Urmia University Forest Research and Development 2476-3551 11 3 2025 11 22 Predicting Potential Distribution of Quercus infectoria Oliv. in Zagros Forests Under Climate Change Scenarios Predicting Potential Distribution of Quercus infectoria Oliv. in Zagros Forests Under Climate Change Scenarios 421 444 121849 10.30466/jfrd.2025.56374.1765 FA Alireza Dosti Ph.D. student of forest sciences, Faculty of Agriculture, Ilam University, Ilam, I.R. Iran Mehdi Heydari Professor, Department of Forest science, Faculty of Agriculture, Ilam University, Ilam, I. R. Iran 0000-0001-6395-8871 Seyed Jalil Alavi Associate Professor, Department of Forest Sciences and Engineering, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, I. R. Iran 0000-0001-7490-406X Reza Omidipour Assistant Professor, Department of Range and Watershed Management, Faculty of Agriculture, Ilam University, Ilam, I. R. Iran Hooman Latifi Associate professor, Department of Photogrammetry and Remote Sensing, School of Surveying and Geospatial Engineering, Khajeh Nasir Toosi University of Technology, Tehran, I. R. Iran Journal Article 2025 07 18 Background and Objective: The Zagros forests, as one of Iran's most vital ecosystems, play an unparalleled role in maintaining biodiversity and environmental sustainability. However, these forests, predominantly composed of oak species, have in recent decades been affected by climate change, recurrent droughts, and destructive human activities, leading to the phenomenon known as "oak decline." Among these species, Aleppo oak (Quercus infectoria Oliv.) holds special ecological and economic value, particularly for the production of “Mazo” used in pharmaceutical and cosmetic industries. The future of this key species is increasingly threatened by climate change and land-use change. Given the lack of comprehensive studies predicting its distribution using modern algorithms, this study was designed with two main objectives: (1) to predict potential distribution changes of Aleppo oak under climate scenarios for 2050 and 2070 using MaxEnt and Random Forest (RF) models, and (2) to compare model performances and identify key environmental variables to provide a scientific basis for conservation strategies. Material and Methods: The study area comprised the Northern Zagros ecoregion, spanning parts of Iran, Iraq, and Turkey. For modeling, 246 species presence points (collected from field surveys and databases) and 29 environmental variables (including climatic, topographic, edaphic, and land cover factors) were used. Presence points were thinned to a minimum distance of one kilometer, and 1,000 pseudo-absence points were generated. Future climate data were obtained from the MIROC6 General Circulation Model (GCM) for two time horizons, 2050 and 2070, under two scenarios: SSP2-4.5 (medium) and SSP5-8.5 (pessimistic). After removing highly collinear variables (VIF>10) using the Variance Inflation Factor test, 17 variables were selected for final modeling. Models were implemented using MaxEnt and RF algorithms in the R environment with the biomod2 package. Model stability was evaluated via 10-fold cross-validation, dividing data into 80% for training and 20% for testing. Model performance was assessed using ROC, TSS, and Kappa statistics. Results: Evaluation results showed that both algorithms exhibited very high accuracy. The RF model achieved near-perfect performance with a mean ROC of 0.965 and TSS of 0.860, while the MaxEnt model also performed excellently with a mean ROC of 0.885 and TSS of 0.718. Variable importance analysis indicated that, for MaxEnt, precipitation seasonality (Bio15) and annual precipitation (Bio12) were the most influential variables. In the RF model, importance was more balanced, with annual precipitation (Bio12), soil organic carbon, and precipitation seasonality (Bio15) being the top factors. Future predictions revealed alarming outcomes. Under the pessimistic SSP5-8.5 scenario by 2070, the RF model projected an 88.4% reduction in suitable habitat, while MaxEnt predicted a 73.0% decline. Newly emerging suitable habitats were minimal compared to the area lost. Spatial analysis indicated that remaining habitats would be limited to small, isolated patches at higher elevations. The species’ optimal elevational range is expected to shift from the current 1,100–1,800 m to 1,500–2,500 m in the future, indicating a forced upward migration of 400–700 meters. Conclusion: The findings indicate that Aleppo oak faces a serious threat from climate change. Severe habitat loss and forced upward migration, coupled with stands fragmentation, place the long-term survival of the species at serious risk. These results emphasize the urgent need for integrated management and conservation strategies. Key recommendations include: (1) protecting climate refugia by identifying and safeguarding high-elevation areas that remain suitable in the future; (2) Adaptive restoration through afforestation programs in high-elevation areas predicted to be suitable habitats in the future; (3) reducing human pressures such as overgrazing to enhance ecosystem resilience; and (4) establishing a gene bank to preserve genetic resources of at-risk populations. This study provides a scientific foundation for effective conservation planning and sustainable management of the Zagros forest ecosystems. Background and Objective: The Zagros forests, as one of Iran's most vital ecosystems, play an unparalleled role in maintaining biodiversity and environmental sustainability. However, these forests, predominantly composed of oak species, have in recent decades been affected by climate change, recurrent droughts, and destructive human activities, leading to the phenomenon known as "oak decline." Among these species, Aleppo oak (Quercus infectoria Oliv.) holds special ecological and economic value, particularly for the production of “Mazo” used in pharmaceutical and cosmetic industries. The future of this key species is increasingly threatened by climate change and land-use change. Given the lack of comprehensive studies predicting its distribution using modern algorithms, this study was designed with two main objectives: (1) to predict potential distribution changes of Aleppo oak under climate scenarios for 2050 and 2070 using MaxEnt and Random Forest (RF) models, and (2) to compare model performances and identify key environmental variables to provide a scientific basis for conservation strategies. Material and Methods: The study area comprised the Northern Zagros ecoregion, spanning parts of Iran, Iraq, and Turkey. For modeling, 246 species presence points (collected from field surveys and databases) and 29 environmental variables (including climatic, topographic, edaphic, and land cover factors) were used. Presence points were thinned to a minimum distance of one kilometer, and 1,000 pseudo-absence points were generated. Future climate data were obtained from the MIROC6 General Circulation Model (GCM) for two time horizons, 2050 and 2070, under two scenarios: SSP2-4.5 (medium) and SSP5-8.5 (pessimistic). After removing highly collinear variables (VIF>10) using the Variance Inflation Factor test, 17 variables were selected for final modeling. Models were implemented using MaxEnt and RF algorithms in the R environment with the biomod2 package. Model stability was evaluated via 10-fold cross-validation, dividing data into 80% for training and 20% for testing. Model performance was assessed using ROC, TSS, and Kappa statistics. Results: Evaluation results showed that both algorithms exhibited very high accuracy. The RF model achieved near-perfect performance with a mean ROC of 0.965 and TSS of 0.860, while the MaxEnt model also performed excellently with a mean ROC of 0.885 and TSS of 0.718. Variable importance analysis indicated that, for MaxEnt, precipitation seasonality (Bio15) and annual precipitation (Bio12) were the most influential variables. In the RF model, importance was more balanced, with annual precipitation (Bio12), soil organic carbon, and precipitation seasonality (Bio15) being the top factors. Future predictions revealed alarming outcomes. Under the pessimistic SSP5-8.5 scenario by 2070, the RF model projected an 88.4% reduction in suitable habitat, while MaxEnt predicted a 73.0% decline. Newly emerging suitable habitats were minimal compared to the area lost. Spatial analysis indicated that remaining habitats would be limited to small, isolated patches at higher elevations. The species’ optimal elevational range is expected to shift from the current 1,100–1,800 m to 1,500–2,500 m in the future, indicating a forced upward migration of 400–700 meters. Conclusion: The findings indicate that Aleppo oak faces a serious threat from climate change. Severe habitat loss and forced upward migration, coupled with stands fragmentation, place the long-term survival of the species at serious risk. These results emphasize the urgent need for integrated management and conservation strategies. Key recommendations include: (1) protecting climate refugia by identifying and safeguarding high-elevation areas that remain suitable in the future; (2) Adaptive restoration through afforestation programs in high-elevation areas predicted to be suitable habitats in the future; (3) reducing human pressures such as overgrazing to enhance ecosystem resilience; and (4) establishing a gene bank to preserve genetic resources of at-risk populations. This study provides a scientific foundation for effective conservation planning and sustainable management of the Zagros forest ecosystems.

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