Vegetation community in relation to the soil characteristics of Rineh rangeland, Iran

• Main Authors: Jafarian Jeloudar, Z., Arzani, H., Jafari, M., Kavian, A., Zahedi, Gh., Azarnivand, H.
• Format: Article
• Language: English
• Published: University of Guilan 2010-05-01
• Series: Caspian Journal of Environmental Sciences
• Subjects: Iran; Vegetation cover; Soil characteristics; Rineh rangelands; Multivariate analysis
• Online Access: https://cjes.guilan.ac.ir/article_1048.html

The aim of this study was to investigate relationships between soil properties and plant species to determine the most effective factors separating vegetation communities in Rineh rangeland. Three stratifying variables were selected including slop, aspect and elevation. The study area was partitioned by combining these classes to generate homogenous units. 1m2 quadrates were located at sampling sites in each homogenous unit randomly. Vegetation cover data were recorded using ordinal scale of Daubenmire cover-abundance scores in each quadrate. Soil samples were collected based on area from 0-15, 15-30 cm depths in each sampling site. Total nitrogen, organic matter, pH, total phosphorus, water retention capacity, permanent wilting point, available water capacity, potassium, water holding capacity, CaCO3, saturation moisture, bulk density, real unit weight and percentage of fine earth fragments (sand, silt and clay) were measured. Both classification and ordination techniques were employed including TWINSPAN classification, DCA and CCA. The TWINSPAN classification of the sample sites have resulted in ten groups. According to the results of DCA, length of gradient represented by axis 1 was >5 SD, indicating that CCA was the appropriate ordination method. CCA axis 1 was correlated to phosphorus (-0.460) in the first layer and phosphorus (-0.493), sand (0.533) in the second layer while the CCA axis 2 was correlated to phosphorus (0.394), sand (0.533) in the second layer. The species-environment correlations are higher for the first three canonical axes, explaining 18% of the cumulative variances.