Variations of niche breadth, range sizes, and geographic exclusion with bat species richness
Data files
Jan 13, 2026 version files 2.94 GB
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distribution_maps.zip
2.93 GB
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README.md
2.67 KB
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richness_maps.zip
12.14 MB
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tables.zip
28.97 KB
Abstract
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.
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
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.
- Continuous suitability predictions based on expert-informed ensembles (file ending "expert_informed")
- Binary range maps obtained from thresholding expert-informed ensembles (i.e., estimates of realized ranges; file ending "expert_informed_binary")
- Continuous suitability predictions based on SDM ensembles not accounting for expert-defined ranges (file ending "sdm_ensemble")
- 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.
- Raw estimate based on stacking binary expert-informed predictions ("richness_raw.tif"
- Estimate correcting for omitting data-deficient species from distribution modeling ("richness_corrected.tif")
C. Tables
There are two tables available:
- 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.
- 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.
