Abstracts

This study demonstrates the application of the Random Forest algorithm in biodiversity analysis, focusing on the prediction of endangerment status for three migratory bird species in central Serbia: the turtle dove (Streptopelia turtur), the partridge (Perdix perdix), and the quail (Coturnix coturnix). By integrating biological, climatic, spatial, and anthropogenic data, the model achieved high predictive accuracy and identified habitat fragmentation and urbanization as the most critical risk factors. The results highlight the practical value of machine learning methods in supporting conservation strategies and decision-making processes for endangered species.

Keywords

Biodiversity conservation, Migratory birds, Random Forest algorithm, Habitat fragmentation, Urbanization impact, Climate change, Species risk prediction

References

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