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Temporal variation and high-resolution spatial heterogeneity in soil CO(2) efflux in a short-rotation tree plantation

机译:短程旋转人工林土壤CO(2)外排的时间变化和高分辨率空间异质性

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Soil CO(2) efflux (SR) is the second largest carbon flux on earth. We investigated the driving factors of the seasonal change and short-distance spatial variation in SR in a short-rotation plantation of willow (Salix viminalis Orm). Total annual SR ranged from 723 to 1149 g C m(-2) year(-1). Both an exponential and a logistic model were fitted to the data, with soil temperature at a depth of 5 cm as the independent variable. The R(2) values for individual sampling points ranged from 0.83 to 0.95 and from 0.85 to 0.93 for the exponential and logistic models, respectively, indicating that soil temperature largely determined the seasonal variation in SR. Modeled soil SR at 10 degrees C ranged from 1.22 to 1.95 micromol m(-2) s(-1), whereas modeled annual Q(10) values were between 3.31 and 6.13. These high Q(10) values were attributed to the absence of drought during the study in 2005. When the coefficients of the general SR models were replaced by linear dependencies on soil and vegetation-related characteristics, the resulting spatially explicit exponential and logistic SR models explained 85 and 86%, respectively, of the variability within the dataset. The analysis indicated that soil carbon concentration, leaf area index, soil pH and root biomass caused differences in SR at the short distances considered in this study. However, incorporating information on variables considered to account for spatial variability in the model did not result in a higher R(2) compared with a simple temperature function. When the general SR models were applied to independent datasets from the same plantation, the logistic model provided a better fit than the exponential model when drought occurred. Drought greatly reduced the annual Q(10) values of SR.
机译:土壤CO(2)外排(SR)是地球上第二大碳通量。我们调查了短旋柳人工林(Salix viminalis Orm)中SR的季节变化和短距离空间变化的驱动因素。年度总SR范围为723至1149 g C m(-2)年(-1)。数据采用了指数模型和逻辑模型,以5 cm深度的土壤温度为自变量。对于指数模型和逻辑模型,单个采样点的R(2)值分别为0.83至0.95和0.85至0.93,这表明土壤温度很大程度上决定了SR的季节性变化。在10摄氏度下模拟的土壤SR范围为1.22至1.95 micromol m(-2)s(-1),而模拟的年度Q(10)值在3.31和6.13之间。这些较高的Q(10)值归因于2005年的研究期间没有干旱。当将通用SR模型的系数替换为对土壤和植被相关特征的线性依赖关系时,得到的空间显式指数和逻辑SR模型分别解释了数据集中85%和86%的可变性。分析表明,在本研究中,土壤碳浓度,叶面积指数,土壤pH和根生物量在短距离内引起SR的差异。但是,与简单的温度函数相比,在模型中考虑到考虑了空间变异性的变量的信息并不会导致较高的R(2)。当将通用SR模型应用于来自同一人工林的独立数据集时,当干旱发生时,逻辑模型比指数模型提供了更好的拟合度。干旱大大降低了SR的年度Q(10)值。

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