Estimation of biomass allocation and carbon density in alpine dwarf shrubs in Garzê Zangzu Autonomous Prefecture of Sichuan Province, China
Aims Shrub recovery is identified as a major cause of an increase in carbon stocks in terrestrial ecosystems in China,and yet there is a great uncertainty in the contribution of shrubs to the carbon sink.Our objectives were to determine the biomass allocation pattern and carbon density in alpine shrubs.Methods We conducted investigations in 14 shrub communities in eastern Qinghai-Xizang Plateau,at 3 500 m above sea level.Plant samples were collected from each plot and measured for biomass in leaves,branches and stems,and roots in laboratory; the data were used to analyze the biomass allocation and carbon density.Important findings The mean biomass was (5.38 ± 3.30) Mg·hm-2 in the shrub layer.There were significant differences in biomass between different shrub types,with the mean of (7.28 ± 4.96) Mg·hm-2 for the broadleaved deciduous shrubs and (4.32 ± 1.36) Mg·hm-2 for the leathery-leaved shrubs.The indicators of individual feature and community structure were significantly correlated with biomass per unit land area.However,these relationships were developed based on multiple community structure factors; any single factor alone was insufficient to explain the patterns of biomass variations.The patterns of biomass allocation differed significantly between different shrub types.In this study,there was more allocation of photosynthetic products to roots.The mean total community biomass was (6.41 ± 3.86) Mg·hm-2 and the shrub layer accounted for (83.18 ± 8.14)％ of the total community biomass.There were significant correlations (p ＜ 0.05) between shrub layer biomass and herb layer biomass,between shrub layer biomass and litter layer biomass,and between shrub layer biomass and the total community biomass.The biomass of various organs were also significantly correlated (p ＜ 0.01) with the total community biomass.The mean biomass carbon density of the shrubs was estimated at (3.20 ± 1.93) Mg·hrn-2 across the 14 communities by using biomass conversion factor method.
NETL
NSTL
万方数据
维普
