نوع مقاله : علمی - پژوهشی
نویسندگان
1 دانشجوی دکتری علوم زیستی جنگل، گروه علوم و مهندسی جنگل، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس، نور، ایران
2 استاد، گروه علوم و مهندسی جنگل، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس، نور، ایران
3 دانشیار، گروه علوم و مهندسی جنگل، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس، نور، ایران
4 دکتری علوم مرتع، گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان، اصفهان، ایران و مدرس گروه علوم کشاورزی، دانشگاه فنی و حرفهای، تهران، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Background and Objective: Beech forests, spanning from Europe’s largest woodlands to the mountainous regions of southern Europe and the Caspian Sea coasts, provide a crucial habitat for the Oriental beech (Fagus orientalis Lipsky), the dominant species in these ecosystems. These forests play a vital role in carbon sequestration and climate change mitigation. Predicting the impacts of climate change on ecosystems and species is a fundamental objective of ecological research. Understanding how climate influences plant distribution is essential for sustainable forest management. Species Distribution Models (SDMs) are powerful tools for identifying suitable habitats and informing conservation strategies in response to climate change.
Material and Methods: This study assessed the distribution of Oriental beech in the Hyrcanian forests under present and future climate conditions using multiple modeling algorithms, including Artificial Neural Networks, Generalized Linear Models, Multivariate Adaptive Regression Splines, Maximum Entropy, and Random Forest. A Digital Elevation Model (DEM) was used to generate slope, aspect, and elevation layers, while 19 bioclimatic variables with a spatial resolution of one kilometer were obtained from the CHELSA database. A total of 1,068 occurrence points, each spaced at least one kilometer apart, were used as the dependent variable. Eight physiographic and bioclimatic variables, selected through Pearson correlation analysis (|r| < 0.8), served as independent variables. Models were trained on 75% of the data and evaluated with the remaining 25% using performance metrics such as the Area Under the ROC Curve (AUC), sensitivity, specificity, and the True Skill Statistic (TSS).
Results: All individual models successfully identified the distribution range of Oriental beech, with the ensemble model and Random Forest performing the best. The ensemble approach reduced prediction uncertainty. Variable importance analysis revealed that elevation, seasonal temperature variation, and slope were the most influential factors, with elevation alone explaining approximately 40% of the variation. In contrast, isothermality had the least impact. The species was primarily distributed from Astara to Gorgan, with a higher probability of occurrence in Gilan and Mazandaran provinces compared to Golestan. According to the ensemble model, 31.05% of the study area (6,030.6 km²) was classified as suitable habitat, though this is projected to decline under future climate scenarios. Response curves indicated that optimal conditions included elevations of 1,300–2,000 meters and slopes of approximately 30%. Under the SSP5-8.5 scenario, habitat loss was more pronounced than under SSP1-2.6, with greater reductions projected for 2071–2100 compared to 2041–2070. Based on the GFDL-ESM4 model, Oriental beech distribution is expected to decline by 7.65% under the optimistic scenario (2041–2070) and by 34.8% under the pessimistic scenario (2071–2100).
Conclusion: The ensemble model provided a more precise prediction of species distribution by integrating common patterns across multiple models. Given the high accuracy of the models used, these approaches offer valuable insights into the potential effects of climate change on the distribution of Oriental beech in the Hyrcanian forests. The findings provide a scientific foundation for developing conservation strategies, implementing sustainable management practices, and guiding habitat restoration efforts.
کلیدواژهها [English]