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

• Published in: Journal of vegetation science 2024-05, Vol.35 (3), p.n/a
• Main Authors: Flores‐Tolentino, Mayra, Villaseñor, José Luis, Ibarra‐Manríquez, Guillermo, Rodríguez, Rolando Ramírez, Morales‐Linares, Jonas, Dorado, Óscar
• Format: Article
• Language: English
• Subjects: Algorithms; Biogeography; Cluster analysis; Clustering; Distribution patterns; Dry forests; Ecological niches; Endemic species; endemism; Environmental conditions; environmental turnover; Flowering; Flowering plants; Geographical distribution; Maxent; Multidimensional scaling; Niches; Ordination; Plant species; Population distribution; Spatial analysis; species distribution; Species richness; Tropical forests; turnover species
• ISSN: 1100-9233; 1654-1103
• DOI: 10.1111/jvs.13261

Aim Biogeographic 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. Location Balsas Depression Floristic Province, Mexico. Methods Based 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. Results The 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 Conclusions The 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. The sum of 134 ecological niche models of endemic and/or characteristic species of the Balsas Depression represents the potential distribution of the plant diversity of the seasonally dry tropical forest.