中文摘要：

东北地区森林生态系统因其面积大，碳贮量高而在本地区和我国碳平衡中占有重要的地位。土壤表面CO2通量（RS）作为陆地生态系统向大气圈释放的主要CO2源，其时空变化直接影响到区域碳循环。该研究采用红外气体分析法比较测定我国东北东部次生林区6个典型的森林生态系统的RS及其相关的土壤水热因子，并深入分析土壤水热因子对RS的影响。研究结果表明：影响RS的主要环境因子是土壤温度、土壤含水量及其交互作用，但其影响程度因生态系统类型和土壤深度而异。包括这些环境因子的综合Rs模型解释了67．5％，90．6％的Rs变异。在整个生长季中，不同生态系统类型的土壤温度差异不显著，而土壤湿度的差异显著（α=0．05）。蒙古栎（Quercus mongolica）林、红松（Pinus koralensis）林、落叶松（Larix gmelinii）林、硬阔叶林、杂木林和杨桦（Populus davidiana-Betola platyphylla）林的Rs变化范围依次为：1．89—5．23μmol CO2·m^-2·s^-1，1．09—4．66μmol CO2·m^-2·s^-1，0．95—3．52μmol CO2·m^-2·s^-1，1．13—5．97μmol CO2·m^-2·s^-1，1．05—6．58μmol CO2·m^-2·s^-1和1．11—5．76μmol CO2·m^-2·s^-1。Rs的季节动态主要受土壤水热条件的驱动而呈现单峰曲线，其变化趋势大致与土壤温度的变化相吻合。Q10从小到大依次为：蒙古栎林2．32，落叶松林2．57，红松林2．76，硬阔叶林2．94，杨桦林3．54和杂木林3．55。Q10随土壤湿度的升高而增大；但超过一定的阈值后，土壤湿度对Q10起抑制作用。该研究结果强调对该地区生态系统土壤表面CO2通量的估测应同时考虑土壤水热条件的综合效应。

英文摘要：

Forest ecosystems in northeastern China play an important role in both local and national carbon budgets because of their large area extent and huge amount of carbon storage. The spatial and temporal changes in soil surface CO2 flux （Rs）, the major CO2 source to the atmosphere from terrestrial ecosystems, directly influence the local and regional carbon budgets. However, few data on Rs were available for this region. In this study, we used an infrared gas exchange analyzer （LI-COR 6400） to measure the Rs and related biophysical factors, and examined soil temperature and moisture effects on soil respiration for six secondary temperate forest ecosystem types： Mongolian oak （dominated by Quewus mongolica ）, poplar-birch （dominated by Populus davidiana and Betula platyphylla）, mixed-wood （no dominant tree species）, hard-wood forests （dominated by Fraxinus mandshurica , Juglans mandshurica and Phellodendron amurense ）, Korean pine （ Pinus koraiensis ） and Dahurian larch （ Larix gmelinii ） plantations. Our specific objectives were to： 1 ） compare the soil temperature, soil moisture, Rs, and Q10（temperature coefficient） of the six forest types; 2） quantify the seasonality of Rs and related environmental factors; and 3） determine the environmental factors affecting the Rs, and construct models of Rs against the related environmental factors. Soil temperature, soil. moisture and their interactions significantly （p 〈 0.01） influenced the Rs, but their effects depended on forest type and soil depth. These factors could explain 67.5% - 90.6% of the variations in the Rs data. During the growing season, the soil temperature at 10 cm depth in the different forest types did not differ significantly but soil moisture did. The Rs for the oak, pine, larch, hardwood, mixedwood, and poplar-birch stands varied from 1.89-5.23, 1.09-4.66, 0.95-3.52, 1.13 -5.97, 1.05- 6.58, and 1.11 -5.76 μmol CO2·m^-2·s^-1, respectively; the Q10 values for those stands were 2.32, 2.76,2.57, 2.94,