Introduction: Climate change plays a key role in shaping and changing the distribution patterns of plant species by reducing or expanding their geographical ranges. In particular, endemic species, with their localized populations and low dispersal rates, show higher vulnerability to environmental changes, and as a consequence, the potential distribution of these taxa is a critical step in conservation planning. In this regard, species distribution modelling (SDM) has become a key method in ecology and conservation biogeography to predict the distribution of a species across geographic space and time using environmental data. Here, the objective of our study was to predict the current and future spatial distributions of Colutea persica, which is an endemic species in the flora of Iran.

Methods: In this study, we developed a maximum entropy model (MaxEnt) to predict the present and future distributions of Colutea persica under two representative concentration pathways (RCP 4.5 and RCP 8.5) for the 2050s and 2070s.

Results: The findings of our study showed that solar radiation, sand and silt content, and precipitation of the wettest month (BIO13) are important environmental variables influencing the potential distributions of this species. Moreover, our results confirmed that the performance of the prediction model with an AUC of at least 0.9 was excellent. The projected climate maps under optimistic and pessimistic scenarios (RCP2.6 and RCP8.5, respectively) of 2050 and 2070 resulted in negative range changes for this species in comparison to its current predicted distributions.

Conclusions: Our results highlight the need for designing and applying conservation planning, cultivation, and rehabilitation strategies for this target species.