基于模型数据融合的千烟洲亚热带人工林碳水通量模拟

人工林生态系统是我国森林生态系统的重要组成部分,在全球碳平衡中的作用越来越受到重视.利用千烟洲亚热带人工针叶林通量观测站的碳水通量和气象观测数据,通过模型数据融合方法对碳水循环过程模型——SIPNET模型关键参数进行反演,模拟了2004-2009年千烟洲人工林生态系统的碳水通量.结果表明:仅用碳通量观测数据优化模型参数时,净生态系统碳交换量(NEE)模拟效果较好(R2=0.934),而生态系统蒸散(ET)模拟效果较差(R2=0.188);同时用碳水通量观测数据优化时,NEE模拟效果稍差(R2=0.929),但ET模拟效果显著提升(R2=0.824),说明利用碳水通量观测数据同时优化,SIPNET模型才能较好地模拟试验站点碳水通量.在此基础上,开展了人工林生态系统碳通量对降水变化响应的敏感性分析,发现降水量减少对光合作用的影响比对呼吸作用的影响更为强烈,且碳水通量同时参与优化时模型才能较好地模拟碳通量随降水减少而快速降低的趋势,表明如果不能同时利用碳水通量进行参数优化,模型无法正确揭示生态系统碳循环对降水变异的响应.     

基于FORCCHN模型的中国典型森林生态系统碳通量模拟

森林生态系统是陆地碳循环的重要组成部分,其固碳能力显著高于其他陆地生态系统,研究森林生态系统碳通量是认识和理解全球变化对碳循环影响的关键。碳循环模型是研究森林生态系统碳通量有效工具。以长白山温带落叶阔叶林、千烟洲亚热带常绿针叶林、鼎湖山亚热带常绿阔叶林和西双版纳热带雨林等4种中国典型森林生态系统为研究对象,利用涡度相关2003-2012年观测数据,评估FORCCHN模型对生态系统呼吸（ER）,总初级生产力（GPP）,净生态系统生产力（NEP）的模型效果。结果表明：（1） FORCCHN模型能够较好的模拟中国4种典型森林生态系统不同时间尺度的碳通量。落叶阔叶林和常绿针叶林ER和GPP的逐日变化模拟效果较好（ER的相关系数分别为0.94和0.92,GPP的相关系数分别为0.86和0.74）;（2）4种森林生态系统碳通量季节动态模拟值和观测值显著相关（P<0.01）,ER、GPP、NEP的观测值和模拟值的R²分别为0.77-0.93、0.54-0.88和0.15-0.38;模型可以很好地模拟森林生态系统不同季节碳汇（NEP>0）,碳源（NEP<0）的变化规律;（3）4种森林生态系统碳通量模拟值与观测值的年际变化有很好的吻合度,但在数值大小上存在差异,模型高估了常绿阔叶林的ER和GPP,略微低估了其他3种森林生态系统ER和GPP。     

NEE观测误差分布类型对陆地生态系统机理模型参数估计的影响——以长白山温带阔叶红松林为例

基于观测数据的陆地生态系统模型参数估计有助于提高模型的模拟和预测能力,降低模拟不确定性.在已有参数估计研究中,涡度相关技术测定的净生态系统碳交换量(NEE)数据的随机误差通常被假设为服从零均值的正态分布.然而近年来已有研究表明NEE数据的随机误差更服从双指数分布.为探讨NEE观测误差分布类型的不同选择对陆地生态系统机理模型参数估计以及碳通量模拟结果造成的差异,以长白山温带阔叶红松林为研究区域,采用马尔可夫链-蒙特卡罗方法,利用2003～2005年测定的NEE数据对陆地生态系统机理模型CEVSA2的敏感参数进行估计,对比分析了两种误差分布类型(正态分布和双指数分布)的参数估计结果以及碳通量模拟的差异.结果表明,基于正态观测误差模拟的总初级生产力和生态系统呼吸的年总量分别比基于双指数观测误差的模拟结果高61～86 g C m-2 a-1和107～116 g C m-2 a-1,导致前者模拟的NEE年总量较后者低29～47 g C m-2 a-1,特别在生长旺季期间有明显低估.在参数估计研究中,不能忽略观测误差的分布类型以及相应的目标函数的选择,它们的不合理设置可能对参数估计以及模拟结果产生较大影响.     

Optimization and evaluation of vegetation photosynthesis and respiration model using the measurements collected from the forest site of subtropical coniferous-evergreen

 碳循环模型参数的确定和优化对生态系统净CO₂交换(NEE)的模型计算至关重要。该文利用2010–2012年ChinaFLUX千烟洲站点的通量观测资料, 对植被光合呼吸模型(VPRM)的参数进行了优化。通过比较两种不同的拟合方案, 发现利用传统光响应方程得到的参数不适用于VPRM, 而利用模型自身反演方案拟合得到的参数最大光量子效率(λ)达0.203, 大于C₃植物平均值, 但与其他相关研究结果吻合。采用VPRM模型反演方案优化得到的参数后, VPRM能较准确地模拟千烟洲站不同季节的NEE。其对全年半小时NEE模拟的平均误差为–0.86 μmol·m^–2·s^–1, 相关系数为0.72。模型可准确地模拟生长旺季NEE平均日变化, 但低估了非生长旺季白天吸收峰值约52%。通过个例分析发现, VPRM模型可以准确模拟晴天条件下NEE的时间变化, 但对阴雨天条件下NEE的模拟还存在较大的不确定性。该研究将有助于进一步改进CO₂通量及浓度的区域数值模拟。     

利用大气二氧化碳和羰基硫浓度评估陆地生态系统模型碳通量模拟的不确定性

生态系统模型是模拟全球陆地生态系统碳循环的重要工具,但是其在全球不同区域的模拟存在很大的不确定性。如何评估陆地生态系统模型的不确定性是一项重要的研究。以北美地区为例,利用8个高塔观测站点同步获取的大气CO_2和羰基硫(OCS)浓度数据,结合WRF-STILT大气粒子扩散模型,评估了CASA-GFED3、SiB3和SiBCASA三种陆地生态系统模型模拟总初级生产力(GPP)和净生态系统CO_2交换(NEE)通量的不确定性。结果表明,SiB3模型能很好地模拟北美陆地生态系统GPP和NEE的季节变化时相和幅度,在3种模型中具有最佳的模拟能力;CASA-GFED3模型模拟的NEE季节变化较为理想、但对生长季GPP的模拟存在较大的误差,SiBCASA模型在模拟冬季晚期和春季早期的NEE和GPP时表现较不理想。研究证明了大气CO_2和OCS在评估陆地生态系统模型碳通量模拟的不确定性中的作用,为利用大气CO_2和OCS观测数据优化计算陆地生态系统光合和呼吸碳通量提供了理论支撑。     

千烟洲马尾松人工林生态系统的碳循环模拟及模型参数的敏感性分析

应用改进后的碳水循环过程模型——景观尺度生态系统生产力过程模型(ecosystem productivity process model for landscape,EPPML)模拟了2003和2004年千烟洲马尾松人工林生态系统的碳循环过程,并对模型参数的敏感性进行了分析.结果表明:EPPML可用于模拟千烟洲马尾松人工林的碳循环过程,不仅总初级生产力(GPP)、生态系统净生产力(NEP)和生态系统总呼吸(Re)的年总值和季节变化与实测值十分吻合,而且也能反映极端天气对碳流的重要影响;千烟洲马尾松人工林生态系统具有较强的净碳吸收能力,但2003年生长最旺季的高温和重旱天气的耦合作用使其碳吸收能力明显低于2004年,2003和2004年平均NEP分别为481.8和516.6gC.m-2.a-1;马尾松生长初期的光照、生长旺期的干旱、生长末期的降水量是改变碳循环季节变化的关键气象条件;自养呼吸(Ra)与净初级生产力(NPP)的季节进程一致;异养呼吸(Rh)在年尺度上受土壤温度控制,而在月尺度上则受土壤含水量波动的影响;在生长季的丰水期,土壤含水量越大,Rh越小;而在生长季的枯水期,前两个月的降雨量越大,Rh也越大.EPPML参数中,25℃时的最大RuBP羧化速率(Vm25)、比叶面积(SLA)、最大叶N含量(LNm)、平均叶含N量(LN)、生物量与碳的转换率(C/B)对年NEP的影响最大;不同碳循环过程变量对敏感参数变化的响应也不尽相同,其中,Vm25和LN的增加能有效促进植物的碳吸收和呼吸;LN/LNm越小,对碳吸收和呼吸的抑制作用越强;C/B和SLA的增大会促进碳吸收,抑制呼吸.将全年区分为生长季与非生长季时得到的最敏感参数的结论与全年不尽相同.     

基于Biome-BGC模型和集合卡尔曼滤波方法的阔叶红松林生态系统水碳通量模拟

数据同化为模型与遥感观测结合提供了一条有效的途径,通过在模型运行过程中融入遥感观测数据,调整模型运行轨迹从而降低模型误差,提高模拟精度。本文利用集合卡尔曼滤波(En KF)算法同化生长季中分辨率成像光谱仪(MODIS)叶面积指数(LAI)与Biome-BGC模型模拟的LAI模拟长白山阔叶红松林的水碳通量。同时,通过改进模拟的雪面升华与土壤温度计算方法的参数,旨在降低冬季生态呼吸的模拟误差。结果表明,相对于原始模型,数据同化与模型改进后使得生态系统总初级生产力(GPP)的模拟值与观测值之间的相关系数提高0.06,中心化均方根误差(RMSE)降低0.48 g C·m~(-2)·d~(-1);生态系统呼吸(RE)的相关系数提高0.02,中心化均方根误差降低0.20 g C·m~(-2)·d~(-1);净生态系统碳交换量(NEE)相关系数提高0.35,中心化均方根误差降低0.50 g C·m~(-2)·d~(-1)。同时,数据同化对蒸散发(ET)的模拟精度没有显著影响,改进的模型提高了其相关系数。基于En KF算法的数据同化提高了长白山阔叶红松林碳通量模拟精度,对于精确估算区域碳通量有着重要的意义。     

基于模型数据融合的长白山阔叶红松林碳循环模拟

 充分、有效地利用各种陆地生态系统碳观测数据改善陆地生态系统模型, 是当前我国陆地生态系统碳循环研究领域亟待解决的重要问题之一。该研究以2003~2005年长白山阔叶红松林的6组生物计量观测数据和涡度相关技术测定的碳通量数据为基础, 利用马尔可夫链-蒙特卡罗方法对陆地生态系统模型的关键参数(即碳滞留时间)进行了反演, 进而预测了长白山阔叶红松林生态系统碳库、碳通量及其不确定性。反演结果表明, 长白山阔叶红松林叶凋落物和微生物碳的平均滞留时间最短, 为2~6个月; 其次是叶和细根生物量碳, 二者的平均滞留时间为1~2 a; 慢性土壤有机碳的平均滞留时间为8~16 a; 碳在木质生物量和惰性土壤有机质库中的滞留时间最长, 平均滞留时间分别为77~109 a和409~1 879 a。模拟结果显示, 碳库和累积碳通量模拟值的不确定性将随着模拟时间的延长而增大。当气温升高10%和20%时, 长白山阔叶红松林总初级生产力年总量将分别增加6.5%和9.9%, 净生态系统生产力(NEP)年总量的变化取决于土壤温度的变化。若土壤温度保持不变, NEP年总量将分别增加11.4%~21.9%和17.6%~33.1%; 若土壤温度也相应升高10%和20%, NEP年总量的增幅反而下降甚至低于原来的水平。假设气候和植被保持在2003~2005年的状态, 2020年长白山阔叶红松林NEP年总量为(163±12) g C·m^–2·a^–1, 土壤呼吸年总量为(721±14) g C·m^–2·a^–1。马尔可夫链-蒙特卡罗方法是反演模型参数、优化模拟结果和评估模拟结果不确定性的有效方法, 但今后仍需在惰性土壤碳滞留时间的估计、驱动数据和模型结构的不确定性分析、模型数据融合方法方面进行深入研究, 以进一步提高碳循环模拟的准确性。     

植被光合呼吸模型在长白山温带阔叶红松林的优化及验证

植被光合呼吸模型(VPRM)关键参数的确定和优化是准确计算生态系统净CO_2交换(NEE)的基础。利用中国通量观测研究联盟(China FLUX)长白山站温带阔叶红松林2005年的通量观测资料,对VPRM的4个参数(最大光能利用率ε_0、光照为半饱和条件下光合有效辐射值PAR0和呼吸参数(α、β))进行优化,并使用2006年的观测资料对参数优化前后的模拟结果进行评估。结果表明:参数优化后,VPRM能够较好地模拟长白山地区2006年植物生长季NEE的变化。对30min NEE模拟的平均误差为-1.81μmol m~(-2)s~(-1),相关系数为0.72,模拟NEE平均日变化的峰值约为观测值的91%,相关系数为0.97。但在植物非生长季模型对森林NEE的模拟效果较差。模型模拟30min NEE的平均误差为0.39μmol m~(-2)s~(-1),相关系数仅为0.10,并且模拟低估NEE平均日变化白天吸收峰值约82%,日变化模拟值与观测值的相关系数为0.50。通过分析不同天气个例,发现模型可以较好地模拟晴天条件下NEE的变化,而对阴雨天NEE的模拟误差较大。该研究有利于提高VPRM模型对温带落叶阔叶林NEE的模拟能力,对进一步改进区域陆地NEE的模拟具有重要意义。     

三江并流核心区亚高山森林非生长季净生态系统CO2交换量及其影响因素

采用开路式涡度相关系统,针对三江并流核心区西藏红拉山滇金丝猴国家自然保护区,通过测量和分析非生长季亚高山常绿针叶林净生态系统碳交换量(NEE),探讨了亚高山森林非生长季CO₂通量特征及其主要影响因子。保护区常绿针叶林NEE值在非生长季具有明显“U”型变化曲线,白天表现为碳吸收,夜间表现为碳释放,日间CO₂吸收高峰介于12:00到15:00之间,平均每天碳汇时间在10 h左右。非生长季各月NEE大小依次为：4月> 3月>2月>11月>1月>12月。研究期内气温(T)、相对湿度(RH)、饱和水汽压差(VPD)和光合有效辐射(PAR)等气象因子对净生态系统CO₂交换量影响显著。此外,森林碳吸收对温度响应敏感,光合作用在整个非生长季较为明显。各影响因子中光合有效辐射对碳交换影响最大;夜间NEE与5 cm土壤温度呈极显著相关性(P<0.01)且NEE随着土壤温度升高而增大;整个非生长季NEE、生态系统呼吸量(Re)和总生态系统CO₂交换量(GEE)分别为-596.759 g...     

Seasonal variability in net ecosystem carbon dioxide exchange over a young Switchgrass stand

Understanding carbon dynamics of switchgrass ecosystems is crucial as switchgrass (Panicum virgatum L.) acreage is expanding for cellulosic biofuels. We used eddy covariance system and examined seasonal changes in net ecosystem CO₂ exchange (NEE) and its components – gross ecosystem photosynthesis (GEP) and ecosystem respiration (ER) – in response to controlling factors during the second (2011) and third (2012) years of stand establishment in the southern Great Plains of the United States (Chickasha, OK). Larger vapor pressure deficit (VPD > 3 kPa) limited photosynthesis and caused asymmetrical diurnal NEE cycles (substantially higher NEE in the morning hours than in the afternoon at equal light levels). Consequently, rectangular hyperbolic light–response curve (NEE partitioning algorithm) consistently failed to provide good fits at high VPD. Modified rectangular hyperbolic light–VPD response model accounted for the limitation of VPD on photosynthesis and improved the model performance significantly. The maximum monthly average NEE reached up to ?33.02 ± 1.96 μmol CO₂ m^?2 s^?1 and the highest daily integrated NEE was ?35.89 g CO₂ m^?2 during peak growth. Although large differences in cumulative seasonal GEP and ER were observed between two seasons, total seasonal ER accounted for about 75% of GEP regardless of the growing season lengths and differences in aboveground biomass production. It suggests that net ecosystem carbon uptake increases with increasing GEP. The ecosystem was a net sink of CO₂ during 5–6 months and total seasonal uptakes were ?1128 ± 130 and ?1796 ± 217 g CO₂ m^?2 in 2011 and 2012, respectively. In conclusion, our findings suggest that the annual carbon status of a switchgrass ecosystem can be a small sink to small source in this region if carbon loss from biomass harvesting is considered. However, year‐round measurements over several years are required to assess a long‐term source‐sink status of the ecosystem.     

Environmental controls over carbon exchange of three forest ecosystems in eastern China

Net ecosystem productivity (NEP) was continuously measured using the eddy covariance (EC) technique from 2003 to 2005 at three forest sites of ChinaFLUX. The forests include Changbaishan temperate mixed forest (CBS), Qianyanzhou subtropical coniferous plantation (QYZ), and Dinghushan subtropical evergreen broad‐leaved forest (DHS). They span wide ranges of temperature and precipitation and are influenced by the eastern Asian monsoon climate to varying extent. In this study, we estimated ecosystem respiration (RE) and gross ecosystem productivity (GEP). Comparison of ecosystem carbon exchange among the three forests shows that RE was mainly determined by temperature, with the forest at CBS exhibiting the highest temperature sensitivity among the three ecosystems. The RE was highly dependent on GEP across the three forests, and the ratio of RE to GEP decreased along the North–South Transect of Eastern China (NSTEC) (i.e. from the CBS to the DHS), with an average of 0.77 ± 0.06. Daily GEP was mainly influenced by temperature at CBS, whereas photosynthetic photon flux density was the dominant factor affecting the daily GEP at both QYZ and DHS. Temperature mainly determined the pattern of the interannual variations of ecosystem carbon exchange at CBS. However, water availability primarily controlled the interannual variations of ecosystem carbon exchange at QYZ. At DHS, NEP attained the highest values at the beginning of the dry seasons (autumn) rather than the rainy seasons (summer), probably because insufficient radiation and frequent fog during the rainy seasons hindered canopy photosynthesis. All the three forest ecosystems acted as a carbon sink from 2003 to 2005. The annual average values of NEP at CBS, QYZ, and DHS were 259 ± 19, 354 ± 34, and 434 ± 66 g C m⁻² yr⁻¹, respectively. The slope of NEP that decreased with increasing latitude along the NSTEC was markedly different from that observed on the forest transect in the European continent. Long‐term flux measurements over more forest ecosystems along the NSTEC will further help verify such a difference between the European forest transect and the NSTEC and provide insights into the responses of ecosystem carbon exchange to climate change in China.     

Six-year Stable Annual Uptake of Carbon Dioxide in Intensively Managed Humid Temperate Grassland

Variability and future alterations in regional and global climate patterns may exert a strong control on the carbon dioxide (CO₂) exchange of grassland ecosystems. We used 6 years of eddy-covariance measurements to evaluate the impacts of seasonal and inter-annual variations in environmental conditions on the net ecosystem CO₂ exchange (NEE), gross ecosystem production (GEP), and ecosystem respiration (ER) of an intensively managed grassland in the humid temperate climate of southern Ireland. In all the years of the study period, considerable uptake of atmospheric CO₂ occurred in this grassland with a narrow range in the annual NEE from −245 to −284 g C m⁻² y⁻¹, with the exception of 2008 in which the NEE reached −352 g C m⁻² y⁻¹. None of the measured environmental variables (air temperature (Ta), soil moisture, photosynthetically active radiation, vapor pressure deficit (VPD), precipitation (PPT), and so on) correlated with NEE on a seasonal or annual scale because of the equal responses from the component fluxes GEP and ER to variances in these variables. Pronounced reduction of summer PPT in two out of the six studied years correlated with decreases in both GEP and ER, but not with NEE. Thus, the stable annual NEE was primarily achieved through a strong coupling of ER and GEP on seasonal and annual scales. Limited inter-annual variations in Ta (±0.5°C) and generally sufficient soil moisture availability may have further favored a stable annual NEE. Monthly ecosystem carbon use efficiency (CUE; as the ratio of NEE:GEP) during the main growing season (April 1–September 30) was negatively correlated with temperature and VPD, but positively correlated with soil moisture, whereas the annual CUE correlated negatively with annual NEE. Thus, although drier and warmer summers may mildly reduce the uptake potential, the annual uptake of atmospheric CO₂, in this intensively managed grassland, may be expected to continue even under predicted future climatic changes in the humid temperate climate region.     

Net ecosystem carbon dioxide exchange over grazed steppe in central Mongolia

This paper presents results of 1 year (from March 25, 2003 to March 24, 2004, 366 days) of continuous measurements of net ecosystem CO₂ exchange (NEE) above a steppe in Mongolia using the eddy covariance technique. The steppe, typical of central Mongolia, is dominated by C₃ plants adapted to the continental climate. The following two questions are addressed: (1) how do NEE and its components: gross ecosystem production (GEP) and total ecosystem respiration (R_eco) vary seasonally? (2) how do NEE, GEP, and R_eco respond to biotic and abiotic factors? The hourly minimal NEE and the hourly maximal R_eco were −3.6 and 1.2 μmol m⁻² s⁻¹, respectively (negative values denoting net carbon uptake by the canopy from the atmosphere). Peak daily sums of NEE, GEP, and R_eco were −2.3, 3.5, and 1.5 g C m⁻² day⁻¹, respectively. The annual sums of GEP, R_eco, and NEE were 179, 138, and −41 g C m⁻², respectively. The carbon removal by sheep was estimated to range between 10 and 82 g C m⁻² yr⁻¹ using four different approaches. Including these estimates in the overall carbon budget yielded net ecosystem productivity of −23 to +20 g C m⁻² yr⁻¹. Thus, within the remaining experimental uncertainty the carbon budget at this steppe site can be considered to be balanced. For the growing period (from April 23 to October 21, 2003), 26% and 53% of the variation in daily NEE and GEP, respectively, could be explained by the changes in leaf area index. Seasonality of GEP, R_eco, and NEE was closely associated with precipitation, especially in the peak growing season when GEP and R_eco were largest. Water stress was observed in late July to early August, which switched the steppe from a carbon sink to a carbon source. For the entire growing period, the light response curves of daytime NEE showed a rather low apparent quantum yield (α=−0.0047 μmol CO₂ μmol⁻¹ photons of photosynthetically active radiation). However, the α values varied with air temperature (T_a), vapor pressure deficit, and soil water content.     

Modelling night‐time ecosystem respiration by a constrained source optimization method

One of the main challenges to quantifying ecosystem carbon budgets is properly quantifying the magnitude of night‐time ecosystem respiration. Inverse Lagrangian dispersion analysis provides a promising approach to addressing such a problem when measured mean CO₂ concentration profiles and nocturnal velocity statistics are available. An inverse method, termed ‘Constrained Source Optimization’ or CSO, which couples a localized near‐field theory (LNF) of turbulent dispersion to respiratory sources, is developed to estimate seasonal and annual components of ecosystem respiration. A key advantage to the proposed method is that the effects of variable leaf area density on flow statistics are explicitly resolved via higher‐order closure principles. In CSO, the source distribution was computed after optimizing key physiological parameters to recover the measured mean concentration profile in a least‐square fashion. The proposed method was field‐tested using 1 year of 30‐min mean CO₂ concentration and CO₂ flux measurements collected within a 17‐year‐old (in 1999) even‐aged loblolly pine (Pinus taeda L.) stand in central North Carolina. Eddy‐covariance flux measurements conditioned on large friction velocity, leaf‐level porometry and forest‐floor respiration chamber measurements were used to assess the performance of the CSO model. The CSO approach produced reasonable estimates of ecosystem respiration, which permits estimation of ecosystem gross primary production when combined with daytime net ecosystem exchange (NEE) measurements. We employed the CSO approach in modelling annual respiration of above‐ground plant components (c. 214 g C m^?2 year^?1) and forest floor (c. 989 g C m^?2 year^?1) for estimating gross primary production (c. 1800 g C m^?2 year^?1) with a NEE of c. 605 g C m^?2 year^?1 for this pine forest ecosystem. We conclude that the CSO approach can utilise routine CO₂ concentration profile measurements to corroborate forest carbon balance estimates from eddy‐covariance NEE and chamber‐based component flux measurements.     

High Arctic Dry Heath CO2 Exchange During the Early Cold Season

Climate change may alter the terrestrial ecosystem carbon balance in the Arctic, and previous studies have emphasized the importance of cold season gas exchange when considering the annual carbon balance. Here, we examined gross ecosystem production (GEP), ecosystem respiration (R _eco) and net ecosystem exchange (NEE) during autumn at a high arctic dry open heath, over a period where air temperatures decreased from +9.8 to ?16.5°C. GEP declined by 95–100% during autumn but GEP significantly different from 0 was measured on October 8 despite sub-zero temperatures. R _eco declined by 90% and dominated NEE throughout the study as the ecosystem on all measurement days was a source of atmospheric CO₂. We estimated net September carbon losses (NEE) to be 17?g?CO₂?m^?2, emphasizing the importance of autumn in relation to annual carbon budgets. The study site has been subjected to 14 summers of water addition, and occasional pulses of nitrogen (N) addition in a fully factorial design. N addition enhanced GEP up to 17-fold during September, although there was no effect in October when GEP was very low. Summer water addition decreased autumn R _eco by up to 25%. Both N amendment and water addition decreased carbon loss, that is, increased NEE; N amendment increased NEE on all dates by 13–64% whereas water addition increased NEE by 20–54% late in September and onward, demonstrating the importance of nutrient and water availability on carbon balance in high arctic tundra, also during the autumn freeze-in.     

Carbon dynamics and environmental controls of a hilly tea plantation in Southeast China

Tea plantations are widely distributed and continuously expanding across subtropical China in recent years. However, carbon flux exchanges from tea plantation ecosystems are poorly understood at the ecosystem level. In this study, we use the eddy covariance technique to quantify the magnitude and temporal variations of the net ecosystem exchange (NEE) in tea plantation in Southeast China over four years (2014–2017). The result showed that the tea plantation was a net carbon sink, with an annual NEE that ranged from ?182.40 to ?301.51 g C/m², which was a much lower carbon sequestration potential than other ecosystems in subtropical China. Photosynthetic photon flux density (PPFD) explained the highest proportion of the variation in NEE and gross primary productivity (GPP) (for NEE: F = 389.89, p < .01; for GPP: F = 1,018.04, p < .01), and air temperature (T_a) explained the highest proportion of the variation in ecosystem respiration (RE) (F = 13,141.81, p < .01). The strong pruning activity in April not only reduced the carbon absorption capacity but also provided many plant residues for respiration, which switched the tea plantation to a carbon source from April to June. Suppression of NEE at higher air temperatures was due to the decrease in GPP more than the decrease in RE, which indicated that future global warming may transform this subtropical tea plantation from a carbon sink to carbon source.     

Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation

The measured net ecosystem exchange (NEE) of CO₂ between the ecosystem and the atmosphere reflects the balance between gross CO₂ assimilation [gross primary production (GPP)] and ecosystem respiration (R_eco). For understanding the mechanistic responses of ecosystem processes to environmental change it is important to separate these two flux components. Two approaches are conventionally used: (1) respiration measurements made at night are extrapolated to the daytime or (2) light–response curves are fit to daytime NEE measurements and respiration is estimated from the intercept of the ordinate, which avoids the use of potentially problematic nighttime data. We demonstrate that this approach is subject to biases if the effect of vapor pressure deficit (VPD) modifying the light response is not included. We introduce an algorithm for NEE partitioning that uses a hyperbolic light response curve fit to daytime NEE, modified to account for the temperature sensitivity of respiration and the VPD limitation of photosynthesis. Including the VPD dependency strongly improved the model's ability to reproduce the asymmetric diurnal cycle during periods with high VPD, and enhances the reliability of R_eco estimates given that the reduction of GPP by VPD may be otherwise incorrectly attributed to higher R_eco. Results from this improved algorithm are compared against estimates based on the conventional nighttime approach. The comparison demonstrates that the uncertainty arising from systematic errors dominates the overall uncertainty of annual sums (median absolute deviation of GPP: 47 g C m^?2 yr^?1), while errors arising from the random error (median absolute deviation: ～2 g C m^?2 yr^?1) are negligible. Despite site‐specific differences between the methods, overall patterns remain robust, adding confidence to statistical studies based on the FLUXNET database. In particular, we show that the strong correlation between GPP and R_eco is not spurious but holds true when quasi‐independent, i.e. daytime and nighttime based estimates are compared.     

Evaluating the carbon balance estimate from an automated ground‐level flux chamber system in artificial grass mesocosms

Measuring and modeling carbon (C) stock changes in terrestrial ecosystems are pivotal in addressing global C‐cycling model uncertainties. Difficulties in detecting small short‐term changes in relatively large C stocks require the development of robust sensitive flux measurement techniques. Net ecosystem exchange (NEE) ground‐level chambers are increasingly used to assess C dynamics in low vegetation ecosystems but, to date, have lacked formal rigorous field validation against measured C stock changes. We developed and deployed an automated and multiplexed C‐flux chamber system in grassland mesocosms in order rigorously to compare ecosystem total C budget obtained using hourly C‐flux measurements versus destructive net C balance. The system combines transparent NEE and opaque respiration chambers enabling partitioning of photosynthetic and respiratory fluxes. The C‐balance comparison showed good agreement between the two methods, but only after NEE fluxes were corrected for light reductions due to chamber presence. The dark chamber fluxes allowed assessing temperature sensitivity of ecosystem respiration (R_eco) components (i.e., heterotrophic vs. autotrophic) at different growth stages. We propose that such automated flux chamber systems can provide an accurate C balance, also enabling pivotal partitioning of the different C‐flux components (e.g., photosynthesis and respiration) suitable for model evaluation and developments.