冬小麦农田尺度瞬态CO2通量与水分利用效率日变化及影响因素分析

以华北平原冬小麦农田尺度为研究对象,采用涡度相关技术,研究冬小麦灌浆期瞬态CO2通量日变化特征及其与农田热量平衡各分量的关系。结果表明,非水分胁迫下CO2通量日变化(负值表示通量指向冠层)为U型,群体净光合速率最高值为-1.2~-1.4mg/m2.s,夜间瞬态CO2通量呈非稳定变化,最高值达0.4~0.54mg/m2.s。白天时段内CO2通量与净辐射、潜热通量呈高度相关,8:00~15:30时段内CO2和水汽通量呈同步日变化趋势,水分利用效率处于稳定状态,瞬态水分利用效率基本维持在0.012~0.014g(CO2)/g(H2O)范围内;但早晨和傍晚时段内水分利用效率变化较大。     

小兴安岭天然阔叶混交林生长季CO_2通量特征分析

森林生态系统CO2通量的研究已成为全球变化研究的热点之一。本文采用开路式涡度相关系统对小兴安岭天然阔叶混交林CO2通量进行为期1a的连续观测（2008年）,分析了生长季（5-9月）CO2通量的变化特征。结果表明,在生长季,天然阔叶混交林系统的CO2通量变化范围为-0.46～0.42mg.m-2.s-1;最大吸收量出现在6月份的9：00,最大释放量出现在7月份的5：00。白天气温低于26.63℃时,碳吸收量随气温的升高而加大;但气温超过26.63℃后,则呈相反趋势。夜晚气温在13.50℃时的碳释放量最大。2008年整个生长季呈现白天碳吸收,夜晚碳释放的现象,总体表现为碳吸收,吸收总量为212.32g.m-2。     

淮河流域典型农田生态系统碳通量变化特征

为了准确评价农田生态系统在全球碳平衡中的作用,利用涡度相关技术对安徽省寿县冬小麦／水稻生态系统进行了碳通量的监测,并在数据校正、剔除和插补的基础上,研究生长季农田净生态系统碳交换（NEE）的变化特征。结果显示,2008年寿县农田生态系统CO2通量的日变化进程为单峰型,冬小麦和水稻最大的CO2吸收速率分别为2．45和2．48mg·m^-2·s^-1。从物候期的角度来看,冬小麦在抽穗期碳通量值最小,乳熟期最大;水稻拔节时期碳通量值最小,即固碳能力最强。冬小麦,水稻生态系统不同月份碳通量月均日变化也呈U型曲线,作物生命活动越旺盛,NEE峰值越高,夜间CO2排放则在8月份达到最高值。2008年冬小麦和水稻月平均最大日CO2吸收峰分别出现在4月和8月,分别为1．30和1．07mg·m^-2．s^-1。冬小麦生态系统NEE的日最大累积吸收量出现在4月16日．可达11．76gC·m^-2·d^-1,水稻生态系统的出现在8月3日,为10．40gC·m^-2·d^-1。冬小麦从拔节到成熟时间段内的固碳能力为326．87gC·m^-1,水稻从返青到成熟时间段内的固碳能力也达到了300．05gC·m^-2。     

江汉平原稻-油连作系统冠层CO2通量变化特征

采用涡度相关法,于2010年和2011年对江汉平原水稻-油菜连作田冠层CO2通量进行周年观测,研究该系统CO2源、汇的季节和日变化规律。结果表明,CO2通量的日变化特征明显,各生育期平均CO2通量日变化幅度较大。将观测期通量数据插值后得到CO2净交换通量(NEE)的逐日变化过程,油菜收割后闲置期-中稻移栽期、分蘖期、拔节-抽穗期、乳熟期的平均NEE分别为1.63、-11.86、-20.61、-4.65g.m-2.d-1;水稻收割后的闲置期、油菜苗期-现蕾期、抽薹期、开花期、绿熟期平均NEE值分别为2.18、0.43、-5.00、-11.70、-13.91g.m-2.d-1。全年稻-油连作农田生态系统净CO2吸收量为19.26 t.hm-2。     

通量及其不确定性对农业区高塔CO_2浓度模拟的影响

利用WRF-STILT模型模拟玉米种植区生长季(6-9月)小时CO_2浓度,并基于美国最大农业种植区‘玉米带’100m高塔CO_2浓度观测数据,对WRF-STILT模型的模拟能力及CO_2通量的不确定性对模拟结果的影响进行分析。结果表明:(1)WRF-STILT能够模拟高塔观测的CO_2浓度日变化特征,模拟值与观测值的均方根误差为13.70mmol×mol~(-1),模拟结果偏高7.26mmol×mol~(-1)。(2)EDGAR和Carbon Tracker两种典型化石燃料的CO_2通量,其区域平均值相差6%,但两者对CO_2浓度增加值的模拟结果相差约10%;(3)CO_2通量空间分辨率的差异会导致模拟结果产生偏差,使用区域边长为1o的EDGAR化石燃料CO_2通量模拟的浓度贡献值仅为0.1o的0.4倍,且空间分辨率越低,模拟误差越大;(4)白天和夜晚Carbon Tracker模拟的植被生态系统净交换数据是高塔涡度相关方法观测结果的2.26和1.56倍,下垫面分类的误差以及相应的通量模拟误差使模拟的CO_2浓度贡献出现12mmol×mol~(-1)的差异,这是模拟结果偏高7.26mmol×mol~(-1)的潜在误差来源。研究认为,WRF-STILT模型和高空间及时间分辨率的CO_2通量能够较好模拟出农业区生长季的CO_2强日变化特征,CO_2通量的误差是模拟结果误差的主要来源,研究结果表明该方法具有评估和优化通量的巨大潜力。     

东亚森林、草地碳利用效率及碳通量空间变化的影响因素分析

森林和草地是陆地生态系统的重要组成部分,研究整合基于涡度相关法观测碳通量的已发表文献,共选取东亚地区40个拥有1年以上数据的通量站(森林26个,草地14个),分析碳利用效率(CUE)以及净生态系统生产力(NEP)、总生态系统生产力(GEP)、生态系统呼吸(RE)的空间变异特征及其影响因素。东亚地区的森林和草地为碳汇,且森林的碳汇显著高于草地(p0.001),其NEP分别为328.64±256.46gC/(m~2·a),63.43±42.99gC/(m~2·a)。森林和草地的CUE分别为0.21,0.20,影响森林CUE变化的因素主要是林龄,呈线性负相关关系(p0.001)。影响草地CUE的因素主要是年均降水量(MAP),呈线性负相关关系(p0.05)。森林和草地的GEP,RE均是随纬度的升高而线性降低,NEP与纬度呈现二次函数关系,随纬度升高而先升高后降低。森林和草地的GEP,RE都与MAP呈线性正相关关系,且NEP与MAP呈先升高后降低的二次函数关系,其中森林和草地的饱和降水量大约为1 300mm和390mm。森林的GEP,RE与年均温(MAT)呈现线性正相关关系。森林和草地的GEP,RE与增强型植被指数(EVI)呈线性正相关关系。     

不同通量计算方法对静态箱法测定农田N2O排放通量的影响

通过观测冬小麦拔节期施肥后1周内N2O排放,研究了采用静态箱技术时,线性回归（LR）、Quad回归和HM计算方法对N2O排放通量的影响,同时分析了施肥（Nc）和不施肥（CK）对N2O气体交换的影响。结果表明：通过LR、Quad和HM方法处理相同数据得到的N2O排放通量及其特征确实存在较大的差异,由3种方法得到的通量变异系数最高可达到71%;未采用TFU技术校正前,3种计算方法之间的变异系数平均为29%,而校正后则降低到13%;同时还发现,这3种技术均在一定程度上低估了N2O的排放通量,与校正后的排放通量相比,施肥处理中LR、Quad和HM的N2O排放通量分别偏低了14%～31%、5%～48%和3%～62%,对照则分别偏低了14.9%～16.0%、15.5%～35.2%和8.4%～57.2%。因此,采用TUF校正方法不仅可定量分析不同计算方法之间的差异,同时也降低了N2O排放通量的误差。     

密度修正对冬小麦/夏玉米轮作田潜热、CO2通量及其能量闭合度的影响

本文利用涡度相关技术对青岛农业大学现代农业科技示范园试验站2013—2014年冬小麦/夏玉米轮作田与大气之间CO_2、水汽和能量交换进行测量,分别对潜热和CO_2通量进行两种密度修正(WPL修正和Liu修正)并进行对比,计算了两种密度修正前后冬小麦/夏玉米轮作田的能量闭合度。结果表明:WPL修正与Liu修正可以提高潜热通量,WPL修正后夏玉米田潜热通量约提高6%,冬小麦田约提高2%;Liu修正后夏玉米田提高不足1%,冬小麦田提高约2%。因此WPL修正对于夏玉米田潜热的修正效果明显优于Liu修正,而对冬小麦田潜热修正两种方法效果相同。两种修正方法对于CO_2通量具有降低的修正效果,WPL修正后夏玉米田和冬小麦田CO_2通量分别降低3%和4%;Liu修正后夏玉米田和冬小麦田CO_2分别降低2%和3%。可以看出,WPL修正和Liu修正对CO_2通量修正前后差别非常小(差距均为1%)。通过对青岛地区冬小麦/夏玉米轮作田能量闭合度的分析,发现密度修正可以提高能量闭合度,但不同下垫面有不同的修正效果。裸地情况下,WPL修正可以提高能量闭合度约2.53%~9.76%,夏玉米田为4.05%,冬小麦田为1.35%;而Liu修正对裸地能量闭合度的提高小于2.53%,对夏玉米田和冬小麦田提高约为1.35%。显然WPL修正对于能量闭合度的修正幅度大于Liu修正。能量闭合度大小关系为裸地Ⅰ(夏玉米出苗前)裸地Ⅱ(冬小麦出苗前)夏玉米田冬小麦田。     

R-K蒸散模型用于华北平原冬小麦农田的参数校正与评价

为了解华北平原冬小麦田蒸散特征,并对蒸散估算模型在冬小麦田的适用性和稳定性进行分析,该文利用涡度相关系统对2013-2015年冬小麦田的蒸散量进行观测,以气象数据为基础对估算模型Rana和Katerji模型(简称R-K模型)进行修正;利用修正后模型对日蒸散量进行预测;并与FAO-PM模型的预测值及涡度相关系统的测量值进行对比,来说明R-K模型在冬小麦田的适用性。结果表明冬小麦田蒸散量有明显的季节变化,日蒸散量在1月底最小,返青期开始逐渐增大,于4、5月份达到最大值;2个冬小麦生长季总蒸散量分别为436.3和334.8 mm。统计参数的对比说明修正后R-K模型对冬小麦田日蒸散量的预测效果优于FAO-PM模型。敏感性分析说明R-K模型对气象因素不敏感,稳定性良好。R-K模型对冬小麦不同生长阶段的蒸散量预测效果在后期表现最佳,其次为发育期、中期和初期,越冬期表现最差。该研究可为利用模型估算蒸散量及指导农田精确灌溉提供参考。     

三江平原稻田能量通量研究

基于三江平原稻田2005~2007年5~10月涡度相关通量观测数据, 分析了该区稻田能量通量的日变化、季节变化和能量分配特征以及能量平衡状况。结果表明: 三江平原稻田净辐射和潜热通量日变化均表现为明显的单峰特征, 感热通量日变化在水稻发育进入成熟期后才较明显, 而土壤热通量在水稻整个发育期内日变化特征都不明显。稻田净辐射季节变化特征显著, 6月下旬至7月上旬达到最大值18~20 MJ·m^-2·d^-1。潜热通量季节变化与净辐射同步, 最大值为13~19 MJ·m^-2·d^-1。相比之下感热通量较小, 观测期间变化于-3.90~ 3.94 MJ·m^-2·d^-1, 且没有明显的季节变化。5~10月土壤热通量呈下降趋势, 变化于-2.67~3.62 MJ·m^-2·d^-1。三江平原地区稻田能量分配特征明显, 潜热通量占净辐射的比例(LE/Rn) 5~10月平均值为0.67, 表明净辐射大部分以潜热通量形式所消耗, 但生长旺季LE/Rn略大于生长季初期和末期。感热通量占净辐射的比例(Hs/Rn)的季节变化特征与LE/Rn比值相反, 观测期间平均值为0.10。这导致波文比在水稻生长旺季较小而在初期和末期较大。5~10月土壤热通量占净辐射的比例(G/Rn)呈逐渐下降趋势, 其月平均值由5月的0.14下降到10月的-0.08。线性回归法和能量平衡比率均表明三江平原稻田能量明显不闭合, 2005、2006年5~10月能量不闭合度分别为22%和16%, 而2007年能量“过闭合”, 能量平衡比率平均值为1.07。     

Resolving systematic errors in estimates of net ecosystem exchange of CO2 and ecosystem respiration in a tropical forest biome

The controls on uptake and release of CO₂ by tropical rainforests, and the responses to a changing climate, are major uncertainties in global climate change models. Eddy-covariance measurements potentially provide detailed data on CO₂ exchange and responses to the environment in these forests, but accurate estimates of the net ecosystem exchange of CO₂ (NEE) and ecosystem respiration (R_eco) require careful analysis of data representativity, treatment of data gaps, and correction for systematic errors. This study uses the comprehensive data from our study site in an old-growth tropical rainforest near Santarem, Brazil, to examine the biases in NEE and R_eco potentially associated with the two most important sources of systematic error in Eddy-covariance data: lost nighttime flux and missing canopy storage measurements. We present multiple estimates for the net carbon balance and R_eco at our site, including the conventional “u* filter”, a detailed bottom-up budget for respiration, estimates by similarity with ²²²Rn, and an independent estimate of respiration by extrapolation of daytime Eddy flux data to zero light. Eddy-covariance measurements between 2002 and 2006 showed a mean net ecosystem carbon loss of 0.25 ± 0.04 μmol m⁻² s⁻¹, with a mean respiration rate of 8.60 ± 0.11 μmol m⁻² s⁻¹ at our site. We found that lost nocturnal flux can potentially introduce significant bias into these results. We develop robust approaches to correct for these biases, showing that, where appropriate, a site-specific u* threshold can be used to avoid systematic bias in estimates of carbon exchange. Because of the presence of gaps in the data and the day–night asymmetry between storage and turbulence, inclusion of canopy storage is essential to accurate assessments of NEE. We found that short-term measurements of storage may be adequate to accurately model storage for use in obtaining ecosystem carbon balance, at sites where storage is not routinely measured. The analytical framework utilized in this study can be applied to other Eddy-covariance sites to help correct and validate measurements of the carbon cycle and its components.     

Estimating nocturnal ecosystem respiration from the vertical turbulent flux and change in storage of CO2

Micrometeorological measurements of nighttime ecosystem respiration can be systematically biased when stable atmospheric conditions lead to drainage flows associated with decoupling of air flow above and within plant canopies. The associated horizontal and vertical advective fluxes cannot be measured using instrumentation on the single towers typically used at micrometeorological sites. A common approach to minimize bias is to use a threshold in friction velocity, u_*, to exclude periods when advection is assumed to be important, but this is problematic in situations when in-canopy flows are decoupled from the flow above. Using data from 25 flux stations in a wide variety of forest ecosystems globally, we examine the generality of a novel approach to estimating nocturnal respiration developed by van Gorsel et al. (van Gorsel, E., Leuning, R., Cleugh, H.A., Keith, H., Suni, T., 2007. Nocturnal carbon efflux: reconciliation of eddy covariance and chamber measurements using an alternative to the u_*-threshold filtering technique. Tellus 59B, 397–403, Tellus, 59B, 307-403). The approach is based on the assumption that advection is small relative to the vertical turbulent flux (F_C) and change in storage (F_S) of CO₂ in the few hours after sundown. The sum of F_C and F_S reach a maximum during this period which is used to derive a temperature response function for ecosystem respiration. Measured hourly soil temperatures are then used with this function to estimate respiration R_Rmax. The new approach yielded excellent agreement with (1) independent measurements using respiration chambers, (2) with estimates using ecosystem light-response curves of F_c + F_s extrapolated to zero light, R_LRC, and (3) with a detailed process-based forest ecosystem model, R_cast. At most sites respiration rates estimated using the u_*-filter, R_ust, were smaller than R_Rmax and R_LRC. Agreement of our approach with independent measurements indicates that R_Rmax provides an excellent estimate of nighttime ecosystem respiration.     

黄土区土壤CO2释放及其影响因素研究

研究表明黄土区土壤CO2释放具有一定特殊性。从当日清晨至次日晨土壤CO2释放量呈由高至低再变高的规律,其变化趋势大体与温度变化一致,但时间上有一定滞后性。土壤CO2释放量有明显季节变化,夏季日释放量最高,秋季次之,冬季最低。不同覆被土壤CO2释放量存在差异,裸地释放量较高。CO2释放量对土质变化敏感,致密土壤则释放量小。     

Regional surface flux of CO2 inferred from changes in the advected CO2 column density

A Lagrangian experiment was conducted over Iowa during the daytime (9:00–17:30 LT) on June 19, 2007 as part of the North American Carbon Program's Mid-Continent Intensive using a light-weight and operationally flexible aircraft to measure a net drawdown of CO₂ concentration within the boundary layer. The drawdown can be related to net ecosystem exchange when anthropogenic emissions are estimated using a combination of the Vulcan fossil fuel emissions inventory coupled with a source contribution analysis using HYSPLIT. Results show a temporally and spatially averaged net CO₂ flux of −9.0 ± 2.4 μmol m⁻² s⁻¹ measured from the aircraft data. The average flux from anthropogenic emissions over the measurement area was 0.3 ± 0.1 μmol CO₂ m⁻² s⁻¹. Large-scale subsidence occurred during the experiment, entraining 1.0 ± 0.2 μmol CO₂ m⁻² s⁻¹ into the boundary layer. Thus, the CO₂ flux attributable to the vegetation and soils is −10.3 ± 2.4 μmol m⁻² s⁻¹. The magnitude of the calculated daytime biospheric flux is consistent with tower-based eddy covariance fluxes over corn and soybeans given existing land-use estimates for this agricultural region. Flux values are relatively insensitive to the choice of integration height above the boundary layer and emission footprint area. Flux uncertainties are relatively small compared to the biospheric fluxes, though the measurements were conducted at the height of the growing season.     

Interactions between physical and biotic factors influence CO2 flux in Antarctic dry valley soils

Soil carbon dioxide (CO₂) flux is an integrative measure of ecosystem functioning representing both biotic and physical controls over carbon (C) balance. In the McMurdo Dry Valleys of Antarctica, soil CO₂ fluxes (approximately −0.1-0.15 μmol m⁻² s⁻¹) are generally low, and negative fluxes (uptake of CO₂) are sometimes observed. A combination of biological respiration and physical mechanisms, driven by temperature and mediated by soil moisture and mineralogy, determine CO₂ flux and, therefore, soil organic C balance. The physical factors important to CO₂ flux are being altered with climate variability in many ecosystems including arid forms such as the Antarctic terrestrial ecosystems, making it critical to understand how climate factors interact with biotic drivers to control soil CO₂ fluxes and C balances. We measured soil CO₂ flux in experimental field manipulations, microcosm incubations and across natural environmental gradients of soil moisture to estimate biotic soil respiration and abiotic sources of CO₂ flux in soils over a range of physical and biotic conditions. We determined that temperature fluctuations were the most important factor influencing diel variation in CO₂ flux. Variation within these diel CO₂ cycles was explained by differences in soil moisture. Increased temperature (as opposed to temperature fluctuations) had little or no effect on CO₂ flux if moisture was not also increased. We conclude that CO₂ flux in dry valley soils is driven primarily by physical factors such as soil temperature and moisture, indicating that future climate change may alter the dry valley soil C cycle. Negative CO₂ fluxes in arid soils have recently been identified as potential net C sinks. We demonstrate the potential for arid polar soils to take up CO₂, driven largely by abiotic factors associated with climate change. The low levels of CO₂ absorption into soils we observed may not constitute a significant sink of atmospheric CO₂, but will influence the interpretation of CO₂ flux for the dry valley soil C cycle and possibly other arid environments where biotic controls over C cycling are secondary to physical drivers.     

Soil CO2 flux in six monospecific forest plantations in Southern Rwanda

Forest soils contain the largest carbon stock of all terrestrial biomes and are probably the most important source of carbon dioxide (CO₂) to atmosphere. Soil CO₂ fluxes from 54 to 72-year-old monospecific stands in Rwanda were quantified from March 2006 to December 2007. The influences of soil temperature, soil water content, soil carbon (C) and nitrogen (N) stocks, soil pH, and stand characteristics on soil CO₂ flux were investigated. The mean annual soil CO₂ flux was highest under Eucalyptus saligna (3.92 μmol m⁻² s⁻¹) and lowest under Entandrophragma excelsum (3.13 μmol m⁻² s⁻¹). The seasonal variation in soil CO₂ flux from all stands followed the same trend and was highest in rainy seasons and lowest in dry seasons. Soil CO₂ flux was mainly correlated to soil water content (R² = 0.36-0.77), stand age (R² = 0.45), soil C stock (R² = 0.33), basal area (R² = 0.21), and soil temperature (R² = 0.06-0.17). The results contribute to the understanding of factors that influence soil CO₂ flux in monocultural plantations grown under the same microclimatic and soil conditions. The results can be used to construct models that predict soil CO₂ emissions in the tropics.     

不同水分条件麦田能量与CO2通量变化特征研究

试验观测不同水分处理冬小麦田能量平衡各分量、反射率和CO2 通量日变化及日际变化特征结果表明 ,小麦拔节期麦田地表反射率平均值约为 0 .18,不同水分处理农田潜热通量和显热通量均有明显差异 ,晴朗天气冬小麦冠层顶部CO2 通量日变化呈抛物线形 ,麦田主要表现为CO2 的汇。     

Strong seasonal variations in net ecosystem CO2 exchange of a tropical pasture and afforestation in Panama

Pasture and afforestation are land-use types of major importance in the tropics, yet, most flux tower studies have been conducted in mature tropical forests. As deforestation in the tropics is expected to continue, it is critical to improve our understanding of alternative land-use types, and the impact of interactions between land use and climate on ecosystem carbon dynamics. Thus, we measured net ecosystem CO₂ fluxes of a pasture and an adjacent tropical afforestation (native tree species plantation) in Sardinilla, Panama from 2007 to 2009. The objectives of our paired site study were: (1) to assess seasonal and inter-annual variations in net ecosystem CO₂ exchange (NEE) of pasture and afforestation, (2) to identify the environmental controls of net ecosystem CO₂ fluxes, and (3) to constrain eddy covariance derived total ecosystem respiration (TER) with chamber-based soil respiration (R_Soil) measurements. We observed distinct seasonal variations in NEE that were more pronounced in the pasture compared to the afforestation, reflecting changes in plant and microbial activities. The land conversion from pasture to afforestation increased the potential for carbon uptake by trees vs. grasses throughout most of the year. R_Soil contributed about 50% to TER, with only small differences between ecosystems or seasons. Radiation and soil moisture were the main environmental controls of CO₂ fluxes while temperature had no effect on NEE. The pasture ecosystem was more strongly affected by soil water limitations during the dry season, probably due to the shallower root system of grasses compared to trees. Thus, it seems likely that predicted increases in precipitation variability will impact seasonal variations of CO₂ fluxes in Central Panama, in particular of pasture ecosystems.