Impact of plot area on structural attributes estimation in a mixed beech (Fagus orientalis Lipsky) stand

Document Type : Scientific article

Authors

1 Ph.D. Student of Silvicultural and Forest Ecology, Faculty of Forest Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

2 Associate Prof., Faculty of Forest Science, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran Department of Silviculture and Forest Ecology Faculty of Forest Sciences Gorgan University of Agricultural Sciences and Natural Resources (GUASNR)

3 Associate Prof., Faculty of Forest Science, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

4 Postdoc Researcher, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland

Abstract

     In continuous cover forestry, the evaluation of forest structure by sampling plots is an important source of information for monitoring biodiversity and resistance criteria in forest ecosystems. Therefore, a precise and accurate sampling design to estimate the structural attributes is required. This study aimed to investigate the impact of plot area on variability and estimates of 1) traditional structural attributes including basal area, density and volume of living trees, and 2) unconventional structural attributes including the number of large trees, total deadwood volume, and the number of large deadwood elements. For this purpose, a 16-ha permanent research plot was divided into 256 0.0625-ha plots, in which all information on living trees and deadwoods was collected. Then, the traditional and unconventional structural attributes were calculated for all sample plots of different sizes (0.0625, 0.125, 0.25, 0.375, 0.5625, 0.75, and 1 ha), followed by calculating the coefficient of variation for each attribute. The results showed that the variability of the structural attributes decreased with increasing plot area. The coefficient of variation on unconventional structural attributes is generally higher than traditional attributes. By calculating the minimal number of plots within a 20% mean error, it was found that the small plots (0.026 and 0.125 ha) are more appropriate for estimating the structural attributes including basal area, density, the volume of living trees, and the number of large trees. Moreover, large plots (0.5625, 0.75, and 1 ha) are more effective to estimate the structural attributes including total deadwood volume and the number of large deadwood elements.

Keywords

References

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