二氧化碳储存通量对森林生态系统碳收支的影响

涡度相关系统观测高度以下的CO₂储存通量对准确评价森林生态系统与大气间净CO₂交换量（NEE）有着重要的影响.本研究以长白山阔叶红松林为研究对象,利用2003年的涡度相关观测数据以及CO₂浓度廓线数据,分析了CO₂储存通量的变化规律及其对碳收支过程的影响.结果表明：涡度相关观测高度以下的CO₂储存通量具有典型的日变化特征,其最大变化量出现在大气稳定与不稳定层结转换期.利用涡度相关系统观测的单点CO₂浓度变化方法与利用CO₂浓度廓线方法计算的CO₂储存通量差异不显著.忽略CO₂储存通量,在半小时尺度上会造成对夜间和白天的NEE分别低估25%和19%,在日和年尺度上,会对NEE低估10%和25%;忽略CO₂储存通量,会低估Michaelis-Menten光响应方程及Lloyd-Taylor呼吸方程的参数,并且对表观初始量子效率α和参考呼吸R_ref的低估最大;忽略CO₂储存通量,在半小时、日及年尺度上,均会对总光合作用（GPP）和生态系统呼吸（R_e）低估约20%.     

开放式空气CO2浓度增高影响稻田大气CO2净交换的静态暗箱法观测研究

首先介绍静态暗箱法气相色谱法观测确定陆地生态系统地气CO₂净交换通量的基本原理和方法,然后讨论在开放式空气CO₂增加(FACE)试验中应用该原理和方法观测研究大气CO₂浓度升高对稻田生态系统大气CO₂净交换通量的影响.因缺乏必要参数的实际观测值,本文只能根据暗箱观测值计算CO₂净交换通量的最小取值NEE_min.NEE_min计算结果表明,在插秧1个月之后的水稻生长期内,大气CO₂浓度升高200±40μmol·mol^-1使稻田生态系统对大气CO₂的净吸收约为对照的3倍.为根据暗箱观测准确确定NEE,还必须在FACE和对照条件下观测水稻植株的暗维持呼吸系数、地上生物量及根冠比动态.     

甲烷排放部分抵消湿地生态系统碳汇功能：全球数据分析

湿地生态系统是吸收全球大气二氧化碳(CO₂)的汇,同时土壤厌氧环境造成其是大气甲烷(CH₄)的源。尽管有证据表明,湿地生态系统CH₄排放部分抵消其对大气CO₂的净吸收,但目前未见全球尺度湿地CH₄排放对其净生态系统CO₂交换(NEE)抵消效应的研究。本研究分析了全球内陆湿地(泥炭湿地和非泥炭湿地)以及滨海湿地(海草床、盐沼和红树林)中同时测定湿地NEE和CH₄排放通量的数据。结果表明：各类型湿地生态系统均为大气CO₂的汇,NEE值排序为红树林(-2011.0 g CO₂·m^-2·a^-1)<盐沼(-1636.6 g CO₂·m^-2·a^-1)<非泥炭地(-870.8 g CO₂·m^-2·a^-1)<泥炭地(...     

基于FLUXNET观测数据与VPM模型的森林生态系统光合作用关键参数优化及验证

生态系统总初级生产力(GPP)是全球生态系统碳循环研究的重要组成部分.植被最大光能利用率(ε_max)是陆地生态系统GPP模拟的关键参数.本文基于植被光合模型(VPM)和全球通量网(FLUXNET)40个站点(179条站点年数据)的涡度相关通量观测数据,采用单因素轮换法对VPM模型进行参数敏感性分析,并利用交叉验证法对全球森林生态系统的光合作用关键参数进行优化和验证.结果表明:森林生态系统GPP模型受ε_max、光合最高温度(T_max)以及光合最适温度(T_opt)的影响最大;优化后的ε_max在不同植被类型之间存在明显差异,介于0.05～0.08 μmol CO₂·μmol^-1 PAR,常绿阔叶林>常绿针叶林>混交林>落叶阔叶林;优化后的森林生态系统T_max为38～48 ℃,T_opt为18～22 ℃;利用分植被类型优化后的模型关键参数,VPM模型可较好地模拟全球主要森林生态系统GPP的季节和年际变化.     

基于稳定碳同位素技术研究大气CO2浓度升高对植物-土壤系统碳循环的影响

大气CO₂浓度升高影响植物光合作用过程和生物量积累,改变植物地上和地下生物量的动态分配.土壤有机质的形成和周转依赖于植物组分的输入,因此,CO₂浓度升高所造成的植物生理和代谢的变化对土壤碳库收支平衡具有重要影响.采用稳定碳同位素(¹³C)技术研究土壤-植物系统的碳循环可阐明大气CO₂浓度升高条件下光合碳在植物各器官的分配特征和时间动态,明确光合碳在土壤中的积累、分解与迁移转化过程以及对土壤有机碳库周转的影响.本文综述了基于¹³C自然丰度法或¹³C示踪技术研究大气CO₂浓度升高对土壤-植物系统碳循环的影响,主要包括:1)对植物光合作用的同位素分馏的影响;2)对植物光合碳(新碳)分配动态的影响;3)对土壤有机碳新老碳库动态以及微生物转化过程的影响.明确上述过程及其调控机制可为预测CO₂浓度升高对陆地生态系统碳循环及源汇效应的长期影响奠定基础.     

基于稳定碳同位素技术研究大气CO2浓度升高对植物-土壤系统碳循环的影响

大气CO₂浓度升高影响植物光合作用过程和生物量积累,改变植物地上和地下生物量的动态分配.土壤有机质的形成和周转依赖于植物组分的输入,因此,CO₂浓度升高所造成的植物生理和代谢的变化对土壤碳库收支平衡具有重要影响.采用稳定碳同位素(¹³C)技术研究土壤-植物系统的碳循环可阐明大气CO₂浓度升高条件下光合碳在植物各器官的分配特征和时间动态,明确光合碳在土壤中的积累、分解与迁移转化过程以及对土壤有机碳库周转的影响.本文综述了基于¹³C自然丰度法或¹³C示踪技术研究大气CO₂浓度升高对土壤-植物系统碳循环的影响,主要包括:1)对植物光合作用的同位素分馏的影响;2)对植物光合碳(新碳)分配动态的影响;3)对土壤有机碳新老碳库动态以及微生物转化过程的影响.明确上述过程及其调控机制可为预测CO₂浓度升高对陆地生态系统碳循环及源汇效应的长期影响奠定基础.     

基于不同浓度变量的温带落叶阔叶林CO2储存通量的误差分析

利用帽儿山温带落叶阔叶林通量塔8层CO₂/H₂O浓度廓线的测定数据,比较分析了基于不同浓度变量\[密度(ρ_c)、摩尔分数(c_c)和混合比(χ_c)\]计算CO₂储存通量(F_s)的误差.结果表明： 通量观测的控制体积内部干空气储存量不为常数,其波动可引起CO₂分子进出控制体积,即干空气储存通量调整项(F_sd)的变化.在夜间以及昼夜转换期,F_sd相对于涡动通量而言较大,忽略F_sd将为森林与大气之间净CO₂交换量的计算带来误差.大气水热过程对F_s计算引起的误差包括3方面：空气温度变化引起的误差最大,比大气压强(P)的影响高1个数量级;水蒸气的影响在温暖湿润的夏季大于P的影响,但在寒冷干燥的冬季则相反; P的效应在全年均较低.基于ρ_c、c_c和χ_c计算F_s分别平均高估CO₂有效储存通量(F_{s_E})8.5%、0.6%和0.1%.在通量计算过程中,建议选择对大气水热过程守恒的χ_c计算F_s.     

青海湖北岸草甸草原CO2通量年际动态及其驱动机制

青藏高原草甸草原是生态系统中重要的植被类型,准确评估高寒草甸草原生态系统碳源汇状况及碳储量变化尤为重要。基于涡度相关系统观测,分析了2009年至2016年8年期间青海湖北岸草甸草原环境因子以及碳通量的变化特征,运用结构方程模型(SEM)分析环境因子对总初级生产力(GPP)、净生态系统CO₂交换量(NEE)、生态系统呼吸(Re)的调控机制。结果表明：2009—2016年8年NEE日均值在-2.02—0.88 gC m^-2 d^-1之间,5—9月NEE为负值,表现为碳吸收,雨热同期的6、7、8月是CO₂净吸收最强的时期,平均每月吸收CO₂ 39.85 gC m^-2 month^-1,NEE负值日数约占全年的48%,10月—翌年4月为正值,表现为碳释放,初春3月和秋末11月是CO₂净释放最强的时期;Re日均值为1.69 gC m^-2 d^-1,受季节温度的影响,呈夏季强,冬季弱的态...     

2020—2050年CO2施肥效应促进全球陆地生态系统碳吸收

CO₂施肥效应是全球变绿的主要原因,随着大气中CO₂浓度的持续增加,预估未来气候变化条件下,CO₂施肥效应对陆地生态系统的影响对减缓全球气候变化具有重大意义。基于未来气候情景数据和Farquhar模型,并结合生态过程模型BEPS(Boreal Ecosystem Productivity Simulator),定量化研究2020—2050年CO₂施肥效应对全球叶面积指数(LAI)和总初级生产力(GPP)的影响。研究结果显示2020—2050年,在RCP2.6、RCP4.5和RCP8.5气候情景下,CO₂施肥效应导致的LAI年际变化趋势分别为0.002、0.003和0.005 m^-2m^-2a^-1;三个气候情景下CO₂施肥效应对LAI的影响为CO₂每增加0.1%,LAI平均增加约8.1%—9.2%,由此导致GPP对应增加7.9%—14.6%;由CO₂施...     

生态系统光合与呼吸拆分的同位素理论、方法和应用进展

生态系统光合和呼吸是构成净生态系统CO₂交换量(NEE)的重要组分。涡度相关技术可直接观测生态系统NEE,并通过建立温度回归或光响应曲线等函数将NEE统计拆分为生态系统光合和呼吸,但是存在自相关和高估白天呼吸等问题。稳定同位素红外光谱技术的进步使高时间分辨率大气CO₂及其稳定碳同位素组成(δ¹³C)的连续观测成为可能,与涡度相关技术观测的NEE数据相结合,可实现昼夜和季节尺度生态系统光合和呼吸拆分。本文系统阐述了生态系统光合与呼吸的同位素通量拆分方法的基本理论与假设,阐述了同位素通量观测技术的发展及其应用进展,综述了同位素通量拆分理论解析生态系统光合与呼吸过程的新机制认识,最后总结并展望了同位素通量拆分理论的不确定性以及开展多种拆分方法综合比较的必要性。     

Photosynthesis drives anomalies in net carbon-exchange of pine forests at different latitudes

The growth rate of atmospheric CO₂ exhibits large temporal variation that is largely determined by year‐to‐year fluctuations in land–atmosphere CO₂ fluxes. This land–atmosphere CO₂‐flux is driven by large‐scale biomass burning and variation in net ecosystem exchange (NEE). Between‐ and within years, NEE varies due to fluctuations in climate. Studies on climatic influences on inter‐ and intra‐annual variability in gross photosynthesis (GPP) and net carbon uptake in terrestrial ecosystems have shown conflicting results. These conflicts are in part related to differences in methodology and in part to the limited duration of some studies. Here, we introduce an observation‐driven methodology that provides insight into the dependence of anomalies in CO₂ fluxes on climatic conditions. The methodology was applied on fluxes from a boreal and two temperate pine forests. Annual anomalies in NEE were dominated by anomalies in GPP, which in turn were correlated with incident radiation and vapor pressure deficit (VPD). At all three sites positive anomalies in NEE (a reduced uptake or a stronger source than the daily sites specific long‐term average) were observed on summer days characterized by low incident radiation, low VPD and high precipitation. Negative anomalies in NEE occurred mainly on summer days characterized by blue skies and mild temperatures. Our study clearly highlighted the need to use weather patterns rather than single climatic variables to understand anomalous CO₂ fluxes. Temperature generally showed little direct effect on anomalies in NEE but became important when the mean daily air temperature exceeded 23 °C. On such days GPP decreased likely because VPD exceeded 2.0 kPa, inhibiting photosynthetic uptake. However, while GPP decreased, the high temperature stimulated respiration, resulting in positive anomalies in NEE. Climatic extremes in summer were more frequent and severe in the South than in the North, and had larger effects in the South because the criteria to inhibit photosynthesis are more often met.     

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。     

Terrestrial higher-plant response to increasing atmospheric [CO2] in relation to the global carbon cycle

Terrestrial higher plants exchange large amounts of CO₂ with the atmosphere each year; c. 15% of the atmospheric pool of C is assimilated in terrestrial-plant photosynthesis each year, with an about equal amount returned to the atmosphere as CO₂ in plant respiration and the decomposition of soil organic matter and plant litter. Any global change in plant C metabolism can potentially affect atmospheric CO₂ content during the course of years to decades. In particular, plant responses to the presently increasing atmospheric CO₂ concentration might influence the rate of atmospheric CO₂ increase through various biotic feedbacks. Climatic changes caused by increasing atmospheric CO₂ concentration may modulate plant and ecosystem responses to CO₂ concentration. Climatic changes and increases in pollution associated with increasing atmospheric CO₂ concentration may be as significant to plant and ecosystem C balance as CO₂ concentration itself. Moreover, human activities such as deforestation and livestock grazing can have impacts on the C balance and structure of individual terrestrial ecosystems that far outweigh effects of increasing CO₂ concentration and climatic change. In short-term experiments, which in this case means on the order of 10 years or less, elevated atmospheric CO₂ concentration affects terrestrial higher plants in several ways. Elevated CO₂ can stimulate photosynthesis, but plants may acclimate and (or) adapt to a change in atmospheric CO₂ concentration. Acclimation and adaptation of photosynthesis to increasing CO₂ concentration is unlikely to be complete, however. Plant water use efficiency is positively related to CO₂ concentration, implying the potential for more plant growth per unit of precipitation or soil moisture with increasing atmospheric CO₂ concentration. Plant respiration may be inhibited by elevated CO₂ concentration, and although a naive C balance perspective would count this as a benefit to a plant, because respiration is essential for plant growth and health, an inhibition of respiration can be detrimental. The net effect on terrestrial plants of elevated atmospheric CO₂ concentration is generally an increase in growth and C accumulation in phytomass. Published estimations, and speculations about, the magnitude of global terrestrial-plant growth responses to increasing atmospheric CO₂ concentration range from negligible to fantastic. Well-reasoned analyses point to moderate global plant responses to CO₂ concentration. Transfer of C from plants to soils is likely to increase with elevated CO₂ concentrations because of greater plant growth, but quantitative effects of those increased inputs to soils on soil C pool sizes are unknown. Whether increases in leaf-level photosynthesis and short-term plant growth stimulations caused by elevated atmospheric CO₂ concentration will have, by themselves, significant long-term (tens to hundreds of years) effects on ecosystem C storage and atmospheric CO₂ concentration is a matter for speculation, not firm conclusion. Long-term field studies of plant responses to elevated atmospheric CO₂ are needed. These will be expensive, difficult, and by definition, results will not be forthcoming for at least decades. Analyses of plants and ecosystems surrounding natural geological CO₂ degassing vents may provide the best surrogates for long-term controlled experiments, and therefore the most relevant information pertaining to long-term terrestrial-plant responses to elevated CO₂ concentration, but pollutants associated with the vents are a concern in some cases, and quantitative knowledge of the history of atmospheric CO₂ concentrations near vents is limited. On the whole, terrestrial higher-plant responses to increasing atmospheric CO₂ concentration probably act as negative feedbacks on atmospheric CO₂ concentration increases, but they cannot by themselves stop the fossil-fuel-oxidation-driven increase in atmospheric CO₂ concentration. And, in the very long-term, atmospheric CO₂ concentration is controlled by atmosphere-ocean C equilibrium rather than by terrestrial plant and ecosystem responses to atmospheric CO₂ concentration.     

华北平原玉米田生态系统光合作用特征及影响因素

采用涡度相关法对华北平原夏玉米田进行了连续4a(2003-2006年)的碳通量观测,结果表明:夏玉米田生态系统初始量子效率(α)、最大光合速率(P_max)、暗呼吸速率(R_d)和总初级生产力(GPP)随作物生长发育而变化。在夏玉米生育前期和后期,α、P_max、R_d和GPP都比较小,其最大值出现在抽穗期/灌浆期。2003-2006年,夏玉米生长季平均α、P_max、R_d的范围分别为0.054-0.124 μmol/μmol、1.72-2.93 mg CO₂ · m^-2 · s^-1、0.23-0.38 mg CO₂ · m^-2 · s^-1。α、P_max和R_d均随叶面积指数(LAI)增加呈指数增长。2003-2006年夏玉米生长季GPP总量分别为806.2、741.5、703.0、817.4 g C/m²,年际差异较大。玉米田生态系统GPP随温度升高呈指数增长。在玉米营养生长阶段,GPP随LAI增加而增大,两者之间的关系可用直角双曲线方程来表示;生殖生长阶段,GPP随LAI降低而下降.相同LAI下,生殖生长阶段的GPP明显低于营养生长阶段。     

中国陆地生态系统通量观测站点空间代表性

涡度相关技术是测定大气与陆地生态系统之间CO₂交换、水分和能量通量最直接的方法,可用于研究土壤、植被与大气间的CO₂交换及其调控机制。收集了11个影响净碳交换量的主要变量信息,包括气象因素、土壤因素和地形因素的非生物因子、实际植被状态以及植被生产力,采用多元地理变量空间聚类分析方法,绘制出不同聚类数（25、50、75、85、100、150和200类）的通量生态区。结合中国现有通量观测站点的空间分布格局,与新生成的通量生态区和已有的自然地理区划进行对比分析,发现由于中国地形复杂,生态系统类型多样,现有85个涡度相关通量观测站点仅能刻画部分中国生态系统类型的净碳交换量时空特征,通量生态区划分为100-150类比较合适。考虑到涡度相关通量观测运行成本,通量站点可增加至150个,从而使得优化后的通量观测网络能够代表中国主要类型的生态系统,并且有利于通量观测数据与遥感资料的有效结合,提高碳水通量观测从站点扩展到区域尺度的精度,从而更好地检验过程机理模型的模拟结果。     

A simple calibrated model of Amazon rainforest productivity based on leaf biochemical properties

A simple ‘big leaf’ ecosystem gas exchange model was developed, using eddy covariance data collected at an undisturbed tropical rainforest in south-western Amazonia (Brazil). The model used mechanistic equations of canopy biochemistry combined with an empirical stomatal model describing responses to light, temperature and humidity. After calibration, the model was driven using hourly data from a weather station at the top of the tower at the measurement site, yielding an estimate of gross primary productivity (annual photosynthesis) in 1992/1993 of about 200 mol C m^?2 year ^?. Although incoming photon flux density emerged as the major control on photosynthesis in this forest, at a given PAR CO₂ assimilation rates were higher in the mornings than in the afternoons. This was attributable to stomatal closure in the afternoon in response to increasing canopy-to-air vapour pressure differences. Although most morning gas exchange was clearly limited by the rate of electron transport, afternoon gas exchange was generally observed to be very nearly co-limited by both Rubisco activity (V_max) and electron transport rate. The sensitivity of the model to changes in nitrogen allocation showed that the modelled ratio of V_max to electron transport (J_max) served nearly to maximize the annual carbon gain, and indeed, would have resulted in almost maximum annual carbon gain at the pre-industrial revolution atmospheric CO₂ concentration of 27 Pa. Modelled gross primary productivity (GPP) was somewhat lower at 27 Pa, being about 160 mol C m^?2 year^?1. The model suggests that, in the absence of any negative feedbacks on GPP, future higher concentrations of atmospheric CO₂ will continue to increase the GPP of this rainforest, up to about 230 mol C m^?2 year^?1 at 70 Pa.     

Nonlinear CO2 flux response to 7 years of experimentally induced permafrost thaw

Rapid Arctic warming is expected to increase global greenhouse gas concentrations as permafrost thaw exposes immense stores of frozen carbon (C) to microbial decomposition. Permafrost thaw also stimulates plant growth, which could offset C loss. Using data from 7 years of experimental Air and Soil warming in moist acidic tundra, we show that Soil warming had a much stronger effect on CO₂ flux than Air warming. Soil warming caused rapid permafrost thaw and increased ecosystem respiration (R_eco), gross primary productivity (GPP), and net summer CO₂ storage (NEE). Over 7 years R_eco, GPP, and NEE also increased in Control (i.e., ambient plots), but this change could be explained by slow thaw in Control areas. In the initial stages of thaw, R_eco, GPP, and NEE increased linearly with thaw across all treatments, despite different rates of thaw. As thaw in Soil warming continued to increase linearly, ground surface subsidence created saturated microsites and suppressed R_eco, GPP, and NEE. However R_eco and GPP remained high in areas with large Eriophorum vaginatum biomass. In general NEE increased with thaw, but was more strongly correlated with plant biomass than thaw, indicating that higher R_eco in deeply thawed areas during summer months was balanced by GPP. Summer CO₂ flux across treatments fit a single quadratic relationship that captured the functional response of CO₂ flux to thaw, water table depth, and plant biomass. These results demonstrate the importance of indirect thaw effects on CO₂ flux: plant growth and water table dynamics. Nonsummer R_eco models estimated that the area was an annual CO₂ source during all years of observation. Nonsummer CO₂ loss in warmer, more deeply thawed soils exceeded the increases in summer GPP, and thawed tundra was a net annual CO₂ source.     

Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks

The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO₂ between ecosystems and the atmosphere, offering a unique opportunity to study ecosystem responses to climate change. NEE is the difference between the total CO₂ release due to all respiration processes (RECO), and the gross carbon uptake by photosynthesis (GPP). These two gross CO₂ fluxes are derived from EC measurements by applying partitioning methods that rely on physiologically based functional relationships with a limited number of environmental drivers. However, the partitioning methods applied in the global FLUXNET network of EC observations do not account for the multiple co‐acting factors that modulate GPP and RECO flux dynamics. To overcome this limitation, we developed a hybrid data‐driven approach based on combined neural networks (NN_C‐part). NN_C‐part incorporates process knowledge by introducing a photosynthetic response based on the light‐use efficiency (LUE) concept, and uses a comprehensive dataset of soil and micrometeorological variables as fluxes drivers. We applied the method to 36 sites from the FLUXNET2015 dataset and found a high consistency in the results with those derived from other standard partitioning methods for both GPP (R² > .94) and RECO (R² > .8). High consistency was also found for (a) the diurnal and seasonal patterns of fluxes and (b) the ecosystem functional responses. NN_C‐part performed more realistic than the traditional methods for predicting additional patterns of gross CO₂ fluxes, such as: (a) the GPP response to VPD, (b) direct effects of air temperature on GPP dynamics, (c) hysteresis in the diel cycle of gross CO₂ fluxes, (d) the sensitivity of LUE to the diffuse to direct radiation ratio, and (e) the post rain respiration pulse after a long dry period. In conclusion, NN_C‐part is a valid data‐driven approach to provide GPP and RECO estimates and complementary to the existing partitioning methods.     

Assessing canopy performance using carbonyl sulfide measurements

Carbonyl sulfide (COS) is a tracer of ecosystem photosynthesis that can advance carbon cycle research from leaf to global scales; however, a range of newly reported caveats related to sink/source strength of various ecosystem components hinder its application. Using comprehensive eddy‐covariance and chamber measurements, we systematically measure ecosystem contributions from leaf, stem, soil, and litter and were able to close the ecosystem COS budget. The relative contributions of nonphotosynthetic components to the overall canopy‐scale flux are relatively small (~4% during peak activity season) and can be independently estimated based on their responses to temperature and humidity. Converting COS to photosynthetic CO₂ fluxes based on the leaf relative uptake of COS/CO₂, faces challenges due to observed daily and seasonal changes. Yet, this ratio converges around a constant value (~1.6), and the variations, dominated by light intensity, were found unimportant on a flux‐weighted daily time‐scale, indicating a mean ratio of daytime gross‐to‐net primary productivity of ~2 in our ecosystem. The seasonal changes in the leaf relative uptake ratio may indicate a reduction in mesophyll conductance in winter, and COS‐derived canopy conductance permitted canopy temperature estimate consistent with radiative skin temperature. These results support the feasibility of using COS as a powerful and much‐needed means of assessing ecosystem function and its response to change.