山西省油松林生态系统碳密度与分配格局

Density and Distribution Patterns of Carbon of Pinus tabulaeformis Carr Forest Ecosystem in Shanxi Province,China

针对森林生态系统的碳密度估算精度低的问题,以山西的油松人工林和天然林为对象,在林分尺度上采用实测样地数据和异速生长方程相结合的方法,分析了油松幼龄林和中龄林生态系统各组分的碳密度及分布特征.结果表明,(1)人工幼龄林(AY)、人工中龄林(AM)、天然幼龄林(NY)和天然中龄林(NM)生态系的统碳密度分别为44538.05kg/hm2、90314.68kg/hm2、119928.99kg/hm2和261036.39kg/hm2;(2)相应的4种生态系统中乔木层碳密度所占的百分比分别为12.99%、34.51%、26.25%和45.34%,灌草层和凋落物层碳密度合占的百分比分别为0.77%、3.96%、9.71%和2.98%,土壤层碳密度所占的百分比分别为86.24%、61.53%、64.04%和51.68%;(3)山西油松林生态系统碳密度平均为127525.25kg/hm2低于全国油松林平均值,但0—100cm土壤层平均碳密度76975kg/hm2与全国的平均水平相当,反映出林分的质量不高需要采取抚育措施;(4)采用林分尺度调查与异速生长方程相结合的方法,比采用材积源生物量法推算乔木层的生物量估算森林整体碳密度法具有更高精度.

To solve the problem of low accuracy forest ecosystem carbon density estimation, selected artificial and natural Pinus tabulaeformis forests in Shanxi, using field investigation data and the allometric models at the stand scale analyzed carbon densities of each component and distribution characteristics of young and middle-aged forest ecosystem. The results show that： （ 1 ） Ecosystem carbon density statistics of artificial young forest （AY）, artificial middle-aged forest（ AM）, natural young forest （NY） and natural middle-aged forest （NM） were respectively 44538.05kg/hm2, 90314.68kg/hm2, 119928.99kg/hm2 and 261036.39kg/hm2 ; （ 2 ） In the four forest ecosystems, arbor layer carbon density percentages were 12.99%, 34.51%, 26.25 % and 45.34%, total carbon density percentages of shrub, grass and litter layer were 0. 77%, 3.96% ,9.71% and 2.98% ,the soil layer carbon density percentages are 86.24% ,61.53%, 64.04% and 51.68% ;（3 ）Carbon density 127525.25kg/hm2 of Shanxi＇ s Pinus tabulaeformis forest ecosystem was lower than the national average, but carbon density 76975kg/hm2 in 0--100cm depth soil layer was equal to the national average, implying requirement of tending measures for the forest quality improvement; （4）The method combined stand-scale investigation with allometric models to estimate forest ecosystem carbon density has a higher accuracy than volume derived biomass method.