Abstract:

Three 50 m×50 m plots were set respectively in a pure Pinus tabulaeformis forest, a conifer-broad mixed forest dominated by Quercus liaotungensis and a broad mixed forest dominated by Quercus mongolicus in Miyun Chaoguan watershed. Soil samples were collected in three different sampling scales of 5 m×5 m, 10 m×10 m and 25 m×25 m by using the mechanical grid-sampling method under the different vegetation types. The soil pH value and concentrations of organic matter, nitrogen, phosphorus and potassium in the soil were investigated. The results showed that the soil pH value, concentrations of soil organic matter, total nitrogen, available nitrogen and phosphorus, under the pure pine forest were significantly lower than both of the conifer-broad mixed forest and the broad mixed forest at 5 m×5 m sampling scale. At 10 m×10 m sampling scale, the difference of soil nutrient indicators except soil organic matter between the pine forest and the two mixed forests were as same as they were at 5 m×5 m sampling scale. However, only available nitrogen and phosphorus under the pure pine forest were significantly lower than the two mixed forests at 25 m×25 m sampling scale. The coefficient of variation of each soil nutrient concentrations was not correlated to different soil sampling scale. The average coefficient of variation of the soil nutrient indicators under the three vegetation types at three sampling scales followed the order: soil available phosphorus > soil organic matter > soil total nitrogen > soil available potassium > soil available nitrogen > soil total phosphorus > soil total potassium > soil pH value. In order to analyze soil nutrients with a confidence level of 95% and an estimated accuracy of 80%, the soil sampling number of soil pH, soil organic matter, soil total nitrogen, soil available nitrogen, soil total phosphorus, soil available phosphorus, soil total potassium and soil available potassium under the three vegetation types at 25 m×25 m sampling scale were 3,13,15,10,9,23,4 and 9,respectively.

Key words: vegetation type, forest soil nutrient, sampling scale, spatial variability, sampling number