Modeling the Effects of Climate Change on the Current and Future Potential Distribution of Berberis vulgaris L. with Machine Learning

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dc.authorid0000-0002-0641-4445
dc.contributor.authorSarikaya, Ayse Gul
dc.contributor.authorUzun, Almira
dc.date.accessioned2026-02-08T15:16:02Z
dc.date.available2026-02-08T15:16:02Z
dc.date.issued2024
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractSpecies of the Berberis genus, which are widely distributed naturally throughout the world, are cultivated and used for various purposes such as food, medicinal applications, and manufacturing dyes. Model-based machine learning is a language for specifying models, allowing the definition of a model using concise code, and enabling the automatic creation of software that implements the specified model. Maximum entropy (MaxEnt 3.4.1) is an algorithm used to model the appropriate distribution of species across geographical regions and is based on the species distribution model that is frequently also used in modeling the current and future potential distribution areas of plant species. Therefore, this study was conducted to estimate the current and future potential distribution areas of Berberis vulgaris in T & uuml;rkiye for the periods 2041-2060 and 2081-2100, according to the SSP2 4.5 and SSP5 8.5 scenarios based on the IPSL-CM6A-LR climate change model. For this purpose, the coordinates obtained in the WGS 84 coordinate system were marked using the 5 m high spatial resolution Google Satellite Hybrid base maps, which are readily available in the 3.10.4 QGIS program, the current version of QGIS (Quantum GIS). The CM6A-LR climate model, the latest version of the IPSL climate models, was used to predict the species' future distribution area. The area showed a high correlation with the points representing B. vulgaris, which is generally distributed in the Mediterranean and the central and eastern Black Sea regions of T & uuml;rkiye, and the very suitable areas encompassed 45,413.82 km(2). However, when the SSP2 4.5 scenario was considered for the period 2041-2060, the areas very suitable for Berberis vulgaris comprised 59,120.05 km(2), and in the SSP2 4.5 scenario, very suitable areas were found to encompass 56,730.46 km(2) in the 2081-2100 period. Considering the SSP5 8.5 scenario for the period 2041-2060, the area most suitable for the B. vulgaris species is 66,670.39 km(2). In the SSP5 8.5 scenario, very suitable areas were found to cover 20,108.29 km(2) in the 2081-2100 period. Careful consideration of both the potential positive and negative impacts of climate change is essential, and these should be regarded as opportunities to implement appropriate adaptation strategies. The necessary conditions for the continued existence and sustainability of B. vulgaris-that is, areas with ecological niche potential-have been determined.
dc.identifier.doi10.3390/su16031230
dc.identifier.issn2071-1050
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85184501209
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.3390/su16031230
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6078
dc.identifier.volume16
dc.identifier.wosWOS:001161103600001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofSustainability
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzWOS_KA_20260207
dc.subjectBerberis vulgaris
dc.subjectclimate change
dc.subjectmaxent
dc.subjectmachine learning
dc.subjectsustainability
dc.subjectdistribution
dc.titleModeling the Effects of Climate Change on the Current and Future Potential Distribution of Berberis vulgaris L. with Machine Learning
dc.typeArticle

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