The Soil And Litters Enzyme Activity In Pinus Tabulaeformis And Quercus Variabis Forest At Lower Mountain Area, Beijing

Litter is "link"that connect soil and plant in the forest nutrient cycling. It plays an important role in the promotion of organic carbon and nutrient cycling, maintenance of soil productivity and water conservation function of forest in forest ecosystems. Soils extracellular enzymes destruct litter structure and restore organic C, N, P in the process of litter decomposition. The litter decomposition belongs to a complex biochemical process that subject to enzyme systems in the litter and soil. The enzyme activity in soil and litter that related to the cycle of carbon, nitrogen and phosphorus beneath Quercus variabis, Pinus tabulaeformis and mixed forest at lower mountain area were studied. The results will reveal the differences of the enzyme activity in soil and litter between different forests, and provide the scientific basis for the management of forest litter and plantations rational allocation of tree species. The main results are followed:(1)The different stands have different activity of soil a-glucosidase enzyme and polyphenol oxidase, and the difference is related with the sampling time. At0-5cm soil layer, soil β-glucosidase activity is different in different forest stands, but5～10cm soil layer of β-glycosidase activity is not different due to the sampling time. The soil cellobioseenzyme, acid phosphatase, alkaline phosphatase activity in different forest are different due to soil depth and sampling time. The difference of soil peroxidase, chitinase in different stand types is not significant.(2)Soil depth can influence enzyme activity. Soil enzyme activity of a-glucoside, β-glycosidase, peroxidase, chitinase, acid phosphatase and alkaline phosphatase are declined with soil depth increasing. Soil cellobiohydrolase and polyphenol oxidase activity have no significant difference between different soil layers.(3)Soil a-glucosidase enzyme activity and soil organic C, total N, water-soluble organic carbon, water-soluble total nitrogen, water-soluble organic nitrogen are significantly correlated. The activity of soil β-glucosidase enzyme and cellobiose enzyme are highly significant positive correlated with soil organic C, total N, water-soluble organic carbon and nitrogen. Soil polyphenol oxidase activity is significantly negative correlated with soil pH, but positively correlated with soil total N, water-soluble total nitrogen, water-soluble organic nitrogen. Soil chitinase is significantly positive related to soil organic C content, water-soluble organic carbon and water-soluble total nitrogenare. Soil acid phosphatase is significantly negatively correlated with soil pH, whereas significantly positively correlated with the organic C.(4)In the different months, the activity of soil a-glucoside remained unchanged but cellobiohydrolase plummet. The dynamic change trend of (β-glycosidase, chitinase, acid phosphatase and alkaline phosphatase activities are first increased and then decreased, and activity is the highest in august. The highest activity of polyphenol oxidase is in the spring, and dynamic change trend is first plummeting then remained unchanged. Like most hydrolytic enzymes, the changes of peroxidase activity trends are highest in summer, autumn and spring are followed.(5) The difference of a-glucosidase activity of litter among different stands is related to the sampling time. The enzyme activity of β-glucosidase, polyphenol oxidase, chitinase, acid phosphatase, alkaline phosphatase among the different stands litter have certain differences, and the differences relate to sampling time. Litter peroxidase activity is always highest in the Pinus tabulaeformis, however the difference among different stands does not show a uniform trend. There is no significant difference for protease activity under the different stands.On the whole, the activity of hydrolase and oxidoreductase in soil and litter beneath different forest stands exist some difference, but the difference is particularly significant in May. Considering the workload, sampling and analysis in May can better reflect the biological properties between the different forest stands.