Document Type : Research Article
Authors
Ilam University
Abstract
Forests are recognized as one of the most vital components of terrestrial ecosystems, playing a multifaceted role in maintaining environmental equilibrium, supporting biodiversity, regulating climate, conserving water resources, and providing a wide range of essential ecosystem services. The long-term sustainability and productivity of forest ecosystems are closely linked to the quality of the soil and the inherent biological potential of the site in which the forest stands. These two critical factors—soil quality and site potential—are, in turn, profoundly shaped and affected by various environmental parameters, including geomorphological characteristics such as topography and elevation, the density and structure of vegetation or canopy cover, as well as anthropogenic influences stemming from land use changes, deforestation, and other human activities. In light of these considerations, the primary objective of this research was to conduct a detailed, quantitative evaluation of soil quality and site potential indices within the semi-arid Zagros forest regions. The study specifically focused on analyzing the impacts of key variables such as elevation gradients, slope orientation (aspect), and the density of canopy cover. In addition to the empirical assessment of these factors, the research employed advanced spatial analysis techniques and geostatistical tools to develop a reliable spatial prediction model. This model aims to enhance our understanding of spatial variability in forest conditions and provide a scientific basis for implementing more informed, effective, and sustainable forest management and restoration strategies tailored to the unique ecological context of the Zagros Mountains.
Materials and Methods: The study was conducted in the Zagros forests (Shalam Mountain, east of Ilam) within an elevation range of 1500 to 2150 meters. Sixty forest stands were selected across three elevation classes (lower, middle, and upper), two slope aspects (north-facing and south-facing), and two canopy cover classes (less than and more than 25%). Soil samples were collected from a depth of 0–15 cm in each stand, mixed, and their physical and chemical properties were analyzed in the laboratory. The Soil Quality Index (SQI) was calculated using the SQI-2 standard model based on normalization and weighting of selected soil properties. Site quality was estimated using a logarithmic model of tree height to log tree age ratio for Persian oak (the dominant species). For spatial structure analysis, variograms were fitted using spherical, exponential, Gaussian, and linear models, and the best model was identified for each index. Interpolation and spatial mapping were performed using ordinary kriging, simple kriging, universal kriging, co-kriging, and inverse distance weighting (IDW). The accuracy of these methods was evaluated using the mean standardized root mean square error, and the most accurate method for each index was determined.
Results: The findings showed significant differences in soil quality between north- and south-facing slopes across all elevation classes. The highest soil quality (0.84 ± 0.01) was found in densely canopied, north-facing mid-elevation stands, while the lowest (0.60 ± 0.03) was in open-canopy, south-facing upper elevation stands. Site quality also decreased with increasing elevation. Its highest value (25.26 ± 2.08 m) was recorded in densely canopied, north-facing lower elevation stands, and the lowest (16.51 ± 0.79 m) in open-canopy, south-facing upper elevation stands. Statistical analysis revealed a generally positive and significant correlation between soil quality and site quality, which was stronger on south-facing slopes. Regression analysis confirmed this relationship. Variogram modeling indicated that the spherical model best fit soil quality, while the exponential model was most suitable for site quality. Interpolation accuracy assessments showed that ordinary kriging was the most accurate method for soil quality, and universal kriging was best for site quality.
Conclusion: The study comprehensively demonstrated that both soil properties and overall site quality within the Zagros forests are significantly influenced by key environmental variables, including topographical features, the extent of canopy cover, and variations in elevation. The interrelationship between the two assessed indices—soil and site quality—is statistically significant, and the strength of this relationship fluctuates in response to differing ecological conditions, particularly on south-facing slopes, which are more exposed to solar radiation and drier microclimates. The results of the analysis underscore the necessity of incorporating both soil attributes and broader environmental characteristics when evaluating the biological productivity and ecological potential of forested regions. Moreover, observed differences in the spatial distribution patterns and the structure of the variogram models emphasize the critical importance of selecting appropriate and context-sensitive spatial modeling techniques. These findings not only provide a robust scientific basis for ongoing ecological assessment and environmental monitoring but also offer valuable guidance for implementing targeted forest restoration strategies and developing long-term, sustainable management plans tailored to the unique conditions of the semi-arid Zagros forest ecosystems.
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