Species Distribution Models in plant conservation science: a comprehensive review with a focus on Iran

Abstract

This review article thoroughly examines the role of Species Distribution Models (SDMs) in plant conservation science, with a specific focus on applications within Iran. Commencing with an extensive methodological approach, involving an exhaustive search across reputable academic databases such as Scopus, Web of Science, and Google Scholar, the review synthesizes a comprehensive set of studies. It offers deep insights into SDM principles, challenges, and transformative applications. Addressing these challenges, the review explores contemporary data collection methods, including the use of remote sensing, drones, and citizen science, which enhance the precision and scope of SDMs. A detailed examination of various modelling algorithms and approaches, including MaxEnt, Random Forest, Bayesian models, and others, highlights their specific applications and contributions to plant conservation. The review also integrates climate change data and various scenarios into SDMs, showcasing case studies that illustrate SDMs' potential to predict shifts in plant distributions in response to changing climate conditions and overexploitation. Emphasizing the importance of spatial scale, the review discusses its critical impact on the accuracy of modelling and conservation planning. The article concludes by underlining the indispensable role of SDMs in advancing plant conservation efforts, offering tailored recommendations for researchers, policymakers, and conservation practitioners.

Keywords

• Climate change impacts
• modeling algorithms
• overexploitation
• plant conservation
• spatial scale
• species distribution modeling