兴安落叶松
植物
白蜡树
生物
温带气候
生长季节
根系
木本植物
生物量(生态学)
落叶松
农学
作者
Zhengquan Wang,Dali Guo,Xiangrong Wang,Jiacun Gu,Li Mei
出处
期刊:Plant and Soil
[Springer Science+Business Media]
日期:2006-09-21
卷期号:288 (1-2): 155-171
被引量:162
标识
DOI:10.1007/s11104-006-9101-8
摘要
We have limited understanding of architecture and morphology of fine root systems in large woody trees. This study investigated architecture, morphology, and biomass of different fine root branch orders of two temperate tree species from Northeastern China—Larix gmelinii Rupr and Fraxinus mandshurica Rupr —by sampling up to five fine root branch orders three times during the 2003 growing season from two soil depths (i.e., 0–10 and.10–20 cm). Branching ratio (R
b) differed with the level of branching: R
b values from the fifth to the second order of branching were approximately three in both species, but markedly higher for the first two orders of branching, reaching a value of 10.4 for L. gmelinii and 18.6 for F. mandshurica. Fine root diameter, length, SRL and root length density not only had systematic changes with root order, but also varied significantly with season and soil depth. Total biomass per order did not change systematically with branch order. Compared to the second, third and/or fourth order, the first order roots exhibited higher biomass throughout the growing season and soil depths, a pattern related to consistently higher R
b values for the first two orders of branching than the other levels of branching. Moreover, the differences in architecture and morphology across order, season, and soil depth between the two species were consistent with the morphological disparity between gymnosperms and angiosperms reported previously. The results of this study suggest that root architecture and morphology, especially those of the first order roots, should be important for understanding the complexity and multi-functionality of tree fine roots with respect to root nutrient and water uptake, and fine root dynamics in forest ecosystems.
科研通智能强力驱动
Strongly Powered by AbleSci AI