Search

The sunlight received by plants is affected by cloudiness and pollution. Future changes in cloud cover will differ among regions, while aerosol concentrations are expected to continue increasing globally as a result of wildfires, fossil fuel combustion, and industrial pollution. Clouds and aerosols increase the diffuse fraction and modify the spectral composition of incident solar radiation, and both will affect photosynthesis and terrestrial ecosystem productivity. Thus, an assessment of how canopy and leaf-level processes respond to these changes is needed as part of accurately forecasting future global carbon assimilation. To review these processes and their implications: first, we discuss the physical basis of the effect of clouds and aerosols on solar radiation as it penetrates the atmosphere; second, we consider how direct and diffuse radiation are absorbed and transmitted by plant canopies and their leaves; and finally, we assess the consequences for photosynthesis at the canopy and ecosystem levels. Photobiology will be affected at the atmospheric level by a shift in spectral composition toward shorter or longer wavelengths under clouds or aerosols, respectively, due to different scattering. Changes in the microclimate and spectral composition of radiation due to an enhanced diffuse fraction also depend on the acclimation of canopy architectural and physiological traits, such as leaf area index, orientation, and clumping. Together with an enhancement of light-use efficiency, this makes the effect of diffuse solar radiation on canopy photosynthesis a multilayered phenomenon, requiring experimental testing to capture those complex interactions that will determine whether it produces the persistent enhancement in carbon assimilation that land-surface models currently predict.

Surface-atmosphere energy exchange is strongly ecosystem-specific. At the same time, as the energy balance constitutes responses of an ecosystem to environmental stressors including precipitation, humidity and solar radiation, it results in feedbacks of potential importance for the regional climate. Northern peatlands represent a diverse class of ecosystems that cover nearly 6 x 10(6) km(2) in the Boreal region, which makes the inter-comparison of their energy balances an important objective. With this in mind we studied energy exchange across a broad spectrum of peatlands from pristine fens and bogs to forested and agriculturally managed peatlands, which represent a large fraction of the landscape in Finland and Sweden. The effects of management activities on the energy balance were extensively examined from the micrometeorological point of view, using eddy covariance data from eight sites in these two countries (56 degrees 12'-62 degrees 11' N, 13 degrees 03'-30 degrees 05' E). It appears that the surface energy balance varies widely amongst the different peatland types. Generally, energy exchange features including the Bowen ratio, surface conductance, coupling to the atmosphere, responses to water table fluctuations and vapour pressure deficit could be associated directly with the peatland type. The relative constancy of the Bowen ratio in natural open mires contrasted with its variation in tree-covered and agricultural peatlands. We conclude that the impacts of management and the consequences of land-use change in peatlands for the local and regional climate might be substantial.

The seasonality of the NEE of the northern boreal coniferous forests was investigated by means of inversion modelling using eddy covariance data. Eddy covariance data was used to optimize the biochemical model parameters. Our study sites consisted of three Scots pine (l. Pinus sylvestris) forests and one Norway spruce (l. Picea abies) forest that were located in Finland and Sweden. We obtained temperature and seasonal dependence for the biochemical model parameters: the maximum rate of carboxylation (Vc(max)) and the maximum rate of electron transport (Jmax). Both of the parameters were optimized without assumptions about their mutual magnitude. The values obtained for the biochemical model parameters were similar at all the sites during summer time. To describe seasonality, different temperature fits were made for the spring, summer and autumn periods. During summer, average Jmax across the sites was 54.0 μmol m−2 s−1 (variance 31.2 μmol m−2 s−1) and Vc(max) was 12.0 μmol m−2 s−1 (variance 6.6 μmol m−2 s−1) at 17°C. The sensitivity of the model to LAI and atmospheric soil water stress was also studied. The impact of seasonality on annual GPP was 17% when only summertime parameterization was used throughout the year compared to seasonally changing parameterizations.

Accurate predictions of net ecosystem productivity (NEPc) of forest ecosystems are essential for climate change decisions and requirements in the context of national forest growth and greenhouse gas inventories. However, drivers and underlying mechanisms determining NEPc (e.g., climate and nutrients) are not entirely understood yet, particularly when considering the influence of past periods. Here we explored the explanatory power of the compensation day (cDOY)—defined as the day of year when winter net carbon losses are compensated by spring assimilation—for NEPc in 26 forests in Europe, North America, and Australia, using different NEPc integration methods. We found cDOY to be a particularly powerful predictor for NEPc of temperate evergreen needleleaf forests (R2 = 0.58) and deciduous broadleaf forests (R2 = 0.68). In general, the latest cDOY correlated with the lowest NEPc. The explanatory power of cDOY depended on the integration method for NEPc, forest type, and whether the site had a distinct winter net respiratory carbon loss or not. The integration methods starting in autumn led to better predictions of NEPc from cDOY then the classical calendar method starting 1 January. Limited explanatory power of cDOY for NEPc was found for warmer sites with no distinct winter respiratory loss period. Our findings highlight the importance of the influence of winter processes and the delayed responses of previous seasons' climatic conditions on current year's NEPc. Such carry-over effects may contain information from climatic conditions, carbon storage levels, and hydraulic traits of several years back in time.

Networks that merge and harmonise eddy-covariance measurements from many different parts of the world have become an important observational resource for ecosystem science. Empirical algorithms have been developed which combine direct observations of the net ecosystem exchange of carbon dioxide with simple empirical models to disentangle photosynthetic (GPP) and respiratory fluxes (Reco). The increasing use of these estimates for the analysis of climate sensitivities, model evaluation and calibration demands a thorough understanding of assumptions in the analysis process and the resulting uncertainties of the partitioned fluxes. The semi-empirical models used in flux partitioning algorithms require temperature observations as input, but as respiration takes place in many parts of an ecosystem, it is unclear which temperature input – air, surface, bole, or soil at a specific depth – should be used. This choice is a source of uncertainty and potential biases. In this study, we analysed the correlation between different temperature observations and nighttime NEE (which equals nighttime respiration) across FLUXNET sites to understand the potential of the different temperature observations as input for the flux partitioning model. We found that the differences in the correlation between different temperature data streams and nighttime NEE are small and depend on the selection of sites. We investigated the effects of the choice of the temperature data by running two flux partitioning algorithms with air and soil temperature. We found the time lag (phase shift) between air and soil temperatures explains the differences in the GPP and Reco estimates when using either air or soil temperatures for flux partitioning. The impact of the source of temperature data on other derived ecosystem parameters was estimated, and the strongest impact was found for the temperature sensitivity. Overall, this study suggests that the choice between soil or air temperature must be made on site-by-site basis by analysing the correlation between temperature and nighttime NEE. We recommend using an ensemble of estimates based on different temperature observations to account for the uncertainty due to the choice of temperature and to assure the robustness of the temporal patterns of the derived variables.

Networks that merge and harmonise eddy-covariance measurements from many different parts of the world have become an important observational resource for ecosystem science. Empirical algorithms have been developed which combine direct observations of the net ecosystem exchange of carbon dioxide with simple empirical models to disentangle photosynthetic (GPP) and respiratory fluxes (R-eco). The increasing use of these estimates for the analysis of climate sensitivities, model evaluation and calibration demands a thorough understanding of assumptions in the analysis process and the resulting uncertainties of the partitioned fluxes. The semi-empirical models used in flux partitioning algorithms require temperature observations as input, but as respiration takes place in many parts of an ecosystem, it is unclear which temperature input - air, surface, bole, or soil at a specific depth - should be used. This choice is a source of uncertainty and potential biases. In this study, we analysed the correlation between different temperature observations and nighttime NEE (which equals nighttime respiration) across FLUXNET sites to understand the potential of the different temperature observations as input for the flux partitioning model. We found that the differences in the correlation between different temperature data streams and nighttime NEE are small and depend on the selection of sites. We investigated the effects of the choice of the temperature data by running two flux partitioning algorithms with air and soil temperature. We found the time lag (phase shift) between air and soil temperatures explains the differences in the GPP and Reco estimates when using either air or soil temperatures for flux partitioning. The impact of the source of temperature data on other derived ecosystem parameters was estimated, and the strongest impact was found for the temperature sensitivity. Overall, this study suggests that the choice between soil or air temperature must be made on site-by-site basis by analysing the correlation between temperature and nighttime NEE. We recommend using an ensemble of estimates based on different temperature observations to account for the uncertainty due to the choice of temperature and to assure the robustness of the temporal patterns of the derived variables.

In this study we examined ecosystem respiration (RECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of RECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of RECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of RECO. The maximum seasonal leaf area index (LAIMAX) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature Tref515 1C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r250.52, Po0.001, n5104) even within each PFT. Besides LAIMAX, we found that reference respiration may be explained partially by total soil carbon content (SoilC). For undisturbed temperate and boreal forests a negative control of total nitrogen deposition (Ndepo) on reference respiration was also identified. We developed a new semiempirical model incorporating abiotic factors (climate), recent productivity (daily GPP), general site productivity and canopy structure (LAIMAX) which performed well in predicting the spatio-temporal variability of RECO, explaining 470% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands

Over the last two and half decades, strong evidence showed that the terrestrial ecosystems are acting as a net sink for atmospheric carbon. However the spatial and temporal patterns of variation in the sink are not well known. In this study, we examined latitudinal patterns of interannual variability (IAV) in net ecosystem exchange (NEE) of CO2 based on 163 site-years of eddy covariance data, from 39 northern-hemisphere research sites located at latitudes ranging from ~29°N to ~64°N. We computed the standard deviation of annual NEE integrals at individual sites to represent absolute interannual variability (AIAV), and the corresponding coefficient of variation as a measure of relative interannual variability (RIAV). Our results showed decreased trends of annual NEE with increasing latitude for both deciduous broadleaf forests and evergreen needleleaf forests. Gross primary production (GPP) explained a significant proportion of the spatial variation of NEE across evergreen needleleaf forests, whereas, across deciduous broadleaf forests, it is ecosystem respiration (Re). In addition, AIAV in GPP and Re increased significantly with latitude in deciduous broadleaf forests, but AIAV in GPP decreased significantly with latitude in evergreen needleleaf forests. Furthermore, RIAV in NEE, GPP, and Re appeared to increase significantly with latitude in deciduous broadleaf forests, but not in evergreen needleleaf forests. Correlation analyses showed air temperature was the primary environmental factor that determined RIAV of NEE in deciduous broadleaf forest across the North American sites, and none of the chosen climatic factors could explain RIAV of NEE in evergreen needleleaf forests. Mean annual NEE significantly increased with latitude in grasslands. Precipitation was dominant environmental factor for the spatial variation of magnitude and IAV in GPP and Re in grasslands.

Terrestrial ecosystems sequester 2.1 Pg of atmospheric carbon annually. A large amount of the terrestrial sink is realized by forests. However, considerable uncertainties remain regarding the fate of this carbon over both short and long timescales. Relevant data to address these uncertainties are being collected at many sites around the world, but syntheses of these data are still sparse. To facilitate future synthesis activities, we have assembled a comprehensive global database for forest ecosystems, which includes carbon budget variables (fluxes and stocks), ecosystem traits (e.g. leaf area index, age), as well as ancillary site information such as management regime, climate, and soil characteristics. This publicly available database can be used to quantify global, regional or biome-specific carbon budgets; to re-examine established relationships; to test emerging hypotheses about ecosystem functioning [e.g. a constant net ecosystem production (NEP) to gross primary production (GPP) ratio]; and as benchmarks for model evaluations. In this paper, we present the first analysis of this database. We discuss the climatic influences on GPP, net primary production (NPP) and NEP and present the CO2 balances for boreal, temperate, and tropical forest biomes based on micrometeorological, ecophysiological, and biometric flux and inventory estimates. Globally, GPP of forests benefited from higher temperatures and precipitation whereas NPP saturated above either a threshold of 1500 mm precipitation or a mean annual temperature of 10 °C. The global pattern in NEP was insensitive to climate and is hypothesized to be mainly determined by nonclimatic conditions such as successional stage, management, site history, and site disturbance. In all biomes, closing the CO2 balance required the introduction of substantial biome-specific closure terms. Nonclosure was taken as an indication that respiratory processes, advection, and non-CO2 carbon fluxes are not presently being adequately accounted for.

The vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs). PFTs are used in global land-surface models to provide parameter values for every model grid cell. With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set. We compare the model parameters within and between PFTs and statistically group the sites. Fluxnet data is used to validate the photosynthesis model parameter variation within a PFT classification. Our major result is that model parameters appear more variable than assumed in PFTs. Simulated fluxes are of higher quality when model parameters of individual sites or site years are used. A simplification with less variation in model parameters results in poorer simulations. This indicates that a PFT classification introduces uncertainty in the variation of the photosynthesis and transpiration fluxes. Statistically derived groups of sites with comparable model parameters do not share common vegetation types or climates. A simple PFT classification does not reflect the real photosynthesis and transpiration variation. Although site year parameters give the best predictions, the parameters are generally too specific to be used in a global study. The site year parameters can be further used to explore the possibilities of alternative classification schemes. © 2010 Elsevier B.V.

In this study we examined ecosystem respiration (RECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of RECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of RECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of RECO. The maximum seasonal leaf area index (LAIMAX) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature Tref515 1C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r250.52, Po0.001, n5104) even within each PFT. Besides LAIMAX, we found that reference respiration may be explained partially by total soil carbon content (SoilC). For undisturbed temperate and boreal forests a negative control of total nitrogen deposition (Ndepo) on reference respiration was also identified. We developed a new semiempirical model incorporating abiotic factors (climate), recent productivity (daily GPP), general site productivity and canopy structure (LAIMAX) which performed well in predicting the spatio-temporal variability of RECO, explaining 470% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands

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 (FNEP), 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 gCm-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 FNEP 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.

Over the last two and half decades, strong evidence showed that the terrestrial ecosystems are acting as a net sink for atmospheric carbon. However the spatial and temporal patterns of variation in the sink are not well known. In this study, we examined latitudinal patterns of interannual variability (IAV) in net ecosystem exchange (NEE) of CO2 based on 163 site-years of eddy covariance data, from 39 northern-hemisphere research sites located at latitudes ranging from ~ 29°Nto ~ 64°N. We computed the standard deviation of annual NEE integrals at individual sites to represent absolute interannual variability (AIAV), and the corresponding coefficient of variation as a measure of relative interannual variability (RIAV). Our results showed decreased trends of annual NEE with increasing latitude for both deciduous broadleaf forests and evergreen needleleaf forests. Gross primary production (GPP) explained a significant proportion of the spatial variation of NEE across evergreen needleleaf forests, whereas, across deciduous broadleaf forests, it is ecosystem respiration (Re). In addition, AIAV in GPP and Re increased significantly with latitude in deciduous broadleaf forests, but AIAV in GPP decreased significantly with latitude in evergreen needleleaf forests. Furthermore, RIAV in NEE, GPP, and Re appeared to increase significantly with latitude in deciduous broadleaf forests, but not in evergreen needleleaf forests. Correlation analyses showed air temperature was the primary environmental factor that determined RIAV of NEE indeciduous broadleaf forest across the North American sites, and none of the chosen climatic factors could explain RIAV of NEE in evergreen needleleaf forests. Mean annual NEE significantly increased with latitude in grasslands. Precipitation was dominant environmental factor for the spatial variation of magnitude and IAV in GPP and Re in grasslands.

Some of the plant hydrology schemes implemented in global land surface models (LSMs) are relatively simple. This is despite evidence that simulated carbon, water, and energy fluxes are sensitive to both the availability of soil moisture and the formulation of plant hydrology. The current study introduces a mechanistic scheme of plant hydrology (soil-plant-atmosphere (SPA)) into a global LSM (Joint U. K. Land Environmental Simulator (JULES)) in order to compare with a traditional, semiempirical plant hydrology scheme (SiB) based on the Ball-Berry stomatal relation. The SPA scheme simulates explicitly the physical processes which change leaf water potential and account for the flow of water through the soil-plant-atmosphere media. Using both plant hydrology schemes, the annually averaged global evaporation-to-precipitation ratio is 0.58+/-0.9. The annually averaged global transpiration-to-precipitation ratio is 0.22+/-0.09 and 0.28+/-0.08 using the SPA and SiB plant hydrology schemes, respectively. The output from the two plant hydrology schemes typically differs less than the systematic errors associated with the different observational data sets (eddy covariance fluxes, continental runoff, etc.) employed to calibrate and validate the LSM. However, SPA is more conservative with respect to plant water use efficiency compared to SiB. This is partly due to the exhaustion of stored leaf water (not accounted for with the SiB scheme) which acts to limit afternoon transpiration when diurnal vapor pressure deficit is greatest. The trend in global runoff simulated with both plant hydrology schemes for the latter half of the 20th century (-1% per 50 years) agrees well with recent observational estimates that sample 80% of the global runoff network.

Quantification of an ecosystem's carbon balance and its components is pivotal for understanding both ecosystem functioning and global cycling. Several methods are being applied in parallel to estimate the different components of the CO2 balance. However, different methods are subject to different sources of error. Therefore, it is necessary that site level component estimates are cross-checked against each other before being reported. Here we present a two-step approach for testing the accuracy and consistency of eddy covariance–based gross primary production (GPP) and ecosystem respiration (Re) estimates with biometric measurements of net primary production (NPP), autotrophic (Ra) and heterotrophic (Rh) respiration. The test starts with closing the CO2 balance to account for reasonable errors in each of the component fluxes. Failure to do so within the constraints will classify the flux estimates on the site level as inconsistent. If the CO2 balance can be closed, the test continues by comparing the closed site level Ra/GPP with the Rh/GPP ratio. The consistency of these ratios is then judged against expert knowledge. Flux estimates of sites that pass both steps are considered consistent. An inconsistent ratio is not necessarily incorrect but provides a signal for careful data screening that may require further analysis to identify the possible biological reasons of the unexpected ratios. We reviewed the literature and found 16 sites, out of a total of 529 research forest sites, that met the data requirements for the consistency test. Thirteen of these sites passed both steps of the consistency cross-check. Subsequently, flux ratios (NPP/GPP, Rh/NPP, Rh/Re, and Re/GPP) were calculated for the consistent sites. Similar ratios were observed at sites which lacked information to check consistency, indicating that the flux data that are currently used for validating models and testing ecological hypotheses are largely consistent across a wide range of site productivities. Confidence in the output of flux networks could be further enhanced if the required fluxes are independently estimated at all sites for multiple years and harmonized methods are used

The net ecosystem exchange of CO2 (NEE) varies at time scales from seconds to years and longer via the response of its components, gross ecosystem productivity (GEP) and ecosystem respiration (RE), to physical and biological drivers. Quantifying the relationship between flux and climate at multiple time scales is necessary for a comprehensive understanding of the role of climate in the terrestrial carbon cycle. Orthonormal wavelet transformation (OWT) can quantify the strength of the interactions between gappy eddy covariance flux and micrometeorological measurements at multiple frequencies while expressing time series variance in few energetic wavelet coefficients, offering a low-dimensional view of the response of terrestrial carbon flux to climatic variability. The variability of NEE, GEP and RE, and their co-variability with dominant climatic drivers, are explored with nearly one thousand site-years of data from the FLUXNET global dataset consisting of 253 eddy covariance research sites. The NEE and GEP wavelet spectra were similar among plant functional types (PFT) at weekly and shorter time scales, but significant divergence appeared among PFT at the biweekly and longer time scales, at which NEE and GEP were relatively less variable than climate. The RE spectra rarely differed among PFT across time scales as expected. On average, RE spectra had greater low frequency (monthly to interannual) variability than NEE, GEP and climate. CANOAK ecosystem model simulations demonstrate that "multi-annual" spectral peaks in flux may emerge at low (4+ years) time scales. Biological responses to climate and other internal system dynamics, rather than direct ecosystem response to climate, provide the likely explanation for observed multi-annual variability, but data records must be lengthened and measurements of ecosystem state must be made, and made available, to disentangle the mechanisms responsible for low frequency patterns in ecosystem CO2 exchange. ISSN:1726-4170 ISSN:1726-4170

Quantification of an ecosystem's carbon balance and its components is pivotal for understanding both ecosystem functioning and global cycling. Several methods are being applied in parallel to estimate the different components of the CO2 balance. However, different methods are subject to different sources of error. Therefore, it is necessary that site level component estimates are cross-checked against each other before being reported. Here we present a two-step approach for testing the accuracy and consistency of eddy covariance-based gross primary production (GPP) and ecosystem respiration (Re) estimates with biometric measurements of net primary production (NPP), autotrophic (Ra) and heterotrophic (Rh) respiration. The test starts with closing the CO2 balance to account for reasonable errors in each of the component fluxes. Failure to do so within the constraints will classify the flux estimates on the site level as inconsistent. If the CO2 balance can be closed, the test continues by comparing the closed site level Ra/GPP with the Rh/GPP ratio. The consistency of these ratios is then judged against expert knowledge. Flux estimates of sites that pass both steps are considered consistent. An inconsistent ratio is not necessarily incorrect but provides a signal for careful data screening that may require further analysis to identify the possible biological reasons of the unexpected ratios. We reviewed the literature and found 16 sites, out of a total of 529 research forest sites, that met the data requirements for the consistency test. Thirteen of these sites passed both steps of the consistency cross-check. Subsequently, flux ratios (NPP/GPP, Rh/NPP, Rh/Re, and Re/GPP) were calculated for the consistent sites. Similar ratios were observed at sites which lacked information to check consistency, indicating that the flux data that are currently used for validating models and testing ecological hypotheses are largely consistent across a wide range of site productivities. Confidence in the output of flux networks could be further enhanced if the required fluxes are independently estimated at all sites for multiple years and harmonized methods are used. [References: 99]

The eddy covariance measurements of carbon dioxide fluxes collected around the world offer a rich source for detailed data analysis. Simple, aggregated models are attractive tools for gap filling, budget calculation, and upscaling in space and time. Key in the application of these models is their parameterization and a robust estimate of the uncertainty and reliability of their predictions. In this study we compared the use of ordinary least squares (OLS) and weighted absolute deviations (WAD, which is the objective function yielding maximum likelihood parameter estimates with a double exponential error distribution) as objective functions within the annual parameterization of two respiration models: the Q10 model and the Lloyd and Taylor model. We introduce a new parameterization method based on two nonparametric tests in which model deviation (Wilcoxon test) and residual trend analyses (Spearman test) are combined. A data set of 9 years of flux measurements was used for this study. The analysis showed that the choice of the objective function is crucial, resulting in differences in the estimated annual respiration budget of up to 40%. The objective function should be tested thoroughly to determine whether it is appropriate for the application for which the model will be used. If simple models are used to estimate a respiration budget, a trend test is essential to achieve unbiased estimates over the year. The analyses also showed that the parameters of the Lloyd and Taylor model are highly correlated and difficult to determine precisely, thereby limiting the physiological interpretability of the parameters

Terrestrial ecosystems sequester 2.1 Pg of atmospheric carbon annually. A large amount of the terrestrial sink is realized by forests. However, considerable uncertainties remain regarding the fate of this carbon over both short and long timescales. Relevant data to address these uncertainties are being collected at many sites around the world, but syntheses of these data are still sparse. To facilitate future synthesis activities, we have assembled a comprehensive global database for forest ecosystems, which includes carbon budget variables (fluxes and stocks), ecosystem traits (e.g. leaf area index, age), as well as ancillary site information such as management regime, climate, and soil characteristics. This publicly available database can be used to quantify global, regional or biome-specific carbon budgets; to re-examine established relationships; to test emerging hypotheses about ecosystem functioning [e.g. a constant net ecosystem production (NEP) to gross primary production (GPP) ratio]; and as benchmarks for model evaluations. In this paper, we present the first analysis of this database. We discuss the climatic influences on GPP, net primary production (NPP) and NEP and present the CO2 balances for boreal, temperate, and tropical forest biomes based on micrometeorological, ecophysiological, and biometric flux and inventory estimates. Globally, GPP of forests benefited from higher temperatures and precipitation whereas NPP saturated above either a threshold of 1500 mm precipitation or a mean annual temperature of 10 °C. The global pattern in NEP was insensitive to climate and is hypothesized to be mainly determined by nonclimatic conditions such as successional stage, management, site history, and site disturbance. In all biomes, closing the CO2 balance required the introduction of substantial biome-specific closure terms. Nonclosure was taken as an indication that respiratory processes, advection, and non-CO2 carbon fluxes are not presently being adequately accounted for.

Tower CO2 flux measurements from 20 European grasslands in the EUROGRASSFLUX data set covering a wide range of environmental and management conditions were analyzed with respect to their ecophysiological characteristics and CO2 exchange (gross primary production, P g, and ecosystem respiration, R e) using light-response function analysis. Photosynthetically active radiation (Q ) and top-soil temperature (T s) were identified as key factors controlling CO2 exchange between grasslands and the atmosphere at the 30-min scale. A nonrectangular hyperbolic light-response model P (Q ) and modified nonrectangular hyperbolic light–temperature-response model P (Q , T s) proved to be flexible tools for modeling CO2 exchange in the light. At night, it was not possible to establish robust instantaneous relationships between CO2 evolution rate r n and environmental drivers, though under certain conditions, a significant relationship rn=r0 ekTTsrn=r0 ekTTs was found using observation windows 7–14 days wide. Principal light-response parameters—apparent quantum yield, saturated gross photosynthesis, daytime ecosystem respiration, and gross ecological light-use efficiency, ɛ = Pg/Q, display patterns of seasonal dynamics which can be formalized and used for modeling. Maximums of these parameters were found in intensively managed grasslands of Atlantic climate. Extensively used semi-natural grasslands of southern and central Europe have much lower production, respiration, and light-use efficiency, while temperate and mountain grasslands of central Europe ranged between these two extremes. Parameters from light–temperature-response analysis of tower data are in agreement with values obtained using closed chambers and free-air CO2 enrichment. Correlations between light-response and productivity parameters provides the possibility to use the easier to measure parameters to estimate the parameters that are more difficult to measure. Gross primary production (Pg) of European grasslands ranges from 1700 g CO2 m−2 year−1 in dry semi-natural pastures to 6900 g CO2 m−2 year−1 in intensively managed Atlantic grasslands. Ecosystem respiration (Re) is in the range 1800 2400 g CO2 m−2 year−1) to significant release (Tower CO2 flux measurements from 20 European grasslands in the EUROGRASSFLUX data set covering a wide range of environmental and management conditions were analyzed with respect to their ecophysiological characteristics and CO2 exchange (gross primary production, P-g, and ecosystem respiration, R-e) using light-response function analysis. Photosynthetically active radiation (Q) and top-soil temperature (T-s) were identified as key factors controlling CO2 exchange between grasslands and the atmosphere at the 30-min scale. A nonrectangular hyperbolic light-response model P(Q) and modified nonrectangular hyperbolic light-temperature-response model P(Q, T-s) proved to be flexible tools for modeling CO2 exchange in the light. At night, it was not possible to establish robust instantaneous relationships between CO2 evolution rate r(n) and environmental drivers, though under certain conditions, a significant relationship r(n) = r(0) e(kTTs) was found using observation windows 7-14 days wide. Principal light-response parameters-apparent quantum yield, saturated gross photosynthesis, daytime ecosystem respiration, and gross ecological light-use efficiency, epsilon = P-g/Q, display patterns of seasonal dynamics which can be formalized and used for modeling. Maximums of these parameters were found in intensively managed grasslands of Atlantic climate. Extensively used semi-natural grasslands of southern and central Europe have much lower production, respiration, and light-use efficiency, while temperate and mountain grasslands of central Europe ranged between these two extremes. Parameters from light-temperature-response analysis of tower data are in agreement with values obtained using closed chambers and free-air CO, enrichment. Correlations between light-response and productivity parameters provides the possibility to use the easier to measure parameters to estimate the parameters that are more difficult to measure. Gross primary production (P,) of European grasslands ranges from 1700 g CO2 m(-2) year(-1) in dry semi-natural pastures to 6900 g CO2 m(-2) year(-1) in intensively managed Atlantic grasslands. Ecosystem respiration (R-e) is in the range 1800 2400 g CO2 m(-2) year(-1)) to significant release (