Spatial pattern of trees in different dominant types along the elevation gradient of Hyrcanian Forests, Iran (Case study: Kheiroud Forest of Nowshahr)

Document Type : Research article

Authors

1 PhD Candidate of Forest Biology, Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran

2 Corresponding author, Associate Prof., Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran

3 Associate Prof., Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran

4 Prof., Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran

5 Associate Prof., Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran

Abstract

Background and objectives: To better understand forest types and implement management strategies that align with natural processes, studying their structure and spatial patterns is essential for addressing various ecological issues. Research on natural forests, particularly their spatial structure, provides pathways for developing forest management strategies to achieve desirable structures. The spatial pattern of trees and their mutual relationships offer valuable insights into forest structure. These patterns are qualitative characteristics that need to be quantified for more detailed analysis. This research aims to determine the spatial distribution pattern of trees in the dominant types of Hyrcanian forests in Iran to investigate forest dynamics.
Methodology: This research was conducted in the educational and research forest of Kheiroud Nowshahr. After identifying the primary forest types based on habitat potential and forest community characteristics—such as species appearance, predominance, mixture, diversity (overall abundance of all species), physiographic conditions (elevation, aspect, and slope), and species expansion area—four one-hectare sample plots of dominant types were studied. These included hornbeam-ironwood, hornbeam-beech with oak, mixed beech, and pure beech. In each plot, a 100% inventory was applied, and the diameter at breast height of all trees with a diameter over 7.5 cm was measured. The coordinates of the southwest corner of each plot were recorded using GPS. The distance and azimuth of the first tree were measured with a Vertex device and inclinometer, and its coordinates were calculated using trigonometric relations. The coordinates of other trees were obtained similarly relative to the previous tree. Ripley's K function was used to analyze the spatial pattern.
Results: The results showed that tree density in the studied types varied between 158 and 314 trees per hectare. For hornbeam (Carpinus betulus L.) in the hornbeam-ironwood type, the L function value was higher than the Monte Carlo interval up to a distance of 32 meters, indicating a cumulative spatial pattern. Between 32 and 45 meters, the pattern was random due to being within the Monte Carlo interval. In this forest type, ironwood (Parrotia persica C.A.Mey.) exhibited a completely cumulative distribution pattern. In the hornbeam-beech with oak type, the L function for hornbeam and beech (Fagus orientalis Lipsky) was significantly above the Monte Carlo interval, showing a cumulative pattern. Due to the low number of oak (Quercus castaneifolia C.A.Mey.) individuals, its spatial pattern could not be determined. In the mixed beech type, the L function was entirely within the Monte Carlo interval, indicating a random spatial pattern for beech. In the pure beech type, the distribution was random up to 4 meters, cumulative from 4 to 30 meters, and random again beyond 30 meters.
Conclusion: The results of such studies can serve as models for implementing sustainable management in other forest types and as patterns for conducting breeding interventions to adjust tree locations and species mixtures. Additionally, for afforestation with different species, it is possible to use the natural structure of forests as a model.
 

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References

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