The Relationship Between Certain Oak Species and Ecological Factors: An Analysis of Indicator Plant Species in Bozdağlar

This study aims to examine the relationships between Quercus cerris L. var. cerris, Quercus coccifera L., and Quercus infectoria Oliv. subsp. boissieri (Reut.) O.Schwarz and ecological variables using indicator species analysis and logistic regression methods. The modeling results demonstrated significant and high-accuracy performance for each species. For Q. cerris, the model yielded an AUC value of 0.774 for the training dataset and 0.761 for the test dataset, indicating "good" performance. The species' distribution was influenced by the variables BIO7, BIO3, BIO1, RUGI, and BIO12. For Q. coccifera, the model showed an AUC value of 0.892 for the training dataset and 0.887 for the test dataset, reflecting "very good" performance. The distribution of this species was primarily determined by BIO12 and BIO1. The model for Q. infectoria achieved an AUC value of 0.766 for the training dataset and 0.736 for the test dataset, indicating "good" performance, with BIO12 and BIO3 identified as the key variables affecting its distribution. Indicator species analysis was conducted using PC-ORD software to identify indicator species. The analysis revealed 11 positive and 31 negative indicator plant species for Q. cerris. For Q. coccifera, 8 positive and 1 negative indicator plant species were identified. Similarly, Q. infectoria was associated with 22 positive and 1 negative indicator plant species. This study provides a crucial foundation for understanding the distribution of oak species by integrating climate scenarios into modeling approaches, facilitating the prediction of climate change impacts and the development of strategies to mitigate these effects. The findings are expected to offer valuable insights into the ecological functionality and sensitivity of target species to environmental changes, serving as a reference for similar studies in various geographic regions. Additionally, this research establishes a significant scientific basis for sustainable forest management planning and biodiversity conservation, particularly within the Mediterranean Basin.