Geostatistically estimation and mapping of forest stock in a natural unmanaged forest in the Caspian region of Iran

Abstract

Estimation and mapping of forest resources are preconditions for management, planning and research. In this study, we applied kriging interpolation of geostatistics for estimation and mapping of forest stock at-tributes in a natural, uneven-aged, unmanaged forest in the Caspian region of northern Iran. The site of the study has an area of 516 ha and an elevation that ranges from 1100 to 1450 m a.s.l. Field sampling was per-formed on a 75m × 200m systematic grid using 309 geo-referenced circular sample plots of 1000 m2 area. Experimental variograms were calculated and plotted for basal area (BA), volume (V) and stem density (N). Whereas the calculated variograms of BA and V exhibited spatial auto-correlation only after data stratification based on diameter size classes and tree species, the variogram of stem density displayed a moderate spatial structure that was fitted by a spherical model. Stem density was estimated by ordinary block kriging and the accuracy of estimation was validated by cross-validation result. We conclude that geostatistical approaches have the potential to more accurately capture and describe the spatial variability of forest stock, and thus reduce the uncertainty in estimates of stem density as well as produce more accurate stem density maps of forests in comparison with the spatially uninformed classic method. Geostatistical methods provide a very suitable tool to derive more accurate estimates of growing stock, particularly in structurally complex, unmanaged, uneven-aged forest such as this one from the Caspian region of northern Iran.