DOI: 10.5061/dryad.zgmsbccrd
title: Geographic range shapes influence species richness in global hotspots

description: The extraordinary richness of species in tropical mountain regions is
 often attributed to aggregations of small-ranged species, allowing tight
 spatial packing of their ranges. However, the ranges of species in these
 regions are also distinctly more patchy and elongated than those found in
 adjacent lowlands. Our global analysis of mainland birds demonstrates that
 these range shapes augment spatial variation in species richness. Both the
 linearity and patchiness of species ranges are most pronounced in
 aseasonal and topographically complex regions, most notably in the
 tropical Andes, where these range shapes contribute more to the pattern of
 species richness than broad-scale variations in range size. Consequently,
 niche-based processes that govern the spatial configuration of habitats
 contribute to patterns of species richness in global hotspots over and
 above the processes that affect species richness through range sizes.
description: # Geographic range shapes influence species richness in global hotspots
 Dryad DOI: https://doi.org/10.5061/dryad.zgmsbccrd The file
 AvianRangeShapes.jl.zip contains supplementary data and code used for the
 biogeographical simulation models that simulate species ranges with
 different assumptions about range linearity and patchiness. The files are
 copied from the GitHub repository, July 3, 2025:
 [https://github.com/JesSonne/AvianRangeShapes.jl](https://github.com/JesSonne/AvianRangeShapes.jl) ## Package files Project.toml: Defines the package’s metadata (name, version, dependencies). Required for managing the package with Julia's package manager. Manifest.toml: Captures the exact versions of all dependencies used. LICENSE: Specifies the license under which the package is distributed. ## script/null models.jl file Contains the Julia script for running each of the biogeographical simulations. ## data folder Data files used in the biogeographical simulations. clim1.tif, clim4.tif, clim12.tif, clim15.tif: Rasters of bioclimatic variables used for determining the climate volume occupied by a focal species sf1_mainland.tif: Raster file of global mainland regions used as dispersal domain in the study top_q_proj.tif: Topographical raster used for constraining the geographical domain according to the elevational range limits of a focal species bird ranges.jld2: Julia file containing the geographical distribution of example species elevational range limits.jld2: Julia file containing the elevational range limits of the example species standardized_range_sizes.jld2: Julia file containing the standardized range sizes of the example species ## src folder AvianRangeShapes.jl: Contains the source code, but see functions.jl for the main functionality functions.jl: contains the code (written in Julia) used for running the simulations. ## misc/output folder Contains raster maps of empirical (empirical_richness) and simulated species richness (null_rich), respectively, at 0.25 (025deg) and 1.0 degree (1deg) spatial resolution. The null models have different assumptions about the linearity and patchiness of a species' distribution. Null Model 1 (nm1) has the fewest constraints, as the species can disperse anywhere on a geographic domain from a specified starting position. This null model tends to generate compact range shapes that are restricted only by the boundaries of the continental coastlines. In contrast, Null Model 2 (nm2) allows species to disperse only within their minimum and maximum elevational range limits. This constraint generates range shapes that are bound to the spatial configuration of the topographic landscape and the contemporary climate conditions in which the species is found. The resulting ranges become geographically structured (usually linear, in mountain cordilleras), following the elevational zones of habitats. Null Models 3 (nm3) and 4 (nm4) are similar to 1 and 2 but relax the assumption of range coherency, allowing multiple starting positions, one for each individual empirical range patch. We reran each null model with range sizes within the mainland realms of the world standardised to match the global range size frequency distribution (RsStd). ### Example: "null_rich_nm4_RsStd_1deg.tif" contains a raster map of the simulated species richness by null model 4 using standardized range size frequency distributions at a 1-degree spatial resolution. "null_rich_nm2_025deg.tif" contains a raster map of the simulated species richness by null model 2 using empirical range size frequency distributions at a 0.25 degrees spatial resolution.