DOI: 10.5061/dryad.bcc2fqzmq
title: Variations of niche breadth, range sizes, and geographic exclusion with bat species richness

description: Aim More species-rich communities are often assumed to contain more
 specialist species with narrower niches and smaller ranges. Stronger
 interspecific competition in species-rich communities is thought to be a
 key mechanism explaining these patterns. Yet, the relationship between
 richness and specialization has so far only been studied for a few taxa,
 and characterizing the effects of interspecific competition on species
 distributions is challenging. Here, we assess broad-scale relationships
 between niche breadth, range sizes, and geographic exclusion along
 richness gradients of bats. Location Eastern Mediterranean, Western Asia,
 and Central Asia. Taxon Bats (Chiroptera) Methods Based on a novel
 integrated species distribution modeling approach that combines occurrence
 information with expert range maps, we assessed how niche breadth and
 range sizes varied with species richness. In addition, by contrasting
 species’ potential and realized distributions in areas where species pairs
 overlap, we derive indicators of geographic exclusion to understand how
 potential interspecific competition is affecting range limits along
 richness gradients. Results and Main conclusions We found a non-linear
 association between niche breadth and richness, with the most specialized
 species occurring in species-poor regions and niche breadth peaking at
 intermediate richness. Despite a positive association of niche breadth and
 range sizes at the species level, range sizes in predicted bat communities
 declined continuously with species richness. In addition, patterns of
 geographic exclusion were linked to patterns of niche breadth, with
 species filling less of their potential range overlaps when overlapping
 species were more specialized. Our findings suggest that small range sizes
 in species-rich bat communities are better explained by the number of
 interacting species than by environmental specialization or stronger
 exclusion between individual species. More broadly, we show how integrated
 distribution modeling approaches can shed new light on the interplay of
 species richness, specialization, and community structure, and caution
 against generalizing relationships between richness and specialization
 across taxa and geographies.
description: # Variations of niche breadth, range sizes, and geographic exclusion with
 bat species richness This repository contains data associated with the
 research article "Variations of niche breadth, range sizes, and
 geographic exclusion with bat species richness". There are three
 datasets available: **A.** Raster data of the modeled distributions for 49
 bat species **B.** Raster data of bat species richness obtained from
 stacking individual bat distribution maps **C.** Tables containing
 species-level estimates of range size and niche breadth as well as
 geographic avoidance and exclusion scores for species-pairs overlapping in
 their potential distributions. The occurrence data and environmental
 predictor data as well as code demonstrating the use of stacked
 generalization for integrating expert range maps into species distribution
 models are available via another Dryad repository for the article
 "The best of two worlds: using stacked generalization for integrating
 expert range maps in species distribution models":
 [https://doi.org/10.5061/dryad.6q573n65m](https://doi.org/10.5061/dryad.6q573n65m) Raster datasets are in Albers equal area projection at 1km resolution. ## Description of the data and file structure ### A. Distribution maps The distribution maps (raster data) contain four different maps per species. 1. Continuous suitability predictions based on expert-informed ensembles (file ending "expert_informed") 2. Binary range maps obtained from thresholding expert-informed ensembles (i.e., estimates of realized ranges; file ending "expert_informed_binary") 3. Continuous suitability predictions based on SDM ensembles not accounting for expert-defined ranges (file ending "sdm_ensemble") 4. Binary range maps obtained from thresholding SDM ensembles (i.e., estimates of potential ranges; file ending "sdm_ensemble_binary") ### B. Richness maps The richness maps (raster data) contain two estimates of bat species richness. 1. Raw estimate based on stacking binary expert-informed predictions ("richness_raw.tif" 2. Estimate correcting for omitting data-deficient species from distribution modeling ("richness_corrected.tif") ### C. Tables There are two tables available: 1. Containing species-level estimates of niche breadth (Levin's B2 metric) and range size (km²) ("niche_breadth_range_size.csv"). In addition, a column giving the average species richness within each species' distribution is provided. 2. Containing geographic avoidance and exclusion scores for all species pairs with overlapping potential ranges ("avoidance_exclusion.csv"). For information on the calculation of these scores please refer to the manuscript.