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Optimal determination of the parameters controlling biospheric CO2 fluxes over Europe using eddy covariance fluxes and satellite NDVI measurements

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Abstract

Ecosystem CO2 flux measurements using the eddy covariance method were compared with the biospheric CO2 exchange estimates of a regional scale atmospheric model. The model described the seasonal patterns quite well, but underestimated the amplitude of the fluxes, especially at the northern sites. Two model parameters, photosynthetic efficiency for light use and Q10 for soil respiration, were re-evaluated on a diurnal and seasonal basis using the results from flux measurements. In most cases the photosynthetic efficiency was higher than the earlier estimate. The resulting flux was very sensitive to the value of photosynthetic efficiency, while changes in Q10 did not have a significant effect.

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... As observation sites have their own characteristics, it is necessary to make local site simulations for model evaluation and calibration as they may reveal new insight into model behaviour and guide further development. Model–data fusion has been applied for boreal forest sites by, e.g., Aalto et al. (2004) Peltoniemi et al. (2015b), Thum et al. (2007) and Wu et al. (2011). In this study we perform site level parameter optimisation in the JSBACH model (Kaminski et al., 2013; Knorr and Kattge, 2005; Reick et al., 2013 ). ...
... Additionally, the coefficient of determination (r 2 ) for GPP in Hyytiälä is in the range of 0.74–0.76 for all tunings, whereas the values reported in literature range from 0.68 (Trusilova et al., 2004) to 0.96 (Peltoniemi et al., 2015b) with most above 0.9 (Aalto et al., 2004; Duursma et al., 2009). For additional comparisons see also Abramowitz et al. (2007) . ...
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We examined parameter optimisation in the JSBACH (Kaminski et al., 2013; Knorr and Kattge, 2005; Reick et al., 2013) ecosystem model, applied to two boreal forest sites (Hyytiälä and Sodankylä) in Finland. We identified and tested key parameters in soil hydrology and forest water and carbon-exchange-related formulations, and optimised them using the adaptive Metropolis (AM) algorithm for Hyytiälä with a 5-year calibration period (2000–2004) followed by a 4-year validation period (2005–2008). Sodankylä acted as an independent validation site, where optimisations were not made. The tuning provided estimates for full distribution of possible parameters, along with information about correlation, sensitivity and identifiability. Some parameters were correlated with each other due to a phenomenological connection between carbon uptake and water stress or other connections due to the set-up of the model formulations. The latter holds especially for vegetation phenology parameters. The least identifiable parameters include phenology parameters, parameters connecting relative humidity and soil dryness, and the field capacity of the skin reservoir. These soil parameters were masked by the large contribution from vegetation transpiration. In addition to leaf area index and the maximum carboxylation rate, the most effective parameters adjusting the gross primary production (GPP) and evapotranspiration (ET) fluxes in seasonal tuning were related to soil wilting point, drainage and moisture stress imposed on vegetation. For daily and half-hourly tunings the most important parameters were the ratio of leaf internal CO2 concentration to external CO2 and the parameter connecting relative humidity and soil dryness. Effectively the seasonal tuning transferred water from soil moisture into ET, and daily and half-hourly tunings reversed this process. The seasonal tuning improved the month-to-month development of GPP and ET, and produced the most stable estimates of water use efficiency. When compared to the seasonal tuning, the daily tuning is worse on the seasonal scale. However, daily parametrisation reproduced the observations for average diurnal cycle best, except for the GPP for Sodankylä validation period, where half-hourly tuned parameters were better. In general, the daily tuning provided the largest reduction in model–data mismatch. The models response to drought was unaffected by our parametrisations and further studies are needed into enhancing the dry response in JSBACH.
... Note that the TURC biospheric fluxes driven by ECMWF fields are naturally more consistent with the models using ECMWF winds (LMDZ, DEHM and REMO) than for the other models (TM3 and HANK). The TURC predicted fluxes have been evaluated both by direct comparison with a few eddy covariance data in Europe (Aalto et al., 2004 ) and by indirect comparison against atmospheric CO 2 data after being transported in atmospheric models (Chevillard, 2001; Geels, 2003). These studies demonstrated that during summer the hourly TURC fluxes are generally reproducing quite well the observed diurnal cycle of NEE at most temperate forest eddy flux sites with regards to timing and amplitude at mid latitudes, while the diurnal NEE and hence the seasonal amplitude is underestimated at higher latitudes. ...
... In general the models underestimate the observed diurnal cycle by a factor of ∼2–7. This is not surprising since the prescribed TURC flux (see Sect. 2.2) is known to underestimate the NEE diurnal cycle amplitude at high latitudes compared to eddy-flux tower measurements (Aalto et al., 2004). The CO 2 diurnal variation reflects the day-night contrast both in NEE and in PBL vertical mixing and its variability. ...
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The CO2 source and sink distribution across Europe can be estimated in principle through inverse methods by combining CO2 observations and atmospheric transport models. Uncertainties of such estimates are mainly due to insufficient spatiotemporal coverage of CO2 observations and biases of the models. In order to assess the biases related to the use of different models the CO2 concentration field over Europe has been simulated with five different Eulerian atmospheric transport models as part of the EU-funded AEROCARB project, which has the main goal to estimate the carbon balance of Europe. In contrast to previous comparisons, here both global coarse-resolution and regional higher-resolution models are included. Continuous CO2 observations from continental, coastal and mountain in-situ atmospheric stations as well as flask samples sampled on aircrafts are used to evaluate the models' ability to capture the spatiotemporal variability and distribution of lower troposphere CO2 across Europe. 14CO2 is used in addition to evaluate separately fossil fuel signal predictions. The simulated concentrations show a large range of variation, with up to ~10 ppm higher surface concentrations over Western and Central Europe in the regional models with highest (mesoscale) spatial resolution. The simulation - data comparison reveals that generally high-resolution models are more successful than coarse models in capturing the amplitude and phasing of the observed short-term variability. At high-altitude stations the magnitude of the differences between observations and models and in between models is less pronounced, but the timing of the diurnal cycle is not well captured by the models. The data comparisons show also that the timing of the observed variability on hourly to daily time scales at low-altitude stations is generally well captured by all models. However, the amplitude of the variability tends to be underestimated. While daytime values are quite well predicted, nighttime values are generally underpredicted. This is a reflection of the different mixing regimes during day and night combined with different vertical resolution between models. In line with this finding, the agreement among models is increased when sampling in the afternoon hours only and when sampling the mixed portion of the PBL, which amounts to sampling at a few hundred meters above ground. Main recommendations resulting from the study for constraining land carbon sources and sinks using high-resolution concentration data and state-of-the art transport models are therefore: 1) low altitude stations are preferable over high altitude stations as these locations are difficult to represent in state-of-the art models, 2) at low altitude stations only afternoon values can be represented sufficiently well to be used to constrain large-scale sources and sinks in combination with transport models, 3) even when using only afternoon values it is clear that data sampled several hundred meters above ground can be represented substantially more robust in models than surface station records, and finally 4) traditional large scale transport models seem not sufficient to resolve CO2 distributions over regions of the size of for example Spain and thus seem too coarse for interpretation of continental data.
... But the present approaches to assess the carbon exchange of an ecosystem have been made possible through direct measurements of carbon dioxide (CO 2 ) and water (H 2 O) fluxes at eddy covariance (EC) sites and indirect modelling approaches for assessing the source or sink nature of an ecosystem. However, the limited spatial representation of flux site and lack of several inputs at required spatial and temporal scales for running the models limit the ecological studies based on these approaches (Aalto et al., 2004). ...
Thesis
With the increase of global warming, the studies on the CO2 and water vapor exchange in natural and man-made vegetation are necessary for quantifying their role in landscape level carbon budget. The present study aimed at measuring C-flux to investigate the status of net sink/source of forest ecosystem using eddy covariance and satellite based modelling technique in Terai Central Forest Division of Nainital district. The LUE based model was driven by biophysical parameters derived from remote sensing and meteorological data. Vegetation indices such as NDVI, LSWI were used to derive the model parameters and its comparison with field observations showed good agreement. The realized LUE of the plantation were also calibrated well by incorporating temperature and water scalar. It was observed that the plantation acted as net carbon source (i.e., positive NEE) with daily mean release of 0.35 g C m-2 day-1 and 0.30 g C m-2 day-1 during Jan 2013 and Feb 2014 while from leaf onset to growing period it acted as sink (i.e., negative NEE) due to the carbon uptake by an increasing number of leaves. The monthly mean daily NEE was noticed to be increasingly more negative in each subsequent month until October. The diurnal trend in NEE closely followed the variations in the intensity of photosynthetically active radiation (PAR). The maximum day-time uptake (-37 µmol m-2 s-1) and night-time release of CO2 (8.2 µmol m-2 s-1) was observed in July. Monthly mean of daily NEE over plantation continuously increased from month of February and was highest (-5.74 g C m-2 day-1) in September. A comparison between predicted GPP with the measured GPP at tower site indicated that the modelled GPP explained about 70% of the observed variations of daily GPP. The model simulated GPP for whole division for the year 2009 also well agreed with the past field observations. The net primary productivity (NPP) converted from GPP showed a significant net sink nature of all the plantation type in the division. It was also observed that the seasonal dynamics of GPP was predominantly controlled by PAR and temperature. The study showed the effectiveness of using both techniques in addressing the net carbon budget at regional scales.
... Through the correlation analyses between GM-XCO2 and NDVI, EVI, LAI, and GPP, it is found that NDVI and EVI have better correlations and spatial pattern with the seasonal variation of XCO2 than LAI and GPP for stronger coefficients over all latitude zones. That is consistent with previous studies [78,79] that NDVI and EVI, directly retrieved from MODIS observed radiance, may be better parameters representing biosphere activities for constraining of the terrestrial CO2 flux than LAI and GPP, which are obtained from semi-empirical biophysical models. Using XCO2 and NDVI, moreover, we show the global distribution of time delay effect in terms of lags of months, which, to our knowledge, is the first such map derived from the completely data-driven approach using satellite observations. ...
Article
Using measurements of the column-averaged CO_2 dry air mole fraction (XCO_2) from GOSAT and biosphere parameters, including normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), leaf area index (LAI), gross primary production (GPP), and land surface temperature (LST) from MODIS, this study proposes a data-driven approach to assess the impacts of terrestrial biosphere activities on the seasonal cycle pattern of XCO_2. A unique global land mapping dataset of XCO_2 with a resolution of 1° by 1° in space, and three days in time, from June 2009 to May 2014, which facilitates the assessment at a fine scale, is first produced from GOSAT XCO_2 retrievals. We then conduct a statistical fitting method to obtain the global map of seasonal cycle amplitudes (SCA) of XCO_2 and NDVI, and implement correlation analyses of seasonal variation between XCO_2 and the vegetation parameters. As a result, the spatial distribution of XCO_2 SCA decreases globally with latitude from north to south, which is in good agreement with that of simulated XCO_2 from CarbonTracker. The spatial pattern of XCO_2 SCA corresponds well to the vegetation seasonal activity revealed by NDVI, with a strong correlation coefficient of 0.74 in the northern hemisphere (NH). Some hotspots in the subtropical areas, including Northern India (with SCA of 8.68 ± 0.49 ppm on average) and Central Africa (with SCA of 8.33 ± 0.25 ppm on average), shown by satellite measurements, but missed by model simulations, demonstrate the advantage of satellites in observing the biosphere–atmosphere interactions at local scales. Results from correlation analyses between XCO_2 and NDVI, EVI, LAI, or GPP show a consistent spatial distribution, and NDVI and EVI have stronger negative correlations over all latitudes. This may suggest that NDVI and EVI can be better vegetation parameters in characterizing the seasonal variations of XCO_2 and its driving terrestrial biosphere activities. We, furthermore, present the global distribution of phase lags of XCO_2 compared to NDVI in seasonal variation, which, to our knowledge, is the first such map derived from a completely data-driven approach using satellite observations. The impact of retrieval error of GOSAT data on the mapping data, especially over high-latitude areas, is further discussed. Results from this study provide reference for better understanding the distribution of the strength of carbon sink by terrestrial ecosystems and utilizing remote sensing data in assessing the impact of biosphere–atmosphere interactions on the seasonal cycle pattern of atmospheric CO_2 columns.
... Carbon pools are not explicitly tracked in some diagnostic models; thus base rates for key parameters like light use efficiency (LUE), autotrophic respiration (R a ) and R h must be specified. Because of the relatively low computational costs, diagnostic models are suitable for optimization of multiple parameters using flux tower data (Aalto et al., 2004). A common application for diagnostic NEP models is in generating NEP estimates for comparison (or as 'priors') to top-down flux estimates derived from inversion modelling (e.g. ...
... However the restricted spatial representativeness of EC fluxes and the lack of several inputs at required spatial and temporal scales for running the models limit the ecological studies based on these approaches. Remote sensing (RS) offers a unique opportunity to address this issue by providing a method for monitoring ecosystems at synoptic temporal and spatial scales through measurements of carbon-related spectral response: from local scale in situ measurements to the global scale by integrating RS data (e.g., MODIS) into ecological models [1][2][3][4][5][6]. The use of optical RS instruments directly mounted on EC towers can be considered as an important step towards addressing the scaling issue because it plays a crucial role for spatial extrapolation of in situ biophysical parameters of vegetation (e.g., phytomass, biomass, LAI, chlorophyll and nitrogen content). ...
Article
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This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903—“Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe” that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites.
... s have their own characteristics, it is necessary to make local site simulations 10 for model evaluation and calibration as they may reveal new insight into model behaviour and promote further development. Model-data fusion has been applied for boreal forest sites by e.g. Peltoniemi et al. (2015a), Wu et al. (2011), Thum et al. (2007 and 2008) and Aalto et al. (2004). In this study we perform site level parameter optimization in the JSBACH model (Reick et al., 2013, see also Knorr et al., 2005 and Kaminski et al., 2013). JSBACH is the land surface component of the Earth System model of Max Planck Institute for 15 Meteorology (MPI-ESM), used to simulate water and carbon storages and fluxes in the soil- ...
Article
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We examined parameter optimization in JSBACH ecosystem model, applied for two boreal forest sites in Finland. We identified and tested key parameters in soil hydrology and forest water and carbon exchange related formulations and optimized them using the Adaptive Metropolis algorithm for a five year calibration period (2000–2004) followed by a four year validation period (2005–2008). We were able to improve the modelled seasonal, daily and diurnal cycles of gross primary production and evapotranspiration but unable to enhance the models response to dryness. The improvements are mostly accounted for by parameters related to the ratio of leaf internal CO2 concentration to external CO2, relative humidity, transpiration and soil moisture stress.
... Model parameter optimisation was implemented using a dual state-parameter estimation method based on the EnKF (Reichstein et al., 2003; Aalto et al., 2004; Moradkhani et al., 2005; Mo et al., 2008; Ju et al., 2010). The parameter ensembles are updated as: ...
Article
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Seasonal variations of photosynthetic capacity parameters, notably the maximum carboxylation rate, Vcmax , play an important role in accurate estimation of CO2 assimilation in gas-exchange models. Satellite-derived normalised difference vegetation index (NDVI), enhanced vegetation index (EVI) and model-data fusion can provide means to predict seasonal variation in Vcmax. In this study, Vcmax was obtained from a process-based model inversion, based on an ensemble Kalman filter (EnKF), and gross primary productivity, and sensible and latent heat fluxes measured using eddy covariance technique at two deciduous broadleaf forest sites and a mixed forest site. Optimised Vcmax showed considerable seasonal and inter-annual variations in both mixed and deciduous forest ecosystems. There was noticeable seasonal hysteresis in Vcmax in relation to EVI and NDVI from 8 d composites of satellite data during the growing period. When the growing period was phonologically divided into two phases (increasing VIs and decreasing VIs phases), significant seasonal correlations were found between Vcmax and VIs, mostly showing R2 > 0.95. Vcmax varied exponentially with increasing VIs during the first phase (increasing VIs), but second and third-order polynomials provided the best fits of Vcmax to VIs in the second phase (decreasing VIs). The relationships between NDVI and EVI with Vcmax were different. Further efforts are needed to investigate Vcmax-VIs relationships at more ecosystem sites to the use of satellite-based VIs for estimating Vcmax.
... Also, simple calibration techniques may not provide information on what data are essential to constrain the models, and they provide no guidance on what data should be collected in field experiments. [3] To improve the parameterization and predictability of ecosystem models, good progress has been made using eddy flux data sets in a model-data fusion manner [e.g., Braswell et al., 2005; Williams et al., 2005; Aalto et al., 2004; Wang et al., 2001 Wang et al., , 2007 Santaren et al., 2007]. These studies often strive to constrain a few parameters of their models and these ecosystem models are mostly operated at finer time steps (e.g., hourly or daily). ...
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A global sensitivity analysis and Bayesian inference framework was developed for improving the parameterization and predictability of a monthly time step process-based biogeochemistry model. Using a Latin Hypercube sampler and an existing Terrestrial Ecosystem Model (TEM), a set of 500,000 Monte Carlo ensemble simulations was conducted for a black spruce forest ecosystem. A global sensitivity analysis was then conducted to identify the key model parameters and examine the interaction structures among TEM parameters. Bayesian inference analysis was also performed using these ensemble simulations and eddy flux data of carbon, latent heat flux, and MODIS gross primary production (GPP) to reduce the uncertainty of parameter estimation and prediction of TEM. We found that (1) the simulated carbon fluxes are mostly affected by parameters of the maximum rate of photosynthesis (CMAX), the half-saturation constant for CO2 uptake by plants (k c), the half-saturation constant for Photosynthetically Active Radiation used by plants (k i), and the change in autotrophic respiration due to 10°C temperature increase (RHQ10); (2) the effect of parameters on seasonal carbon dynamics varies from one parameter to another during a year; (3) to well constrain the uncertainties of TEM predictions and parameters using the Bayesian inference technique, at least two different fluxes of NEP, GPP, and ecosystem respiration (RESP) are required; and (4) different assumptions of the error structures of the flux data used in the Bayesian inference analysis result in different uncertainty bounds of the posterior parameters and model predictions. We further found that, using the Bayesian framework and eddy flux and satellite data, the uncertainty of simulated carbon fluxes has been remarkably reduced. The developed global sensitivity analysis and Bayesian framework could further be used to analyze and improve the predictability and parameterization of relatively coarse time step biogeochemistry models when the eddy flux and satellite data are available for other terrestrial ecosystems.
... Other groups of investigators are inverting flux data to derive stand-scale model parameters (Wang et al. 2001;Reichstein et al. 2003;Aalto et al. 2004;Jarvis et al. 2004;Schulz and Jarvis 2004;Wang et al. 2004;Braswell et al. 2005;Knorr and Kattge 2005;Raupach et al. 2005;Richardson and Hollinger 2005;Gove and Hollinger 2006). One goal of inverting flux data is to produce models that can be used in a data-assimilation mode to improve spatial and temporal integration. ...
Article
Published eddy covariance measurements of carbon dioxide (CO2) exchange between vegetation and the atmosphere from a global network are distilled, synthesised and reviewed according to time scale, climate and plant functional types, disturbance and land use. Other topics discussed include history of the network, errors and issues associated with the eddy covariance method, and a synopsis of how these data are being used by ecosystem and climate modellers and the remote-sensing community. Spatial and temporal differences in net annual exchange, FN, result from imbalances in canopy photosynthesis (FA) and ecosystem respiration (FR), which scale closely with one another on annual time scales. Key findings reported include the following: (1) ecosystems with the greatest net carbon uptake have the longest growing season, not the greatest FA; (2) ecosystems losing carbon were recently disturbed; (3) many old-growth forests act as carbon sinks; and (4) year-to-year decreases in FN are attributed to a suite of stresses that decrease FA and FR in tandem. Short-term flux measurements revealed emergent-scale processes including (1) the enhancement of light use efficiency by diffuse light, (2) dynamic pulses in FR following rain and (3) the acclimation FA and FR to temperature. They also quantify how FA and FR respond to droughts and heat spells.
... Thus, flux towers can play an important role in determining both optimal choice and number of parameters needed for regional scaling and reducing uncertainty in model parameters (White et al., 2000). Other studies have demonstrated that nonlinear optimization techniques are well suited for these tasks, especially on the daily to seasonal time scale (Aalto et al., 2004; Braswell et al., in press; Wang et al., 2001). Simple bottom-up scaling of these data successfully modeled regional growing season GEP measured from a tall eddy flux tower, but significantly underestimated ER. ...
Article
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Fluxes of carbon dioxide over the growing season (June-August) of 2002 and 2003 from 14 different sites in northern Wisconsin and Michigan (USA) were examined to assess the magnitude of spatial variability of ecosystem-atmosphere carbon exchange and related parameters over two years. These fluxes were measured with eight fixed and three roving eddy covariance towers. These sites all experienced a similar climate. The sites spanned a range of vegetation types typical of the region (northern hardwood, mixed forest, red pine, jack pine, pine barrens and shrub wetland). The hardwood and red pine sites also spanned a range of forest stand age (young, intermediate, mature), and were complemented by a mixed old-growth site. Within site interannual variability of carbon fluxes was about half that of across site variability. While interannual changes in net ecosystem exchange (NEE) and some photosynthetic parameters were coherent across years at most sites, changes in ecosystem respiration (ER) and gross ecosystem production (GEP) were not. Both stand age and vegetation type were equally important variables for explaining spatial variability of carbon fluxes across the region. A simple bottom-up scaling of carbon flux observed from canopy towers to a regional estimate was able to accurately model GEP observed from a regionally-integrating 436 m tall flux tower, but significantly underestimated ER by 30%. These results have implications for modeling regional carbon fluxes using multi-tiered bottom-up scaling, suggesting that high spatial sampling density and replication frequency may be needed for scaling fluxes in heterogeneous regions such as the upper Midwest, USA.
... Carbon pools are not explicitly tracked in some diagnostic models; thus base rates for key parameters like light use efficiency (LUE), autotrophic respiration (Ra) and R h must be specified. Because of the relatively low computational costs, diagnostic models are suitable for optimization of multiple parameters using flux tower data (Aalto et al., 2004). A common application for diagnostic NEP models is in generating NEP estimates for comparison (or as`priorsas`priors') to top-down flux estimates derived from inversion modelling (e.g. ...
Article
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Net ecosystem production (NEP) was estimated over a 10.9 × 104 km2 forested region in western Oregon USA for 2 yr (2002–2003) using a combination of remote sensing, distributed meteorological data, and a carbon cycle model (CFLUX). High spatial resolution satellite data (Landsat, 30 m) provided information on land cover and the disturbance regime. Coarser resolution satellite imagery (MODIS, 1 km) provided estimates of vegetation absorption of photosynthetically active radiation. A spatially distributed (1 km) daily time step meteorology was generated for model input by interpolation of meteorological station data. The model employed a light use efficiency approach for photosynthesis. It was run over a 1 km grid. This approach captured spatial patterns in NEP associated with climatic gradients, ecoregional differences in NEP generated by different management histories, temporal variation in NEP associated with interannual variation in climate and changes in NEP associated with recovery from disturbances such as the large forest fire in southern Oregon in 2002. Regional NEP averaged 174 gC m−2 yr−1 in 2002 and 142 gC m−2 yr−1 in 2003. A diagnostic modelling approach of this type can provide independent estimates of regional NEP for comparison with results of inversion or boundary layer budget approaches.
... However the restricted spatial representativeness of EC fluxes and the lack of several inputs at required spatial and temporal scales for running the models limit the ecological studies based on these approaches. Remote sensing (RS) offers a unique opportunity to address this issue by providing a method for monitoring ecosystems at synoptic temporal and spatial scales through measurements of carbon-related spectral response: from local scale in situ measurements to the global scale by integrating RS data (e.g., MODIS) into ecological models123456. The use of optical RS instruments directly mounted on EC towers can be considered as an important step towards addressing the scaling issue because it plays a crucial role for spatial extrapolation of in situ biophysical parameters of vegetation (e.g., phytomass, biomass, LAI, chlorophyll and nitrogen content). ...
Article
Full-text available
This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903—“Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe” that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the
... Satellite remote sensing can provide consistent and systematic observations of vegetation and ecosystems, and has played an increasing role in characterization of vegetation structure and estimation of gross primary production (GPP) or net primary production (NPP) (Behrenfeld et al., 2001; Field et al., 1998; Ruimy et al., 1999; Running et al., 2000). Many studies aim to integrate flux tower data and remote sensing for regional carbon budget research (Aalto et al., 2004; Oechel et al., 2000; Turner et al., 2003). Satellite remote sensing can be used to estimate either GPP or NPP, but is not capable of validating model-generated surfaces for Remote Sensing of Environment 107 (2007) 510 – 519 www.elsevier.com/locate/rse ...
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The eddy covariance technique provides measurements of net ecosystem exchange (NEE) of CO2 between the atmosphere and terrestrial ecosystems, which is widely used to estimate ecosystem respiration and gross primary production (GPP) at a number of CO2 eddy flux tower sites. In this paper, canopy-level maximum light use efficiency, a key parameter in the satellite-based Vegetation Photosynthesis Model (VPM), was estimated by using the observed CO2 flux data and photosynthetically active radiation (PAR) data from eddy flux tower sites in an alpine swamp ecosystem, an alpine shrub ecosystem and an alpine meadow ecosystem in Qinghai–Tibetan Plateau, China. The VPM model uses two improved vegetation indices (Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI)) derived from the Moderate Resolution Imaging Spectral radiometer (MODIS) data and climate data at the flux tower sites, and estimated the seasonal dynamics of GPP of the three alpine grassland ecosystems in Qinghai–Tibetan Plateau. The seasonal dynamics of GPP predicted by the VPM model agreed well with estimated GPP from eddy flux towers. These results demonstrated the potential of the satellite-driven VPM model for scaling-up GPP of alpine grassland ecosystems, a key component for the study of the carbon cycle at regional and global scales.
... Falge et al., 2002). These data not only provide an unprecedented possibility to extend our knowledge about the global variation of F GPP , but also to validate/calibrate the parameters of the F GPP algorithms used with MODIS or other satellite sensors (Turner et al., 2003; Aalto et al., 2004; Xiao et al., 2004a, b). The usual way of inferring F GPP from net ecosystem production ( F NEP = À F NEE ) is by adding total daytime ecosystem respiration, which is modelled using functional relationships between temperature (and possibly some measure of soil water availability) and nighttime total ecosystem respiration (R eco ; Valentini et al., 2000; Janssens et al., 2001; Falge et al., 2002). ...
Article
Gross primary production (FGPP) may be calculated from net ecosystem CO2 exchange (FNEE), measured, for example, by means of the eddy covariance method, provided an estimate of daytime ecosystem respiration is available. The latter is now often estimated by extrapolating functional relationships between nighttime FNEE, when FGPP is zero, and temperature to daytime conditions. The present paper deals with one problem associated with this approach, namely the reduction of leaf respiration in light relative to darkness, which causes an overestimation of daytime ecosystem respiration, and hence FGPP. The overestimation of FGPP is quantified for a mountain meadow in the Austrian Alps using a coupled model of the reduction of leaf dark respiration as a function of light intensity and within-canopy radiative transfer. For the two study years analysed in the present paper, model simulations suggest a reduction of FGPP by 11–13% and 13–17%, for a low and a high estimate of the maximum leaf-level reduction of dark respiration, respectively. This reduction is shown to be most sensitive to the ratio between FGPP and total ecosystem respiration, as well as to the ratio between leaf and total ecosystem respiration. The largest factors of uncertainty in this modelling approach are the cause for and the actual level of the reduction of leaf dark respiration in light. The significance of the present findings for estimating FGPP of other sites is discussed.
... ameters, but rather poor constraints on parameters relating to soil decomposition that varies at considerably longer time scale than canopy photosynthesis and transpiration. Willaims et al. (2005) also concluded that long-term measurements of carbon pool sizes are required to estimate the parameters relating to decomposition of soil organic matter. Aalto et al. (2004) estimated two-key parameters in their global biosphere model by applying nonlinear inversion to eddy flux measurements and satellite measurements of NDVI for 13 FLUXNET sites in Europe, even though the actual number of parameters needed by the model for each biome is far greater than two. Over 250 flux towers are now installed worldwide ...
Article
Flux measurements from eight global FLUXNET sites were used to estimate parameters in a process-based, land-surface model (CSIRO Biosphere Model (CBM), using nonlinear parameter estimation techniques. The parameters examined were the maximum photosynthetic carboxylation rate () the potential photosynthetic electron transport rate (jmax, 25) of the leaf at the top of the canopy, and basal soil respiration (rs, 25), all at a reference temperature of 25°C. Eddy covariance measurements used in the analysis were from four evergreen forests, three deciduous forests and an oak-grass savanna. Optimal estimates of model parameters were obtained by minimizing the weighted differences between the observed and predicted flux densities of latent heat, sensible heat and net ecosystem CO2 exchange for each year. Values of maximum carboxylation rates obtained from the flux measurements were in good agreement with independent estimates from leaf gas exchange measurements at all evergreen forest sites. A seasonally varying and jmax, 25 in CBM yielded better predictions of net ecosystem CO2 exchange than a constant and jmax, 25 for all three deciduous forests and one savanna site. Differences in the seasonal variation of and jmax, 25 among the three deciduous forests are related to leaf phenology. At the tree-grass savanna site, seasonal variation of and jmax, 25 was affected by interactions between soil water and temperature, resulting in and jmax, 25 reaching maximal values before the onset of summer drought at canopy scale. Optimizing the photosynthetic parameters in the model allowed CBM to predict quite well the fluxes of water vapor and CO2 but sensible heat fluxes were systematically underestimated by up to 75 W m−2.
... They concluded that the greatest value of flux data for global carboncycle modelling is evaluating process representation rather than providing an unbiased estimate of carbon fluxes. Other groups of investigators are inverting flux data to derive stand-scale model parameters (Wang et al. 2001; Reichstein et al. 2003; Aalto et al. 2004; Jarvis et al. 2004; Schulz and Jarvis 2004; Wang et al. 2004; Braswell et al. 2005; Knorr and Kattge 2005; Raupach et al. 2005; Gove and Hollinger 2006). One goal of inverting flux data is to produce models that can be used in a data-assimilation mode to improve spatial and temporal integration. ...
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Published eddy covariance measurements of carbon dioxide (CO2) exchange between vegetation and the atmosphere from a global network are distilled, synthesised and reviewed according to time scale, climate and plant functional types, disturbance and land use. Other topics discussed include history of the network, errors and issues associated with the eddy covariance method, and a synopsis of how these data are being used by ecosystem and climate modellers and the remote-sensing community. Spatial and temporal differences in net annual exchange, F-N, result from imbalances in canopy photosynthesis (F-A) and ecosystem respiration (F-R), which scale closely with one another on annual time scales. Key findings reported include the following: (1) ecosystems with the greatest net carbon uptake have the longest growing season, not the greatest F-A; (2) ecosystems losing carbon were recently disturbed; (3) many old-growth forests act as carbon sinks; and (4) year-to-year decreases in F-N are attributed to a suite of stresses that decrease F-A and F-R in tandem. Short-term flux measurements revealed emergent-scale processes including (1) the enhancement of light use efficiency by diffuse light, (2) dynamic pulses in F-R following rain and (3) the acclimation F-A and F-R to temperature. They also quantify how F-A and F-R respond to droughts and heat spells.
... However the restricted spatial representativeness of EC fluxes and the lack of several inputs at required spatial and temporal scales for running the models limit the ecological studies based on these approaches. Remote sensing (RS) offers a unique opportunity to address this issue by providing a method for monitoring ecosystems at synoptic temporal and spatial scales through measurements of carbon-related spectral response: from local scale in situ measurements to the global scale by integrating RS data (e.g., MODIS) into ecological models123456. The use of optical RS instruments directly mounted on EC towers can be considered as an important step towards addressing the scaling issue because it plays a crucial role for spatial extrapolation of in situ biophysical parameters of vegetation (e.g., phytomass, biomass, LAI, chlorophyll and nitrogen content). ...
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This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903-"Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe" that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites.
... Various parameter optimization methods have been successfully adopted in combination with EC measurements to optimize model parameters and to analyze the seasonality of parameters. Parameter optimization can be implemented by minimizing a cost function constructed on the basis of one or several criteria quantifying the differences between simulated fluxes and corresponding measurements (Aalto et al., 2004; 5 Owen et al., 2007; Reichstein et al., 2003; Wang et al., 2006; Wolf et al., 2006) or by using the ensemble Kalman filer based approach (Mo et al., 2008 ). The cost function can be resolved at different temporal intervals to identify the seasonal variations of parameters. ...
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Soil and atmospheric water deficits have significant influences on CO2 and energy exchanges between the atmosphere and terrestrial ecosystems. Model parameterization significantly affects the ability of a model to simulate carbon, water, and energy fluxes. In this study, an ensemble Kalman filter (EnKF) and observations of gross primary productivity (GPP) and latent heat (LE) fluxes were used to optimize model parameters significantly affecting the calculation of these fluxes for a subtropical coniferous plantation in southeastern China. The optimized parameters include the maximum carboxylation rate (Vcmax), the Ball-Berry coefficient (m) and the coefficient determining the sensitivity of stomatal conductance to atmospheric water vapor deficit D0). Optimized Vcmax and m showed larger seasonal and interannual variations than D0. Seasonal variations of Vcmax and m are more pronounced than the interannual variations. Vcmax and m are associated with soil water content (SWC). During dry periods, SWC at the 20 cm depth can explain 61% and 64% of variations of Vcmax and m, respectively. EnKF parameter optimization improves the simulations of GPP, LE and sensible heat (SH), mainly during dry periods. After parameter optimization using EnKF, the variations of GPP, LE and SH explained by the model increased by 1% to 4% at half-hourly steps and by 3% to 5% at daily time steps. Efforts are needed to develop algorithms that can properly describe the variations of these parameters under different environmental conditions.
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Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI) and carbon flux data of AmeriFlux to conduct such a study. We first modify the Gross Primary Production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of the changes of canopy photosynthetic capacity, phenology and water stress. Second, we parameterize and verify the new version of TEM with eddy flux data. We then apply the model to the conterminous United States over the period 2000-2005 at a 0.05°×0.05° spatial resolution. We find that the new version of TEM generally captured the expected temporal and spatial patterns of regional carbon dynamics. We estimate that regional GPP is between 7.02 and 7.78 Pg C yr-1 and Net Primary Production (NPP) ranges from 3.81 to 4.38 Pg C yr-1 and Net Ecosystem Production (NEP) varies within 0.08-0.73 Pg C yr-1 over the period 2000-2005 for the conterminous United States. The uncertainty due to parameterization is 0.34, 0.65 and 0.18 Pg C yr-1 for the regional estimates of GPP, NPP and NEP, respectively. The effects of extreme climate and disturbances such as severe drought in 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Our study provides a new independent and more adequate measure of carbon fluxes for the conterminous United States, which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon management and climate.
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Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measure-ments and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution Imaging Spectroradiome-ter (MODIS) Enhanced Vegetation Index (EVI), Land Sur-face Water Index (LSWI) and carbon flux data of AmeriFlux to conduct such a study. We first modify the gross primary production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of the changes of canopy photosynthetic capacity, phenology and water stress. Sec-ond, we parameterize and verify the new version of TEM with eddy flux data. We then apply the model to the con-terminous United States over the period 2000–2005 at a 0.05 • × 0.05 • spatial resolution. We find that the new ver-sion of TEM made improvement over the previous version and generally captured the expected temporal and spatial patterns of regional carbon dynamics. We estimate that re-gional GPP is between 7.02 and 7.78 Pg C yr −1 and net pri-mary production (NPP) ranges from 3.81 to 4.38 Pg C yr −1 and net ecosystem production (NEP) varies within 0.08– 0.73 Pg C yr −1 over the period 2000–2005 for the contermi-nous United States. The uncertainty due to parameterization Correspondence to: M. Chen (chenm@purdue.edu) is 0.34, 0.65 and 0.18 Pg C yr −1 for the regional estimates of GPP, NPP and NEP, respectively. The effects of extreme cli-mate and disturbances such as severe drought in 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Our study provides a new independent and more ade-quate measure of carbon fluxes for the conterminous United States, which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon management and cli-mate.
Conference Paper
Estimation of gross primary production (GPP) from remote sensing data is an important approach to study regional or global carbon cycle. In this study, a satellite-driven model, vegetation photosynthesis model (VPM) was introduced to estimate gross primary production (GPP) of the semi-arid grassland ecosystem for the growing season (2006) in North China. Meanwhile, observed GPP derived from eddy covariance flux data were used to critically evaluate the performance of the model. As defined by the input variables of VPM, two improved vegetation indices (enhanced vegetation index (EVI) and land surface water index (LSWI)) derived from the standard data product MOD09A1 of Moderate Resolution Imaging Spectroradimeter (MODIS), air temperature and photosynthetic active radiation at the flux site, were included for the model calculating. The seasonal dynamics of GPP predicted by the VPM model agreed well with estimated GPP from the eddy flux tower�» and simulation with time step of 8-day was better than with 1-day time step. Results of this study demonstrate that the satellite-driven VPM has potential for estimating site-level or regional grassland GPP, and might be an effective tool for scaling-up carbon fluxes.
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We evaluate the modelling of carbon fluxes from eddy covariance (EC) tower observations in different water-limited land-cover/land-use (LCLU) and biome types in semi-arid Inner Mongolia, China. The vegetation photosynthesis model (VPM) and modified VPM (MVPM), driven by the enhanced vegetation index (EVI) and land-surface water index (LSWI), which were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) surface-reflectance product (MOD09A1), were used to model and validate the temporal changes in gross primary production (GPP) from the EC towers during the 2006 and 2007 growing seasons. The annual GPP predicted by the VPM model (GPP(VPM)) was predicted reasonably well in 2006 and 2007 at the cropland (coefficient of determination, R-2=0.67 and 0.71, for 2006 and 2007, respectively) and typical steppe (R-2=0.80 and 0.73) sites. The predictive power of the VPM model varied in the desert steppe, which includes an irrigated poplar stand (R-2=0.74 and 0.68) and shrubland (R-2=0.31 and 0.49) sites. The comparison between GPP obtained from the eddy covariance tower (GPP(tower)) and GPP obtained from MVPM (GPP(MVPM)) (predicted GPP) showed good agreement for the typical steppe site of Xilinhaote (R-2=0.84 and 0.70 in 2006 and 2007, respectively) and for the Duolun steppe site (R-2=0.63) and cropland site (R-2=0.63) in 2007. The predictive power of the MVPM model decreased slightly in the desert steppe at the irrigated poplar stand (R-2=0.56 and 0.47 in 2006 and 2007 respectively) and the shrubland (R-2=0.20 and 0.41). The results of this study demonstrate the feasibility of modelling GPP from EC towers in semi-arid regions.
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Detailed information from the Swedish National Forest Inventory was used to simulate the carbon balance for Sweden by the process-based model Biome-BGC. A few shortcomings of the model were identified and solutions to those are proposed and also used in the simulations. The model was calibrated against CO2 flux data from 3 forests in central Sweden and then applied to the whole country divided into 30 districts and 4 age classes. Gross primary production (GPP) ranged over districts and age classes from 0.20 to 1.71 kg C m−2 y−1 and net ecosystem production (NEP) ranged from −0.01 to 0.44. The 10- to 30-year age class was the strongest carbon sink because of its relatively low respiration rates. When the simulation results were scaled up to the whole country, GPP and NEP were 175 and 29 Mton C y−1, respectively, for the 22.7 Mha of forests in Sweden. A climate change scenario was simulated by assuming a 4°C increase in temperature and a doubling of the CO2 concentration; GPP and NEP then increased to 253 and 48 Mton C y−1, respectively. A sensitivity analysis showed that at present CO2 concentrations NEP would peak at an increase of 5°C for the mean annual temperature. At higher CO2 levels NEP showed a logarithmic increase.
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Light use efficiency (LUE) is used widely in scaling and modeling contexts. However, the variation and biophysical controls on LUE remain poorly documented. Networks of eddy covariance (EC) towers offer an opportunity to quantify ɛg, the ratio of P, gross primary productivity, to Qa, absorbed photosynthetically active radiation (PAR), across climate zones and vegetation types. Using data from the Fluxnet Canada Research Network (n = 24 sites) in 2004, we examined the relationship between daily and yearly ɛg, driving variables, and site characteristics on a site-specific and plant functional type (PFT) basis using tree regression and linear regression. Data were available for three biomes: grassland, forest, and wetland. Yearly ɛg values ranged from 0.1 to 3.6 g C MJ−1Qa overall. Daily ɛg was highest in the grassland (daily median ± interquartile range: 3.68 ± 1.98 g C MJ−1Qa), intermediate in the forested biome (0.84 ± 0.82 g C MJ−1Qa), and lowest for the wetlands (0.65 ± 0.54 g C MJ−1Qa). The most important biophysical controls were light and temperature, to the exclusion of water-related variables: a homogeneity of slopes model explained c. 75% of the variation in daily ɛg. For a subset of sites with diffuse PAR data, the ratio of diffuse to total PAR, a proxy for cloudiness, was a key predictor. On the yearly time scale, ɛg was related to leaf area index and mean annual temperature. Aggregating to PFTs did not show functional convergence within any PFT except for the three wetland sites and the Picea mariana toposequence at the daily time step, and when using the Köppen climate classification on a yearly time step. The general lack of conservative daily ɛg behavior within PFTs suggests that PFT-based parameterizations are inappropriate, especially when applied on shorter temporal scales.
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Carbon dioxide fluxes were examined over the growing seasons of 2002 and 2003 from 14 different sites in Upper Midwest (USA) to assess spatial variability of ecosystem–atmosphere CO2 exchange. These sites were exposed to similar temperature/precipitation regimes and spanned a range of vegetation types typical of the region (northern hardwood, mixed forest, red pine, jack pine, pine barrens and shrub wetland). The hardwood and red pine sites also spanned a range of stand ages (young, intermediate, mature). While seasonal changes in net ecosystem exchange (NEE) and photosynthetic parameters were coherent across the 2 years at most sites, changes in ecosystem respiration (ER) and gross ecosystem production (GEP) were not. Canopy height and vegetation type were important variables for explaining spatial variability of CO2 fluxes across the region. Light-use efficiency (LUE) was not as strongly correlated to GEP as maximum assimilation capacity (Amax). A bottom-up multi-tower land cover aggregated scaling of CO2 flux to a 2000 km2 regional flux estimate found June to August 2003 NEE, ER and GEP to be −290 ± 89, 408 ± 48, and 698 ± 73 gC m−2, respectively. Aggregated NEE, ER and GEP were 280% larger, 32% smaller and 3% larger, respectively, than that observed from a regionally integrating 447 m tall flux tower. However, when the tall tower fluxes were decomposed using a footprint-weighted influence function and then re-aggregated to a regional estimate, the resulting NEE, ER and GEP were within 11% of the multi-tower aggregation. Excluding wetland and young stand age sites from the aggregation worsened the comparison to observed fluxes. These results provide insight on the range of spatial sampling, replication, measurement error and land cover accuracy needed for multi-tiered bottom-up scaling of CO2 fluxes in heterogeneous regions such as the Upper Midwest, USA.
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Vegetation growth models are used with remotely sensed and meteorological data to monitor terrestrial carbon dynamics at a range of spatial and temporal scales. Many of these models are based on a light-use efficiency equation and two-component model of whole-plant growth and maintenance respiration that have been parameterized for distinct vegetation types and biomes. This study was designed to assess the robustness of these parameters for predicting interannual plant growth and carbon exchange, and more specifically to address inconsistencies that may arise during forest disturbances and the loss of canopy foliage. A model based on the MODIS MOD17 algorithm was parameterized for a mature upland hardwood forest by inverting CO₂ flux tower observations during years when the canopy was not disturbed. This model was used to make predictions during a year when the canopy was 37% defoliated by forest tent caterpillars. Predictions improved after algorithms were modified to scale for the effects of diffuse radiation and loss of leaf area. Photosynthesis and respiration model parameters were found to be robust at daily and annual time scales regardless of canopy disturbance, and differences between modeled net ecosystem production and tower net ecosystem exchange were only approximately 2 g C m-² d-¹ and less than 23 g C m-² y-¹. Canopy disturbance events such as insect defoliations are common in temperate forests of North America, and failure to account for cyclical outbreaks of forest tent caterpillars in this stand could add an uncertainty of approximately 4-13% in long-term predictions of carbon sequestration.
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Soil and atmospheric water deficits have significant influences on CO2 and energy exchanges between the atmosphere and terrestrial ecosystems. Model parameterization significantly affects the ability of a model to simulate carbon, water, and energy fluxes. In this study, an ensemble Kalman filter (EnKF) and observations of gross primary productivity (GPP) and latent heat (LE) fluxes were used to optimize model parameters significantly affecting the calculation of these fluxes for a subtropical coniferous plantation in southeastern China. The optimized parameters include the maximum carboxylation rate (Vcmax), the slope in the modified Ball-Berry model (M) and the coefficient determining the sensitivity of stomatal conductance to atmospheric water vapor deficit (D0). Optimized Vcmax and M showed larger variations than D0. Seasonal variations of Vcmax and M were more pronounced than the variations between the two years. Vcmax and M were associated with soil water content (SWC). During dry periods, SWC at the 20 cm depth explained 61% and 64% of variations of Vcmax and M, respectively. EnKF parameter optimization improved the simulations of GPP, LE and SH, mainly during dry periods. After parameter optimization using EnKF, the variations of GPP, LE and SH explained by the model increased by 1% to 4% at half-hourly steps and by 3% to 5% at daily time steps. Further efforts are needed to differentiate the real causes of parameter variations and improve the ability of models to describe the change of stomatal conductance with net photosynthesis rate and the sensitivity of photosynthesis capacity to soil water stress under different environmental conditions.
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The CO2 source and sink distribution across Europe can be estimated in principle through inverse methods by combining CO2 observations and atmospheric transport models. Uncertainties of such estimates are mainly due to insufficient spatiotemporal coverage of CO2 observations and biases of the models. In order to assess the biases related to the use of different models the CO2 concentration field over Europe has been simulated with five different Eulerian atmospheric transport models as part of the EU-funded AEROCARE project, which has the main goal to estimate the carbon balance of Europe. In contrast to previous comparisons, here both global coarse-resolution and regional higher-resolution models are included. Continuous CO2 observations from continental, coastal and mountain sites as well as flasks sampled on aircrafts are used to evaluate the models' ability to capture the spatiotemporal variability and distribution of lower troposphere CO2 across Europe. 914CO2 is used in addition to evaluate separately fossil fuel signal predictions. The simulated concentrations show a large range of variation, with up to ∼10ppm higher surface concentrations over Western and Central Europe in the regional models with highest (mesoscale) spatial resolution.The simulation - data comparison reveals that generally high-resolution models are more successful than coarse models in capturing the amplitude and phasing of the observed short-term variability. At high-altitude stations the magnitude of the differences between observations and models and in between models is less pronounced, but the timing of the diurnal cycle is not well captured by the models.The data comparisons show also that the timing of the observed variability on hourly to daily time scales at lowaltitude stations is generally well captured by all models. However, the amplitude of the variability tends to be underestimated. While daytime values are quite well predicted, nighttime values are generally underpredicted. This is a reflection of the different mixing regimes during day and night combined with different vertical resolution between models. In line with this finding, the agreement among models is increased when sampling in the afternoon hours only and when sampling the mixed portion of the PBL, which amounts to sampling at a few hundred meters above ground. The main recommendations resulting from the study for constraining land carbon sources and sinks using high-resolution concentration data and state-of-the art transport models through inverse methods are given in the following: 1) Low altitude stations are presently preferable in inverse studies. If high altitude stations are used then the model level that represents the specific sites should be applied, 2) at low altitude sites only the afternoon values of concentrations can be represented sufficiently well by current models and therefore afternoon values are more appropriate for constraining large-scale sources and sinks in combination with transport models, 3) even when using only afternoon values it is clear that data sampled several hundred meters above ground can be represented substantially more robustly in models than surface station records, which emphasize the use of tower data in inverse studies and finally 4) traditional large scale transport models seem not sufficient to resolve fine-scale features associated with fossil fuel emissions, as well as larger-scale features like the concentration distribution above the south-western Europe. It is therefore recommended to use higher resolution models for interpretation of continental data in future studies.
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A new diagnostic model for the estimation of net primary productivity (NPP) is presented. It is derived from the Kumar and Monteith model for remote sensing of crop growth, with a separate parameterization of autotrophic respiration. The NPP model is coupled to a soil respiration model, calibrated in order to balance the resulting net ecosystem productivity (NEP) over a year. This model is run over the years 1986 to 1991 with NOAA-AVHRR derived normalized difference vegetation index (NDVI) as inputs, for which the radiometric calibration drift has been accounted for. The outputs of the model are analysed in terms of interannual variations: the model seems to be able to simulate the effects of events such as El Nino on the terrestrial net primary productivity. The NEP outputs are compared to CO 2 concentration measurements in the atmosphere, on a zonally averaged basis, without taking into account atmospheric transport. Seasonal evolution of NEP and atmospheric CO 2 are well in phase in latitudes of the temperate northern hemisphere, but the correspondence is weaker or absent in the tropics and southern hemisphere. DOI: 10.1034/j.1600-0889.47.issue1.15.x
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We review measured rates of soil respiration from terrestrial and wetland ecosystems to define the annual global CO 2 flux from soils, to identify uncertainties in the global flux estimate, and to investigate the influences of temperature, precipitation, and vegetation on soil respiration rates. The annual global CO 2 flux from soils is estimated to average (± S.D.) 68 ± 4 PgC/ yr, based on extrapolations from biome land areas. Relatively few measurements of soil respiration exist from arid, semi-arid, and tropical regions; these regions should be priorities for additional research. On a global scale, soil respiration rates are positively correlated with mean annual air temperatures and mean annual precipitation. There is a close correlation between mean annual net primary productivity (NPP) of different vegetation biomes and their mean annual soil respiration rates, with soil respiration averaging 24% higher than mean annual NPP. This difference represents a minimum estimate of the contribution of root respiration to the total soil CO 2 efflux. Estimates of soil C turnover rates range from 500 years in tundra and peaty wetlands to 10 years in tropical savannas. We also evaluate the potential impacts of human activities on soil respiration rates, with particular focus on land use changes, soil fertilization, irrigation and drainage, and climate changes. The impacts of human activities on soil respiration rates are poorly documented, and vary among sites. Of particular importance are potential changes in temperatures and precipitation. Based on a review of in situ measurements, the Q 10 value for total soil respiration has a median value of 2.4. Increased soil respiration with global warming is likely to provide a positive feedback to the greenhouse effect. DOI: 10.1034/j.1600-0889.1992.t01-1-00001.x
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We report the results on eddy covariance measurements of net ecosystem exchange (NEE) and accompanying latent and sensible heat fluxes for 44 months in boreal Scots pine forest (southern Finland). We analysed the temperature dependence of ecosystem respiration and PPFD (photosynthetic photon flux density) dependence of daytime CO 2 exchange and calculated the annual carbon budget filling the gaps in data series with the temperature and light dependences. The estimated annual balances of the NEE's were –234 g C m –2 , –262 g C m –2 and –191 g C m –2 in 1997, 1998 and 1999, respectively. We calculated also NEE's for every possible 365-day periods included in the data series and the maximum and minimum of such NEE's were –165 g C m –2 and –304 g C m –2 . The growing season started around 28 April, 16 April and 25 March in 1997, 1998 and 1999, respectively. The maximum light saturated CO 2 uptake rate reached the value of 12 µmol m –2 s –1 gradually by the end of June. In autumn, the uptake did not decline gradually but ceased rapidly round the beginning of November. The non-growing season activity is also important, because soil carbon decomposition occurs all year around, even in cold climates under snow cover. The wintertime average CO 2 respiration rate was 0.44 µmol m –2 s –1 .
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TURC, a diagnostic model for the estimation of continental gross primary productivity (GPP) and net primary productivity (NPP), is presented. This model uses a remotely sensed vegetation index to estimate the fraction of solar radiation absorbed by canopies, and an original parameterization of the relationship between absorbed solar radiation and GPP, based on measurements of CO2 fluxes above plant canopies. An independent, uncalibrated model of autotrophic maintenance and growth respiration is parameterized from literature data, and uses databases on temperature, biomass, and remotely sensed vegetation index. This model results in global estimates of GPP and NPP of 133.1 and 62.3 Gt(C) per year, respectively, which is consistent with commonly admitted values. The ratio of autotrophic respiration to GPP is about 70% for equatorial rain forests and 50% for temperate forests, as a result the highest predicted NPP are in tropical savannas of Africa and South America, and in temperate, highly cultivated zones of North America, not in equatorial rain forest zones. Conversion efficiencies defined as the ratio of yearly integrated NPP to absorbed photosynthetically active radiation (PAR) compare relatively well with a previous compilation of literature values, except for ecosystems with probable reduction of conversion efficiency due to water stress. Several sensitivity studies are performed on some input data sets, model assumptions, and model parameters.
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Kumar and Monteith's [1981] model for the remote sensing of crop growth has been used to estimate continental net primary productivity (NPP) as well as its seasonal and spatial variations. The model assumes a decomposition of NPP into independent parameters such as incident solar radiation (S0), radiation absorption efficiency by canopies (f), and conversion efficiency of absorbed radiation into organic dry matter (e). The precision on some of the input parameters has been improved, compared to previous uses of this model at a global scale: remote sensing data used to derive f have been calibrated, corrected of some atmospheric effects, and filtered; e has been considered as biome-dependent and derived from literature data. The resulting global NPP (approximatively 60 Gtc per year) is within the range of values given in the literature. However, mean NPP estimates per biome do not agree with the literature (in particular, the estimation for tropical rain forests NPP is much lower and for cultivations much higher than field estimates), which results in zonal and seasonal variations of continental NPP giving more weight to the temperate northern hemisphere than to the equatorial zone.
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Information about regional carbon sources and sinks can be derived from variations in observed atmospheric CO2 concentrations via inverse modelling with atmospheric tracer transport models. A consensus has not yet been reached regarding the size and distribution of regional carbon fluxes obtained using this approach, partly owing to the use of several different atmospheric transport models. Here we report estimates of surface-atmosphere CO2 fluxes from an intercomparison of atmospheric CO2 inversion models (the TransCom 3 project), which includes 16 transport models and model variants. We find an uptake of CO2 in the southern extratropical ocean less than that estimated from ocean measurements, a result that is not sensitive to transport models or methodological approaches. We also find a northern land carbon sink that is distributed relatively evenly among the continents of the Northern Hemisphere, but these results show some sensitivity to transport differences among models, especially in how they respond to seasonal terrestrial exchange of CO2. Overall, carbon fluxes integrated over latitudinal zones are strongly constrained by observations in the middle to high latitudes. Further significant constraints to our understanding of regional carbon fluxes will therefore require improvements in transport models and expansion of the CO2 observation network within the tropics.
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FLUXNET is a global network of micrometeorological flux measurement sites that measure the exchanges of car-bon dioxide, water vapor, and energy between the biosphere and atmosphere. At present over 140 sites are operating on a long-term and continuous basis. Vegetation under study includes temperate conifer and broadleaved (deciduous and evergreen) forests, tropical and boreal forests, crops, grasslands, chaparral, wetlands, and tundra. Sites exist on five con-tinents and their latitudinal distribution ranges from 70°N to 30°S. FLUXNET has several primary functions. First, it provides infrastructure for compiling, archiving, and distributing carbon, water, and energy flux measurement, and meteorological, plant, and soil data to the science community. (Data and site information are available online at the FLUXNET Web site, http://www-eosdis.ornl.gov/FLUXNET/.) Second, the project supports calibration and flux intercomparison activities. This activity ensures that data from the regional networks are intercomparable. And third, FLUXNET supports the synthesis, discussion, and communication of ideas and data by supporting project scientists, workshops, and visiting scientists. The overarching goal is to provide infor-mation for validating computations of net primary productivity, evaporation, and energy absorption that are being generated by sensors mounted on the NASA Terra satellite. Data being compiled by FLUXNET are being used to quantify and compare magnitudes and dynamics of annual ecosystem carbon and water balances, to quantify the response of stand-scale carbon dioxide and water vapor flux densities to controlling biotic and abiotic factors, and to validate a hierarchy of soil–plant–atmosphere trace gas ex-change models. Findings so far include 1) net CO 2 exchange of temperate broadleaved forests increases by about 5.7 g C m −2 day −1 for each additional day that the growing season is extended; 2) the sensitivity of net ecosystem CO 2 exchange to sunlight doubles if the sky is cloudy rather than clear; 3) the spectrum of CO 2 flux density exhibits peaks at timescales of days, weeks, and years, and a spectral gap exists at the month timescale; 4) the optimal temperature of net CO 2 exchange varies with mean summer temperature; and 5) stand age affects carbon dioxide and water vapor flux densities.
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The volume of shade within vegetation canopies is reduced by more than an order of magnitude on cloudy and/or very hazy days compared to clear sunny days because of an increase in the diffuse fraction of the solar radiance. Here we show that vegetation is directly sensitive to changes in the diffuse fraction and we conclude that the productivity and structure of vegetation is strongly influenced by clouds and other atmospheric particles. We also propose that the unexpected decline in atmospheric [CO2] which was observed following the Mt. Pinatubo eruption was in part caused by increased vegetation uptake following an anomalous enhancement of the diffuse fraction by volcanic aerosols that would have reduced the volume of shade within vegetation canopies. These results have important implications for both understanding and modelling the productivity and structure of terrestrial vegetation as well as the global carbon cycle and the climate system.
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FLUXNET is a global network of micrometeorological flux measurement sites that measure the exchanges of carbon dioxide, water vapor, and energy between the biosphere and atmosphere. At present over 140 sites are operating on a long-term and continuous basis. Vegetation under study includes temperate conifer and broadleaved (deciduous and evergreen) forests, tropical and boreal forests, crops, grasslands, chaparral, wetlands, and tundra. Sites exist on five continents and their latitudinal distribution ranges from 70°N to 30°S. FLUXNET has several primary functions. First, it provides infrastructure for compiling, archiving, and distributing carbon, water, and energy flux measurement, and meteorological, plant, and soil data to the science community. (Data and site information are available online at the FLUXNET Web site, http://www-eosdis.ornl.gov/FLUXNET/.) Second, the project supports calibration and flux intercomparison activities. This activity ensures that data from the regional networks are intercomparable. And third, FLUXNET supports the synthesis, discussion, and communication of ideas and data by supporting project scientists, workshops, and visiting scientists. The overarching goal is to provide information for validating computations of net primary productivity, evaporation, and energy absorption that are being generated by sensors mounted on the NASA Terra satellite. Data being compiled by FLUXNET are being used to quantify and compare magnitudes and dynamics of annual ecosystem carbon and water balances, to quantify the response of stand-scale carbon dioxide and water vapor flux densities to controlling biotic and abiotic factors, and to validate a hierarchy of soil-plant-atmosphere trace gas exchange models. Findings so far include 1) net CO2 exchange of temperate broadleaved forests increases by about 5.7 g C m-2 day-1 for each additional day that the growing season is extended; 2) the sensitivity of net ecosystem CO2 exchange to sunlight doubles if the sky is cloudy rather than clear; 3) the spectrum of CO2 flux density exhibits peaks at timescales of days, weeks, and years, and a spectral gap exists at the month timescale; 4) the optimal temperature of net CO2 exchange varies with mean summer temperature: and 5) stand age affects carbon dioxide and water vapor flux densities.
Chapter
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The chapter has described the measurement system and the procedure followed for the computation of the fluxes and the procedure of flux summation, including data gap filling strategy, night flux corrections and error estimation. It begins with the introduction of estimates of the annual net carbon and water exchange of forests using the EUROFLUX methodology. The chapter then provides us with the theory and moves on to discuss the eddy covariance system and its sonic anemometer, temperature fluctuation measurements, infrared gas analyser, air transport system, and tower instrumentation. Additional measurements are also given in the chapter. Data acquisition and its computation and correction is discussed next in the chapter by giving its general procedure, half-hourly means (co-)variances and uncorrected fluxes, intercomparison of software, and correction for frequency response losses. The chapter has also discussed about quality control and four criteria are investigated here for the same. Spatial representativeness of measured fluxes and summation procedure are reviewed. The chapter then moves on to the discussion of data gap filling through interpolation and parameterization and neural networks. Corrections to night-time data and error estimation are also explored in the chapter. Finally, the chapter closes with conclusions.
Article
Full-text available
Carbon exchange between the terrestrial biosphere and the atmosphere is one of the key processes that need to be assessed in the context of the Kyoto Protocol. Several studies suggest that the terrestrial biosphere is gaining carbon, but these estimates are obtained primarily by indirect methods, and the factors that control terrestrial carbon exchange, its magnitude and primary locations, are under debate. Here we present data of net ecosystem carbon exchange, collected between 1996 and 1998 from 15 European forests, which confirm that many European forest ecosystems act as carbon sinks. The annual carbon balances range from an uptake of 6.6 tonnes of carbon per hectare per year to a release of nearly 1 t C ha -1 yr-1, with a large variability between forests. The data show a significant increase of carbon uptake with decreasing latitude, whereas the gross primary production seems to be largely independent of latitude. Our observations indicate that, in general, ecosystem respiration determines net ecosystem carbon exchange. Also, for an accurate assessment of the carbon balance in a particular forest ecosystem, remote sensing of the normalized difference vegetation index or estimates based on forest inventories may not be sufficient.
Article
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The concurrent effects of increasing atmospheric CO2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process-based terrestrial biosphere models. Over the long-term (1920-1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long-term analysis based on ice core and atmospheric CO2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO2. During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr(-1), which is within the uncertainty of analysis based on CO2 and O-2 budgets. Three of the four models indicated tin accordance with O-2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long-term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Nino/Southern Oscillation (ENSO)-scale variability in the atmospheric CO2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO2 suggested that the observed trend may be a consequence of CO2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process-based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand-level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system.
Article
Full-text available
Carbon exchange between the terrestrial biosphere and the atmosphere is one of the key processes that need to be assessed in the context of the Kyoto Protocol. Several studies suggest that the terrestrial biosphere is gaining carbon, but these estimates are obtained primarily by indirect methods, and the factors that control terrestrial carbon exchange, its magnitude and primary locations, are under debate. Here we present data of net ecosystem carbon exchange, collected between 1996 and 1998 from 15 European forests, which confirm that many European forest ecosystems act as carbon sinks. The annual carbon balances range from an uptake of 6.6 tonnes of carbon per hectare per year to a release of nearly 1 t C ha(-1) yr(-1), with a large variability between forests. The data show a significant increase of carbon uptake with decreasing latitude, whereas the gross primary production seems to be largely independent of latitude. Our observations indicate that, in general, ecosystem respiration determines net ecosystem carbon exchange. Also, for an accurate assessment of the carbon balance in a particular forest ecosystem, remote sensing of the normalized difference vegetation index or estimates based on forest inventories may not be sufficient.
Article
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For the period 1980–89, we estimate a carbon sink in the coterminous United States between 0.30 and 0.58 petagrams of carbon per year (petagrams of carbon = 1015 grams of carbon). The net carbon flux from the atmosphere to the land was higher, 0.37 to 0.71 petagrams of carbon per year, because a net flux of 0.07 to 0.13 petagrams of carbon per year was exported by rivers and commerce and returned to the atmosphere elsewhere. These land-based estimates are larger than those from previous studies (0.08 to 0.35 petagrams of carbon per year) because of the inclusion of additional processes and revised estimates of some component fluxes. Although component estimates are uncertain, about one-half of the total is outside the forest sector. We also estimated the sink using atmospheric models and the atmospheric concentration of carbon dioxide (the tracer-transport inversion method). The range of results from the atmosphere-based inversions contains the land-based estimates. Atmosphere- and land-based estimates are thus consistent, within the large ranges of uncertainty for both methods. Atmosphere-based results for 1980–89 are similar to those for 1985–89 and 1990–94, indicating a relatively stable U.S. sink throughout the period.
Book
After years of technological development and its important achievements to make our life easier and more comfortable, human society is going to face one of the most difficult challenges of the last century: to stabilize the concentra­ tion levels of greenhouse gases in the atmosphere to prevent harmful effects on the climate system. Through a delicate balance between photosynthesis and respiration, terres­ trial ecosystems, and in particular forests, are today thought to take up a sig­ nificant part of the carbon dioxide emissions in the atmosphere, sometimes called the "terrestrial carbon sink". However, the location, magnitude, and vulnerability of the carbon dioxide sink of the terrestrial biota are still uncer­ tain. The suite of traditional tools in an ecologist's toolbox for studying ecosys­ tem productivity and carbon balance include leaf cuvettes, whole-plant and soil chambers for gas exchange, and biomass and soil carbon inventories. While each of the cited methods has distinct advantages, they are limited with regards to their ability to measure net carbon dioxide exchange of the whole ecosystem across a variety of time scales. This book present a compendium of results of a European project (EURO­ FLUX), funded by the European Commission through its fourth framework program, aiming to elucidate the role of forests in continental carbon balance.
Article
As part of the EU-funded AEROCARB project, transport simulations with seven different atmospheric transport models were performed and compared among each other and with observations. The purpose of the intercomparison is as a precursor step for the use of the highly resolving models to interpret continental trace gas observations in terms of source and sink processes. The participating models use either observed ecmwf or self-containedly simulated meteorology. They differ in the parameterisations of subgrig-scale processes and the spatio-temporal resolutions. Two models cover the entire globe (TM3 and LMDZ) and were run both with coarse (a few degrees) and high horizontal resolution (up to 0.5 degrees). Three of the models (DEHM, MM5-HANK and REMO-D) with high spatial resolution use a limited domain, (covering either the Eurasian continent or the Northern Hemisphere). These limited area models use time varying CO2 fields as lateral boundary conditions that were previously computed with the global model TM3. All models were forced at the surface with the same land-biosphere CO2 fluxes (3-hourly), air-sea fluxes (monthly) and fossil fuel emissions (yearly)to simulate atmospheric CO2. For the simulation of atmospheric Rn-222 a uniform source over ice-free continents was assumed. The simulations are compared at 9 European stations with continuous measurements of CO2 and Rn. Two periods July 1998 and December 1998 were studied. We will discuss how models differ both for daytime and night time, as well as for the different (biotic, oceanic, fossil)components. We will also evaluate the usefulness of Rn-222 to test daily changes in PBL-free troposphere exchange as well as transport connected with weather systems over the European continents.
Article
Summary Net ecosystem CO2 exchange was measured over a mountain birch forest in northern Finland throughout the growing season. The maximal net CO2 uptake rate of about − 0.5 mg(CO2) m−2 s−1 was observed at the end of July. The highest nocturnal respiration rates in early August were 0.2 mg(CO2) m−2 s−1. The daily CO2 balances during the time of maximal photosynthesis were about −15 g(CO2) m−2 d−1. The mountain birch forest acted as a net sink of CO2 from 30 June to 28 August. During that period the net CO2 balance was −448 g(CO2)m−2. The interannual representativeness of the observed balances was studied using a simplified daily balance model, with daily mean global radiation and air temperature as the input parameters. The year-to-year variation in the phenological development was parameterised as a function of the cumulative effective temperature sum. The daily balance model was used for estimating the variability in the seasonal CO2 balances due to the timing of spring and meteorological factors. The sink term of CO2 in 1996 was lower than the 15-year mean, mainly due to the relatively late emergence of the leaves.
Article
Abstract We present results from two years’ net ecosystem flux measurements above a boreal forest in central Sweden. Fluxes were measured with an eddy correlation system based on a sonic anemometer and a closed path CO2 and H2O gas analyser. The measurements show that the forest acted as a source during this period, and that the annual balance is highly sensitive to changes in temperature. The accumulated flux of carbon dioxide during the full two-year period was in the range 480–1600 g CO2 m–2. The broad range is caused by uncertainty regarding assessment of the night-time fluxes. Although annual mean temperature remained close to normal, the results are partly explained by higher than normal respiration, due to abnormal temperature distribution and reduced soil moisture during one growing season. The finding that a closed forest can be a source of carbon over such a long period as two years contrasts sharply with the common belief that forests are always carbon sinks.
Article
The quantum yield for CO2 uptake was measured on a number of C3 and C4 monocot and dicot species. Under normal atmospheric conditions (330 microliters per liter CO2, 21% O2) and a leaf temperature of 30°C, the average quantum yields (moles CO2 per einstein) were as follows: 0.052 for C3 dicots, 0.053 for C3 grasses, 0.053 for NAD-malic enzyme type C4 dicots, 0.060 for NAD-malic enzyme type C4 grasses, 0.064 for phosphoenolpyruvate carboxykinase type C4 grasses, 0.061 for NADP-malic enzyme C4 dicots, and 0.065 for NADP-malic enzyme type C4 grasses. The quantum yield under normal atmospheric conditions was temperature dependent in C3 species, but apparently not in C4 species. Light and temperature conditions during growth appeared not to influence quantum yield. The significance of variation in the quantum yields of C4 plants was discussed in terms of CO2 leakage from the bundle sheath cells and suberization of apoplastic regions of the bundle sheath cells.
Article
Micrometeorological measurements of CO2 and energy fluxes were carried out in a peatland ecosystem in northern Finland (69°08'N, 27°17'E) during a measurement period from April to the end of October 1997. The summer of 1997 was exceptionally warm and dry as compared to the climatological normal period of 1961-1990, and the effects of the high temperature and lowered water table were clearly seen in the CO2 fluxes. The highest individual downward flux densities of about -0.25mg(CO2)m-2s-1 took place at the end of July, while the highest respiration rates of 0.15mg(CO2)m-2s-1 were observed later in August. During the first days of measurements in April the median of respiration flux densities through the snow cover was about 0.006mg(CO2)m-2s-1. In correspondence to the CO2 fluxes the strongest sink terms in the daily net ecosystem exchange (NEE) balances of about -6g(CO2)m-2d-1 were observed in July. The highest positive balances of about 4g(CO2)m-2d-1 were observed in early June and in August. The daily balances in April were about 0.6g(CO2)m-2d-1. The net balances for the sink period (June 15 to August 26, 1997) and for the 6-month measurement period were -188 gm-2 and -30 gm-2, respectively. The wintertime CO2 balance was estimated by modeling the NEE using the NEE values from the first measurement week in April. The wintertime balances obtained yielded estimates for annual balances in the range of 62 to 72 gm-2yr-1.
Article
For the purposes of this discussion, temperate forest is regarded as occurring in broad latitudinal bands between the taiga towards the poles and the mediterranean flora towards the equator. Within these bands temperate forest occurs at moderate elevations below the altitudinal extremes of climate and associated alpine vegetation and away from the continental extremes of temperature and dryness. Temperatures are moderate, usually not falling below about -15 °C in winter, and the soil freezes for less than 3 months. In summer temperatures rarely exceed 35 °C, precipitation exceeds ca. 400 mm and is fairly uniformly distributed through the year so that a dry season lasts for less than ca. 3 months. A more exact definition can be found in Walter (1970).
Article
In preparation for new satellite sensors, such as VEGETATION on SPOT-4 and the MODerate Resolution Imaging Spectrometer (MODIS), we investigate the potential of the shortwave infrared (SWIR) signal to improve Leaf Area Index (LAI) retrieval in the boreal forests of Canada. Our study demonstrates that an empirical SWIR modification to the simple ratio (SR) vegetation index, termed the reduced simple ratio (RSR), has the potential to unify deciduous and conifer species in LAI retrieval, shows increased sensitivity to LAI, and demonstrates an improved correlation with LAI in individual jack pine and black spruce canopies. The unification of deciduous and conifer species suggests the possibility of not requiring a cover type stratification prior to retrieving LAI information from remotely sensed data, and has impact where no cover type information will be made or where the mix of cover types within a pixel is unknown. We use a geometric–optical canopy reflectance model to quantify the potential variation in jack pine and black spruce canopy reflectance caused by differences in background reflectance. The modeling study supports the results from the image analysis of the RSR showing increased sensitivity to LAI and reducing background effects in these conifer canopies.
Article
The book provides an up-to-date description of the methods used for fitting experimental data, or to estimate model parameters, and to unify these methods into the Inverse Problem Theory. The first part of the book deals with problems and describes Maximum likelihood, Monte Carlo, Least squares, and Least absolute values methods. The second part deals with inverse problems involving functions. Theoretical concepts are emphasized, and the author has all the useful formulas listed, with many special cases included. The book serves as a reference manual.
Article
Remotely sensed data were acquired seasonally with an ultralight aircraft to provide a means of scaling the leaf area and leaf pigmentation changes that affected the light absorption of photosynthetically active radiation to larger areas. A linear correlation between chlorophyll concentrations in the upper canopy leaves of four hardwood species and their quantum efficiencies (R2= 0–99) suggested that seasonal changes in quantum efficiency for the entire canopy can be quantified with remotely sensed indices of chlorophyll. Analysis of video data collected from the ultralight aircraft indicated that the fraction of conifer cover varied from < 7% near the instrument tower to about 25% for a larger sized area. At 25% conifer cover, the quantum efficiency model predicted an increase in the estimate of annual GEP of < 5% because unfavourable environmental conditions limited conifer photosynthesis in much of the non-growing season when hardwoods lacked leaves.
Article
A global prognostic physiologically based model of the carbon budget in terrestrial ecosystems, the Frankfurt Biosphere Model (FBM), is applied to simulate the interannual variation of carbon exchange fluxes between the atmosphere and the terrestrial biosphere. The data on climatic forcing are based on Cramer and Leemans climate maps; the interannual variation is introduced according to records of temperature anomalies and precipitation anomalies for the period 1980 to 1993. The calculated net exchange flux between the atmosphere and the terrestrial biosphere is compared to the biospheric signal deduced from C-13 measurements. Some intermediate results are presented as well: the contributions of the most important global ecosystems to the biospheric signal, the contributions of different latitudinal belts to the biospheric signal, and the responses of net primary production (NPP) and heterotrophic respiration (R(h)) From the simulation results it can be inferred that the complex temperature and precipitation responses of NPP and R(h) in different latitudes and different ecosystem types add up to a global CO2 signal contributing substantially to the atmospheric CO2 anomaly on the interannual timescale. The temperature response of NPP was found to be the most important factor determining this signal.
Article
Publisher Summary The purpose of this chapter is to assess the possibility of obtaining general relationships between the CO 2 flux over canopies (F) and absorbed PPFD (Q). In particular, it emphasizes on determining whether the relationship for a closed canopy is linear, consistent with the Monteith model, or curvilinear, consistent with the results of many mechanistic canopy models. Both general relationships and relationships for different vegetation classes are sought. Some methodology-related differences are also investigated, including comparison between micrometeorological and enclosure methods, the effect of taking into account respiration rate, and the effect of integrating measurements in time. For this, statistics are used on similar data sets, that is, except for the variable under study, all environmental conditions are similar, and the data are obtained on the same site, with the same measuring technique, by the same scientific team, and statistics on grouped data sets, that is, all the data sets on closed canopies satisfying the conditions described in the data analysis section are grouped by vegetation class or method of measurement or representation.
Article
ABSTRACTA new diagnostic model for the estimation of net primary productivity (NPP) is presented. It is derived from the Kumar and Monteith model for remote sensing of crop growth, with a separate parameterization of autotrophic respiration. The NPP model is coupled to a soil respiration model, calibrated in order to balance the resulting net ecosystem productivity (NEP) over a year. This model is run over the years 1986 to 1991 with NOAA-AVHRR derived normalized difference vegetation index (NDVI) as inputs, for which the radiometric calibration drift has been accounted for. The outputs of the model are analysed in terms of interannual variations: the model seems to be able to simulate the effects of events such as El Niño on the terrestrial net primary productivity. The NEP outputs are compared to CO2 concentration measurements in the atmosphere, on a zonally averaged basis, without taking into account atmospheric transport. Seasonal evolution of NEP and atmospheric CO2 are well in phase in latitudes of the temperate northern hemisphere, but the correspondence is weaker or absent in the tropics and southern hemisphere.
Article
This paper presents CO2 flux data from 18 forest ecosystems, studied in the European Union funded EUROFLUX project. Overall, mean annual gross primary productivity (GPP, the total amount of carbon (C) fixed during photosynthesis) of these forests was 1380 ± 330 gC m−2 y−1 (mean ±SD). On average, 80% of GPP was respired by autotrophs and heterotrophs and released back into the atmosphere (total ecosystem respiration, TER = 1100 ± 260 gC m−2 y−1). Mean annual soil respiration (SR) was 760 ± 340 gC m−2 y−1 (55% of GPP and 69% of TER). Among the investigated forests, large differences were observed in annual SR and TER that were not correlated with mean annual temperature. However, a significant correlation was observed between annual SR and TER and GPP among the relatively undisturbed forests. On the assumption that (i) root respiration is constrained by the allocation of photosynthates to the roots, which is coupled to productivity, and that (ii) the largest fraction of heterotrophic soil respiration originates from decomposition of young organic matter (leaves, fine roots), whose availability also depends on primary productivity, it is hypothesized that differences in SR among forests are likely to depend more on productivity than on temperature. At sites where soil disturbance has occurred (e.g. ploughing, drainage), soil espiration was a larger component of the ecosystem C budget and deviated from the relationship between annual SR (and TER) and GPP observed among the less-disturbed forests. At one particular forest, carbon losses from the soil were so large, that in some years the site became a net source of carbon to the atmosphere. Excluding the disturbed sites from the present analysis reduced mean SR to 660 ± 290 gC m−2 y−1, representing 49% of GPP and 63% of TER in the relatively undisturbed forest ecosystems.
Article
Diurnal and annual variations of CO2, O3, SO2, black carbon and condensation nuclei and their source areas were studied by utilizing air parcel trajectories and tropospheric concentration measurements at a boreal GAW site in Pallas, Finland. The average growth trend of CO2 was about 2.5 ppm yr−1 according to a 4-yr measurement period starting in October 1996. The annual cycle of CO2 showed concentration difference of about 19 ppm between the summer minimum and winter maximum. The diurnal cycle was most pronounced during July and August. The variation between daily minimum and maximum was about 5 ppm. There was a diurnal cycle in aerosol concentrations during spring and summer. Diurnal variation in ozone concentrations was weak. According to trajectory analysis the site was equally affected by continental and marine air masses. During summer the contribution of continental air increased, although the southernmost influences decreased. During daytime in summer the source areas of CO2 were mainly located in the northern parts of the Central Europe, while during winter the sources were more evenly distributed. Ozone showed similar source areas during summer, while during winter, unlike CO2, high concentrations were observed in air arriving from the sea. Sulfur dioxide sources were more northern (Kola peninsula and further east) and CO2 sources west-weighted in comparison to sources of black carbon. Source areas of black carbon were similar to source areas of aerosols during winter. Aerosol source area distributions showed signs of marine sources during spring and summer.
Article
Models of mass and energy exchanges between the biosphere and the atmosphere generally contain a nonlinear dependence between fluxes and model parameters, and thus estimation of these parameters from measurements in a heterogeneous landscape depends on the scale of the observations. The scale-dependence of a typical surface-exchange model (the CSIRO Biospheric Model, CBM) is examined using the diurnal variation of hourly fluxes of CO2, latent heat, sensible heat and soil heat. The fluxes were measured using micrometeorological techniques over six sites in a grazing/pasture system in SE Australia during a period of three weeks in 1995. Nonlinear parameter inversion was used to determine model parameters. Analysis of the covariance of the estimates of the parameters and the unexplained residuals of the model showed that a maximum of three or four parameters could be determined independently from the observations for all six sites. Estimates of a key model parameter, jmax, the mean of maximum potential electron transport rate of all leaves within the canopy, was best determined by the measurements of net CO2 flux at all sites examined. Measurements of ground heat flux provide little information about any of the model parameters in CBM. Because of nonlinearities in the surface exchange model, calculated fluxes will be in error if parameters for the component vegetation types are simply averaged in proportion to their areal fraction. The magnitude of these errors was examined for CBM using a hypothetical land surface consisting of two surface types, each with different parameter values. Predictions of net CO2, latent heat and ground heat fluxes using a linear combination of model parameters for the two surface types were quite similar with those found using optimal estimates of the parameters for the landscape, but were significantly poorer for sensible heat fluxes.
Article
1. We present measurements of CO2 fluxes over 2 years above and within a young Beech stand in the east of France. This site is part of the Euroflux network set up to monitor fluxes over representative European forests. 2. The net ecosystem carbon (C) exchange was derived from continuous eddy flux measurements. Major components of the total flux (i.e. soil and above-ground biomass respiration and assimilation of leafy branches) were measured independently using chambers. The main C stocks (i.e. root, stem and branch biomass) were also quantified. 3. Daily minima of CO2 flux were typically around −20 µmol CO2 m−2 s−1 during the period of full leaf expansion, while night-time ecosystem respiration varied between 5 and 15 µmol CO2 m−2 s−1. The seasonal pattern of net ecosystem assimilation was very close to that of net assimilation at the single branch scale. The seasonal variation of net ecosystem exchange was closely related to leaf expansion and soil water content during the dry year of 1996. 4. Measurements of ecosystem respiration (eddy flux) were corrected for CO2 storage within the stand. This C flux showed a seasonal pattern, the maximum rates (4–7 g C m−2 day−1) occurring in spring and summer, and appeared to be correlated with soil temperature. Temporal variation of soil respiration showed the same pattern, and effects of both temperature and soil drying were found. Annual soil respiration was ≈ 70% of ecosystem respiration. Root respiration was 60% of the total below-ground respiration. 5. Annual net C exchange was −218 and −257 g C m−2 in 1996 and 1997, respectively, corresponding to net C uptake by the forest. These values are much lower than the annual biomass increment (stems and large roots) of the stand: 427 and 471 g C m−2 year−1, respectively. The difference may be explained by a release of CO2 from the decomposition of woody debris. 6. Ecosystem C loss by respiration was 800–1000 g C m−2 year−1. Gross C gain was 1000–1300 g C m−2 year−1. Ecosystem respiration therefore played a major role in the annual C balance of this forest.
Article
Seventeen global models of terrestrial biogeochemistry were compared with respect to annual and seasonal fluxes of net primary productivity (NPP) for the land biosphere. The comparison, sponsored by IGBP-GAIM/DIS/GCTE, used standardized input variables wherever possible and was carried out through two international workshops and over the Internet. The models differed widely in complexity and original purpose, but could be grouped in three major categories: satellite-based models that use data from the NOAA/AVHRR sensor as their major input stream (CASA, GLO-PEM, SDBM, SIB2 and TURC), models that simulate carbon fluxes using a prescribed vegetation structure (BIOME-BGC, CARAIB 2.1, CENTURY 4.0, FBM 2.2, HRBM 3.0, KGBM, PLAI 0.2, SILVAN 2.2 and TEM 4.0), and models that simulate both vegetation structure and carbon fluxes (BIOME3, DOLY and HYBRID 3.0). The simulations resulted in a range of total NPP values (44.4–66.3 Pg C year–1), after removal of two outliers (which produced extreme results as artefacts due to the comparison). The broad global pattern of NPP and the relationship of annual NPP to the major climatic variables coincided in most areas. Differences could not be attributed to the fundamental modelling strategies, with the exception that nutrient constraints generally produced lower NPP. Regional and global NPP were sensitive to the simulation method for the water balance. Seasonal variation among models was high, both globally and locally, providing several indications for specific deficiencies in some models.
Article
We review measured rates of soil respiration from terrestrial and wetland ecosystems to define the annual global CO2 flux from soils, to identify uncertainties in the global flux estimate, and to investigate the influences of temperature, precipitation, and vegetation on soil respiration rates. The annual global CO2 flux from soils is estimated to average (± S.D.) 68 ± 4 PgC/ yr, based on extrapolations from biome land areas. Relatively few measurements of soil respiration exist from arid, semi-arid, and tropical regions; these regions should be priorities for additional research. On a global scale, soil respiration rates are positively correlated with mean annual air temperatures and mean annual precipitation. There is a close correlation between mean annual net primary productivity (NPP) of different vegetation biomes and their mean annual soil respiration rates, with soil respiration averaging 24% higher than mean annual NPP. This difference represents a minimum estimate of the contribution of root respiration to the total soil CO2efflux. Estimates of soil C turnover rates range from 500 years in tundra and peaty wetlands to 10 years in tropical savannas. We also evaluate the potential impacts of human activities on soil respiration rates, with particular focus on land use changes, soil fertilization, irrigation and drainage, and climate changes. The impacts of human activities on soil respiration rates are poorly documented, and vary among sites. Of particular importance are potential changes in temperatures and precipitation. Based on a review of in situ measurements, the Q10 value for total soil respiration has a median value of 2.4. Increased soil respiration with global warming is likely to provide a positive feedback to the greenhouse effect.
Article
abstractThe Eurosiberian Carbonflux project was designed to address the feasibility of inferring the regional carbon balance over Europe and Siberia from a hierarchy of models and atmospheric CO2 measurements over the continent. Such atmospheric CO2 concentrations result from the combination of connective boundary layer dynamics, synoptic events, large-scale transport of CO2, and regional surface fluxes and depend on the variability of these processes in time and space. In this paper we investigate the spatial and temporal variability of the land surface CO2 fluxes derived from the TURC model. This productivity model is driven by satellite NDVI and forced by ECMWF or REMO meteorology. We first present an analysis of recent CO2 flux measurements over temperate and boreal forests, which are used to update the TURC model. A strong linear relationship has been found between maximum hourly CO2 fluxes and the mean annual air temperature, showing that boreal biomes have a lower photosynthetic capacity than temperate ones. Then, model input consistency and simulated CO2 flux accuracy are evaluated against local measurements from two sites in Russia. Finally, the spatial and temporal patterns of the daily CO2 fluxes over Eurasia are analysed. We show that, during the growing season (spring and summer), the daily CO2 fluxes display characteristic spatial patterns of positive and negative fluxes at the synoptic scale. These patterns are found to correspond to cloudy areas (areas with low incoming radiation) and to follow the motion of cloud cover areas over the whole domain. As a consequence, we argue that covariations of surface CO2 fluxes and atmospheric transport at the synoptic scale may impact CO2 concentrations over continents and need to be investigated.
Article
abstractThe spatial distribution and the temporal variability of atmospheric CO2 over Europe and western Siberia are investigated using the regional atmospheric model, REMO. The model, of typical horizontal resolution 50 km, is part of a nested modelling framework that has been established as a concerted action during the EUROSIBERIAN CARBONFLUX project. In REMO, the transport of CO2 is simulated together with climate variables, which offers the possibility of calculating at each time step the land atmosphere CO2 fluxes as driven by the modelled meteorology. The uptake of CO2 by photosynthesis is calculated using a light use efficiency formulation, where the absorbed photosynthetically active solar radiation is inferred from satellite measurements. The release of CO2 from plant and soil respiration is driven by the simulated climate and assumed to be in equilibrium with photosynthesis over the course of one year. Fossil CO2 emissions and air–sea fluxes within the model domain are prescribed, whereas the influence of sources outside the model domain is computed from as a boundary condition CO2 fields determined a global transport model. The modelling results are compared against pointwise eddy covariance fluxes, and against atmospheric CO2 records. We show that a necessary condition to simulate realistically the variability of atmospheric CO2 over continental Europe is to account for the diurnal cycle of biospheric exchange. Overall, for the study period of July 1998, REMO realistically simulates the short-term variability of fluxes and of atmospheric mixing ratios. However, the mean CO2 gradients from western Europe to western Siberia are not correctly reproduced. This latter deficiency points out the key role of boundary conditions in a limited-area model, as well as the need for using more realistic geographic mean patterns of biospheric carbon fluxes.
Article
CO2 flux measurements give access to two critical terms of the carbon budget of terrestrial ecosystems, the gross primary productivity (GPP) and the net ecosystem productivity (NEP). CO2 fluxes measured by micrometeorological methods have spatial and temporal characteristics that make them potentially useful in modelling the global terrestrial carbon budget. The first use is in parameterizing ecosystem physiological processes. We present an example, based on parameterizing the mean light response of GPP. This parameterization can be used in diagnostic, satellite-based GPP models. A global application leads to realistic estimates of global GPP. The second use is in testing the seasonality of fluxes predicted by global models. Our example of this use tests two global GPP models. One is a diagnostic, satellite-based model, and one is a prognostic, process-based model. Despite the limitations of the models, both agree reasonably well with the measurements. The agreements and disagreements are useful in addressing the problems of available input datasets and representation of processes, in global models. Long-term CO2 flux measurements give access to key variables of terrestrial vegetation models and therefore offer exciting perspectives.
Article
The aim of this paper is to investigate the feasibility of using Landsat ETM+ data for the determination of leaf area index (LAI). The investigation is prompted by the need for obtaining spatially distributed data on LAI to be used as input for carbon modelling of northern boreal forests. Detailed field data have been collected in a coniferous forest area in Uppland, central Sweden, dominated by Norway spruce and Scots pine. A forest canopy reflectance model (Kuusk and Nilson, 2000) has been used to simulate stand reflectances in the Landsat ETM+ wavelength bands as a means of investigating the theoretical reflectance response to LAI changes. The analysis shows that the response to changes in LAI is strongest in the visible wavelength bands, particularly Channel 3, whereas only weak response is noted in the NIR band and for some vegetation indices [simple ratio (SR) and NDVI]. Modelled reflectances are influenced by various other factors, particularly ground reflectance and leaf biochemical properties. Observed reflectances from the Landsat ETM+ sensor have been compared with reflectance modelling results and with field-based LAI estimates. The results indicate that LAI estimation using inverse canopy reflectance modelling may be difficult, given the large number of input parameters required and the current level of uncertainty in these parameters. Statistical relationships between LAI and observed ETM+ reflectances are strongest in ETM+ Channel 7.
Article
The ‘Le Bray’ site, a 28-year old plantation of maritime pine (Pinus pinaster Ait.) with an understorey of graminae, is part of the European network Euroflux. Carbon dioxide and water vapour fluxes were measured continuously for 2 years above the canopy with an eddy-covariance system. The 2-year accumulated evapotranspiration amounts to 3184±440 MJ m−2 (1331±186 mm of water) compared to 1860 mm rainfall or 6011 MJ m−2 net radiation. The overall gap in the energy balance is 1322 MJ m−2, partly due to the poor estimation of evapotranspiration during rainy periods. The 2-year sum of carbon sequestration is 11.5±0.8 t of carbon per hectare. The 2-year total ecosystem respiration, estimated by adjusting statistically night-time CO2 fluxes against the soil–litter interface temperature for turbulent nights only, is about 33.6±2.0 t of carbon. A fairly good statistical relationship is found by multiple regression between daily gross primary production (GPP) on the one hand, and direct and diffuse absorbed PAR on the other hand. The water use efficiency (defined as the ratio of GPP to evapotranspiration) is inversely related to air saturation deficit.
Book
While the prediction of observations is a forward problem, the use of actual observations to infer the properties of a model is an inverse problem. Inverse problems are difficult because they may not have a unique solution. The description of uncertainties plays a central role in the theory, which is based on probability theory. This book proposes a general approach that is valid for linear as well as for nonlinear problems. The philosophy is essentially probabilistic and allows the reader to understand the basic difficulties appearing in the resolution of inverse problems. The book attempts to explain how a method of acquisition of information can be applied to actual real-world problems, and many of the arguments are heuristic. Prompted by recent developments in inverse theory, Inverse Problem Theory and Methods for Model Parameter Estimation is a completely rewritten version of a 1987 book by the same author. In this version there are lots of algorithmic details for Monte Carlo methods, least-squares discrete problems, and least-squares problems involving functions. In addition, some notions are clarified, the role of optimization techniques is underplayed, and Monte Carlo methods are taken much more seriously. The first part of the book deals exclusively with discrete inverse problems with a finite number of parameters while the second part of the book deals with general inverse problems. While the forward problem has (in deterministic physics) a unique solution, the inverse problem does not. As an example, consider measurements of the gravity field around a planet: given the distribution of mass inside the planet, we can uniquely predict the values of the gravity field around the planet (forward problem), but there are different distributions of mass that give exactly the same gravity field in the space outside the planet. Therefore, the inverse problem — of inferring the mass distribution from observations of the gravity field — has multiple solutions (in fact, an infinite number).
Article
1. From previously published measurements of soil respiration rate (R) and temperature (T) the goodness of fit of various R vs T relationships was evaluated. 2. Exponential (Q10) and conventional Arrhenius relationships between T and R cannot provide an unbiased estimate of respiration rate. Nor is a simple linear relationship appropriate. 3. The relationship between R and T can, however, be accurately represented by an Arrhenius type equation where the effective activation energy for respiration varies inversely with temperature. An empirical equation is presented which yields an unbiased estimator of respiration rates over a wide range of temperatures. 4. When combined with seasonal estimates of Gross Primary Productivity (GPP) the empirical relationship derived provides representative estimates of the seasonal cycle of net ecosystem productivity and its effects on atmospheric CO2. The predicted seasonal cycle of net ecosystem productivity is very sensitive to the assumed respiration vs temperature relationship. 5. For biomes in areas where soil temperatures are low, soil respiration rate is relatively more sensitive to fluctuations in temperature. Nevertheless, more information is required before any predictions can be made about changes in soil carbon pools in response to future temperature changes.
Article
The temperature sensitivity of soil respiration will largely determine the effects of a warmer world on net carbon flux from soils to the atmosphere. CO2 flux from soils to the atmosphere is estimated to be 50–70 petagrams of carbon per year and makes up 20–38% of annual inputs of carbon (in the form of CO2) to the atmosphere from terrestrial and marine sources1,2. Here we show that, for a mixed temperate forest, respiration by roots plus oxidation of rhizosphere carbon, which together produce a large portion of total effluxed soil CO2, is more temperature-sensitive than the respiration of bulk soil. We determine that the Q10 value (the coefficient for the exponential relationship between soil respiration and temperature, multiplied by ten) is 4.6 for autotrophic root respiration plus rhizosphere decomposition, 2.5 for respiration by soil lacking roots and 3.5 for respiration by bulk soil. If plants in a higher-CO2 atmosphere increase their allocation of photosynthate to roots3, 4, 5, 6 these findings suggest that soil respiration should be more sensitive to elevated temperatures, thus limiting carbon sequestration by soils.
Article
A model of crop primary production, which was originally developed to relate the amount of absorbed photosynthetically active radiation (APAR) to net production in field studies, is discussed in the context of coarse resolution regional remote sensing of primary production. The model depends on an approximately linear relationship between APAR and the normalized difference vegetation index. A more comprehensive form of the conventional model is shown to be necessary when different physiological types of plants or heterogeneous vegetation types occur within the study area. The predicted variable in the new model is total assimilation (net production plus respiration) rather than net production alone or harvest yield.
Spatial and temporal variability of land CO2fluxes estimatedwithremotesensingandanalysisdataoverwesternEurasia
  • S Lafont
  • L Kergoat
  • G Dedieu
  • A Chevillard
  • U Karstens
  • O Kolle
Lafont, S., Kergoat, L., Dedieu, G., Chevillard, A., Karstens, U. and Kolle, O. 2002. Spatial and temporal variability of land CO2fluxes estimatedwithremotesensingandanalysisdataoverwesternEurasia. Tellus 54B, 820–834. Tellus 56B (2004), 2 r104 T. AALTO ET AL
Eddy fluxes above a Belgian, Campine forest and their relationship with predicting variables
  • A S Kowalski
  • S Overloop
  • R Ceulemans
  • R Ceulemans
Kowalski, A. S., Overloop, S. and Ceulemans, R. 1999. Eddy fluxes above a Belgian, Campine forest and their relationship with predicting variables. In: Forest Ecosystem Modelling, Upscaling and Remote Sensing (eds Ceulemans, R. et al.), SPB Academic Publishing, The Hague, 3–18.