DOI: 10.5061/dryad.r4xgxd2cj
title: Data from: Multiple dimensions of bird beta diversity support that mountains are higher in the tropics

description: Aim We examine latitudinal effects of breeding bird taxonomic,
 phylogenetic and functional β-diversity (Tβ, Pβ and Fβ, respectively)
 along elevational gradients to test predictions derived from Janzen’s
 (1967) classic ideas that tropical mountains represent stronger dispersal
 barriers than temperate mountains. Location Global Taxon Birds Methods
 Using a global dataset from 46 mountains, we examine latitudinal patterns
 of Tβ, Pβ, and Fβ, and their components: β rich and β repl. For each
 mountain and each dimension of diversity we calculated (a) total
 β-diversity, (b) the steepness of distance decay patterns, and (c)
 within-mountain variability in pairwise β-diversity and regressed each one
 of these response variables against absolute latitude. We predicted that
 tropical montane biotas would have (1) overall higher Tβ, Pβ, and Fβ, (2)
 faster distance decay patterns and (3) higher within-mountain variability
 in pairwise β-diversity. Furthermore, we expected the richness component β
 rich to be more important in temperate mountains, and the replacement
 component β repl in tropical mountains. Results Latitude had a negative
 effect on total β-diversity for all dimensions of diversity. Similarly,
 metrics of Tβ and Pβ mostly agree with our expectations, whereas Fβ showed
 contrasting results with steeper distance decay curves and higher
 within-mountain variability in temperate mountains. Overall, β rich was a
 more important component at high elevations in the tropics and across
 elevations in temperate mountains, and β repl more important in tropical
 low and mid-elevations. Main Conclusions Our findings are consistent with
 tropical mountain assemblages containing species with narrow elevational
 distributions, low dispersal ability and potentially high allopatric
 speciation, resulting in high β-diversity across elevations. Contrasting
 results for Fβ indicate high niche packing in tropical assemblages, with
 most changes in functional diversity among assemblages involving species
 redundant in trait space. --
description: Elevational data for bird assemblages were extracted from
 published articles; for details see Montaño-Centellas et al. (2019) [See
 Appendix A, in main text]. We assumed that a species was present between
 its highest and lowest reported elevation (range interpolation) and used
 that range for each species in the analyses. Each gradient was then
 partitioned into 200 m wide elevational bands and all species occurring in
 each band were considered as an assemblage.
 Phylogenetic information was extracted from an updated version of
 the avian phylogeny (Jetz, Thomas, Joy, Hartmann, & Mooers, 2012),
 based on the backbone tree by Hackett et al. (2008). Functional traits
 were compiled from Wilman et al. (2014). We used three subsets of traits.
 Two subsets describe specific ecological strategies thought to be
 important in mediating biotic interactions: diet and foraging strata
 (Marra & Remsen, 1997; Naoki & Stouffer, 2007), and one,
 body mass, considered to be a surrogate of environmental tolerance and
 caloric requirements. We calculated overall values of
 Tβ, Pβ and Fβ in each mountain using the framework proposed by Chao et al.
 (2014) and extended by Chiu & Chao (2014) and Chiu et al. (2014)
 to calculate Tβ, Pβ and Fβ. This framework takes advantage of the
 relationship between local diversity (alpha diversity, α), diversity
 turnover among localities (beta diversity, β) and regional diversity
 (gamma diversity, γ), and results in one single value of β-diversity per
 mountain (as opposed to a set of pairwise values across elevations) (Hill,
 1973; Jost, 2007). Then, we calculated the relationship
 between assemblage dissimilarity (Tβ, Pβ and Fβ) and elevational distance
 between two elevational bands (i.e. distance decay patterns). for this
 we calculated pairwise Tβ, Fβ and Pβ among all pairs of assemblages with
 Sorensen-family indices using the frameworks proposed by Podani and
 Schmera (2011) and Carvalho et al. (2012) and fitted fitted power-law
 models with dissimilarity (pairwise β-diversity) as response variable and
 elevational distance between two elevations as predictor, for each
 mountain separately. Distance decay models were calculated with function
 decay.model in package ‘betapart’ (Baselga, Orme, Villeger, De Bortoli,
 & Leprieur, 2018). In these models, higher slopes represent curves
 with faster rates of change in diversity. We extracted the slope, its
 significance and overall model fit (pseudo r<sup>2</sup>) for
 each distance decay model fitted.  Finally, we
 calculated the variability of pairwise Tβ, Pβ and Fβ within each mountain.
 To do this, we used our calculated pair-wise Tβ<sub>sor</sub>,
 Pβ<sub>sor</sub> and FB<sub>sor</sub> matrices and
 extracted only pair-wise distances between consecutive elevational bands
 to represent change in diversity for a 200 m increase in elevation. For
 each mountain, we summarized overall variability in every 200 m increase
 in elevation as the SD of Tβ, Pβ and Fβ values.