Interannual variability in carbon dioxide fluxes and flux–climate relationships on grazed and ungrazed northern mixed-grass prairie

The annual carbon (C) budget of grasslands is highly dynamic, dependent on grazing history and on effects of interannual variability (IAV) in climate on carbon dioxide (CO₂) fluxes. Variability in climatic drivers may directly affect fluxes, but also may indirectly affect fluxes by altering the response of the biota to the environment, an effect termed ‘functional change’. We measured net ecosystem exchange of CO₂ (NEE) and its diurnal components, daytime ecosystem CO₂ exchange (P_D) and night‐time respiration (R_E), on grazed and ungrazed mixed‐grass prairie in North Dakota, USA, for five growing seasons. Our primary objective was to determine how climatic anomalies influence variability in CO₂ exchange. We used regression analysis to distinguish direct effects of IAV in climate on fluxes from functional change. Functional change was quantified as the improvement in regression on fitting a model in which slopes of flux–climate relationships vary among years rather than remain invariant. Functional change and direct effects of climatic variation together explained about 20% of variance in weekly means of NEE, P_D, and R_E. Functional change accounted for more than twice the variance in fluxes of direct effects of climatic variability. Grazing did not consistently influence the contribution of functional change to flux variability, but altered which environmental variable best explained year‐to‐year differences in flux–climate slopes, reduced IAV in seasonal means of fluxes, lessened the strength of flux–climate correlations, and increased NEE by reducing R_E relatively more than P_D. Most of these trends are consistent with the interpretation that grazing reduced the influence of plants on ecosystem fluxes. Because relationships between weekly values of fluxes and climatic regulators changed annually, year‐to‐year differences in the C balance of these ecosystems cannot be predicted from knowledge of IAV in climate alone.     

Spatial variability and controls over biomass stocks,carbon fluxes,and resource-use efficiencies across forest ecosystems

Key message

Stand age, water availability, and the length of the warm period are the most influencing controls of forest structure, functioning, and efficiency.

Abstract

We aimed to discern the distribution and controls of plant biomass, carbon fluxes, and resource-use efficiencies of forest ecosystems ranging from boreal to tropical forests. We analysed a global forest database containing estimates of stand biomass and carbon fluxes (400 and 111 sites, respectively) from which we calculated resource-use efficiencies (biomass production, carbon sequestration, light, and water-use efficiencies). We used the WorldClim climatic database and remote-sensing data derived from the Moderate Resolution Imaging Spectroradiometer to analyse climatic controls of ecosystem functioning. The influences of forest type, stand age, management, and nitrogen deposition were also explored. Tropical forests exhibited the largest gross carbon fluxes (photosynthesis and ecosystem respiration), but rather low net ecosystem production, which peaks in temperate forests. Stand age, water availability, and length of the warm period were the main factors controlling forest structure (biomass) and functionality (carbon fluxes and efficiencies). The interaction between temperature and precipitation was the main climatic driver of gross primary production and ecosystem respiration. The mean resource-use efficiency varied little among biomes. The spatial variability of biomass stocks and their distribution among ecosystem compartments were strongly correlated with the variability in carbon fluxes, and both were strongly controlled by climate (water availability, temperature) and stand characteristics (age, type of leaf). Gross primary production and ecosystem respiration were strongly correlated with mean annual temperature and precipitation only when precipitation and temperature were not limiting factors. Finally, our results suggest a global convergence in mean resource-use efficiencies.     

Impacts of Diffuse Radiation on Light Use Efficiency across Terrestrial Ecosystems Based on Eddy Covariance Observation in China

Ecosystem light use efficiency (LUE) is a key factor of production models for gross primary production (GPP) predictions. Previous studies revealed that ecosystem LUE could be significantly enhanced by an increase on diffuse radiation. Under large spatial heterogeneity and increasing annual diffuse radiation in China, eddy covariance flux data at 6 sites across different ecosystems from 2003 to 2007 were used to investigate the impacts of diffuse radiation indicated by the cloudiness index (CI) on ecosystem LUE in grassland and forest ecosystems. Our results showed that the ecosystem LUE at the six sites was significantly correlated with the cloudiness variation (0.24≤R²≤0.85), especially at the Changbaishan temperate forest ecosystem (R² = 0.85). Meanwhile, the CI values appeared more frequently between 0.8 and 1.0 in two subtropical forest ecosystems (Qianyanzhou and Dinghushan) and were much larger than those in temperate ecosystems. Besides, cloudiness thresholds which were favorable for enhancing ecosystem carbon sequestration existed at the three forest sites, respectively. Our research confirmed that the ecosystem LUE at the six sites in China was positively responsive to the diffuse radiation, and the cloudiness index could be used as an environmental regulator for LUE modeling in regional GPP prediction.     

Climate controls over ecosystem metabolism: insights from a fifteen-year inductive artificial neural network synthesis for a subalpine forest

Eddy covariance (EC) datasets have provided insight into climate determinants of net ecosystem productivity (NEP) and evapotranspiration (ET) in natural ecosystems for decades, but most EC studies were published in serial fashion such that one study’s result became the following study’s hypothesis. This approach reflects the hypothetico-deductive process by focusing on previously derived hypotheses. A synthesis of this type of sequential inference reiterates subjective biases and may amplify past assumptions about the role, and relative importance, of controls over ecosystem metabolism. Long-term EC datasets facilitate an alternative approach to synthesis: the use of inductive data-based analyses to re-examine past deductive studies of the same ecosystem. Here we examined the seasonal climate determinants of NEP and ET by analyzing a 15-year EC time-series from a subalpine forest using an ensemble of Artificial Neural Networks (ANNs) at the half-day (daytime/nighttime) time-step. We extracted relative rankings of climate drivers and driver–response relationships directly from the dataset with minimal a priori assumptions. The ANN analysis revealed temperature variables as primary climate drivers of NEP and daytime ET, when all seasons are considered, consistent with the assembly of past studies. New relations uncovered by the ANN approach include the role of soil moisture in driving daytime NEP during the snowmelt period, the nonlinear response of NEP to temperature across seasons, and the low relevance of summer rainfall for NEP or ET at the same daytime/nighttime time step. These new results offer a more complete perspective of climate–ecosystem interactions at this site than traditional deductive analyses alone.     

Estimating daytime ecosystem respiration from eddy-flux data

To understand what governs the patterns of net ecosystem exchange of CO₂, an understanding of factors influencing the component fluxes, ecosystem respiration and gross primary production is needed. In the present paper, we introduce an alternative method for estimating daytime ecosystem respiration based on whole ecosystem fluxes from a linear regression of photosynthetic photon flux density data vs. daytime net ecosystem exchange data at forest ecosystem level. This method is based on the principles of the Kok-method applied at leaf level for estimating daytime respiration. We demonstrate the method with field data and provide a discussion of the limitations of the method.     

Evaluation of six process‐based forest growth models using eddy‐covariance measurements of CO2 and H2O fluxes at six forest sites in Europe

Reliable models are required to assess the impacts of climate change on forest ecosystems. Precise and independent data are essential to assess this accuracy. The flux measurements collected by the EUROFLUX project over a wide range of forest types and climatic regions in Europe allow a critical testing of the process‐based models which were developed in the LTEEF project. The ECOCRAFT project complements this with a wealth of independent plant physiological measurements. Thus, it was aimed in this study to test six process‐based forest growth models against the flux measurements of six European forest types, taking advantage of a large database with plant physiological parameters. The reliability of both the flux data and parameter values itself was not under discussion in this study. The data provided by the researchers of the EUROFLUX sites, possibly with local corrections, were used with a minor gap‐filling procedure to avoid the loss of many days with observations. The model performance is discussed based on their accuracy, generality and realism. Accuracy was evaluated based on the goodness‐of‐fit with observed values of daily net ecosystem exchange, gross primary production and ecosystem respiration (gC m^?2 d^?1), and transpiration (kg H₂O m^?2 d^?1). Moreover, accuracy was also evaluated based on systematic and unsystematic errors. Generality was characterized by the applicability of the models to different European forest ecosystems. Reality was evaluated by comparing the modelled and observed responses of gross primary production, ecosystem respiration to radiation and temperature. The results indicated that: Accuracy. All models showed similar high correlation with the measured carbon flux data, and also low systematic and unsystematic prediction errors at one or more sites of flux measurements. The results were similar in the case of several models when the water fluxes were considered. Most models fulfilled the criteria of sufficient accuracy for the ability to predict the carbon and water exchange between forests and the atmosphere. Generality. Three models of six could be applied for both deciduous and coniferous forests. Furthermore, four models were applied both for boreal and temperate conditions. However, no severe water‐limited conditions were encountered, and no year‐to‐year variability could be tested. Realism. Most models fulfil the criterion of realism that the relationships between the modelled phenomena (carbon and water exchange) and environment are described causally. Again several of the models were able to reproduce the responses of measurable variables such as gross primary production (GPP), ecosystem respiration and transpiration to environmental driving factors such as radiation and temperature. Stomatal conductance appears to be the most critical process causing differences in predicted fluxes of carbon and water between those models that accurately describe the annual totals of GPP, ecosystem respiration and transpiration. As a conclusion, several process‐based models are available that produce accurate estimates of carbon and water fluxes at several forest sites of Europe. This considerable accuracy fulfils one requirement of models to be able to predict the impacts of climate change on the carbon balance of European forests. However, the generality of the models should be further evaluated by expanding the range of testing over both time and space. In addition, differences in behaviour between models at the process level indicate requirement of further model testing, with special emphasis on modelling stomatal conductance realistically.     

Assimilation exceeds respiration sensitivity to drought: A FLUXNET synthesis

The intensification of the hydrological cycle, with an observed and modeled increase in drought incidence and severity, underscores the need to quantify drought effects on carbon cycling and the terrestrial sink. FLUXNET, a global network of eddy covariance towers, provides dense data streams of meteorological data, and through flux partitioning and gap filling algorithms, estimates of net ecosystem productivity (F_NEP), gross ecosystem productivity (P), and ecosystem respiration (R). We analyzed the functional relationship of these three carbon fluxes relative to evaporative fraction (EF), an index of drought and site water status, using monthly data records from 238 micrometeorological tower sites distributed globally across 11 biomes. The analysis was based on relative anomalies of both EF and carbon fluxes and focused on drought episodes by biome and climatic season. Globally P was ≈50% more sensitive to a drought event than R. Network‐wide drought‐induced decreases in carbon flux averaged ?16.6 and ?9.3 g C m^?2 month^?1 for P and R, i.e., drought events induced a net decline in the terrestrial sink. However, in evergreen forests and wetlands drought was coincident with an increase in P or R during parts of the growing season. The most robust relationships between carbon flux and EF occurred during climatic spring for F_NEP and in climatic summer for P and R. Upscaling flux sensitivities to a global map showed that spatial patterns for all three carbon fluxes were linked to the distribution of croplands. Agricultural areas exhibited the highest sensitivity whereas the tropical region had minimal sensitivity to drought. Combining gridded flux sensitivities with their uncertainties and the spatial grid of FLUXNET revealed that a more robust quantification of carbon flux response to drought requires additional towers in all biomes of Africa and Asia as well as in the cropland, shrubland, savannah, and wetland biomes globally.     

Ecosystem‐scale volatile organic compound fluxes during an extreme drought in a broadleaf temperate forest of the Missouri Ozarks (central USA)

Considerable amounts and varieties of biogenic volatile organic compounds (BVOCs) are exchanged between vegetation and the surrounding air. These BVOCs play key ecological and atmospheric roles that must be adequately represented for accurately modeling the coupled biosphere–atmosphere–climate earth system. One key uncertainty in existing models is the response of BVOC fluxes to an important global change process: drought. We describe the diurnal and seasonal variation in isoprene, monoterpene, and methanol fluxes from a temperate forest ecosystem before, during, and after an extreme 2012 drought event in the Ozark region of the central USA. BVOC fluxes were dominated by isoprene, which attained high emission rates of up to 35.4 mg m^?2 h^?1 at midday. Methanol fluxes were characterized by net deposition in the morning, changing to a net emission flux through the rest of the daylight hours. Net flux of CO₂ reached its seasonal maximum approximately a month earlier than isoprenoid fluxes, which highlights the differential response of photosynthesis and isoprenoid emissions to progressing drought conditions. Nevertheless, both processes were strongly suppressed under extreme drought, although isoprene fluxes remained relatively high compared to reported fluxes from other ecosystems. Methanol exchange was less affected by drought throughout the season, confirming the complex processes driving biogenic methanol fluxes. The fraction of daytime (7–17 h) assimilated carbon released back to the atmosphere combining the three BVOCs measured was 2% of gross primary productivity (GPP) and 4.9% of net ecosystem exchange (NEE) on average for our whole measurement campaign, while exceeding 5% of GPP and 10% of NEE just before the strongest drought phase. The megan v2.1 model correctly predicted diurnal variations in fluxes driven mainly by light and temperature, although further research is needed to address model BVOC fluxes during drought events.     

The Carbon Balance of Two Contrasting Mountain Forest Ecosystems in Switzerland: Similar Annual Trends,but Seasonal Differences

Net ecosystem exchange (NEE) of two contrasting mountain forest types in Switzerland was measured by eddy covariance (EC) measurements at a montane mixed forest, the Lägeren forest, over 5 years (2005–2009), and at a subalpine coniferous forest, the Seehornwald in Davos, over 12 years (1997–2009). NEE was validated against annual carbon (C) storage estimates, based on biometric and soil respiration measurements as well as soil C modeling. Three different approaches were used: (1) calculation of net ecosystem production by quantifying C pools and fluxes, (2) assessment of change in wood biomass and soil C storage (ΔC), and (3) application of biomass expansion factors. Although biometric estimates were sensitive to assumptions made for each method applied, they agreed well with measured NEE. Comparing 5 years of EC measurements available at both sites during 2005 and 2009 revealed that NEE, gross primary production (GPP), and total ecosystem respiration (TER) were larger at the Lägeren forest compared to the Davos forest, whereas soil respiration and soil C sequestration were of similar magnitudes. Both sites showed similar annual trends for NEE, GPP and TER, but different seasonal courses, due to different responses to environmental conditions (temperature, soil moisture, and radiation). Differences in the magnitude as well as in the seasonality of ecosystem CO₂ exchange could mainly be attributed to tree phenology, productivity, and carbon allocation patterns, which are combined effects of tree type (broad-leaved vs. coniferous trees) and site-specific climatic conditions. Flux differences between the two mountain sites highlight the importance of considering the role of altitude in ecological studies and modeling.     

珠三角城市绿地CO2通量的季节特征

城市绿地是城市碳循环的重要组成部分,利用长期定位观测资料估算珠三角典型城市绿地的CO2通量,可以为应对气候变化、评价区域碳源汇提供参考。应用2009、2010年,东莞市植物园内的涡度相关法CO2通量定位观测资料,分析了净生态系统交换量(NEE)的年变化及其与气象要素的关系,结果表明:(1)年平均NEE总量为-104.2 gC.m-.2a-1,表明城市绿地生态系统具有固碳能力。(2)NEE随光温条件变化呈现明显的季节动态,12至3月表现为碳源,其他月份表现为碳汇。(3)根据白天NEE与光合有效辐射(PAR)逐月拟合Michaelis-Menten方程,得到年平均表观初始光能利用率(α)为(0.00134±0.00035)mgCO.2μmol-1光子,年平均光饱和生态系统生产力(Pmax)为(1.006±0.283)mgCO.2m-.2s-1。(4)利用夜间呼吸(Reco)与5 cm土壤温度(Ts)拟合指数方程,得到年平均Reco总量为1378.1 gC.m-.2a-1。(5)NEE与PAR、气温(Ta)和饱和水压差(VPD)的相关性分析显示,NEE与PAR偏相关系数的绝对值大于Ta和VPD,表明PAR对NEE的影响最大。     

土壤-植物-大气连续体水热、CO2通量估算模型研究进展

土壤-植物-大气连续体(SPAC)水热、CO2通量的准确估算对理解陆地和大气的物质和能量交换过程有着重要意义.重点阐述了基于过程的土壤-植物-大气连续体水热、CO2通量模型,综述了统计模型、综合模型及基于遥感的模型的发展过程.其中水热通量统计模型包括基于温度和湿度以及基于温度和辐射的方法;CO2通量统计模型包括基于气候因子或蒸散因子以及基于光能利用率的方法.水热通量过程模型包括大叶、双源、多源和多层的水热传输物理模型;CO2通量过程模型包括叶片尺度及由大叶、双叶和多层方法扩展到冠层尺度的生理生态模型以及光合-蒸腾耦合模型.综合模型包括生物物理模型、生物化学模型和生物地理模型.统计模型形式简单,资料易得,对大范围的水热通量模拟具有指导意义;过程模型准确的揭示了水热和CO2通量传输的物理和生理过程,是大尺度综合模型的基础.未来生态系统水热、CO2通量估算模型将集成各种技术手段进行多尺度网络观测和大尺度机理模拟.     

内蒙古克氏针茅草原生态系统-大气通量交换特征

基于内蒙古克氏针茅草原生态系统的涡动相关观测资料和小气候梯度系统观测资料,对研究区碳通量和水热通量的日、季动态进行了研究.结果表明：克氏针茅草原生态系统生长季的碳通量日动态呈U型曲线,即日出前释放CO₂,日出后开始吸收CO₂,正午前后达峰值,午后吸收CO₂减弱,日落后重新转为释放CO₂;9月白天CO₂吸收最为强烈,8月次之,10月最低.克氏针茅草原的感热和潜热通量的日动态均呈倒U型曲线,与碳通量日动态相反,即白天感热和潜热通量多为正值,夜间感热为负值,潜热接近于零;感热通量以5月最高,潜热通量以9月最高.冬季草地为弱碳源,CO₂通量较小,夏季表现为明显的碳汇.     

Net ecosystem exchange modifies the relationship between the autotrophic and heterotrophic components of soil respiration with abiotic factors in prairie grasslands

We investigated the relationships of net ecosystem carbon exchange (NEE), soil temperature, and moisture with soil respiration rate and its components at a grassland ecosystem. Stable carbon isotopes were used to separate soil respiration into autotrophic and heterotrophic components within an eddy covariance footprint during the 2008 and 2009 growing seasons. After correction for self‐correlation, rates of soil respiration and its autotrophic and heterotrophic components for both years were found to be strongly influenced by variations in daytime NEE – the amount of C retained in the ecosystem during the daytime, as derived from NEE measurements when photosynthetically active radiation was above 0 μmol m^?2 s^?1. The time scale for correlation of variations in daytime NEE with fluctuations in respiration was longer for heterotrophic respiration (36–42 days) than for autotrophic respiration (4–6 days). In addition to daytime NEE, autotrophic respiration was also sensitive to soil moisture but not soil temperature. In contrast, heterotrophic respiration from soils was sensitive to changes in soil temperature, soil moisture, and daytime NEE. Our results show that – as for forests – plant activity is an important driver of both components of soil respiration in this tallgrass prairie grassland ecosystem. Heterotrophic respiration had a slower coupling with plant activity than did autotrophic respiration. Our findings suggest that the frequently observed variations in the sensitivity of soil respiration to temperature or moisture may stem from variations in the proportions of autotrophic and heterotrophic components of soil respiration. Rates of photosynthesis at seasonal time scales should also be considered as a driver of both autotrophic and heterotrophic soil respiration for ecosystem flux modeling.     

北京海淀公园绿地二氧化碳通量

作为城市生态系统的重要组成部分,城市绿地有着释氧固碳、降温增湿、吸收有毒有害气体、降尘、减噪等多种生态功能。在对北京海淀公园2006年5月到2007年3月的CO2通量观测数据进行质量评价、数据剔除和插补的基础上,通过与温度、太阳辐射等气象数据的相关性分析,定量研究了海淀公园绿地CO2通量的日变化、年变化以及影响因子。结果表明,海淀公园绿地日CO2通量在一年内具有明显的季节变化,植物生长季3—10月份以吸收CO2为主,11月至翌年2月份以释放CO2为主;年净生态系统生产力(NEP)为8.7554 tCO2/hm2a,反映了海淀公园绿地具有较强的固碳能力。     

Forest productivity recovery or collapse? Model-data integration insights on drought-induced tipping points

More frequent and severe droughts are driving increased forest mortality around the globe. We urgently need to describe and predict how drought affects forest carbon cycling and identify thresholds of environmental stress that trigger ecosystem collapse. Quantifying the effects of drought at an ecosystem level is complex because dynamic climate–plant relationships can cause rapid and/or prolonged shifts in carbon balance. We employ the CARbon DAta MOdel fraMework (CARDAMOM) to investigate legacy effects of drought on forest carbon pools and fluxes. Our Bayesian model-data fusion approach uses tower observed meteorological forcing and carbon fluxes to determine the response and sensitivity of aboveground and belowground ecological processes associated with the 2012–2015 California drought. Our study area is a mid-montane mixed conifer forest in the Southern Sierras. CARDAMOM constrained with gross primary productivity (GPP) estimates covering 2011–2017 show a ~75% reduction in GPP, compared to negligible GPP change when constrained with 2011 only. Precipitation across 2012–2015 was 45% (474 mm) lower than the historical average and drove a cascading depletion in soil moisture and carbon pools (foliar, labile, roots, and litter). Adding 157 mm during an especially stressful year (2014, annual rainfall = 293 mm) led to a smaller depletion of water and carbon pools, steering the ecosystem away from a state of GPP tipping-point collapse to recovery. We present novel process-driven insights that demonstrate the sensitivity of GPP collapse to ecosystem foliar carbon and soil moisture states—showing that the full extent of GPP response takes several years to arise. Thus, long-term changes in soil moisture and carbon pools can provide a mechanistic link between drought and forest mortality. Our study provides an example for how key precipitation threshold ranges can influence forest productivity, making them useful for monitoring and predicting forest mortality events.     

The annual carbon budget of a French pine forest (Pinus pinaster) following harvest

Eddy covariance measurements of net ecosystem exchange (NEE) of carbon dioxide and sensible and latent heat have operated since clear felling of a 50‐year old maritime pine stand in Les Landes, in Southwestern France. Turbulent fluxes from the closed‐path system are computed via different methodologies, including those recommended from EUROFLUX (Adv. Ecol. Res. 30 (2000) 113; Agric. Forest Meteorol. 107 (2001a, b) 43 and 71), and sensitivity analysis demonstrates the merit of post‐processing for accurate flux calculation. Footprint modeling, energy balance closure, and empirical modeling corroborate the eddy flux measurements, indicating best reliability in the daytime. The ecosystem, a net source of atmospheric CO₂, is capable of fixing carbon during fair weather during any season due to the abundance of re‐growing species (mostly grass), formerly from the understorey. Annual carbon loss of 200–340 g m^?2 depends on the period chosen, with inter‐annual variability evident during the 18‐month measurement period and apparently related to available light. Empirical models, with weekly photosynthetic parameters corresponding to seasonal vegetation and respiration depending on soil temperature, fit the data well and allow partitioning of annual NEE into GPP and TER components. Comparison with a similar nearby mature forest (Agric. Forest Meteorol. 108 (2001) 183) indicates that clear‐cutting reduces GPP by two thirds but TER by only one third, transforming a strong forest sink into a source of CO₂. Likewise, the loss of 50% of evapotranspiration (by the trees) leads to increased temperatures and thus reduced net radiation (by one third), and a 50% increase in sensible heat loss by the clear cut.     

Lagged climatic effects on carbon fluxes over three grassland ecosystems in China

Aims The plasticity of ecosystem responses could buffer and postpone the effects of climates on ecosystem carbon fluxes, but this lagged effect is often ignored. In this study, we used carbon flux data collected from three typical grassland ecosystems in China, including a temperate semiarid steppe in Inner Mongolia (Neimeng site, NM), an alpine shrub-meadow in Qinghai (Haibei site, HB) and an alpine meadow steppe in Tibet (Dangxiong site, DX), to examine the time lagged effects of environmental factors on CO₂ exchange.Methods Eddy covariance data were collected from three typical Chinese grasslands. In linking carbon fluxes with climatic factors, we used their averages or cumulative values within each 12-month period and we called them 'yearly' statistics in this study. To investigate the lagged effects of the climatic factors on the carbon fluxes, the climatic 'yearly' statistics were kept still and the 'yearly' statistics of the carbon fluxes were shifted backward 1 month at a time.Important findings Soil moisture and precipitation was the main factor driving the annual variations of carbon fluxes at the alpine HB and DX, respectively, while the NM site was under a synthetic impact of each climatic factor. The time lagged effect analysis showed that temperature had several months, even half a year lag effects on CO₂ exchange at the three studied sites, while moisture's effects were mostly exhibited as an immediate manner, except at NM. In general, the lagged climatic effects were relatively weak for the alpine ecosystem. Our results implied that it might be months or even 1 year before the variations of ecosystem carbon fluxes are adjusted to the current climate, so such lag effects could be resistant to more frequent climate extremes and should be a critical component to be considered in evaluating ecosystem stability. An improved knowledge on the lag effects could advance our understanding on the driving mechanisms of climate change effects on ecosystem carbon fluxes.     

高效经营雷竹林生态系统能量通量过程及闭合度

利用开路涡度相关系统和常规气象仪,对高效经营的雷竹林生态系统2011年的显热通量、潜热通量、净辐射、土壤热通量以及气温、地温、降雨量进行了观测,分析该生态系统能量通量的变化,以及各能量分量的分配特征,并计算了波文比及能量闭合.结果表明：雷竹林全年净辐射为2928.92 MJ·m^-2,潜热通量、显热通量和土壤热通量分别为1384.90、92754和-28.27 MJ·m^-2,各能量分量的日变化和月变化基本呈单峰曲线.潜热通量为能量散失主要形式,占净辐射的47.3%,显热通量占31.7%,波文比呈“U”型曲线,在0.285～2.062之间变化,土壤为热源.雷竹林年能量闭合度为0.782,月平均闭合度为0.808.
     

森林生态系统碳循环的基本概念和野外测定方法评述

全球气候变化与森林生态系统碳循环息息相关,定量评估森林碳收支是生态系统与全球变化研究的重要任务。30年来森林生态系统碳循环研究已经取得了长足的进展,但全球和区域森林碳收支仍然存在很大的不确定性。这一方面与森林生态系统本身的复杂性有关,另一方面也与具体研究方法有关。评述了森林生态系统碳循环的基本概念和主要野外测定方法,为我国森林生态系统碳循环研究提供可参考的方法论。从生态系统碳浓度、密度、通量、分配和周转5个方面回顾了碳循环相关概念,指出碳浓度和碳储量是对碳库的静态描述,而碳通量和碳周转是对碳库的动态描述。净初级生产力是测量最普遍的碳通量组分,但大多数情况下因忽略了一些细节而被系统低估。普遍使用的净生态系统生产力,由于没有包含非CO2形式的水文、气象和干扰过程产生的碳通量,通常情况下高于生态系统净碳累积速率。在详细介绍碳通量组分的基础上,改进了森林生态系统碳循环的概念模型。重点讨论了碳通量的3种地面实测方法:测树学方法、箱法和涡度协方差法,并指出了其注意事项和不确定性来源。针对当前碳循环研究的突出问题,建议从4个方面减小碳循环测定的不确定性:(1)恰当运用生物量方程估算乔木生物量;(2)尽可能全面测定生态系统碳组分;(3)给出碳通量估算值的不确定性;(4)多种途径交互验证。     

散射辐射测量及其对陆地生态系统生产力影响的研究进展

全球变化,特别是大气成分变化引起的散射辐射变化已经并将继续影响陆地生态系统的生产力与碳收支。该文综述了散射辐射的影响因子及其估算方法,分析了散射辐射对植被光能利用率(light-use efficiency,LUE)、陆地生态系统生产力及其碳收支的影响过程与控制机理,在此基础上提出了未来拟加强研究的方面:1)散射辐射对植物光合作用影响的机理及其在不同时空尺度的反应;2)散射辐射及其与其他环境因子的相互作用对植物与冠层光合作用影响的定量描述;3)散射辐射及其与其他环境因子的相互作用对土壤呼吸作用的影响过程与控制机理;4)植物对散射辐射及其与其他环境因子相互作用的适应性研究;5)散射辐射及其与其他环境因子的相互作用对陆地生态系统生产力及其碳收支的影响过程与调控对策。