华西雨屏区苦竹人工林土壤呼吸各组分特征及其温度敏感性

通过在华西雨屏区苦竹(Pleioblastus amarus)人工林内建立固定样地、定期监测等方法,研究该人工林生态系统土壤呼吸各组分特征及其温度敏感性.结果表明:2010年2月-2011年1月,苦竹林平均土壤呼吸速率为1.13 μmol·m-2·s-1,仲夏最高,深冬最低;凋落物层、无根土壤和植物根系对苦竹林土壤呼吸的贡献率分别为30.9％、20.8％和48.3％,各呼吸组分的季节动态均与土壤总呼吸类似,并与温度和凋落量等因素相关;苦竹林土壤总呼吸(RST)、凋落物层CO2排放(RSL)、无根土壤CO2排放(RSS)和植物根系呼吸(RSR)的年碳排放量分别为4.27、1.32、0.87和2.08 MgC· hm-2 ·a-1;土壤总呼吸及其各组分与凋落量呈显著正线性相关,与土壤10 cm温度和气温均呈显著正指数相关;基于土壤温度计算的RST、RSL、RSS和RSR的Q10值分别为2.90、2.28、3.09和3.19,凋落物层CO2排放的温度敏感性显著低于总呼吸和其他各组分.     

中国土壤呼吸温度敏感性空间格局的反演

土壤呼吸的温度敏感性（Q10）是模拟全球变暖与生态系统碳释放之间反馈强度的重要参数．虽然实验研究表明Q10值具有明显的空间异质性,但由于其空间分布格局的定量数据的缺乏,目前绝大多数生物地球化学模型将其简化成一个常数,并以此来预测未来的气候变化,这在一定程度上增大了模型预测的不确定性．本研究基于土壤有机碳的实测数据,并结合碳循环过程模型（CASA模型）,利用反演分析方法估算了8km空间分辨率下中国土壤呼吸温度敏感性的空间分布．结果表明,Q10值具有明显的空间异质性,且与实验方法估算的Q10值具有一致性;不同土壤类型的Q10值在1．09～2．38之间变化,其中火山灰土的Q10值最大,冷棕钙土的值最小;Q10值的空间分布与降水及土壤有机碳含量的关系密切．研究表明,该方法能有效反演Q10值的空间分布,从而有助于揭示碳循环规律并降低未来大气CO2浓度及气候变化预测的不确定性．     

土壤呼吸温度敏感性的影响因素和不确定性

土壤呼吸是陆地生态系统碳循环的重要环节之一, 其对温度升高的敏感程度在很大程度上决定着全球气候变化与碳循环之间的反馈关系。为了深刻理解地下生态过程对气候变化的响应和适应,本文综述了土壤呼吸温度敏感性（Q10）的影响因子及其内在机制,并分析了当前研究存在的不确定性。土壤生物、底物质量和底物供应显著调控着土壤呼吸的Q10值,但研究结论仍然有很大差异。温度和水分等环境因子则通过对土壤生物和底物的影响而作用于土壤呼吸的温度敏感性,一般情况下,随着温度的升高,土壤呼吸的Q10值下降;水分过高或过低时Q10值降低。另外本文从土壤温度测定深度、时空尺度、土壤呼吸不同组分温度敏感性差异、激发效应以及采用方法的不同等几方面分析了温度敏感性研究存在的不确定性。并在此基础上, 指出了未来拟重点加强的研究方向:（1）土壤呼吸不同组分温度敏感性差异的机理;（2）底物质量和底物供应对温度敏感性的交互影响;（3）生物因子对土壤呼吸温度敏感性的影响。     

施肥对油茶园土壤呼吸和异养呼吸及其温度敏感性的影响

油茶是中国南方重要的木本食用油料树种,研究施肥对油茶园土壤呼吸及其温度敏感性的影响,对于估算中国南方典型种植园林温室气体排放及其对气候变化的响应具有重要意义。设置对照(CK)、施肥(OF)、断根(CK-T)和断根施肥(OF-T)4个处理,采用静态箱-气相色谱法,通过多年观测,分析探讨施肥对油茶园土壤呼吸和异养呼吸及其温度敏感性的影响。结果表明:(1)施肥对油茶园土壤呼吸和异养呼吸无显著影响。研究期间,各处理(OF、CK、OF-T、CK-T)土壤CO_2通量依次为(77.91±2.59)、(73.71±0.97)、(66.82±1.02)mg C m~(-2)h~(-1)和(66.84±3.94)mg C m~(-2)h~(-1);(2)各处理土壤呼吸温度敏感性(Q_(10))表现为OF-T(1.96±0.01)CK-T(1.79±0.03)OF(1.77±0.01)CK(1.75±0.03),其中,OF-T处理下Q_(10)显著高于其他3个处理,即施肥显著增加了断根处理土壤呼吸Q_(10);(3)施肥显著增加了土壤表层NH_4~+-N和NO_3~--N含量,Q_(10)与土壤表层NH_4~+-N和NO_3~--N含量表现出显著的正相关关系。     

施石灰对杉木人工林土壤呼吸及其温度敏感性的影响

我国酸沉降主要分布区域与杉木人工林主要分布区域重合,石灰添加是改良酸化土壤的有效措施。为探究酸沉降背景下施石灰对土壤呼吸及其温度敏感性的影响,本研究以杉木人工林土壤为对象,在2018年6月一次性添加0、1和5 t·hm^-2的氧化钙,于2020年6月开始进行为期一年的原位土壤呼吸速率观测。结果表明：与不施石灰相比,施石灰显著提高了土壤pH值和交换性Ca²⁺含量,不同石灰施用量之间无显著差异。杉木人工林土壤呼吸及其组分具有明显的季节差异,表现为夏季最高,冬季最低,施石灰未显著改变其季节动态特征。施石灰显著降低了土壤异养呼吸速率,提高了自养呼吸速率,最终导致施石灰对土壤呼吸无显著影响。土壤呼吸月动态变化与温度月动态变化基本保持一致,土壤呼吸与土壤温度呈显著的指数关系,施石灰后土壤呼吸及自养呼吸的温度敏感性(Q₁₀)呈上升趋势,土壤异养呼吸的Q₁₀呈下降趋势。综上,施石灰提高了杉木人工林土壤自养呼吸,显著降低了土壤异养呼吸,这有利于杉木人工林土壤固碳。     

两种农田土壤不同组分呼吸及其温度敏感性

为探讨农田土壤不同组分呼吸及其对温度变化的响应,选取山东平邑旱耕土和湖南桃江水稻土为供试土壤,设置4个温度水平(5、15、25、35 ℃),对两种土壤的轻组、重组及全土进行63 d的培养试验.结果表明: 两种土壤全土的呼吸均高于轻组和重组.旱耕土重组的呼吸高于轻组,水稻土重组和轻组的呼吸在5～25 ℃温度水平下无显著差异,但35 ℃下重组高于轻组.在不同温度水平下,旱耕土轻组、重组和全土累积呼吸量分别占其初始碳的0.3%～2.8%、0.4%～3.7%和0.6%～7.0%,水稻土分别占其初始碳的0.4%～3.0%、0.3%～3.8%和0.7%～5.3%.两种土壤全土及轻、重组呼吸的温度敏感性(Q₁₀)均随温度升高和培养时间延长而降低;水稻土重组的Q₁₀高于轻组,旱耕土重组和轻组Q₁₀的差异无明显规律.在5～25 ℃温度水平下,旱耕土全土Q₁₀显著高于水稻土,但在25～35 ℃下低于水稻土.说明平邑旱耕土有机碳矿化强度高于桃江水稻土,且对温度变化的响应总体比水稻土更敏感.     

Spatial variation and controlling factors of temperature sensitivity of soil respiration in forest ecosystems across China

土壤呼吸的温度敏感性(Q₁₀)是陆地碳循环与气候系统间相互作用的关键参数。尽管已有大量关于不同类型森林Q₁₀季节和年际变化规律的研究, 但是对Q₁₀在区域尺度的空间变异特征及其影响因素仍认识不足, 已有结果缺乏一致结论。该研究通过整合已发表论文, 构建了中国森林生态系统年尺度Q₁₀数据集, 共包含399条记录、5种森林类型(落叶阔叶林(DBF)、落叶针叶林(DNF)、常绿阔叶林(EBF)、常绿针叶林(ENF)、混交林(MF))。分析了不同森林类型Q₁₀的空间变异特征及其与地理、气候和土壤因素的关系。结果显示, 1) Q₁₀介于1.09到6.24之间, 平均值(±标准误差)为2.37 (± 0.04), 且在不同森林类型之间无显著差异; 2)当考虑所有森林类型时, Q₁₀随纬度、海拔、土壤有机碳含量(SOC)和土壤全氮含量(TN)的增加而增大, 随经度、年平均气温(MAT)、平均年降水量(MAP)的增加而减小。气候(MAT、MAP)和土壤(SOC、TN)因素间存在相互作用, 共同解释了33%的Q₁₀空间变异, 其中MAT和SOC是Q₁₀空间变异的主要驱动因素; 3)不同类型森林Q₁₀对气候和土壤因素的响应存在差异。在DNF中Q₁₀随MAP的增加而减小, 而其他类型森林中Q₁₀与MAP无显著相关性; 在EBF、DBF、ENF中Q₁₀随TN的增加而增大, 但Q₁₀对TN的敏感性在EBF中最高, 在ENF中最低。这些结果表明, 尽管Q₁₀有一定的集中分布趋势, 但仍有较大范围的空间变异, 在进行碳收支估算时应注意尺度问题。Q₁₀的主要驱动因素和Q₁₀对环境因素的响应随森林类型而变化, 在气候变化情景下, 不同森林类型间Q₁₀可能发生分异。因此, 未来的碳循环-气候模型还应考虑不同类型森林碳循环关键参数对气候变化的响应差异。     

氮添加对高寒草甸土壤微生物呼吸及其温度敏感性的影响

土壤氮素的可利用性是控制土壤微生物呼吸的重要因素之一,大量研究已经表明增加土壤活性氮的含量可以降低微生物呼吸,但是土壤氮输入对土壤微生物呼吸温度敏感性的影响还不清楚。以青藏高原高寒草甸为研究对象,通过野外施氮试验和室内控制试验相结合的方式,在5℃、15℃和25℃条件下对3种施氮水平的土壤(对照,0g N m~(-2)a~(-1);低氮,5g N m~(-2)a~(-1);高氮,15g N m~(-2)a~(-1))进行培养,探讨土壤微生物呼吸及其温度敏感性对不同氮添加水平的响应情况。结果表明:(1)3个温度培养下的土壤微生物呼吸速率和累积碳释放量均随施氮量的增加而显著降低(P0.05);(2)氮添加对5℃和15℃培养条件下的微生物呼吸温度敏感性没有显著影响,但显著地增加了15℃和25℃培养条件下的微生物呼吸温度敏感性(P0.05);(3)线性相关分析表明,土壤累积碳释放量与土壤有机碳的难降解性显著负相关(P0.05),而15℃和25℃培养条件下的微生物呼吸温度敏感性与土壤有机碳的难降解性显著正相关(P0.05)。结果表明,在全球气候变暖的背景下,土壤氮输入将增加预测青藏高原高寒草甸地区土壤碳排放的不确定性。     

不同土地利用方式下土壤呼吸及其温度敏感性

采用静态箱-气相色谱法对四川盆地中部紫色土丘陵区3种土地利用方式（林地、草地和轮作旱地）土壤呼吸进行测定,结果表明,林地、草地和旱地土壤呼吸速率变化范围分别为78．63～577．97、39．28～584．18和34．48～484．65mgCO2·m^-2·h^-1,年平均土壤呼吸速率分别为264．68、242．91、182．21mgCO2·m^-2h^-1。3种土地利用方式的土壤呼吸速率季节变化趋势均呈单峰曲线,林地和草地土壤呼吸速率最大值均出现在夏末（7月底与8月初之间）,旱地土壤呼吸速率最大值出现的时间比林地和草地要早,在6月底与7月初之间;最小值均出现在12月底与翌年1月初之间。土壤温度和土壤湿度是影响本地区土壤呼吸的主要因子,双因素关系模型（R=αe^bTw^c）较好地拟合了土壤温度和土壤湿度对土壤呼吸的影响,二者共同解释了土壤呼吸变化的64％～90％。土壤呼吸的温度敏感性指数Q10值受土壤（5cm处）温度和土壤（0～10cm）湿度的影响。分析表明3种土地利用土壤的Q10值与土壤温度呈显著负相关关系,而与土壤湿度呈显著正相关关系。     

模拟氮沉降对长江滩地杨树林土壤呼吸温度敏感性的影响

研究氮沉降量增加对土壤呼吸温度敏感性的影响,对于研究土壤呼吸在气候变化中的作用有重要意义。以长江中下游滩地杨树人工林为对象,通过定位模拟氮沉降实验的方法,研究了滩地杨树人工林生态系统土壤呼吸的变化特征和土壤呼吸各组分的温度敏感性对几种氮沉降量浓度的短期响应。结果表明:(1)各处理土壤总呼吸、土壤微生物呼吸、根系呼吸与各层次土壤温度均呈显著正相关关系,和5cm层土壤温度相关性最大。5cm层土壤温度可以解释土壤总呼吸、土壤微生物呼吸和根系呼吸季节变化的比例分别为50.5%—71.0%、51.5%—73.9%、35.7%—63.2%;(2)对照组(CK,0g N m-2a-1)土壤总呼吸、土壤微生物呼吸与根呼吸的Q10值分别为2.54、2.72和1.94;(3)在各氮添加水平中,中氮水平(MN,10g N m-2a-1)促进了土壤总呼吸、土壤微生物呼吸和植物根呼吸的温度敏感性。高氮水平(HN,20g N m-2a-1)都降低了土壤总呼吸、土壤微生物呼吸和植物根呼吸的温度敏感性,低氮水平(LN,5g N m-2a-1)降低了土壤总呼吸和土壤微生物呼吸的温度敏感性,促进了根呼吸的敏感性。     

Partitioning soil respiration of temperate forest ecosystems in northeastern China

Quantifying soil respiration components and their relations to environmental controls are essential to estimate both local and regional carbon (C) budgets of forest ecosystems. In this study, we used the trenching-plot and infrared gas exchange analyzer approaches to determine heterotrophic (R_H) and autotrophic respiration (R_A) in the soil surface CO₂ flux for six major temperate forest ecosystems in northeastern China. The ecosystems were: Mongolian oak forest (dominated by Quercus mongolica), aspen-birch forest (dominated by Populous davidiana and Betula platyphylla), mixed wood forest (composed of P. davidiana, B. platyphylla, Fraxinus mandshurica, Tilia amurensis, Acer amono, etc.), hardwood forest (dominated by F. mandshurica, Juglans mandshurica, and Phellodendron amurense), Korean pine (Pinus koraiensis), and Dahurian larch (Larix gmelinii) plantations, representing the typical secondary forest ecosystems in this region. Our specific objectives were to: (1) quantify R_H and its relationship with the environmental factors of the forest ecosystems, (2) characterize seasonal dynamics in the contribution of root respiration to total soil surface CO₂ flux (RC), and (3) compare annual CO₂ fluxes from R_H and R_A among the six forest ecosystems. Soil temperature, water content, and their interactions significantly affected R_H in the ecosystems and accounted for 46.5%–78.8% variations in R_H. However, the environmental controlling factors of R_H varied with ecosystem types: soil temperature in hardwood and Dahurian larch forest ecosystems, soil temperature, and water content in the others. The RC for hardwood, poplar-birch, mixed wood, Mongolian oak, Korean pine, and Dahurian larch forest ecosystems varied between 32.40%–51.44%, 39.72%–46.65%, 17.94%–47.74%, 34.31%–37.36%, 33.78%–37.02%, and 14.39%–35.75%, respectively. The annual CO₂ fluxes from R_H were significantly greater than those from R_A for all the ecosystems, ranging from 337–540 g Cm^-2a^-1 and 88‐331 gCm^-2a^-1 for R_H and R_A, respectively. The annual CO₂ fluxes from R_H and R_A differed significantly among the six forest ecosystems.     

东北东部森林生态系统土壤呼吸组分的分离量化

对森林生态系统的土壤呼吸组分进行分离和量化,确定不同组分CO2释放速率的控制因子,是估测局域和区域森林生态系统碳平衡研究中必不可少的内容。采用挖壕法和红外气体分析法测定无根和有根样地的土壤表面CO2通量(RS),确定东北东部6种典型森林生态系统RS中异养呼吸(RH)和根系自养呼吸(RA)的贡献量及其影响因子。具体研究目标包括:(1)量化各种生态系统的RH及其与主要环境影响因子的关系;(2)量化各种生态系统RS中根系呼吸贡献率(RC)的季节动态;(3)比较6种森林生态系统RH和RA的年通量。土壤温度、土壤含水量及其交互作用显著地影响森林生态系统的RH(R2=0.465~0.788),但其影响程度因森林生态系统类型而异。硬阔叶林和落叶松人工林的RH主要受土壤温度控制,其他生态系统RH受土壤温度和含水量的联合影响。各个森林生态系统类型的RC变化范围依次为:硬阔叶林32.40%~51.44%;杨桦林39.72%~46.65%;杂木林17.94%~47.74%;蒙古栎林34.31%~37.36%;红松人工林33.78%~37.02%;落叶松人工林14.39%~35.75%。每个生态系统类型RH年通量都显著高于RA年通量,其变化范围分别为337~540 gC.m-2.a-1和88~331 gC.m-2.a-1。不同生态系统间的RH和RA也存在着显著性差异。     

Carbon quality and soil microbial property control the latitudinal pattern in temperature sensitivity of soil microbial respiration across Chinese forest ecosystems

Understanding the temperature sensitivity (Q₁₀) of soil organic C (SOC) decomposition is critical to quantifying the climate–carbon cycle feedback and predicting the response of ecosystems to climate change. However, the driving factors of the spatial variation in Q₁₀ at a continental scale are fully unidentified. In this study, we conducted a novel incubation experiment with periodically varying temperature based on the mean annual temperature of the soil origin sites. A total of 140 soil samples were collected from 22 sites along a 3,800 km long north–south transect of forests in China, and the Q₁₀ of soil microbial respiration and corresponding environmental variables were measured. Results showed that changes in the Q₁₀ values were nonlinear with latitude, particularly showing low Q₁₀ values in subtropical forests and high Q₁₀ values in temperate forests. The soil C:N ratio was positively related to the Q₁₀ values, and coniferous forest soils with low SOC quality had higher Q₁₀ values than broadleaved forest soils with high SOC quality, which supported the “C quality temperature” hypothesis. Out of the spatial variations in Q₁₀ across all ecosystems, gram‐negative bacteria exhibited the most importance in regulating the variation in Q₁₀ and contributed 25.1%, followed by the C:N ratio (C quality), fungi, and the fungi:bacteria ratio. However, the dominant factors that regulate the regional variations in Q₁₀ differed among the tropical, subtropical, and temperate forest ecosystems. Overall, our findings highlight the importance of C quality and microbial controls over Q₁₀ value in China's forest ecosystems. Meanwhile, C dynamics in temperate forests under a global warming scenario can be robustly predicted through the incorporation of substrate quality and microbial property into models.     

Spatial patterns in temperature sensitivity of soil respiration in China: Estimation with inverse modeling

Temperature sensitivity of soil respiration (Q₁₀) is an important parameter in modeling the effects of global warming on ecosystem carbon release. Experimental studies of soil respiration have ubiquitously indicated that Q₁₀ has high spatial heterogeneity. However, most biogeochemical models still use a constant Q₁₀ in projecting future climate change and no spatial pattern of Q₁₀ values at large scales has been derived. In this study, we conducted an inverse modeling analysis to retrieve the spatial pattern of Q₁₀ in China at 8 km spatial resolution by assimilating data of soil organic carbon into a process-based terrestrial carbon model (CASA model). The results indicate that the optimized Q₁₀ values are spatially heterogeneous and consistent to the values derived from soil respiration observations. The mean Q10 values of different soil types range from 1.09 to 2.38, with the highest value in volcanic soil, and the lowest value in cold brown calcic soil. The spatial pattern of Q₁₀ is related to environmental factors, especially precipitation and top soil organic carbon content. This study demonstrates that inverse modeling is a useful tool in deriving the spatial pattern of Q₁₀ at large scales, with which being incorporated into biogeochemical models, uncertainty in the projection of future carbon dynamics could be potentially reduced.     

Soil respiration in six temperate forests in China

Scaling soil respiration (R_S), the major CO₂ source to the atmosphere from terrestrial ecosystems, from chamber‐based measurements to ecosystems requires studies on variations and correlations of R_S from various biomes and across geographic regions. However, few studies on R_S are available for Chinese temperate forest despite the importance of this forest in the national and global carbon budgets. In this study, we conducted 18‐month R_S measurements during 2004–2005 in six temperate forest types, representing the typical secondary forest ecosystems across various site conditions in northeastern China: Mongolian oak (Quercus mongolica Fisch.), aspen‐birch (Populous davidiana Dode and Betula platyphylla Suk.), mixed deciduous (no dominant tree species), hardwood (dominated by Fraxinus mandshurica Rupr., Juglans mandshurica Maxim., and Phellodendron amurense Rupr.) forests, Korean pine (Pinus koraiensis Sieb. et Zucc.) and Dahurian larch (Larix gmelinii Rupr.) plantations. Our specific objectives were to: (1) explore relationships of R_S against soil temperature and water content for the six forest ecosystems, (2) quantify annual soil surface CO₂ flux and its relations to belowground carbon storage, (3) examine seasonal variations in R_S and related environmental factors, and (4) quantify among‐ and within‐ecosystem variations in R_S. The R_S was positively correlated to soil temperature in all forest types, and was significantly influenced by the interactions of soil temperature and water content in the pine, larch, and mixed deciduous forests. The sensitivity of R_S to soil temperature at 10 cm depth (Q₁₀) ranged from 2.61 in the oak forest to 3.75 in the aspen‐birch forests. The Q₁₀ tended to increase with soil water content until reaching a threshold, and then decline. The annual R_S for the larch, pine, hardwood, oak, mixed deciduous, and aspen‐birch forests averaged 403, 514, 781, 785, 786, and 813 g C m^?2 yr^?1, respectively. The annual R_S of the broadleaved forests was 72% greater than that of the coniferous forests. The annual R_S was positively correlated to soil organic carbon (SOC) concentration at O horizon (R²=0.868) and total biomass of roots <0.5 cm in diameter (R²=0.748). The coefficient of variation (CV) of R_S among forest types averaged 25% across the 18‐month measurements. The CV of R_S within plots varied from 20% to 27%, significantly (P<0.001) greater than those among plots (9–15%), indicating the importance of the fine‐scaled heterogeneity in R_S. This study emphasized that variations in soil respiration and potential sampling bias should be appropriately tackled for accurate soil CO₂ flux estimates.     

Temperature-independent diel variation in soil respiration observed from a temperate deciduous forest

The response of soil respiration (R_s) to temperature depends largely on the temporal and spatial scales of interest and how other environmental factors interact with this response. They are often represented by empirical exponential equations in many ecosystem analyses because of the difficulties in separating covarying environmental responses and in observing below ground processes. The objective of this study was to quantify a soil temperature‐independent component in R_s by examining the diel variation of an R_s time series measured in a temperate deciduous forest located at Oak Ridge, TN, USA between March and December 2003. By fitting 2 hourly, continuous automatic chamber measurements of CO₂ efflux at the soil surface to a Q₁₀ function to obtain the temperature‐dependent respiration (R_t) and plotting the diel cycles of R_t, R_s, and their difference (R_i), we found that an obvious temperature‐independent component exists in R_s during the growing season. The diel cycle of this component has a distinct day/night pattern and agrees well with diel variations in photosynthetically active radiation (PAR) and air temperature. Elevated canopy CO₂ concentration resulted in similar patterns in the diel cycle of the temperature‐independent component but with different daily average rates in different stages of growing season. We speculate that photosynthesis of the stand is one of the main contributors to this temperature‐independent respiration component although more experiments are needed to draw a firm conclusion. We also found that despite its relatively small magnitude compared with the temperature‐dependent component, the diel variation in the temperature‐independent component can lead to significantly different estimates of the temperature sensitivity of soil respiration in the study forest. As a result, the common practice of using fitted temperature‐dependent function from night‐time measurements to extrapolate soil respiration during the daytime may underestimate daytime soil respiration.     

杉木人工林去除根系土壤呼吸的季节变化及影响因子

2007年1月至2008年12月,在长沙天际岭国家森林公园内,采用挖壕法研究杉木人工林去除根系后土壤呼吸速率季节动态及其与5 cm土壤温、湿度的相关关系。结果表明:去除根系与对照5 cm土壤温度的差异性不显著(P=0.987),5 cm土壤湿度差异显著(P=0.035)。杉木林去除根系处理后土壤呼吸速率明显降低,2007至2008两年实验期间去除根系与对照处理变化范围分别为0.19-2.01μmol.m-2s-1和0.26-2.61μmo.lm-2s-1,年均土壤呼吸速率分别为0.90μmo.lm-2s-1和1.30μmol.m-2s-1。去除根系土壤呼吸速率降低幅度为9.4%-59.7%,平均降低了30.4%。去除根系和对照的土壤呼吸速率与5 cm土壤温度之间均呈显著指数相关,模拟方程分别为:y=0.120e0.094t(R2=0.882,P=0.000),y=0.291e0.069t(R2=0.858,P=0.000)。Q10值分别为2.56和2.01。