheses). The left-hand column presents habitat utilization overlap values whereas the right-hand column represents electivity overlap valu es, which are scaled to account for the areas of different habitats in Denmark. Yellow shading indi cates statistically significant overlap in habitat utilization or electivity (p < 0.01 for most analyses ). Unshaded entries indicate a pattern that was not statistically significant. None of the foraging guilds ex hibited significant segregation in habitat utilization or electivity. Ecological Guild Grain size Utilization Overlap Electivity Overlap aquatic pursuers (8) 5 ? 5 0.852 0.800 10 ? 10 0.887 0.776 wading birds (6) 5 ? 5 0.860 0.585 10 ? 10 0.797 0.615 grazing waterfowl (5) 5 ? 5 0.882 0.873 10 ? 10 0.852 0.911 dabbling ducks (7) 5 ? 5 0.937 0.903 10 ? 10 0.938 0.905 diving ducks (4) 5 ? 5 0.768 0.618 10 ? 10 0.793 0.797 diurnal raptors (12) 5 ? 5 0.913 0.764 10 ? 10 0.942 0.866 gallinaceous birds (4) 5 ? 5 0.936 0.835 10 ? 10 0.905 0.834 rails (5) 5 ? 5 0.980 0.831 10 ? 10 0.99 0.889 plovers (8) 5 ? 5 0.725 0.725 10 ? 10 0.667 0.658 2 sandpipers ( 11) 5 ? 5 0.897 0.704 10 ? 10 0.857 0.729 gulls (7) 5 ? 5 0.843 0.730 10 ? 10 0.900 0.755 terns (6) 5 ? 5 0.806 0.694 10 ? 10 0.820 0.810 pigeons (4) 5 ? 5 0.978 0.862 10 ? 10 0.927 0.883 owls (6) 5 ? 5 0.936 0.836 10 ? 10 0.916 0.864 woodpeckers (5) 5 ? 5 0.970 0.863 10 ? 10 0.978 0.902 aerial insectivores (4) 5 ? 5 0.997 0.984 10 ? 10 0.986 0.987 openland insectivores (9) 5 ? 5 0.786 0.785 10 ? 10 0.866 0.820 terrestrial & low strata flycatchers (10) 5 ? 5 0.890 0.853 10 ? 10 0.931 0.874 thrushes(5) 5 ? 5 0.978 0.880 10 ? 10 0.925 0.926 marsh warblers (7) 5 ? 5 0.965 0.850 10 ? 10 0.954 0.902 foliage gleaners (12) 5 ? 5 0.884 0.870 10 ? 10 0.907 0.841 tit-like birds (12) 5 ? 5 0.984 0.934 10 ? 10 0.974 0.937 corvids (7) 5 ? 5 0.988 0.954 10 ? 10 0.984 0.960 passerine seedeaters (7) 5 ? 5 0.944 0.931 10 ? 10 0.980 0.958