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    王鑫, 同小娟, 张劲松, 孟平, 解晗, 胡海洋, 李俊. 太行山南麓栓皮栎人工林光合作用对土壤呼吸的影响[J]. 北京林业大学学报, 2021, 43(1): 66-76. DOI: 10.12171/j.1000-1522.20200010
    引用本文: 王鑫, 同小娟, 张劲松, 孟平, 解晗, 胡海洋, 李俊. 太行山南麓栓皮栎人工林光合作用对土壤呼吸的影响[J]. 北京林业大学学报, 2021, 43(1): 66-76. DOI: 10.12171/j.1000-1522.20200010
    Wang Xin, Tong Xiaojuan, Zhang Jinsong, Meng Ping, Xie Han, Hu Haiyang, Li Jun. Effects of photosynthesis on soil respiration of Quercus variabilis plantation in southern Taihang Mountain of northern China[J]. Journal of Beijing Forestry University, 2021, 43(1): 66-76. DOI: 10.12171/j.1000-1522.20200010
    Citation: Wang Xin, Tong Xiaojuan, Zhang Jinsong, Meng Ping, Xie Han, Hu Haiyang, Li Jun. Effects of photosynthesis on soil respiration of Quercus variabilis plantation in southern Taihang Mountain of northern China[J]. Journal of Beijing Forestry University, 2021, 43(1): 66-76. DOI: 10.12171/j.1000-1522.20200010

    太行山南麓栓皮栎人工林光合作用对土壤呼吸的影响

    Effects of photosynthesis on soil respiration of Quercus variabilis plantation in southern Taihang Mountain of northern China

    • 摘要:
        目的  探究光合作用对土壤呼吸的影响并构建新的土壤呼吸模型,可以提高对研究区域土壤呼吸变化的解释程度,为准确估算太行山南麓土壤呼吸强度与碳收支平衡提供理论依据。
        方法  以太行山南麓栓皮栎人工林为研究对象,采用野外控制实验,通过断根与非断根处理对照,分析光合产物对土壤呼吸的贡献比例。并通过土壤呼吸与土壤温湿度及光合数据进行模型拟合,探究加入光合因子是否能对传统土壤呼吸模型进行优化。
        结果  在小时尺度上,土壤温度是影响栓皮栎林土壤呼吸的主要因子,两者呈显著指数相关关系(R2 = 0.74,P < 0.01);在日间尺度上,土壤呼吸与温度的变化曲线并不一致,各个月份土壤温度在10:00—18:00均呈现持续增加的状态,但土壤呼吸速率并未呈现相同的规律,其日变化呈现单峰或双峰曲线,一般在14:00—16:00之间出现最高点。不同处理下土壤呼吸温度敏感性Q10值存在差异,断根处理组分(1.90) > 非断根组分(1.77),表明除温度外存在其他因子对土壤呼吸速率产生影响。研究显示,林木光合作用对土壤呼吸影响占比最高可达到36.5%,光合作用与土壤呼吸存在显著线性相关关系(R2 = 0.39,P < 0.01),将光合速率加入土壤呼吸模型能显著提高土壤呼吸拟合的R2值。
        结论  土壤呼吸是一个受多因素共同影响的复杂过程,仅根据单因素的作用规律来分析和预估土壤呼吸是不全面的,土壤温度只能单独解释土壤呼吸74%的变异,而不同模型中土壤温度和光合两个因子共同决定了土壤呼吸80%以上的变异,其模型拟合度最高可达到0.81。

       

      Abstract:
        Objective  This study aims to explore the effects of photosynthesis on soil respiration and build a new soil respiration model, which can improve the interpretation of soil respiration changes in the study area, and provide a theoretical basis for accurately estimating the intensity of soil respiration and the carbon budget in southern foot of the Taihang Mountains, northern China.
        Method  Taking the Quercus variabilis on the southern foot of Taihang Mountain as research object using field control experiments, which compared the treatment of cut roots and non-cut roots and the contribution rate of photosynthetic products to soil respiration. Through the model fitting of soil respiration, soil temperature, humidity and photosynthesis data, we explored whether adding photosynthetic factors can optimize the traditional soil respiration model.
        Result  On the hourly scale, soil temperature was the main factor affecting the soil respiration of the cork oak forests, and the relationship between them was significant (R2 = 0.74, P < 0.01). On the day scale, the curves of soil respiration and temperature were not consistent. The soil temperature in each month showed a continuous increase from 10:00−18:00, but the soil respiration rate did not show the same law. The daily change of soil respiration showed a single peak or a double peak curve, and the highest point generally appeared between 14:00−16:00. The temperature sensitivity (Q10 values) dissimilated under different conditions with the root cutting treatment component (1.90) > control group score (1.77). Results showed that forest photosynthesis can account for up to 36.5% of soil respiration, and there was a significant linear correlation between photosynthesis and soil respiration (R2 = 0.39, P < 0.01). Regression model with adding photosynthesis variable significantly improved the fitting R2.
        Conclusion  Soil respiration is a complex process affected by multiple factors. It is not comprehensive to analyze and estimate soil respiration based on the function of a single factor. Soil temperature can only explain 74% variations of soil respiration, whereas soil temperature and photosynthesis in the model jointly determine the variation of soil respiration above 80%, and the model fit degree can reach up to 0.81.

       

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