A zoogeographic model for the evolution of diversity and endemism in Madagascar

The delineation of zoogeographic regions is essential for understanding the evolution of biodiversity. Madagascar, characterized by high levels of endemism and habitat diversity, presents unique challenges and opportunities for such studies. Traditional global zoogeographic classifications, largely based on vertebrates, may overlook finer-scale patterns of diversity. This study employs comprehensive ant distribution datasets and phylogenomic data to propose a refined zoogeographic model for Madagascar. Utilizing Phylogenetic Simpson’s Turnover, we identified three primary regions—Eastern, Northern, and Western—each characterized by distinct environmental and phylogenetic profiles. Further subdivision revealed nine subregions, reflecting variations in elevation, net primary productivity, and terrain ruggedness. Our findings highlight the importance of topographical and environmental barriers in shaping phylogenetic diversity and endemism. Notably, we observed significant phylogenetic clustering in lowland areas and distinct differences in net primary productivity and elevation across regions. This study underscores the value of integrating phylogenetic data in zoogeographic analyses and provides a nuanced framework for investigating biodiversity patterns in Madagascar, offering insights into the processes driving speciation and endemism on the island.

Methods
We developed a species distribution database for Madagascar’s ants using data from AntWeb. We removed non-endemic species, unassigned morphospecies, and duplicated records for spatial consistency. Geographic ranges were estimated using ecological niche modeling (ENM) with environmental data from MadaClim. To address sampling bias, we created a sampling density map from 33,295 collection events and used Maxent for model estimation. The final database included distribution estimates for 779 taxa, covering 91.7% of Madagascar’s valid species, based on over 120 million locality records. For phylogenomic data, we sequenced DNA from 1,183 ant specimens, combining target enrichment of ultraconserved elements (UCEs) with next-generation sequencing. We inferred phylogenetic relationships for eight ant clades and created a backbone phylogeny using IQ-TREE and ModelFinder, generating ultrametric trees with the R package APE. Spatial analyses of phylogenetic diversity and endemism were conducted using 10×10 km grid cells, calculating various indices such as species richness, weighted endemism, phylogenetic diversity, and endemism. We identified zoogeographic regions through cluster analysis and correlated diversity metrics with environmental variables, performing statistical comparisons to elucidate regional differences.