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In recent years many bee species have expanded/contracted their ranges in response to natural or human-induced changes in habitats. Therefore, identifying suitable habitats and evaluating connectivity between them is crucial for the conservation of species. Species distribution models (SDMs) and connectivity algorithms are the main tools currently available to provide knowledge of species potential to shift/expand their ranges. We aimed to identify the core habitats of  Apis florea  and evaluate connectivity between populations. We carried out a multi-level modeling framework to predict an ensemble model of habitat suitability of the species in three critical months (May, October, and January) based on (1) only the climatic variables; (2) both climatic and environmental data. Then, we used the concept of circuit theory to evaluate potential linkages between core habitats. Spatial patterns of suitable habitats and connectivity between them varied across months. Potential habitats of the species appeared to be strongly influenced by the normalized difference vegetation index (NDVI), croplands, village density, and water vapor pressure. Most of the predicted core habitats and connectivity were found in the western half of the species range in May due to the abundance of nectar and pollen in habitats. Contrary to the western parts, core habitats in eastern regions appeared to be fragmented with limited connectivity. Our results provided the first map of connectivity for  A. florea  that could improve the understanding of the distribution of red dwarf honey bees and contribute to conservation strategies to protect core areas for this keystone pollinator species.

Assessment of connectivity between core habitats of the red dwarf honey bees in Iran based on climate and environmental niche modeling