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چکیده
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The Zagros forest ecosystem, the largest forested region in Iran, is dominated by Quercus species and characterized by a semi-arid Mediterranean climate. Over the past two decades, increasing temperatures and evapotranspiration have imposed significant stress on even the drought-tolerant Quercus species. In this study, we investigated the climate-growth relationships of Quercus brantii Lindl., a dominant tree species in the western Iranian forest ecosystem. We collected 29 cross-sections from Q. brantii at the Melehpanjab and Pashmin sites for dendrochronological analysis. Generalized additive models (GAMs) were employed to identify nonlinear relationships and radial growth responses to monthly climatic variables, including precipitation and temperature, over the past 18 years (2005-2022). The model explained 66.7% of the variation in ring width. Our findings highlight the sensitivity of Q. brantii to climatic variability, with key drivers of growth being precipitation from October to May (PrcOct_May), precipitation from October to March (PrcOct_Mar), temperature from October to December (TempOct_Dec), and potential evapotranspiration (PET) during spring and summer. Radial growth increased following moist periods (e.g., 2005–2007) but declined during dry periods (e.g., 2007–2010). Q. brantii exhibited a positive response to water availability prior to the growing season, and interactions between precipitation and calendar year were significant during moist periods. However, radial growth showed a negative response to elevated temperatures (particularly above 22.5°C from October to September) and limited summer precipitation, which acted as a critical growth constraint. Tree growth was enhanced by PET during spring (April and May), while low soil moisture in June (linear trend) and July (nonlinear trend) restricted growth. In conclusion, moisture availability emerged as the most critical factor influencing the growth of Zagros oak forests, where precipitation is a primary limiting factor. Additionally, the application of GAMs provides valuable insights into estimating optimal precipitation and temperature conditions for Quercus brantii in this region.
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