The Dry and Wet Aggregates Stability Indices of Soils Covered by Lichen Dominated Biocrusts

Document Type : Research Paper


1 Department of Desert and Arid Land Management, Faculty of Desert Studies, University of Semnan, IranExtension Organization (AREEO), Tehran, Iran

2 Department of Desert and Arid Land Management, Faculty of Desert Studies, University of Semnan, Iran

3 Department of Soil Biology Soil and Water Research Institute. Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran

4 Biotechnology Department, Iranian Research Organization for Science and Technology

5 Desert Research Division, Research Institute of Forests and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran


Biological soil crusts play an important role to improve soil structure, aggregate formation and soil stability by increasing organic carbon. Aggregate stability determines its resistance to soil erosive agents. In this study, due to the severity of soil erosion of Sejzi plain of Isfahan province, the role of biological crusts as a soil erosion controller has been investigated in terms of stabilizing dry and wet aggregates. For this purpose, sampling was done from lichen dominated areas, both from the soil covered with biocrust also the soil without biological crusts. Soil physicochemical properties including pH, EC, Sodium Adsorption Ratio, bulk density, soil saturation percentage, soil texture, OC%, soil particles with d<0.84 mm, MWD and WESS indexes were measured. Classification of soil parameters affected by biocrust and without biocrust was performed by PCA method. After determining the role of biocrusts in increasing aggregate stability in the soil covered by biocrusts, in two cases (wet and dry), the effect of each soil parameters on increasing aggregate stability was investigated based on multivariate linear regression model using stepwise method. The results of stepwise modeling showed that the dry aggregate stability depends on five influential factors including pH, OC%, clay%, sand% and MWD, with R square value of 0.68. Also, the regression model for wet aggregate stability was established using three effective factors including pH, d<0.84mm and TNV%, and R square was estimated 0.667. Aggregate stability in both cases, dry and wet conditions, are affected by each other and it is depended on the amount of OC%.


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