Abstract
The Maoershan forestry centre is situated in the Zhangguangcai Mountain of the Changbai mountain range. The main forest types in the Maoershan region are plantation (Pinus sylvestris var. mongolica, Pinus koraiensis and Larix gmelinii) and natural secondary forests (Fraxinus mandshurica, Quercus mongolica and Populus davidiana). Fine roots have enormous surface areas, growing and turning over quickly, which plays an important role in terms of substance cycling and energy flow in the forest ecosystem. This study deals with the dynamics of live, dead, and total fine roots (≤ 5 mm) biomass in the 0–30 cm soil layer using the soil core method. Differences between the six stands in the Maoershan region showed the following results: 1) the fine root biomass in the various stands showed obvious differences. The total fine root biomass of six stands from high to low were F. mandshurica (1,030.0 g/m2) > Q. mongolica (973.4 g/m2) > Pinus koraiensis (780.9 g/m2) > L. gmelinii (718.2 g/m2) > Populus davidiana (709.1 g/m2) > Pinus sylvestris var. mongolica (470.4 g/m2); 2) except for L. gmelinii, the development of live fine root biomass agreed with the trend of total fine root biomass. The maximum biomass of live fine roots in Pinus koraiensis or L. gmelinii stand appeared in May, others in June; in the F. mandshurica stand, the minimum biomass of live fine roots occurred in September, others in July or August; 3) the proportions of dead fine root biomass varied in different stands; 4) the vertical distribution of fine roots was affected by temperature, water, and nutrients; the proportion of fine root biomass was concentrated in the 0–10 cm soil layer. The fine root biomass of six stands in the 0–10 cm soil layer was over 40% of the total fine root biomass; this proportion was 60.3% in F. mandshurica. Space-time dynamics of the various stands had different characteristics. When investigating the substance cycling and energy flows of all forest ecosystems, we should consider the characteristics of different stands in order to improve the precision of our estimates.
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