Akhavan, R. (2010). Spatial variability of forest growing stock using geostatistics in the Caspian region of Iran. Caspian Journal of Environmental Sciences, 8(1), 43-53.
R. Akhavan. "Spatial variability of forest growing stock using geostatistics in the Caspian region of Iran". Caspian Journal of Environmental Sciences, 8, 1, 2010, 43-53.
Akhavan, R. (2010). 'Spatial variability of forest growing stock using geostatistics in the Caspian region of Iran', Caspian Journal of Environmental Sciences, 8(1), pp. 43-53.
Akhavan, R. Spatial variability of forest growing stock using geostatistics in the Caspian region of Iran. Caspian Journal of Environmental Sciences, 2010; 8(1): 43-53.
Spatial variability of forest growing stock using geostatistics in the Caspian region of Iran
R. Akhavan *1, Gh. Zahedi Amiri 2, M. Zobeiri 2
1- Research Institute of Forests and Rangelands, P.O. Box, 13185-116, Tehran, Iran.
2- Department of Forestry, Faculty of Natural Resources, University of Tehran, P.O. Box, 31585-4314, Karaj, Iran.
* Corresponding author?s E-mail: akhavan@rifr-ac.ir
Abstract
Estimating the amount of variation due to spatial dependence at different scales provides a basis for designing effective experiments. Accurate knowledge of spatial structures is needed to inform silvicultural guidelines and management decisions for long term sustainability of forests. Furthermore, geostatistics is a useful tool to describe and draw map the spatial variability and estimation of forest variables. Therefore, this research was conducted to investigate on spatial variability and to estimate forest stock variables using geostatistical approach in a mixed hardwood forest, located in the Caspian region of Iran. Field sampling was performed based on a 150m by 200m systematic rectangular grid of 3 clustered plots (50m away). Each sample plot consisted of two concentric circles. Overall, 434 sample plots were measured in 502 hectares. Experimental variograms for forest basal area, volume and tree density were calculated and plotted using the geo- referenced inventory plots. All the variograms showed weak spatial auto- correlations between samples, even in short distances. Estimations were made using fitted variogram models and ordinary block kriging. Cross- validation results showed that all the estimations are biased, because of the large variability and weak spatial structure in the forest stock variables. Therefore, kriging could not make accurate estimations because of high spatial variability of forest growing stock related variables in this heterogeneous and uneven-aged forest.
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