沙坡头人工固沙植被土壤水分空间异质性

利用传统统计学和地统计学相结合的方法对沙坡头人工固沙植被区0～200 cm 之间的各层土壤水分的空间变异性进行研究.结果表明,1）土壤水分相对变异较大的层是在160～180 cm层和180～200 cm层,变异系数分别为0.72和0.73.表层0～5 cm层的相对变异也较大,变异系数为0.662）半方差函数分析结果表明,各层土壤水分均具有明显的空间变异性,各层土壤水分自相关部分的空间异质性占总空间异质性的程度很高,所占比例在87.7%～99.9%范围内.各层土壤水分的有效变程大小有较大差异,最小值出现在60～80 cm层(7.04 m),最大值出现在20～40 cm层(19.71 m),土壤水分有效变程从表层到深层没有明显的变化规律;3）土壤水分插值图反映出0～140 cm之间相邻各层土壤水分变化较大,140～200 cm各层土壤水分变化较小;4）土壤水分在0°、45°、90°、135°四个方向的半方差函数基本上是一条直线,表明在这四个方向上半方差和距离的相关性较低,土壤水分变化是独立、随机的,是同质性的.     

长白山阔叶红松林土壤无机氮空间异质性

利用地统计学方法,研究了长白山阔叶红松林内土壤表层(0～10cm)铵态氮和硝态氮的空间异质性.结果表明:长白山阔叶红松林内土壤表层铵态氮和硝态氮的半方差函数可用球状模型或高斯模型拟合.土壤表层铵态氮和硝态氮的空间分布均呈现中等程度的空间自相关,结构比范围分别在0.70%～41.47%和32.26%～52.66%;铵态氮的空间自相关尺度小于硝态氮,变程分别为8.87和9.76m.土壤表层铵态氮和硝态氮在空间上呈斑块状分布;铵态氮的空间异质性程度高于硝态氮,硝态氮与土壤水分呈显著负相关关系(r=-0.3743,P0.05),而铵态氮与土壤水分无显著的相关关系.     

黄土高原丘陵沟壑小流域土壤水分垂直分布变异特征及影响因子

以地统计学的半变异函数为分析工具,分析了黄土高原丘陵沟壑区小流域土壤水分在垂直方向的空间变异特征以及土地利用类型和地形等因子对其的影响.结果表明:1)球状模型可以很好地拟合土壤水分在垂直方向的半变异函数曲线,其存在强烈或中等程度的空间自相关,变程范围从2～5 m不等;2)果园对土壤水分含量的影响主要表现在1～2 m深度,5月份含量最高,且分布均匀,8月份由于气温和叶面蒸腾作用,水分含量最低.坡耕地和梯田的水分含量都较高,垂直变化不明显,梯田的土壤水分含量最低月份是9月,比坡耕地晚1个月,这是因为所种作物的主要生长季节为9月份,这期间消耗水分较多而造成的.林地由于根系发达,对土壤水分垂直方向的变化的影响比较大,变化为先增大、再减小、最后再增大且分布趋于平缓.灌木林的土壤水分含量整体较低,主要变化深度范围集中在0～2 m;草地的土壤水分含量较高,垂直变化的深度范围集中在1 m以内;3)坡度、坡向地形因子和土壤水分的垂直方向变异特征没有呈现明显的相关性.     

石栎-青冈常绿阔叶林土壤有机碳和全氮空间变异特征

在1hm2(100 m×100 m)石栎(Lithocarpus glaber)-青冈(Cyclobalanopsis glauca)常绿阔叶林内100个10 m×10 m小样方的中心位置,按0—10 cm、10—20 cm和20—30 cm土层采集土壤样品,测定土壤有机碳(C)和全氮(N)含量。基于区域化变量理论和地质统计软件(GS+Version 9)的空间分析功能,应用地统计学的半方差函数定量研究该常绿阔叶林土壤有机C和全N的空间变异特征。结果表明:该林地土壤有机C含量平均值为18.61 g/kg,变化范围为9.53—39.40 g/kg,全N含量平均值为1.63g/kg,变化范围为0.73—3.32 g/kg。土壤有机C半方差函数的理论模型符合球状模型,全N半方差函数的理论模型符合高斯模型。土壤有机C和全N的空间异质性主要是由结构性因素引起的,且空间自相关程度均为中等程度。分形维数反映了有机C和全N空间格局差异及尺度依赖特征,有机C分形维数较大,空间格局比全N略为复杂。采用Kriging插值方法,1hm2森林内土壤有机C和全N具有相似的空间分布格局,呈现明显的条带状和斑块状的梯度变化。土壤有机C含量与海拔、凹凸度呈负相关,但相关性不显著,与林地凋落物量呈极显著正相关。土壤全N含量与海拔、凹凸度呈显著负相关,与林地凋落物量呈正相关,反映出土壤N的淋溶特性。     

喀斯特峰丛洼地旱季土壤水分的空间变化及主要影响因子

基于动态监测样地(200 m×40 m)的网格(10 m×10 m)取样,用地统计学方法研究了喀斯特峰丛洼地4类典型生态景观类型旱季表层土壤(0—10 cm)水分的空间变化,通过主成分分析和相关分析,探讨了其生态学过程和机制。结果表明,沿严重、重度、中度和轻度的干扰递减梯度,喀斯特峰丛洼地产生了农作物(Ⅰ)→人工林(Ⅱ)→次生林(Ⅲ)→原生林(Ⅳ) 的4类典型生态景观格局变化,土壤水分显著提高,变异系数逐渐增大;4类生态景观类型的土壤水分均具有良好的空间自相关性,正负空间自相关距离反映了性质不同的两大斑块,Ⅰ、Ⅲ和Ⅳ下半部斑块的半径为50 m,拐点在坡地和洼地的分界处,Ⅱ的下半部斑块的半径为75 m,拐点是土地利用方式的转折点;不同景观类型空间变异特征不同,Ⅰ、Ⅱ、Ⅲ和Ⅳ的半变异函数分别符合指数模型、高斯模型、指数模型和球状模型,基台值(C0+C)升高,变程缩小,系统的空间总变异增强,其中Ⅰ和Ⅳ的\[C0/(C0+C)\]值分别为48.3%和39.4%,空间相关中等,Ⅱ和Ⅲ的\[C0/(C0+C)\]值≤25%,空间相关强烈;Kriging等值线图清楚表明Ⅰ和Ⅳ土壤水分呈凸型分布,Ⅱ呈单峰分布,Ⅲ呈凹型分布。主成分分析显示除海拔和坡位始终是影响4类生态景观类型土壤水分的主导因子外,不同景观类型的其他主导因子不同,且同一因子在不同景观类型与土壤水分的正负作用关系和相关程度也不同。因此,应根据4类典型生态景观类型土壤水分的空间变化及主要影响因子制定相应的水资源合理利用和管理策略。     

喀斯特常绿落叶阔叶混交林土壤磷钾养分空间异质性

在木论国家级自然保护区内喀斯特常绿落叶阔叶混交林内建立500 m×500 m长期监测样地,采用经典统计学和地统计学方法研究喀斯特森林土壤磷钾养分含量及其空间变异特征。结果表明:研究区土壤全磷(TP)、全钾(TK)、速效磷(AP)、速效钾(AK)含量分别为(1.60±0.76)g/kg、(5.42±2.74)g/kg、(5.74±3.63)mg/kg、(5.20±2.96)mg/kg;磷钾养分含量均为中等变异,变异强度为APAKTKTP。研究区土壤TP、TK、AP、AK变异函数值的最佳拟合模型均为指数模型,决定系数均很高(0.671-0.995),TP、AP呈中等强度空间自相关,TK、AK呈弱空间自相关。TP、AP的变程较长,分别为336.00 m和373.50 m,空间连续性较好,TK、AK变程较短(33.30 m、64.50 m),空间依赖性较强。土壤TP表现为坡下(含洼地)含量高,坡上含量较低;AK表现为坡中含量高于洼地含量;AP、TK呈斑块破碎化分布。海拔、坡度和地面凹凸度是土壤磷钾养分空间异质性的主要影响因素。喀斯特常绿落叶阔叶混交林土壤磷钾养分存在不同空间异质性和空间关联性,这为小流域尺度上土壤养分管理、可持续利用策略、喀斯特退化生态系统生态恢复提供理论依据。     

土壤温度和水分对油松林土壤呼吸的影响

用LI-COR 6400-09土壤呼吸测定系统,在太原天龙山自然保护区对油松林的土壤呼吸进行了4a测定.结果表明,土壤呼吸具有明显的季节变化特点,最大值出现在8月份,在6～10 μmol m~(-2) s~(-1) 之间,最小值出现在12月份和3月份,在0.5 μmol m~(-2) s~(-1)左右.2005、2006、2007和2008年土壤呼吸CO_2的年平均值分别为(4.71±3.74)、(3.08±2.91)、(2.96±2.58) μmol m~(-2) s~(-1)和(2.12±1.54) μmol m~(-2) s~(-1);4a的CO_2总平均值为(3.27±2.95) μmol m~(-2) s~(-1).4个测定年土壤呼吸的平均值总体差异显著.4个测定年土壤CO_2释放C量分别为1103.5、882.8、918.4 g m~(-2)和666.3 g m~(-2),总C平均值为892.8 g m~(-2),具有明显的年际差异.指数方程可以很好的表达土壤呼吸与10 cm深度土壤温度的关系,R~2值4a分别为0.39,0.60,0.68和0.71,Q_(10)值分别为3.10,4.41、4.05和5.18,用4a全部数据计算的Q_(10)值为4.31.土壤水分对土壤呼吸的作用较弱,R~2值4a分别仅为0.31、0.25、0.13和0.02,但是夏季土壤干旱对土壤呼吸的抑制作用非常明显,可使土壤呼吸下降50%以上.夏季土壤干旱是导致土壤呼吸年际变化的主要原因.4个包括土壤温度和水分的双变量模型均可以很好地模拟土壤呼吸的季节变化, 拟合方程的R~2值从0.58到0.79.     

哈尼梯田景观水源区土壤水分时空变异性

哈尼梯田景观的稳定维持依赖于上游水源区对水资源的涵养,土壤水分的时空变异性是揭示水源区土壤水源涵养格局的重要指标。通过网格法采集水源区表层(0~20cm)土样162个(旱季81个,雨季81个),应用经典统计学和地统计学方法分析水源区旱、雨季土壤水分空间变异特征。结果表明:(1)以200 m的间距采样,旱季土壤水分变异系数(Cv)为18.50%,半变异函数结构比值为99.9%,变程为383 m;雨季土壤水分Cv为18.19%,半变异函数结构比值为99.9%,变程475 m。土壤水分均呈中度变异,表现出高度的空间自相关性。从旱季到雨季,土壤水分的空间结构参数存在差异,变程变化最明显;各向异性存在一致性但各向异性比值差异明显。(2)Kriging插值图表明,旱季土壤水分空间格局明显呈斑块分布,斑块破碎度较大,空间连续性较差。雨季呈阶梯状分布,空间连续性强,土壤水分变异的复杂程度变小。旱、雨季土壤水分格局总体变化趋势较一致,但旱季的格局更显著,基本与土地利用格局分布相一致。(3)旱、雨季土壤含水量及其变异受降雨量影响而存在相一致的变化趋势,但旱季土壤水分对降雨量的反应较敏感。(4)土地利用是导致土壤水分空间变异的主要因素,降雨会加强或减弱这种差异的趋势;土壤水分含量受海拔的影响大,受坡度的影响小。(5)土壤水分时空变异能够反映水源涵养格局,对识别水源涵养关键区,保护水源区生态安全格局,维持整个流域水源供给平衡,维持梯田景观的稳定性意义重大。     

喀斯特地区坡耕地与退耕地土壤有机碳空间异质性及其影响因素

利用网格采样(10 m×10 m),对比分析了典型喀斯特坡耕地(长期耕作)和退耕地(自然恢复)表层(0—15 cm)土壤有机碳(SOC)的空间变异特征,以期探究退耕恢复20a后SOC的空间异质性及其主要影响因素的变化。结果表明退耕地SOC含量(75.5 g/kg)显著高于坡耕地(15.1 g/kg),为坡耕地的5.0倍,说明自然恢复能显著提高SOC累积量;半变异函数分析结果表明退耕地基台值(521.7)为坡耕地(25.7)的14.9倍,说明退耕地SOC空间异质性远大于坡耕地。坡耕地和退耕地SOC的主要影响因子存在较大差异,土地覆盖类型、坡位、岩石出露率以及三者的交互作用显著控制着坡耕地SOC的空间格局,其贡献率分别为9.1%、6.3%、4.6%以及17.0%;土壤水分、坡度、岩石出露率以及三者的交互作用显著控制退耕地SOC的空间格局,其贡献率分别为26.0%、10.7%、7.2%以及3.6%;尽管岩石出露率对坡耕地和退耕地SOC的空间格局均有显著影响,但坡耕地SOC的主要控制因子为土地覆盖类型以及各因子的交互作用,而退耕地的主要控制因子为土壤水分。以上研究表明随着植被恢复和物种多样性增加,喀斯特坡地SOC的累积量和空间异质性增强,自然因素对SOC空间格局影响凸显,而岩石出露率始终控制SOC空间格局。     

祁连山东段高原鼢鼠(Eospalax baileyi)土丘空间分布格局及其与环境因子的空间关联性

高原鼢鼠推土造丘行为对高寒草地生态系统的生产和生态功能有重要影响,研究高原鼢鼠土丘空间分布格局及其与环境因子的关系,可以揭示高原鼢鼠栖息地利用和选择规律,为合理控制鼠害及保护草地生物多样性提供科学依据。于2014年8月在祁连山东段选取面积为140m×100m的高原鼢鼠栖息地,消除景观尺度取样带来的气候、地形和土壤的异质性,利用地统计学方法,分析高原鼢鼠土丘的空间分布格局、并揭示其与环境因子中土壤容重、土壤水分、植物地上、地下生物量、根系营养物质含量(可溶性糖、粗蛋白、粗脂肪)以及各功能群丰富度(禾本科、莎草科、杂类草)的空间关系。半方差函数及普通克里格插值表明,高原鼢鼠土丘存在中等程度的空间变异且呈现聚集分布,各环境因子均存在不同程度的空间异质性。交方差函数分析表明,高原鼢鼠分布虽与各环境因子在多种尺度下表现出复杂的空间关联性(正的或负的),但mantel检验发现土壤容重、莎草科丰富度与高原鼢鼠土丘分布呈现显著的负空间关联性,杂类草丰富度和根系粗脂肪含量与高原鼢鼠土丘分布存在显著正空间关联性。综上所述,高原鼢鼠主要栖息利用在土壤疏松、莎草科丰富度较低、杂类草较多和根系粗脂肪含量较高的地方。     

A comparison of manual and automated systems for soil CO2 flux measurements: trade-offs between spatial and temporal resolution

Soil respiration is affected by distributions of roots and soil carbon substrates and by temperature and soil water content, all of which vary spatially and temporally. The objective of this paper was to compare a manual system for measuring soil respiration in a temperate forest, which had a greater spatial distribution of measurements (n=12), but poorer temporal resolution (once per week), with an automated system which had poorer spatial distribution (n=3) but superior temporal frequency of measurements (hourly). Soil respiration was measured between 18 June and 21 August, 2002, at the Harvard Forest in central Massachusetts, USA. The fluxes measured within 1 h of each other by these systems were not significantly different. However, extrapolations of the mid-morning manual measurements to daily flux values were consistently lower (averaging 13% lower) than the daily estimates obtained from summing the 24 hourly measurements of the automated system. On the other hand, seasonal flux estimates obtained by interpolating between weekly manual sampling dates or by summing the hourly automated measurements were nearly identical. Underestimates by interpolated weekly manual measurements during some periods were cancelled by overestimates during other periods. Hence, a weekly sampling schedule may be sufficient to capture the most important variation of seasonal efflux of CO(2) from the soil. The larger number of chambers that could be measured with the manual system (larger n) resulted in a smaller 95% confidence interval for characterizing spatial variability within the study area on most dates. However, the greater sampling frequency of the automated system revealed rapid responses of soil respiration to wetting events, which permitted better empirical modelling of the effects of soil temperature and moisture on soil respiration than could have been achieved with the manual sampling system. Most of the positive residuals of a function that predicts soil respiration based on temperature were from fluxes measured within 12 h of a rain event, and the residuals were positively correlated with water content of the O horizon. The automated system also demonstrated that Q(10) values calculated for diel variation in soil temperature over a few days were not significantly different than Q(10) values for the entire 3 month summer sampling period. In summary, a manual system of numerous, spatially well-distributed flux chambers measured on a weekly basis may be adequate for measuring seasonal fluxes and may maximize confidence in the characterization of spatial variance. The high temporal frequency of measurements afforded by automation greatly improves the ability to measure and model the effects of rapidly varying water content and temperature. When the two approaches can be combined, the temporal representativeness of the manual measurements can be tested with the automated measurements and the spatial representativeness of the automated measurements can be tested by the manual measurements.     

Topographic and climatic controls on soil respiration in six temperate mixed-hardwood forest slopes, Korea

To better understand the effects of local topography and climate on soil respiration, we conducted field measurements and soil incubation experiments to investigate various factors influencing spatial and temporal variations in soil respiration for six mixed‐hardwood forest slopes in the midst of the Korean Peninsula. Soil respiration and soil water content (SWC) were significantly greater (P=0.09 and 0.003, respectively) on north‐facing slopes compared to south‐facing slopes, while soil temperature was not significantly different between slopes (P>0.5). At all sites, soil temperature was the primary factor driving temporal variations in soil respiration (r²=0.84–0.96) followed by SWC, which accounted for 30% of soil respiration spatial and temporal variability. Results from both field measurements and incubation experiments indicate that variations in soil respiration due to aspect can be explained by a convex‐shaped function relating SWC to normalized soil respiration rates. Annual soil respiration estimates (1070–1246 g C m^?2 yr^?1) were not closely related to mean annual air temperatures among sites from different climate regimes. When soils from each site were incubated at similar temperatures in a laboratory, respiration rates for mineral soils from wetter and cooler sites were significantly higher than those for the drier and warmer sites (n=4, P<0.01). Our results indicate that the application of standard temperature‐based Q₁₀ models to estimate soil respiration rates for larger geographic areas covering different aspects or climatic regimes are not adequate unless other factors, such as SWC and total soil nitrogen, are considered in addition to soil temperature.     

土壤呼吸作用时空动态变化及其影响机制研究与展望

测定不同陆地生态系统土壤呼吸速率及其时空波动, 阐明其影响因子, 对于全球碳素平衡预算和全球变化潜在效应估计是最为基本的数据。然而, 有关土壤呼吸作用变异性及其影响因素的知识仍存在局限性, 一些关键的过程和机制还有待阐明。该文综述了近年来土壤呼吸作用时空动态规律、影响机制和模拟方面的研究进展, 指出环境因子和生物因子共同驱动着土壤呼吸作用的时间动态变化; 土壤呼吸作用在不同时间尺度上还具有明显的空间异质性, 这主要是植被覆盖、根系分布、主要的环境因素和土壤特性空间分布的异质性造成的。生物因子是影响土壤呼吸作用时空动态变化的主要因素之一。然而, 目前所使用的土壤呼吸作用经验模型通常利用土壤温度、土壤湿度或者两者的交互作用模拟土壤呼吸作用动态变化, 但没有考虑生物因子的影响, 这可能会导致明显的偏差和错误。因此, 为了精确估算土壤呼吸作用, 必须解决土壤呼吸作用小尺度上的空间变异性; 加强不同时间尺度上生物要素对土壤呼吸作用动态变化的影响研究; 除了气候因子外, 土壤呼吸作用经验模型应该纳入生物因子等其它影响因素作为变量, 用以提高模型模拟的正确性和准确性。     

Frontiers and challenges in soil respiration research: from measurements to model-data integration

Soil respiration, the flux of CO₂ from the soil to the atmosphere represents a major flux in the global carbon cycle. Our ability to predict this flux remains limited because of multiple controlling mechanisms that interact over different temporal and spatial scales. However, new advances in measurement and analyses present an opportunity for the scientific community to improve the understanding of the mechanisms that regulate soil respiration. In this paper, we address several recent advancements in soil respiration research from experimental measurements and data analysis to new considerations for model-data integration. We focus on the links between the soil?Cplant-atmosphere continuum at short (i.e., diel) and medium (i.e., seasonal-years) temporal scales. First, we bring attention to the importance of identifying sources of soil CO₂ production and highlight the application of automated soil respiration measurements and isotope approaches. Second, we discuss the need of quality assurance and quality control for applications in time series analysis. Third, we review perspectives about emergent ideas for modeling development and model-data integration for soil respiration research. Finally, we call for stronger interactions between modelers and experimentalists as a way to improve our understanding of soil respiration and overall terrestrial carbon cycling.     

Soil respiration fluxes measured along a hydrological gradient in a Norway spruce stand in south Sweden (Skogaby)

Soil respiration fluxes were measured continuously in order to assess the degree to which they were influenced by spatial and temporal variation in soil moisture. The synergistic effects of the variation in soil moisture with the one in soil temperature, soil organic matter and global radiation on respiration fluxes were also analysed. The measurements were performed using an open chamber system along a hydrological gradient in a Norway spruce forest in south Sweden (Skogaby) for 3 weeks in June 1995. The measured soil respiration fluxes were quite stable and somewhat larger compared with those reported in literature. The experiment took place during the shoot elongation period with intensive nutrient uptake, and it might be that soil respiration was dominated by mycorrhizal activity. Variation in the moisture content of the litter layer accounted for most of the spatial variation in respiration fluxes. This revised version was published online in June 2006 with corrections to the Cover Date.     

Spatial and temporal simulation of soil CO2 concentrations in a small forested catchment in Virginia

The question of how to extrapolate point measurements of soil CO₂ processes to coarser scales remains unanswered because we know little about the spatial and temporal variability in the CO₂ concentration of soil air. In this work, we describe a series of simple physically-based models that simulate soil temperature, soil tension, and soil CO₂ processes. We apply these models to simulate the spatial and temporal dynamics of soil CO₂ concentrations throughout a small catchment in the Virginia Blue Ridge. Output from the simulations is compared with field measurements. We find that despite some model deficiencies, we are able to simulate the gross patterns through space and time of soil air CO₂ concentration. During the growing season when soil temperature is high, we find that soil water status is the limiting control on soil respiration and CO₂ concentration. We also find that soil CO₂ concentration can be high despite low respiration values due to decreased soil diffusivity as moisture fills pore spaces.     

中国草原土壤呼吸作用研究进展

中国草原面积约占国土面积的40%, 且大都位于生态脆弱区, 对气候和环境变化十分敏感, 在未来大气CO₂调控中有着重要的作用。为增进对中国草原土壤呼吸作用的理解, 该文综述了近10年来中国草原土壤呼吸作用的最新研究进展, 指出中国草原土壤呼吸作用的研究主要集中在东北平原、内蒙古高原和青藏高原。草原土壤呼吸作用日动态的主导控制因子是温度, 季节动态的主导控制因子可以是温度、水分或二者的交互作用, 取决于研究地点的限制性环境因子, 而年际动态的主导控制因子为水分。草原土壤呼吸作用还存在着巨大的空间变异, 年降水和土壤全氮含量是不同类型草原土壤呼吸作用空间异质性的主导控制因子。土壤呼吸作用对全球变化的响应比较复杂, 取决于各因子之间相互影响的贡献。现有的土壤呼吸作用模型大多只考虑了水热因子, 很少包含土壤因子和生物因子及其协同作用的影响。在此基础上, 指出未来中国草原土壤呼吸作用拟加强的研究重点: 1)温带荒漠草原土壤呼吸作用研究; 2)非生长季土壤呼吸作用研究; 3)多时空尺度草原土壤呼吸作用的比较研究; 4)草原土壤呼吸作用过程模拟研究; 5)草原土壤呼吸作用的遥感监测评估研究。     

Toward a general evaluation model for soil respiration (GEMSR)

Soil respiration is an important component of terrestrial carbon budget. Its accurate evaluation is es- sential to the study of terrestrial carbon source/sink. Studies on soil respiration at present mostly focus on the temporal variations and the controlling factors of soil respiration, but its spatial variations and controlling factors draw less attention. Moreover, the evaluation models for soil respiration at present include only the effects of water and heat factors, while the biological and soil factors controlling soil respiration and their interactions with water and heat factors have not been considered yet. These models are not able to accurately evaluate soil respiration in different vegetation/terrestrial ecosystems at different temporal and spatial scales. Thus, a general evaluation model for soil respiration (GEMSR) including the interacting meteorological (water and heat factors), soil nutrient and biological factors is suggested in this paper, and the basic procedure developing GEMSR and the research tasks of soil respiration in the future are also discussed.     

Toward a general evaluation model for soil respiration (GEMSR)

Soil respiration is an important component of terrestrial carbon budget. Its accurate evaluation is essential to the study of terrestrial carbon source/sink. Studies on soil respiration at present mostly focus on the temporal variations and the controlling factors of soil respiration, but its spatial variations and controlling factors draw less attention. Moreover, the evaluation models for soil respiration at present include only the effects of water and heat factors, while the biological and soil factors controlling soil respiration and their interactions with water and heat factors have not been considered yet. These models are not able to accurately evaluate soil respiration in different vegetation/terrestrial ecosystems at different temporal and spatial scales. Thus, a general evaluation model for soil respiration (GEMSR) including the interacting meteorological (water and heat factors), soil nutrient and biological factors is suggested in this paper, and the basic procedure developing GEMSR and the research tasks of soil respiration in the future are also discussed.     

中国农田土壤呼吸速率及驱动因子

土壤呼吸在全球碳收支中具有重要地位.研究中国典型农业区土壤呼吸的时空格局及影响因素,有助于构建区域尺度土壤呼吸定量评价模型,能够为评估中国乃至全球农业生态系统碳/源汇特征提供依据.本研究整合了2000~2012年中国农田生态系统土壤呼吸的主要研究成果,分析了华南、西南、华北、西北和东北5个典型农业区土壤呼吸的季节变化和区域差异,以及影响土壤呼吸的主要驱动因子.结果表明,5个典型农业区的土壤呼吸均存在明显的季节变化特征;中国农田生态系统年均土壤呼吸速率为(682.8±18.3)g C m?2.5个典型农业区年均土壤呼吸速率大小表现为华南区西南区华北区东北区西北区.全国农业土壤的年呼吸通量为(0.90±0.02)Pg C;水作和旱作两种土地利用类型间土壤呼吸速率差异显著(P0.05),旱作土壤呼吸速率约为水作的1.3倍;不同作物类型间土壤呼吸速率差异显著(P0.05),其排序为棉花玉米大豆水稻小麦;农田土壤呼吸与年均气温、土壤温度、土壤含水量和净初级生产力等影响因素呈显著正相关(P0.01),而与年均降水量的相关性不显著.