The use of ecological niche models improves biogeographic regionalization of the Balsas Depression, Mexico

Abstract

AbstractAimBiogeographic regionalization classifies zones in terms of their biotas and contributes to understanding the ecological and historical factors that affect the distribution of species. We use Ecological Niche Modeling (ENM) to complement missing information on species distribution and thus improve the accuracy of biogeographic boundaries.LocationBalsas Depression Floristic Province, Mexico.MethodsBased on parameters documented in herbarium collections and environmental variables, ENM was carried out to determine the most suitable environmental conditions for a species to thrive (i.e., the species' ecological niche). The ENM and spatial analysis were used to obtain the biogeographic regionalization of the seasonally dry tropical forest (SDTF) in the Balsas Depression (BD), Mexico, through spatial analysis. Using the Maxent algorithm, we constructed ecological niche models (ENMs) of 134 flowering plant species distributed preferentially in the SDTF (characteristic species), most of them endemic to the BD. Subsequently, we obtained an incidence matrix based on the information from the 134 ENMs, which was used to analyze the turnover of species in Biodiverse software. The turnover matrix was used for Non‐metric Multidimensional Scaling (NMDS) ordination and clustering analyses. Finally, the environmental predictors most related to species turnover were identified using the relative environmental turnover method.ResultsThe clustering analysis divided the SDTF in the BD into four floristic districts — two located in its western part and two in the eastern region. The NMDS differentiated, in the first component, two districts in the western region and one in the eastern. Seven environmental variables contributed significantly to explaining the turnover of species in these districts; the most significant were the elevation, pH, and precipitation of the coldest quarter.Main ConclusionsThe use of ENM for the regionalization of areas with high species richness allows for a more detailed classification of subregions and the distribution patterns of the species that define their limits. This provides a more solid theoretical basis for the investigation of biogeographic patterns.