上海4种常见绿化树种地上生物量模型构建

【目的】分析上海市4种常见绿化乔木杜英(Elaeocarpus decipiens)、女贞(Ligustrum lucidum)、黄山栾树(Koelreuteria bipinnata)、无患子(Sapindus mukorossi)木材密度随径级大小的变异。构建更适用城市生态系统的常用绿化乔木生物量模型,并验证木材密度与胸径的关系,为全面估算上海市绿化乔木生物量及碳储量奠定基础。【方法】采用Y=aX^b幂函数构建了生物量模型,汇总分析针对上海地区9种常见绿化乔木地上各器官生物量的模型,与此次研究构建的生物量模型进行比较,并讨论所建生物量模型的适用性。【结果】杜英树干密度显著小于其他3个树种,各树种树干密度随胸径增加没有明显变化趋势; 构建单一树种生物量模型时可以忽略木材密度对生物量的影响。对4个树种构建的生物量模型总体上拟合效果良好,参数a、b大小因树种和器官不同而有所差异; 其中常绿阔叶树种树干、树枝生物量模型参数b显著小于落叶阔叶树种。所构建的各器官生物量模型与有关学者已发表的上海地区相同树种相应器官模型之间存在差异,尤其对大径阶个体,估算的生物量总体上偏小。【结论】在城市中估算生物量时应根据人为管护强度情况选择适合的生物量模型。

Allometric models for estimating aboveground biomass for four common greening tree species in Shanghai City,China

【Objective】The objective of this study was to construct more suitable biomass models for urban greening tree species, and to discuss the relationship between the wood density and diameter at breast height(DBH). We expect that the study will improve methods of estimating biomass of greening trees in Shanghai.【Method】Elaeocarpus decipiens, Ligustrum lucidum,Koelreuteria bipinnata, and Sapindus mukorossi were selected to analyze the variation in their wood densities, and to fit their allometric biomass models to the form of Y=aX^b. Moreover, we compiled published aboveground biomass models of nine common greening trees in Shanghai, and compared these to our results.【Result】The wood density of Elaeocarpus decipiens was significantly lower than those of the other species, and wood density had no apparent correlation with DBH, which suggested that wood density can be ignored when fitting single species biomass models. The allometric models generally fitted the data well, and the values of coefficients a and b varied among species and organs.The coefficient b values of evergreen broad-leaved trees were significantly lower than those of deciduous broad-leaved trees. The published models yielded different biomass estimationsthan ours, especially for large trees.【Conclusion】Suitable allometric models should be selected for estimating tree biomass in urban green areas according to specific conditions, especially the intensity of greening management.