城市绿化景观土壤呼吸变化规律及影响因素

    The Variation and Controlling Factors of Soil Respiration Rate in Urban Green Landscapes

    • 摘要: 采用便携式土壤碳通量自动分析仪ACE对天津国槐梨树(GL)和银杏紫叶李(YZ)2种城市绿化景观土壤呼吸速率(Rs)及其影响因子进行测定,分析了土壤呼吸与土壤温度、土壤湿度和土壤理化性质之间的关系。结果表明:(1)2种绿化景观Rs季节变化规律基本一致,均呈现较明显的单峰变化趋势且峰值同时出现。同时,不同月份Rs变化规律之间存在一定差异。在干季,2种绿化景观Rs较低且月变幅较小,GL和YZ的Rs变化范围分别为(0.20±0.03)~(1.09±0.16)和(-0.06±0.01)~(0.26±0.05)μmol·m-2·s-1;在湿季,2种绿化景观Rs较高且变幅较大,GL和YZ的Rs变化范围分别为(-0.05±0.01)~(3.62±0.26)和(0.38±0.07)~(3.17±0.27)μmol·m-2·s-1。GL的Rs大于YZ。(2)2种绿化景观土壤10 cm处温度(T10)和5 cm处湿度(M5)对土壤呼吸过程均有重要影响,回归分析表明T10M5Rs变化规律的影响程度分别达45.4%~64.8%和21.1%~52.2%;(3)土壤理化性质与Rs具有一定的相关性,其中,土壤有机质含量与Rs的相关性达显著水平(P < 0.05或P < 0.01)。

       

      Abstract: The soil respiration rate (Rs) and its influential factors of two green landscapes (GL and YZ) were measured using a portable automated CO2 exchange station (ACE) during the whole growing season in Tianjin.The relationships be-tween soil respiration and its influential factors of soil temperature, soil moisture and soil physicochemical properties have been analyzed.Results show that:(1) There was basically no difference in the seasonal variation of Rs between the two different types of green landscapes, both of them showed an obvious single-peak variation and the peak appeared at the same time.Simultaneously, the variation of Rs was different in different months.In dry season, the Rs was low with few fluctuations, which ranged from (0.20±0.03) to (1.09±0.16) μmol·m-2·s-1 for GL, and from (-0.06±0.01) to (0.26±0.05) μmol·m-2·s-1 for YZ.Conversely, a relatively higher Rs with more fluctuations was noted in the wet sea-son, it seemed to be varied from (-0.05±0.01) to (3.62±0.26) μmol·m-2·s-1 for GL, and from (0.38±0.07) to (3.17±0.27) μmol·m-2·s-1 for YZ.In summary, the mean value of Rs in GL was significantly higher than that in YZ; (2) The environmental factors that influence Rs are very complicated in the two green landscapes.The two relatively im-portant factors are soil temperature at 10 cm depth (T10) and soil moisture at 5 cm depth (M5).In addition, the regression analysis show that the effective degree of T10 and M5 for Rs were 45.4%-64.8% and 21.1%-52.2%, respectively; (3) There was a certain correlation between soil physicochemical properties and Rs, in which the correlation coefficient between soil organic matter and Rs was highest in all the two green landscapes.

       

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