Recent progress and future directions of ChinaFLUX

The eddy covariance technique has emerged as an important tool to directly measure carbon dioxide, water vapor and heat fluxes between the terrestrial ecosystem and the atmosphere after a long history of fundamental research and technological developments. With the realization of regional networks of flux measurements in North American, European, Asia, Brazil, Australia and Africa, a global-scale network of micrometeorological flux measurement (FLUXNET) was established in 1998. FLUXNET has made great progresses in investigating the environmental mechanisms controlling carbon and water cycles, quantifying spatial-temporal patterns of carbon budget and seeking the “missing carbon sink” in global terrestrial ecosystems in the past ten years. The global-scale flux measurement also built a platform for international communication in the fields of resource, ecology and environment sciences. With the continuous development of flux research, FLUXNET will introduce and explore new techniques to extend the application fields of flux measurement and to answer questions in the fields of bio-geography, eco-hydrology, meteorology, climate change, remote sensing and modeling with eddy covariance flux data. As an important part of FLUXNET, ChinaFLUX has made significant progresses in the past three years on the methodology and technique of eddy covariance flux measurement, on the responses of CO₂ and H₂O exchange between the terrestrial ecosystem and the atmosphere to environmental change, and on flux modeling development. Results showed that the major forests on the North-South Transect of Eastern China (NSTEC) were all carbon sinks during 2003 to 2005, and the alpine meadows on the Tibet Plateau were also small carbon sinks. However, the reserved natural grassland, Leymus chinensis steppe in Inner Mongolia, was a carbon source. On a regional scale, temperature and precipitation are the primary climatic factors that determined the carbon balance in major terrestrial ecosystems in China. Finally, the current research emphasis and future directions of ChinaFLUX were presented. By combining flux network and terrestrial transect, ChinaFLUX will develop integrated research with multi-scale, multi-process, multi-subject observations, placing emphasis on the mechanism and coupling relationships between water, carbon and nitrogen cycles in terrestrial ecosystems.     

Advances in carbon flux observation and research in Asia

As an important component of FLUXNET, Asia is increasingly becoming the hotspot in global carbon research for its vast territory, complex climate type and vegetation diversity. The present three regional flux observation networks in Asia (i.e. AsiaFlux, KoFlux and ChinaFLUX)have 54 flux observation sites altogether, covering tropic rainforest, evergreen broad-leaved forest, broad-leaved and coniferous mixed forest, shrubland, grassland, alpine meadow and cropland ecosystems with a latitudinal distribution from 2°N to 63°N. Long-term and continuous fluxes of carbon dioxide, water vapor and energy between the biosphere and atmosphere are mainly measured with eddy covariance technique to (1) quantify and compare the carbon, water and energy budgets across diverse ecosystems; (2) quantify the environmental and biotic controlling mechanism on ecosystem carbon, water and energy fluxes; (3) validate the soil-vegetation-atmosphere model; and (4) serve the integrated study of terrestrial ecosystem carbon and water cycle. Over the last decades, great advancements have been made in the theory and technology of flux measurement, ecosystem flux patterns, simulation and scale conversion by Asian flux community. The establishment of ChinaFLUX has greatly filled the gap of flux observation and research in Eurasia. To further promote the flux measurement and research,accelerate data sharing and improve the data quality, it is necessary to present a methodological system of flux estimation and evaluation over complex terrain and to develop the integrated research that combines the flux measurement, stable isotope measurement, remote sensing observation and GIS technique. It also requires the establishment of the Joint Committee of Asian Flux Network in the Asia-Pacific region in order to promote the cooperation and communication of ideas and data by supporting project scientists, workshops and visiting scientists.     

Energy balance closure at ChinaFLUX sites

Network of eddy covariance observation is measuring long-term carbon and water fluxes in contrasting ecosystems and climates. As one important reference of independently evaluating scalar flux estimates from eddy covariance, energy balance closure is used widely in study of carbon and water fluxes. Energy balance closure in ChinaFLUX was evaluated by statistical regression of turbulent energy fluxes (sensible and latent heat) against available energy (net radiation, soil heat flux, canopy heat storage) and the energy balance ratio (EBR) and the frequency distribution of relative errors of energy balance (δ). The trends of diurnal and seasonal variation of energy balance in ChinaFLUX were analyzed. The results indicated that the imbalance was prevalent in all observation sites, but there were little differences among sites because of the properties variation of sites. The imbalance was greater during nocturnal periods than daytime and closure was improved with friction velocity intensifying. Generally the results suggested that estimates of the scalar turbulent fluxes of sensible and latent heat were underestimated and/or that available energy was overestimated. Finally, we discussed certain factors that are contributed to the imbalance of energy, such as systematic errors associated with the sampling mismatch, systematic instrument bias, neglected energy sinks, low and high frequency loss of turbulent fluxes and advection of heat and water vapor.     

A preliminary study for spatial representiveness of flux observation at ChinaFLUX sites

The results of eddy covariance observation system could represent the physical process at certain area of the surface. Thus point-to-area representativeness was of primary interest in flux observation. This research presents a preliminary study for flux observation at ChinaFLUX sites by the use of observation data and Flux Source Area Model (FSAM). Results show that the footprint expands and is further away from flux tower when atmosphere becomes more stable, the observation height increases, or the surfaces become smoother. This suggests that the area represented by the flux observation becomes larger. The distances from the reference point to the maximum point Smax and the minimum point x1 of source weight function (Dmax and Dmin, respectively) can be influenced by atmosphere stability which becomes longer when atmosphere is more stable. For more rough surfaces and lower observation point Dmax and Dmin become shorter. This research gives the footprint at level P=90% at ChinaFLUX sites at different atmosphere stability. The preliminary results of spatial representiveness at ChinaFLUX sites were given based on the dominant wind direction and footprint response to various factors. The study also provides some theoretical basis for data quality control and evaluating data uncertainty.     

Seasonal patterns and environmental control of ecosystem respiration in subtropical and temperate forests in China

Continuous measurement of carbon dioxide exchange using the eddy covariance (EC) technique was made at two ChinaFLUX forest sites including the young subtropical Pinus plantation (Qianyanzhou) and old temperate broad-leaved Korean pine mixed forest (Changbai Mountains) as part of the ChinaFLUX network. Seasonal patterns and environmental control of ecosystem respiration in the subtropical and temperate forests were evaluated by the often-used multiplicative model and Q10 model as a function of temperature and soil water content. The resuits suggested that ( i ) temperature was found to be a dominant factor in the ecosystem respiration, and most of the temporal variability of ecosystem respiration was explained by temperature. However, in the drought-stressed ecosystem, soil water content controlled the temporal variability of ecosystem respiration other than temperature effects, and soil water content became a dominat factor when severe drought affected the ecosystem respiration; (ii) the regression models analysis revealed that in the drier soil, ecosystem respiration was more sensitive to soil moisture than was expressed by the often-used multiplicative model. It was possible to accurately estimate the seasonal variation of ecosystem respiration based on the Q10 model; and (iii)annual ecosystem respiration derived from the often-used multiplicative model was 1209 g C m-2and 1303 g C m-2, and was consistently a little higher than the Q10 model estimates of 1197 g C m-2 and 1268 g C m-2 for Qianyanzhou and Changbai Mountains, respectively.     

Seasonal drought effects on carbon sequestration of a mid-subtropical planted forest of southeastern China

Continuous measurement of carbon dioxide exchange using the eddy covariance (EC) technique is made at the Qianyanzhou mid-subtropical planted forest as part of the ChinaFLUX network. Qianyanzhou planted forest is affected by typical subtropical continental monsoon climate. It has plentiful water and heat resource but is in inconsistency of its seasonal distribution in the mid-subtropical region, thus seasonal drought frequently occurs in this planted forest. In this study, seasonal drought effect on ecosystem carbon sequestration was analyzed based on net ecosystem productivity (NEP), ecosystem respiration (RE) and gross ecosystem productivity (GEP) at the month scale in 2003 and 2004. In this drought-stressed planted forest, ecosystem carbon sequestration showed a clear seasonality, with low rates during seasonal drought and in winter. The declining degree of ecosystem carbon sequestration under the seasonal drought condition was determined by the accumulation of soil moisture deficits and a co-occurrence of high temperatures. Different drought effects are expected for RE and GEP. The net effect of ecosystem carbon balance depends on how these two quantities are affected relatively to each other. Summer drought and heat wave are two aspects of weather that likely play an important part in the annual NEP of forest in this region.     

Seasonal dynamics of CO<Subscript>2</Subscript> fluxes from subtropical plantation coniferous ecosystem

As one component of ChinaFLUX, the measurement of CO₂ flux using eddy covariance over subtropical planted coniferous ecosystem in Qianyanzhou was conducted for a long term. This paper discusses the seasonal dynamics of net ecosystem exchange (NEE), ecosystem respiration (RE) and gross ecosystem exchange (GEE) between the coniferous ecosystem and atmosphere along 2003 and 2004. The variations of NEE, RE and GEE show obvious seasonal variabilities and correlate to each other, i.e. lower in winter and drought season, but higher in summer; light, temperature and soil water content are the main factors determining NEE; air temperature and water vapor pressure deficit (VPD) influence NEE with stronger influence from VPD. Under the proper light condition, drought stress could decrease the temperature range for carbon capture in planted coniferous, air temperature and precipitation controlled RE; The NEE, RE, and GEE for planted coniferous in Qianyanzhou are ?387.2 g C·m^?2 a^?1, 1223.3 g C·m^?2 a^?1, ?1610.4 g C·m^?2 a^?1 in 2003 and ?423.8 g C·m^?2 a^?1, 1442.0 g C·m^?2 a^?1, ?1865.8 g C·m^?2 a^?1 in 2004, respectively, which suggest the intensive ability of plantation coniferous forest on carbon absorbing in Qianyanzhou.     

Spatio-temporal patterns of forest carbon dioxide exchange based on global eddy covariance measurements

Spatio-temporal patterns and driving mechanisms of forest carbon dioxide (CO2) exchange are the key issues on terrestrial ecosystem carbon cycles, which are the basis for developing and validating ecosystem carbon cycle models, assessing and predicting the role of forests in global carbon balance. Eddy covariance (EC) technique, an important method for measuring energy and material exchanges between terrestrial ecosystems and the atmosphere, has made a great contribution to understanding CO2 exchanges in the biosphere during the past decade. Here, we synthesized published EC flux measurements at various forest sites in the global network of eddy flux tower sites (FLUXNET) and regional flux networks. Our objective was to explore spatio-temporal patterns and driving factors on forest carbon fluxes, i.e. net ecosystem productivity (NEP), gross primary productivity (GPP) and total ecosystem respiration (TER). Globally, forest NEP exhibited a significant latitudinal pattern jointly controlled by GPP and TER. The NEP decreased in an order of warm temperate forest > cold temperate and tropical rain forests > boreal and subalpine forests. Mean annual temperature (MAT) made a greater contribution to forest carbon fluxes than sum of annual precipitation (SAP). As MAT increased, the GPP increased linearly, whereas the TER increased exponentially, resulting in the NEP decreasing beyond an MAT threshold of 20°C. The GPP, TER and NEP varied substantially when the SAP was less than 1500 mm, but tended to increase with increasing SAP. Temporal dynamics in forest carbon fluxes and determinants depended upon time scales. NEP showed a significant interannual variability mainly driven by climate fluctuations and different responses of the GPP and TER to environmental forcing. In a longer term, forest carbon fluxes had a significant age effect. The ecosystem was a net carbon source right after clearcutting, gradually switched to a net carbon sink when the relative stand age (i.e. ratio of actual stand age to the stand rotation age) approached 0.3, and maximized carbon sequestration capacity at premature or mature stand stages. This temporal pattern of NEP was correlated with stand leaf area index and associated GPP. This study highlights the significance of spatio-temporal dynamics in the CO2 exchange in forest carbon cycling studies. It is also suggested that in addition to forest biomes, interannual variations and stand age effects of forest carbon fluxes should be considered in the global carbon balance.     

Comparison of flux measurement by open-path and close-path eddy covariance systems

For flux measurement, the eddy covariance technique supplies a possibility to directly measure the exchange between vegetation and atmosphere; and there are two kinds of eddy covariance systems, open-path and close-path systems. For the system error, it may result in difference of flux measurements by two systems. Therefore, it is necessary to compare the measured results from them. ChinaFLUX covers of eight sites applied the micrometeorological method, in which Changbai Mountains (CBS) and Qianyanzhou (QYZ) carried out open-path eddy covariance (OPEC) and close-path eddy covariance (CPEC) measurements synchronously.In this paper the data sets of CBS and QYZ were employed. The delay time of close-path analyzer to the open-path analyzer was calculated; the spectra and cospectra of time-series data of OPEC and CPEC were analyzed; the open-path flux measurement was used as a standard comparison, the close-path flux measurement results were evaluated. The results show that, at two sites the delay time of CO2 density for close-path analyzer was about 7.0-8.0 s, H2O density about 8.0-9.0 s; the spectrum from the open-path, close-path and 3D sonic anemometer was consistent with the expected -2/3 slope (log-log plot), and the cospectra showed the expected slope of -4/3 in the internal subrange; the CO2 flux measured by the close-path sensor was about 84% of that of open-path measurement at QYZ, about 80% at CBS, and the latent heat flux was balanced for two systems at QYZ, 86% at CBS. From the flux difference between open-path and close-path analyzers, it could be inferred that the attenuation of turbulent fluctuations in flow through tube of CPEC affected H2O flux more significantly than CO2 flux. The gap between two systems was bigger at CBS than at QYZ; the diurnal variation in CO2 flux of two measurement systems was very consistent.     

Seasonal drought effects on carbon sequestration of a mid-subtropical planted forest of southeastern China

Continuous measurement of carbon dioxide exchange using the eddy covariance (EC) technique is made at the Qianyanzhou mid-subtropical planted forest as part of the ChinaFLUX net-work. Qianyanzhou planted forest is affected by typical subtropical continental monsoon climate. It has plentiful water and heat resource but is in inconsistency of its seasonal distribution in the mid-subtropical region, thus seasonal drought frequently occurs in this planted forest. In this study, seasonal drought effect on ecosystem carbon sequestration was analyzed based on net ecosystem productivity (NEP), ecosystem respiration (RE) and gross ecosystem productivity (GEP) at the month scale in 2003 and 2004. In this drought-stressed planted forest, ecosystem carbon sequestration showed a clear seasonality, with low rates during seasonal drought and in winter. The declining degree of ecosystem carbon sequestration under the seasonal drought condition was determined by the accumulation of soil moisture deficits and a co-occurrence of high temperatures. Different drought effects are expected for RE and GEP. The net effect of ecosystem carbon balance depends on how these two quantities are affected relatively to each other. Summer drought and heat wave are two aspects of weather that likely play an important part in the annual NEP of forest in this region.     

Simulating the exchanges of carbon dioxide, water vapor and heat over Changbai Mountains temperate broad-leaved Korean pine mixed forest ecosystem

A process-based ecosystem productivity model BEPS (Boreal Ecosystem Productivity Simulator) was updated to simulate half-hourly exchanges of carbon, water and energy between the atmosphere and terrestrial ecosystem at a temperate broad-leaved Korean pine forest in the Changbai Mountains, China. The BEPSh model is able to capture the diurnal and seasonal variability in carbon dioxide, water vapor and heat fluxes at this site in the growing season of 2003. The model validation showed that the simulated net ecosystem productivity (NEP), latent heat flux (LE), sensible heat flux (Hs) are in good agreement with eddy covariance measurements with an R2 value of 0.68, 0.86 and 0.72 for NEP, LE and Hs, respectively. The simulated annual NEP of this forest in 2003 was 300.5 gC/m2, and was very close to the observed value. Driving this model with different climate scenarios, we found that the NEP in the Changbai Mountains temperate broad-leaved Korean pine mixed forest ecosystem was sensitive to climate variability, and the current carbon sink will be weakened under the condition of global warming. Furthermore, as a process-based model, BEPSh was also sensitive to physiological parameters of plant, such as maximum Rubisco activity (Vcmax) and the maximum stomatal conductance (gmax), and needs to be carefully calibrated for other applications.     

Seasonal dynamics of CO2 fluxes from subtropical plantation coniferous ecosystem

As one component of ChinaFLUX, the measurement of CO₂ flux using eddy covariance over subtropical planted coniferous ecosystem in Qianyanzhou was conducted for a long term. This paper discusses the seasonal dynamics of net ecosystem exchange (NEE), ecosystem respiration (RE) and gross ecosystem exchange (GEE) between the coniferous ecosystem and atmosphere along 2003 and 2004. The variations of NEE, RE and GEE show obvious seasonal variabilities and correlate to each other, i.e. lower in winter and drought season, but higher in summer; light, temperature and soil water content are the main factors determining NEE; air temperature and water vapor pressure deficit (VPD) influence NEE with stronger influence from VPD. Under the proper light condition, drought stress could decrease the temperature range for carbon capture in planted coniferous, air temperature and precipitation controlled RE; The NEE, RE, and GEE for planted coniferous in Qianyanzhou are −387.2 g C·m⁻² a⁻¹, 1223.3 g C·m⁻² a⁻¹, −1610.4 g C·m⁻² a⁻¹ in 2003 and −423.8 g C·m⁻² a⁻¹, 1442.0 g C·m⁻² a⁻¹, −1865.8 g C·m⁻² a⁻¹ in 2004, respectively, which suggest the intensive ability of plantation coniferous forest on carbon absorbing in Qianyanzhou.

     

A preliminary study for spatial representiveness of flux observation at ChinaFLUX sites

The results of eddy covariance observation system could represent the physical process at certain area of the surface. Thus point-to-area representativeness was of primary interest in flux observation. This research presents a preliminary study for flux observation at ChinaFLUX sites by the use of observation data and Flux Source Area Model (FSAM). Results show that the footprint expands and is further away from flux tower when atmosphere becomes more stable, the observation height increases, or the surfaces become smoother. This suggests that the area represented by the flux observation becomes larger. The distances from the reference point to the maximum point S _max and the minimum point x ₁ of source weight function (D _max and D _min, respectively) can be influenced by atmosphere stability which becomes longer when atmosphere is more stable. For more rough surfaces and lower observation point D _max and D _min become shorter. This research gives the footprint at level P=90% at ChinaFLUX sites at different atmosphere stability. The preliminary results of spatial representiveness at ChinaFLUX sites were given based on the dominant wind direction and footprint response to various factors. The study also provides some theoretical basis for data quality control and evaluating data uncertainty.     

Simulating CO_2 flux of three different ecosystems in ChinaFLUX based on artificial neural networks

The nonlinearity of the relationship between CO2 flux and other micrometeorological variables flux parameters limits the applicability of carbon flux models to accurately estimate the flux dynamics. However, the need for carbon dioxide (CO2) estimations covering larger areas and the limitations of the point eddy covariance technique to address this requirement necessitates the modeling of CO2 flux from other micrometeorological variables. Artificial neural networks (ANN) are used because of their power to fit highly nonlinear relations between input and output variables without explaining the nature of the phenomena. This paper applied a multilayer perception ANN technique with error back propagation algorithm to simulate CO2 flux on three different ecosystems (forest, grassland and cropland) in ChinaFLUX. Energy flux (net radiation, latent heat, sensible heat and soil heat flux) and temperature (air and soil) and soil moisture were used to train the ANN and predict the CO2 flux. Diurnal half-hourly fluxes data of observations from June to August in 2003 were divided into training, validating and testing. Results of the CO2 flux simulation show that the technique can successfully predict the observed values with R2 value between 0.75 and 0.866. It is also found that the soil moisture could not improve the simulative accuracy without water stress. The analysis of the contribution of input variables in ANN shows that the ANN is not a black box model, it can tell us about the controlling parameters of NEE in different ecosystems and micrometeorological environment. The results indicate the ANN is not only a reliable, efficient technique to estimate regional or global CO2 flux from point measurements and understand the spatiotemporal budget of the CO2 fluxes, but also can identify the relations between the CO2 flux and micrometeorological variables.     

Multi-scale observation and cross-scale mechanistic modeling on terrestrial ecosystem carbon cycle

To predict global climate change and to implement the Kyoto Protocol for stabilizing atmospheric greenhouse gases concentrations require quantifying spatio-temporal variations in the terrestrial carbon sink accurately. During the past decade multi-scale ecological experiment and observation networks have been established using various new technologies (e.g. controlled environmental facilities, eddy covariance techniques and quantitative remote sensing), and have obtained a large amount of data about terrestrial ecosystem carbon cycle. However, uncertainties in the magnitude and spatio-temporal variations of the terrestrial carbon sink and in understanding the underlying mechanisms have not been reduced significantly. One of the major reasons is that the observations and experiments were conducted at individual scales independently, but it is the interactions of factors and processes at different scales that determine the dynamics of the terrestrial carbon sink. Since experiments and observations are always conducted at specific scales, to understand cross-scale interactions requires mechanistic analysis that is best to be achieved by mechanistic modeling. However, mechanistic ecosystem models are mainly based on data from single-scale experiments and observations and hence have no capacity to simulate mechanistic cross-scale interconnection and interactions of ecosystem processes. New-generation mechanistic ecosystem models based on new ecological theoretical framework are needed to quantify the mechanisms from micro-level fast eco-physiological responses to macro-level slow acclimation in the pattern and structure in disturbed ecosystems. Multi-scale data-model fusion is a recently emerging approach to assimilate multi-scale observational data into mechanistic, dynamic modeling, in which the structure and parameters of mechanistic models for simulating cross-scale interactions are optimized using multi-scale observational data. The models are validated and evaluated at different spatial and temporal scales and real-time observational data are assimilated continuously into dynamic modeling for predicting and forecasting ecosystem changes realistically. in summary, a breakthrough in terrestrial carbon sink research requires using approaches of multi-scale observations and cross-scale modeling to understand and quantify interconnections and interactions among ecosystem processes at different scales and their controls over ecosystem carbon cycle.     

Simulation of crop growth and energy and carbon dioxide fluxes at different time steps from hourly to daily

Understanding the exchange processes of energy and carbon dioxide (CO₂) in the soil–vegetation–atmosphere system is important for assessing the role of the terrestrial ecosystem in the global water and carbon cycle and in climate change. We present a soil–vegetation–atmosphere integrated model (ChinaAgrosys) for simulating energy, water and CO₂ fluxes, crop growth and development, with ample supply of nutrients and in the absence of pests, diseases and weed damage. Furthermore, we test the hypotheses of whether there is any significant difference between simulations over different time steps. CO₂, water and heat fluxes were estimated by the improving parameterization method of the coupled photosynthesis–stomatal conductance–transpiration model. Soil water evaporation and plant transpiration were calculated using a multilayer water and heat‐transfer model. Field experiments were conducted in the Yucheng Integrated Agricultural Experimental Station on the North China Plain. Daily weather and crop growth variables were observed during 1998–2001, and hourly weather variables and water and heat fluxes were measured using the eddy covariance method during 2002–2003. The results showed that the model could effectively simulate diurnal and seasonal changes of net radiation, sensible and latent heat flux, soil heat flux and CO₂ fluxes. The processes of evapotranspiration, soil temperature and leaf area index agree well with the measured values. Midday depression of canopy photosynthesis could be simulated by assessing the diurnal change in canopy water potential. Moreover, the comparisons of simulated daily evapotranspiration and net ecosystem exchange (NEE) under different time steps indicated that time steps used by a model affect the simulated results. There is no significant difference between simulated evapotranspiration using the model under different time steps. However, simulated NEE produces large differences in the response to different time steps. Therefore, the accurate calculation of average absorbed photosynthetic active radiation is important for the scaling of the model from hourly steps to daily steps in simulating energy and CO₂ flux exchanges between winter wheat and the atmosphere. Copyright © 2007 John Wiley & Sons, Ltd.     

A comparison between simulated and measured CO_2 and water flux in a subtropical coniferous forest

Using data from eddy covariance measurements in a subtropical coniferous forest, a test and evaluation have been made for the model of Carbon Exchange in the Vegetation-Soil-Atmosphere (CEVSA) that simulates energy transfers and water, carbon and nitrogen cycles based on ecophysiological processes. In the present study, improvement was made in the model in calculating LAI, carbon allocation among plant organs, litter fall, decomposition and evapotranspiration. The simulated seasonal variations in carbon and water vapor flux were consistent with the measurements. The model explained 90% and 86% of the measured variations in evapotranspiration and soil water content. However, the modeled evapotranspiration and soil water content were lower than the measured systematically, because the model assumed that water was lost as runoff if it was beyond the soil saturation water content, but the soil at the flux site with abundant rainfall is often above water saturated. The improved model reproduced 79% and 88% of the measured variations in gross primary production (GPP) and ecosystem respiration (Re), but only 31% of the variations in measured net ecosystem exchange (NEP) despite the fact that the modeled annual NEP was close to the observation. The modeled NEP was generally lower in winter and higher in summer than the observations. The simulated responses of photosynthesis and respiration to water vapor deficit at high temperatures were different from measurements. The results suggested that the improved model underestimated ecosystem photosynthesis and respiration in extremely condition. The present study shows that CEVSA can simulate the seasonal pattern and magnitude of CO2 and water vapor fluxes, but further improvement in simulating photosynthesis and respiration at extreme temperatures and water deficit is required.     

The impacts of climate extremes on the terrestrial carbon cycle:A review

The increased frequency of climate extremes in recent years has profoundly affected terrestrial ecosystem functions and the welfare of human society. The carbon cycle is a key process of terrestrial ecosystem changes. Therefore, a better understanding and assessment of the impacts of climate extremes on the terrestrial carbon cycle could provide an important scientific basis to facilitate the mitigation and adaption of our society to climate change. In this paper, we systematically review the impacts of climate extremes(e.g. drought, extreme precipitation, extreme hot and extreme cold) on terrestrial ecosystems and their mechanisms. Existing studies have suggested that drought is one of the most important stressors on the terrestrial carbon sink, and that it can inhibit both ecosystem productivity and respiration. Because ecosystem productivity is usually more sensitive to drought than respiration, drought can significantly reduce the strength of terrestrial ecosystem carbon sinks and even turn them into carbon sources. Large inter-model variations have been found in the simulations of drought-induced changes in the carbon cycle, suggesting the existence of a large gap in current understanding of the mechanisms behind the responses of ecosystem carbon balance to drought, especially for tropical vegetation. The effects of extreme precipitation on the carbon cycle vary across different regions. In general, extreme precipitation enhances carbon accumulation in arid ecosystems, but restrains carbon sequestration in moist ecosystems. However, current knowledge on the indirect effects of extreme precipitation on the carbon cycle through regulating processes such as soil carbon lateral transportation and nutrient loss is still limited. This knowledge gap has caused large uncertainties in assessing the total carbon cycle impact of extreme precipitation. Extreme hot and extreme cold can affect the terrestrial carbon cycle through various ecosystem processes. Note that the severity of such climate extremes depends greatly on their timing, which needs to be investigated thoroughly in future studies. In light of current knowledge and gaps in the understanding of how extreme climates affect the terrestrial carbon cycle, we strongly recommend that future studies should place more attention on the long-term impacts and on the driving mechanisms at different time scales.Studies based on multi-source data, methods and across multiple spatial-temporal scales, are also necessary to better characterize the response of terrestrial ecosystems to climate extremes.     

Photosynthesis-transpiration coupling model at canopy scale in terrestrial ecosystem

At the hypothesis of big leaf, an ecosystem photosynthesis-transpiration coupling cycle model was established by the scaled SMPT-SB model from single leaf to canopy, and model parameterization methods were discussed. Through simulating the canopy light distribution, canopy internal conductance to CO2 can be scaled from single leaf to canopy by integrating to canopy using the relationship between single internal conductance and photosynthetic photon flux density. Using the data observed by eddy covariance method from the Changbai Mountains site of ChinaFLUX, the application of the model at the canopy scale was examined. Under no water stress, the simulated net ecosystem photosynthesis rate fitted with the observed data very well, the slope and R2 of the line regression equation of the observed and simulated values were 0.7977 and 0.8892, respectively (n = 752), and average absolute error was 3.78 μmol CO2 m-2s-1; the slope, R2 and average absolute error of transpiration rate were 0.7314, 0.4355 and 1.60mmol H2O m-2 s-1, respectively (n = 752). The relationship between canopy photosynthesis,transpiration and external environmental conditions was discussed by treating the canopy as a whole and neglecting the comprehensive feedback mechanism within canopy, and it was noted that the precipitation course affected the transpiration rate simulation badly. Compared to the models based on eco-physiological processes, the SMPT-SB model was simple and easy to be used. And it can be used as a basic carbon and water coupling model of soil-plant-atmosphere continuum.     

Progress in plant phenology modeling under global climate change

Plant phenology is the study of the timing of recurrent biological events and the causes of their timing with regard to biotic and abiotic forces. Plant phenology affects the structure and function of terrestrial ecosystems and determines vegetation feedback to the climate system by altering the carbon, water and energy fluxes between the vegetation and near-surface atmosphere. Therefore, an accurate simulation of plant phenology is essential to improve our understanding of the response of ecosystems to climate change and the carbon, water and energy balance of terrestrial ecosystems. Phenological studies have developed rapidly under global change conditions, while the research of phenology modeling is largely lagged. Inaccurate phenology modeling has become the primary limiting factor for the accurate simulation of terrestrial carbon and water cycles.Understanding the mechanism of phenological response to climate change and building process-based plant phenology models are thus important frontier issues. In this review, we first summarized the drivers of plant phenology and overviewed the development of plant phenology models. Finally, we addressed the challenges in the development of plant phenology models and highlighted that coupling machine learning and Bayesian calibration into process-based models could be a potential approach to improve the accuracy of phenology simulation and prediction under future global change conditions.