Document Type : Scientific article
Authors
1
Assistant Professor, Research Division of Natural Resources, Hormozgan Agriculture and Natural Resources Research and Education Center, AREEO, Bandarabbas, Iran and Ph. D graduated from Gorgan University of Agricultural Sciences and Natural Recourses.
2
Associated Professor, Department of Silviculture and Forest Ecology, Gorgan University of Agricultural Sciences and Natural Recourses, Gorgan, I.R. Iran.
3
Associate Professor, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, I.R. Iran.
Abstract
The aim of this study was to evaluate the effectiveness of litterfall production, decomposition, accumulation, temperature, moisture, soil texture and stability on soil organic carbon pool (Socp) and exhibition a model for prediction of it, at three mixed beech-hornbeam stands located in district one of Shastkolate forest, Golestan province from 2/11/2014 to 2/11/2015. In order to perform of this study, 20 points were chosen at each treatment and collected soil samples at the depth of 20 cm, to determine soil organic carbon pool and soil moisture. In order to determine decomposition and litter production, 14 litter bags and 1 litter trap were installed in each point and collected within a year. In 60 samples, bulk density, % volume of coarse fragments, soil texture, weather and soil temperature and weather moisture were determined. To display the relationship between socp and litterfall production, decomposition, accumulation, temperature, moisture, soil texture and stability, path analysis at the level of 99% was used and a network model was exhibited which showed the influence of obvious and unobvious factors on socp. The Chi-square and Root mean square error approximation of corresponding model were 9.089 (P>0.05) and 0.013. So the network model had a good fit. In the relevant model, clay, soil moisture, soil temperature and soil stability were direct influential factors with path coefficients 0.62, -0.27, -0.25 and 0.201 respectively which had the highest contribution in socp estimation. So a formula was exhibited by use of direct factors to predict socp.
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