Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    Changes in net ecosystem exchange over Europe during the 2018 drought based on atmospheric observations
    Thompson, R.L. ; Broquet, G. ; Gerbig, C. ; Koch, T. ; Lang, M. ; Monteil, G. ; Munassar, S. ; Nickless, A. ; Scholze, M. ; Ramonet, M. ; Karstens, U. ; Schaik, E. van; Wu, Z. ; Rödenbeck, C. - \ 2020
    Philosophical Transactions of the Royal Society B. Biological sciences 375 (2020)1810. - ISSN 0962-8436 - 1 p.
    atmospheric inversion - atmospheric tracer transport modelling - drought - net ecosystem exchange

    The 2018 drought was one of the worst European droughts of the twenty-first century in terms of its severity, extent and duration. The effects of the drought could be seen in a reduction in harvest yields in parts of Europe, as well as an unprecedented browning of vegetation in summer. Here, we quantify the effect of the drought on net ecosystem exchange (NEE) using five independent regional atmospheric inversion frameworks. Using a network of atmospheric CO2 mole fraction observations, we estimate NEE with at least monthly and 0.5° × 0.5° resolution for 2009-2018. We find that the annual NEE in 2018 was likely more positive (less CO2 uptake) in the temperate region of Europe by 0.09 ± 0.06 Pg C yr-1 (mean ± s.d.) compared to the mean of the last 10 years of -0.08 ± 0.17 Pg C yr-1, making the region close to carbon neutral in 2018. Similarly, we find a positive annual NEE anomaly for the northern region of Europe of 0.02 ± 0.02 Pg C yr-1 compared the 10-year mean of -0.04 ± 0.05 Pg C yr-1. In both regions, this was largely owing to a reduction in the summer CO2 uptake. The positive NEE anomalies coincided spatially and temporally with negative anomalies in soil water. These anomalies were exceptional for the 10-year period of our study. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

    Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrological models
    Rakovec, O. ; Hill, M.C. ; Clark, M.P. ; Weerts, A.H. ; Teuling, A.J. ; Uijlenhoet, R. - \ 2014
    Water Resources Research 50 (2014)1. - ISSN 0043-1397 - p. 409 - 426.
    measuring uncertainty importance - coupled reaction systems - groundwater-flow system - net ecosystem exchange - parameter-estimation - information-content - rate coefficients - climate-change - land model - indexes
    1] This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.
    Assessing the spatial variability in peak season CO2exchange characteristics across the Arctic tundra using a light response curve parameterization
    Mbufong, H.N. ; Lund, M. ; Aurela, M. ; Molen, M.K. van der - \ 2014
    Biogeosciences 11 (2014)17. - ISSN 1726-4170 - p. 4897 - 4912.
    carbon-dioxide exchange - net ecosystem exchange - photosynthetically active radiation - growing-season - thermal-acclimation - vascular plants - tussock tundra - climate-change - energy flux - alaska
    This paper aims to assess the spatial variability in the response of CO2exchange to irradiance across the Arctic tundra during peak season using light response curve (LRC) parameters. This investigation allows us to better understand the future response of Arctic tundra under climatic change. Peak season data were collected during different years (between 1998 and 2010) using the micrometeorological eddy covariance technique from 12 circumpolar Arctic tundra sites, in the range of 64-74° N. The LRCs were generated for 14 days with peak net ecosystem exchange (NEE) using an NEE-irradiance model. Parameters from LRCs represent site-specific traits and characteristics describing the following: (a) NEE at light saturation (Fcsat), (b) dark respiration (Rd), (c) light use efficiency (a), (d) NEE when light is at 1000 µmol m-2s-1(Fc1000), (e) potential photosynthesis at light saturation (Psat) and (f) the light compensation point (LCP). Parameterization of LRCs was successful in predicting CO2flux dynamics across the Arctic tundra. We did not find any trends in LRC parameters across the whole Arctic tundra but there were indications for temperature and latitudinal differences within sub-regions like Russia and Greenland. Together, leaf area index (LAI) and July temperature had a high explanatory power of the variance in assimilation parameters (Fcsat, Fc1000and Psat, thus illustrating the potential for upscaling CO2exchange for the whole Arctic tundra. Dark respiration was more variable and less correlated to environmental drivers than were assimilation parameters. This indicates the inherent need to include other parameters such as nutrient availability, substrate quantity and quality in flux monitoring activities.
    Enhancement of crop photosynthesis by diffuse light: quantifying the contributing factors
    Li, T. ; Heuvelink, E. ; Dueck, T.A. ; Janse, J. ; Gort, G. ; Marcelis, L.F.M. - \ 2014
    Annals of Botany 114 (2014)1. - ISSN 0305-7364 - p. 145 - 156.
    modeling canopy photosynthesis - net ecosystem exchange - structural plant-model - chlorophyll fluorescence - deciduous forest - global radiation - direct component - solar-radiation - leaf-area - leaves
    Plants use diffuse light more efficiently than direct light. However, experimental comparisons between diffuse and direct light have been obscured by co-occurring differences in environmental conditions (e.g. light intensity). This study aims to analyse the factors that contribute to an increase in crop photosynthesis in diffuse light and to quantify their relative contribution under different levels of diffuseness at similar light intensities. The hypothesis is that the enhancement of crop photosynthesis in diffuse light results not only from the direct effects of more uniform vertical and horizontal light distribution in the crop canopy, but also from crop physiological and morphological acclimation. Tomato (Solanum lycopersicum) crops were grown in three greenhouse compartments that were covered by glass with different degrees of light diffuseness (0, 45 and 71 % of the direct light being converted into diffuse light) while maintaining similar light transmission. Measurements of horizontal and vertical photosynthetic photon flux density (PPFD) distribution in the crop, leaf photosynthesis light response curves and leaf area index (LAI) were used to quantify each factor's contribution to an increase in crop photosynthesis in diffuse light. In addition, leaf temperature, photoinhibition, and leaf biochemical and anatomical properties were studied. The highest degree of light diffuseness (71 %) increased the calculated crop photosynthesis by 7 center dot 2 %. This effect was mainly attributed to a more uniform horizontal (33 % of the total effect) and vertical PPFD distribution (21 %) in the crop. In addition, plants acclimated to the high level of diffuseness by gaining a higher photosynthetic capacity of leaves in the middle of the crop and a higher LAI, which contributed 23 and 13 %, respectively, to the total increase in crop photosynthesis in diffuse light. Moreover, diffuse light resulted in lower leaf temperatures and less photoinhibition at the top of the canopy when global irradiance was high. Diffuse light enhanced crop photosynthesis. A more uniform horizontal PPFD distribution played the most important role in this enhancement, and a more uniform vertical PPFD distribution and higher leaf photosynthetic capacity contributed more to the enhancement of crop photosynthesis than did higher values of LAI.
    Data-based perfect-deficit approach to understanding climate extremes and forest carbon assimilation capacity
    Wei, S. ; Yi, C. ; Hendrey, G. ; Eaton, T. ; Rustic, G. ; Wang, S. ; Liu, H. ; Krakauer, N.Y. ; Wang, W. ; Desai, A.R. ; Moors, E.J. - \ 2014
    Environmental Research Letters 9 (2014). - ISSN 1748-9326
    net ecosystem exchange - drought - respiration - algorithm - heat - reduction - feedbacks - model
    Several lines of evidence suggest that the warming climate plays a vital role in driving certain types of extreme weather. The impact of warming and of extreme weather on forest carbon assimilation capacity is poorly known. Filling this knowledge gap is critical towards understanding the amount of carbon that forests can hold. Here, we used a perfect-deficit approach to identify forest canopy photosynthetic capacity (CPC) deficits and analyze how they correlate to climate extremes, based on observational data measured by the eddy covariance method at 27 forest sites over 146 site-years. We found that droughts severely affect the carbon assimilation capacities of evergreen broadleaf forest (EBF) and deciduous broadleaf forest. The carbon assimilation capacities of Mediterranean forests were highly sensitive to climate extremes, while marine forest climates tended to be insensitive to climate extremes. Our estimates suggest an average global reduction of forest CPC due to unfavorable climate extremes of 6.3 Pg C (~5.2% of global gross primary production) per growing season over 2001–2010, with EBFs contributing 52% of the total reduction.
    Remote sensing of annual terrestrial gross primary productivity from MODIS: an assessment using the FLUXNET La Thuile data set
    Verma, M. ; Friedl, M.A. ; Richardson, A.D. ; Kiely, G. ; Cescatti, A. ; Law, B.E. ; Wohlfahrt, G. ; Gielen, G. ; Roupsard, O. ; Moors, E.J. - \ 2014
    Biogeosciences 11 (2014). - ISSN 1726-4170 - p. 2185 - 2200.
    net ecosystem exchange - carbon-dioxide exchange - use efficiency model - forests green-up - rain-fed maize - interannual variability - vegetation index - surface temperature - climatic controls - deciduous forest
    Gross primary productivity (GPP) is the largest and most variable component of the global terrestrial carbon cycle. Repeatable and accurate monitoring of terrestrial GPP is therefore critical for quantifying dynamics in regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is widely used to monitor and model spatiotemporal variability in ecosystem properties and processes that affect terrestrial GPP. We used data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and FLUXNET to assess how well four metrics derived from remotely sensed vegetation indices (hereafter referred to as proxies) and six remote sensing-based models capture spatial and temporal variations in annual GPP. Specifically, we used the FLUXNET La Thuile data set, which includes several times more sites (144) and site years (422) than previous studies have used. Our results show that remotely sensed proxies and modeled GPP are able to capture significant spatial variation in mean annual GPP in every biome except croplands, but that the percentage of explained variance differed substantially across biomes (10–80%). The ability of remotely sensed proxies and models to explain interannual variability in GPP was even more limited. Remotely sensed proxies explained 40–60% of interannual variance in annual GPP in moisture-limited biomes, including grasslands and shrublands. However, none of the models or remotely sensed proxies explained statistically significant amounts of interannual variation in GPP in croplands, evergreen needleleaf forests, or deciduous broadleaf forests. Robust and repeatable characterization of spatiotemporal variability in carbon budgets is critically important and the carbon cycle science community is increasingly relying on remotely sensing data. Our analyses highlight the power of remote sensing-based models, but also provide bounds on the uncertainties associated with these models. Uncertainty in flux tower GPP, and difference between the footprints of MODIS pixels and flux tower measurements are acknowledged as unresolved challenges.
    What drives the seasonality of photosynthesis across the Amazon basin? A cross-site analysis of eddy flux tower measurements from the Brazil flux network
    Restrepo-Coupe, N. ; Rocha, H.R. da; Hutyra, L.R. ; Araujo, A.C. de; Borma, L.S. ; Christoffersen, B. ; Cabral, O.M.R. ; Camargo, P.B. de; Cardoso, F.L. ; Lola da Costa, A.C. ; Fitzjarrald, D.R. ; Kruijt, B. - \ 2013
    Agricultural and Forest Meteorology 182-183 (2013). - ISSN 0168-1923 - p. 128 - 144.
    net ecosystem exchange - gross primary production - rain-forest - tropical forest - leaf-area - active radiation - carbon balance - co2 flux - climate - covariance
    We investigated the seasonal patterns of Amazonian forest photosynthetic activity, and the effects thereon of variations in climate and land-use, by integrating data from a network of ground-based eddy flux towers in Brazil established as part of the ‘Large-Scale Biosphere Atmosphere Experiment in Amazonia’ project. We found that degree of water limitation, as indicated by the seasonality of the ratio of sensible to latent heat flux (Bowen ratio) predicts seasonal patterns of photosynthesis. In equatorial Amazonian forests (5° N–5° S), water limitation is absent, and photosynthetic fluxes (or gross ecosystem productivity, GEP) exhibit high or increasing levels of photosynthetic activity as the dry season progresses, likely a consequence of allocation to growth of new leaves. In contrast, forests along the southern flank of the Amazon, pastures converted from forest, and mixed forest-grass savanna, exhibit dry-season declines in GEP, consistent with increasing degrees of water limitation. Although previous work showed tropical ecosystem evapotranspiration (ET) is driven by incoming radiation, GEP observations reported here surprisingly show no or negative relationships with photosynthetically active radiation (PAR). Instead, GEP fluxes largely followed the phenology of canopy photosynthetic capacity (Pc), with only deviations from this primary pattern driven by variations in PAR. Estimates of leaf flush at three non-water limited equatorial forest sites peak in the dry season, in correlation with high dry season light levels. The higher photosynthetic capacity that follows persists into the wet season, driving high GEP that is out of phase with sunlight, explaining the negative observed relationship with sunlight. Overall, these patterns suggest that at sites where water is not limiting, light interacts with adaptive mechanisms to determine photosynthetic capacity indirectly through leaf flush and litterfall seasonality. These mechanisms are poorly represented in ecosystem models, and represent an important challenge to efforts to predict tropical forest responses to climatic variations.
    Natural land carbon dioxide exchanges in the ECMWF integrated forecasting system: Implementation and offline validation
    Boussetta, S. ; Balsamo, G. ; Beljaars, A.C.M. ; Panareda, A.A. ; Calvet, J.C. ; Jacobs, C.M.J. ; Hurk, B.J.J.M. van den; Viterbo, P. ; Lafont, S. ; Dutra, E. - \ 2013
    Journal of Geophysical Research: Atmospheres 118 (2013)12. - ISSN 2169-897X - p. 5923 - 5946.
    global vegetation model - data assimilation system - net ecosystem exchange - era-interim reanalysis - isba-a-gs - interannual variability - co2 exchange - stomatal conductance - southwestern france - soil respiration
    The European Centre for Medium-Range Weather Forecasts land surface model has been extended to include a carbon dioxide module. This relates photosynthesis to radiation, atmospheric carbon dioxide (CO2) concentration, soil moisture, and temperature. Furthermore, it has the option of deriving a canopy resistance from photosynthesis and providing it as a stomatal control to the transpiration formulation. Ecosystem respiration is based on empirical relations dependent on temperature, soil moisture, snow depth, and land use. The CO2 model is designed for the numerical weather prediction (NWP) environment where it benefits from good quality meteorological input (i.e., radiation, temperature, and soil moisture). This paper describes the CO2 model formulation and the way it is optimized making use of off-line simulations for a full year of tower observations at 34 sites. The model is then evaluated against the same observations for a different year. A correlation coefficient of 0.65 is obtained between model simulations and observations based on 10 day averaged CO2 fluxes. For sensible and latent heat fluxes there is a correlation coefficient of 0.80. To study the impact on atmospheric CO2, coupled integrations are performed for the 2003 to 2008 period. The global atmospheric growth is well reproduced. The simulated interannual variability is shown to reproduce the observationally based estimates with a correlation coefficient of 0.70. The main conclusions are (i) the simple carbon dioxide model is highly suitable for the numerical weather prediction environment where environmental factors are controlled by data assimilation, (ii) the use of a carbon dioxide model for stomatal control has a positive impact on evapotranspiration, and (iii) even using a climatological leaf area index, the interannual variability of the global atmospheric CO2 budget is well reproduced due to the interannual variability in the meteorological forcing (i.e., radiation, precipitation, temperature, humidity, and soil moisture) despite the simplified or missing processes. This highlights the importance of meteorological forcing but also cautions the use of such a simple model for process attribution.
    The European land and inland water CO2, CO, CH4 and N2O balance between 2001 and 2005
    Luyssaert, S. ; Abril, G. ; Andres, R. ; Bastviken, D. ; Bellassen, V. ; Bergamaschi, P. ; Bousquet, P. ; Chevallier, F. ; Ciais, P. ; Corazza, M. ; Dechow, R. ; Erb, K.H. ; Etiope, G. ; Fortems-Cheiney, A. ; Grassi, G. ; Hartmann, J. ; Jung, M. ; Lathiere, J. ; Lohila, A. ; Mayorga, E. ; Moosdorf, N. ; Njakou, D.S. ; Otto, J. ; Papale, D. ; Peters, W. ; Peylin, P. ; Raymond, P. ; Rodenbeck, C. ; Saarnio, S. ; Schulze, E.D. ; Szopa, S. ; Thompson, R. ; Verkerk, P.J. ; Vuichard, N. ; Wang, R. ; Wattenbach, M. ; Zaehle, S. - \ 2012
    Biogeosciences 9 (2012)8. - ISSN 1726-4170 - p. 3357 - 3380.
    north-atlantic oscillation - net ecosystem exchange - organic-carbon changes - atmospheric co2 - climate-change - nitrous-oxide - terrestrial biosphere - dioxide - fluxes - emissions
    Globally, terrestrial ecosystems have absorbed about 30% of anthropogenic greenhouse gas emissions over the period 2000-2007 and inter-hemispheric gradients indicate that a significant fraction of terrestrial carbon sequestration must be north of the Equator. We present a compilation of the CO2, CO, CH4 and N2O balances of Europe following a dual constraint approach in which (1) a land-based balance derived mainly from ecosystem carbon inventories and (2) a land-based balance derived from flux measurements are compared to (3) the atmospheric data-based balance derived from inversions constrained by measurements of atmospheric GHG (greenhouse gas) concentrations. Good agreement between the GHG balances based on fluxes (1294 +/- 545 Tg C in CO2-eq yr(-1)), inventories (1299 +/- 200 Tg C in CO2-eq yr(-1)) and inversions (1210 +/- 405 Tg C in CO2-eq yr(-1)) increases our confidence that the processes underlying the European GHG budget are well understood and reasonably sampled. However, the uncertainty remains large and largely lacks formal estimates. Given that European net land to atmosphere exchanges are determined by a few dominant fluxes, the uncertainty of these key components needs to be formally estimated before efforts could be made to reduce the overall uncertainty. The net land-to-atmosphere flux is a net source for CO2, CO, CH4 and N2O, because the anthropogenic emissions by far exceed the biogenic sink strength. The dual-constraint approach confirmed that the European biogenic sink removes as much as 205 +/- 72 Tg C yr(-1) from fossil fuel burning from the atmosphere. However, This C is being sequestered in both terrestrial and inland aquatic ecosystems. If the C-cost for ecosystem management is taken into account, the net uptake of ecosystems is estimated to decrease by 45% but still indicates substantial C-sequestration. However, when the balance is extended from CO2 towards the main GHGs, C-uptake by terrestrial and aquatic ecosystems is offset by emissions of non-CO2 GHGs. As such, the European ecosystems are unlikely to contribute to mitigating the effects of climate change.
    An estimate of the terrestrial carbon budget of Russia using inventory based, eddy covariance and inversion methods
    Dolman, A.J. ; Shvidenko, A. ; Schepaschenko, D. ; Ciais, P. ; Tchebakova, N. ; Chen, T. ; Molen, M.K. van der; Belelli Marchesini, L. ; Maximov, T.C. ; Maksyutov, S. ; Schulze, E.D. - \ 2012
    Biogeosciences 9 (2012). - ISSN 1726-4170 - p. 5323 - 5340.
    global vegetation models - net ecosystem exchange - land-use change - climate-change - forest ecosystems - permafrost carbon - boreal ecosystems - co2 sources - balance - siberia
    We determine the net land to atmosphere flux of carbon in Russia, including Ukraine, Belarus and Kazakhstan, using inventory-based, eddy covariance, and inversion methods. Our high boundary estimate is -342 Tg C yr-1 from the eddy covariance method, and this is close to the upper bounds of the inventory-based Land Ecosystem Assessment and inverse models estimates. A lower boundary estimate is provided at -1350 Tg C yr-1 from the inversion models. The average of the three methods is -613.5 Tg C yr-1. The methane emission is estimated separately at 41.4 Tg C yr-1. These three methods agree well within their respective error bounds. There is thus good consistency between bottom-up and top-down methods. The forests of Russia primarily cause the net atmosphere to land flux (-692 Tg C yr-1 from the LEA. It remains however remarkable that the three methods provide such close estimates (-615, -662, -554 Tg C yr–1) for net biome production (NBP), given the inherent uncertainties in all of the approaches. The lack of recent forest inventories, the few eddy covariance sites and associated uncertainty with upscaling and undersampling of concentrations for the inversions are among the prime causes of the uncertainty. The dynamic global vegetation models (DGVMs) suggest a much lower uptake at -91 Tg C yr-1, and we argue that this is caused by a high estimate of heterotrophic respiration compared to other methods.
    State-dependent errors in a land surface model across biomes inferred from eddy covariance observations on multiple timescales
    Wang, T. ; Brender, P. ; Ciais, P. ; Piao, S. ; Mahecha, M.D. ; Chevallier, F. ; Reichstein, M. ; Ottle, C. ; Maignan, F. ; Arain, A. ; Bohrer, G. ; Cescatti, A. ; Kiely, G. ; Law, B.E. ; Lutz, M. ; Montagnani, L. ; Moors, E.J. - \ 2012
    Ecological Modelling 246 (2012). - ISSN 0304-3800 - p. 11 - 25.
    net ecosystem exchange - artificial neural-networks - carbon-dioxide exchange - atmosphere co2 exchange - energy-balance closure - northern temperate grassland - boreal forest stands - water-vapor exchange - interannual variability - soil respiration
    Characterization of state-dependent model biases in land surface models can highlight model deficiencies, and provide new insights into model development. In this study, artificial neural networks (ANNs) are used to estimate the state-dependent biases of a land surface model (ORCHIDEE: ORganising Carbon and Hydrology in Dynamic EcosystEms). To characterize state-dependent biases in ORCHIDEE, we use multi-year flux measurements made at 125 eddy covariance sites that cover 7 different plant functional types (PFTs) and 5 climate groups. We determine whether the state-dependent model biases in five flux variables (H: sensible heat, LE: latent heat, NEE: net ecosystem exchange, GPP: gross primary productivity and Reco: ecosystem respiration) are transferable within and between three different timescales (diurnal, seasonal–annual and interannual), and between sites (categorized by PFTs and climate groups). For each flux variable at each site, the spectral decomposition method (singular system analysis) was used to reconstruct time series on the three different timescales. At the site level, we found that the share of state-dependent model biases (hereafter called “error transferability”) is larger for seasonal–annual and interannual timescales than for the diurnal timescale, but little error transferability was found between timescales in all flux variables. Thus, performing model evaluations at multiple timescales is essential for diagnostics and future development. For all PFTs, climate groups and timescale components, the state-dependent model biases are found to be transferable between sites within the same PFT and climate group, suggesting that specific model developments and improvements based on specific eddy covariance sites can be used to enhance the model performance at other sites within the same PFT-climate group. This also supports the legitimacy of upscaling from the ecosystem scale of eddy covariance sites to the regional scale based on the similarity of PFT and climate group. However, the transferability of state-dependent model biases between PFTs or climate groups is not always found on the seasonal–annual and interannual timescales, which is contrary to transferability found on the diurnal timescale and the original time series.
    On the choice of the driving temperature for eddy-covariance carbon dioxide flux partitioning
    Lasslop, G. ; Migliavacca, M. ; Bohrer, G. ; Reichstein, M. ; Bahn, M. ; Ibrom, A. ; Jacobs, C.M.J. ; Kolari, P. ; Papale, D. ; Vesala, T. ; Wohlfart, G. ; Cescatti, A. - \ 2012
    Biogeosciences 9 (2012)12. - ISSN 1726-4170 - p. 5243 - 5259.
    net ecosystem exchange - scots pine forest - water-vapor exchange - danish beech forest - soil respiration - co2 exchange - deciduous forest - global convergence - seasonal-variation - environmental controls
    Networks that merge and harmonise eddy-covariance measurements from many different parts of the world have become an important observational resource for ecosystem science. Empirical algorithms have been developed which combine direct observations of the net ecosystem exchange of carbon dioxide with simple empirical models to disentangle photosynthetic (GPP) and respiratory fluxes (R-eco). The increasing use of these estimates for the analysis of climate sensitivities, model evaluation and calibration demands a thorough understanding of assumptions in the analysis process and the resulting uncertainties of the partitioned fluxes. The semi-empirical models used in flux partitioning algorithms require temperature observations as input, but as respiration takes place in many parts of an ecosystem, it is unclear which temperature input - air, surface, bole, or soil at a specific depth - should be used. This choice is a source of uncertainty and potential biases. In this study, we analysed the correlation between different temperature observations and nighttime NEE (which equals nighttime respiration) across FLUXNET sites to understand the potential of the different temperature observations as input for the flux partitioning model. We found that the differences in the correlation between different temperature data streams and nighttime NEE are small and depend on the selection of sites. We investigated the effects of the choice of the temperature data by running two flux partitioning algorithms with air and soil temperature. We found the time lag (phase shift) between air and soil temperatures explains the differences in the GPP and Reco estimates when using either air or soil temperatures for flux partitioning. The impact of the source of temperature data on other derived ecosystem parameters was estimated, and the strongest impact was found for the temperature sensitivity. Overall, this study suggests that the choice between soil or air temperature must be made on site-by-site basis by analysing the correlation between temperature and nighttime NEE. We recommend using an ensemble of estimates based on different temperature observations to account for the uncertainty due to the choice of temperature and to assure the robustness of the temporal patterns of the derived variables.
    Evapotranspiration of deforested areas in central and southwestern Amazonia
    Randow, R.C.S. von; Randow, C. ; Hutjes, R.W.A. ; Tomasella, J. ; Kruijt, B. - \ 2012
    Theoretical and Applied Climatology 109 (2012)1-2. - ISSN 0177-798X - p. 205 - 220.
    large-aperture scintillometer - net ecosystem exchange - tropical deforestation - surface conductance - sensible heat - water-vapor - rain-forest - long-term - pasture - fluxes
    Considering the high rates of evapotranspiration of Amazonian forests, understanding the impacts of deforestation on water loss rates is important for assessing those impacts on a regional and global scale. This paper quantifies evapotranspiration rates in two different pasture sites in Amazonia and evaluates the differences between the sites. In both places, measured evapotranspiration varies seasonally, decreasing during the dry season. The decrease is higher at the southwestern Amazonia site, while at the central Amazonia site, the decrease is less pronounced. During the dry season, average values of evapotranspiration are around 2.2¿±¿0.6 mm day-1 in central Amazonia and 2.4¿±¿0.6 mm day-1 in southwestern Amazonia, while during the wet season, those values are 2.1¿±¿0.6 mm day-1 in central Amazonia and 3.5¿±¿0.8 mm day-1 in southwestern Amazonia. On an annual basis, the pasture in southwestern Amazonia has higher evapotranspiration than in central Amazonia. We conclude that the main reason for this difference is the lower available energy in the wet season at the central Amazonian site, combined with a lower leaf area index at this site during the whole year. Still, the evapotranspiration is significantly controlled by the vegetation, which is well coupled with the local moisture conditions in the dry season
    Importance of crop varieties and management practices: evaluation of a process-based model for simulating CO2 and H2O fluxes at five European maize (Zea mays L.) sites
    Li, L. ; Vuichard, N. ; Viovy, N. ; Ciais, P. ; Wang, T. ; Ceschia, E. ; Jans, W.W.P. ; Wattenbach, M. ; Beziat, P. ; Gruenwald, T. ; Lehuger, S. ; Bernhofer, C. - \ 2011
    Biogeosciences 8 (2011)6. - ISSN 1726-4170 - p. 1721 - 1736.
    carbon-dioxide exchange - eddy covariance technique - net ecosystem exchange - rain-fed maize - primary productivity - agricultural soils - nitrogen balances - generic model - water-vapor - wheat
    This paper is a modelling study of crop management impacts on carbon and water fluxes at a range of European sites. The model is a crop growth model (STICS) coupled with a process-based land surface model (ORCHIDEE). The data are online eddy-covariance observations of CO2 and H2O fluxes at five European maize cultivation sites. The results show that the ORCHIDEE-STICS model explains up to 75% of the observed daily net CO2 ecosystem exchange (NEE) variance, and up to 79% of the latent heat flux (LE) variance at five sites. The model is better able to reproduce gross primary production (GPP) variations than terrestrial ecosystem respiration (TER) variations. We conclude that structural deficiencies in the model parameterizations of leaf area index (LAI) and TER are the main sources of error in simulating CO2 and H2O fluxes. A number of sensitivity tests, with variable crop variety, nitrogen fertilization, irrigation, and planting date, indicate that any of these management factors is able to change NEE by more than 15%, but that the response of NEE to management parameters is highly site-dependent. Changes in management parameters are found to impact not only the daily values of NEE and LE, but also the cumulative yearly values. In addition, LE is shown to be less sensitive to management parameters than NEE. Multi-site model evaluations, coupled with sensitivity analysis to management parameters, thus provide important information about model errors, which helps to improve the simulation of CO2 and H2O fluxes across European croplands.
    Seasonal variation of photosynthetic model parameters and leaf area index from global Fluxnet eddy covariance data
    Groenendijk, M. ; Dolman, A.J. ; Ammann, C. ; Arneth, A. ; Cescatti, A. ; Molen, M.K. van der; Moors, E.J. - \ 2011
    Journal of Geophysical Research: Biogeosciences 116 (2011). - ISSN 2169-8953 - 18 p.
    net ecosystem exchange - carbon-dioxide exchange - water-vapor exchange - sub-alpine forest - deciduous forest - co2 exchange - pine forest - terrestrial biosphere - vegetation model - ponderosa pine
    Global vegetation models require the photosynthetic parameters, maximum carboxylation capacity (Vcm), and quantum yield (a) to parameterize their plant functional types (PFTs). The purpose of this work is to determine how much the scaling of the parameters from leaf to ecosystem level through a seasonally varying leaf area index (LAI) explains the parameter variation within and between PFTs. Using Fluxnet data, we simulate a seasonally variable LAIF for a large range of sites, comparable to the LAIM derived from MODIS. There are discrepancies when LAIF reach zero levels and LAIM still provides a small positive value. We find that temperature is the most common constraint for LAIF in 55% of the simulations, while global radiation and vapor pressure deficit are the key constraints for 18% and 27% of the simulations, respectively, while large differences in this forcing still exist when looking at specific PFTs. Despite these differences, the annual photosynthesis simulations are comparable when using LAIF or LAIM (r2 = 0.89). We investigated further the seasonal variation of ecosystem-scale parameters derived with LAIF. Vcm has the largest seasonal variation. This holds for all vegetation types and climates. The parameter a is less variable. By including ecosystem-scale parameter seasonality we can explain a considerable part of the ecosystem-scale parameter variation between PFTs. The remaining unexplained leaf-scale PFT variation still needs further work, including elucidating the precise role of leaf and soil level nitrogen
    Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations
    Jung, M. ; Reichstein, M. ; Cescatti, A. ; Richardson, A.D. ; Arain, A. ; Arneth, A. ; Bernhofer, C. ; Bonal, D. ; Chen, J. ; Gianelle, D. ; Gobron, N. ; Lasslop, G. ; Moors, E.J. - \ 2011
    Journal of Geophysical Research: Biogeosciences 116 (2011)G3. - ISSN 2169-8953 - 16 p.
    net ecosystem exchange - energy-balance closure - co2 flux - primary productivity - vegetation model - climate - uncertainty - respiration - sensitivity - dynamics
    We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5° × 0.5° spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 ± 7 J × 1018 yr-1), H (164 ± 15 J × 1018 yr-1), and GPP (119 ± 6 Pg C yr-1) were similar to independent estimates. Our global TER estimate (96 ± 6 Pg C yr-1) was likely underestimated by 5–10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere
    Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data
    Groenendijk, M. ; Dolman, A.J. ; Molen, M.K. van der; Leuning, R. ; Arneth, A. ; Delpierre, N. ; Gash, J.H.C. ; Lindroth, A. ; Richardson, A.D. ; Verbeeck, H. ; Wohlfahrt, G. - \ 2011
    Agricultural and Forest Meteorology 151 (2011)1. - ISSN 0168-1923 - p. 22 - 38.
    net ecosystem exchange - carbon-dioxide exchange - atmosphere-biosphere system - biochemically based model - tower-based measurements - water-vapor exchange - deciduous forest - co2 exchange - pine forest - interannual variability
    The vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs). PFTs are used in global land-surface models to provide parameter values for every model grid cell. With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set. We compare the model parameters within and between PFTs and statistically group the sites. Fluxnet data is used to validate the photosynthesis model parameter variation within a PFT classification. Our major result is that model parameters appear more variable than assumed in PFTs. Simulated fluxes are of higher quality when model parameters of individual sites or site years are used. A simplification with less variation in model parameters results in poorer simulations. This indicates that a PFT classification introduces uncertainty in the variation of the photosynthesis and transpiration fluxes. Statistically derived groups of sites with comparable model parameters do not share common vegetation types or climates. A simple PFT classification does not reflect the real photosynthesis and transpiration variation. Although site year parameters give the best predictions, the parameters are generally too specific to be used in a global study. The site year parameters can be further used to explore the possibilities of alternative classification schemes
    Carbon exchange of a maize (Zea mays L.) crop: Influence of phenology
    Jans, W.W.P. ; Jacobs, C.M.J. ; Kruijt, B. ; Elbers, J.A. ; Barendse, S.C.A. ; Moors, E.J. - \ 2010
    Agriculture, Ecosystems and Environment 139 (2010)3. - ISSN 0167-8809 - p. 316 - 324.
    netto ecosysteem uitwisseling - koolstofvastlegging - fenologie - rogge - maïs - zea mays - organische meststoffen - nederland - net ecosystem exchange - carbon sequestration - phenology - rye - maize - zea mays - organic fertilizers - netherlands - gross primary production - rain-fed maize - ecosystem respiration - dioxide exchange - eddy covariance - soil respiration - growing-season - use efficiency - united-states - phase-change
    A study was carried out to quantify the carbon budget of a maize (Zea mays L.) crop followed by a rye cover crop in the Netherlands, and to determine the importance of the phenological phases and the fallow phase when modelling the carbon budget. Measurements were made of carbon fluxes, soil respiration, biomass and Plant Area Index (PAI). On the basis of PAI the annual cycle was subdivided into 5 phases: juvenile-vegetative, adult-vegetative, reproductive, senescence and fallow. To model the annual carbon budget, it should be sufficient to assess the light response in the juvenile-vegetative phase, the growing season and the fallow phase, combined with the length of these phases and the PAI development. We conclude that emphasis should be put on determining off-season fluxes while the growing season can be estimated from radiation only. During the cultivation period (from sowing to harvest) 5.97 tC ha−1 was sequestered by the maize crop. The amount of carbon exported from the field was 7.5 tC ha−1, and the estimated amount of carbon imported by organic fertilizer was 0.51 tC ha−1, resulting in a carbon loss of 1.02 tC ha−1 from the soil. The fallow phase, with a rye cover crop at the field, decreased the amount of carbon fixed in the cultivation period by 2.65 tC ha−1 (44% reduction). To enable determination of the carbon sequestration or emission of croplands, farmers should be required to analyze, apart from the nitrogen content, also the carbon content of organic fertilizers.
    A study was carried out to quantify the carbon budget of a maize (Zea mays L) crop followed by a rye cover crop in the Netherlands, and to determine the importance of the phenological phases and the fallow phase when modelling the carbon budget. Measurements were made of carbon fluxes, soil respiration, biomass and Plant Area Index (PAI). On the basis of PAI the annual cycle was subdivided into 5 phases: juvenile-vegetative, adult-vegetative, reproductive, senescence and fallow. To model the annual carbon budget, it should be sufficient to assess the light response in the juvenile-vegetative phase, the growing season and the fallow phase, combined with the length of these phases and the PAI development. We conclude that emphasis should be put on determining off-season fluxes while the growing season can be estimated from radiation only. During the cultivation period (from sowing to harvest) 5.97 tC ha(-1) was sequestered by the maize crop. The amount of carbon exported from the field was 7.5 tC ha(-1), and the estimated amount of carbon imported by organic fertilizer was 0.51 tC ha(-1), resulting in a carbon loss of 1.02 tC ha(-1) from the soil. The fallow phase, with a rye cover crop at the field, decreased the amount of carbon fixed in the cultivation period by 2.65 tC ha(-1) (44% reduction). To enable determination of the carbon sequestration or emission of croplands, farmers should be required to analyze, apart from the nitrogen content, also the carbon content of organic fertilizers. (C) 2010 Elsevier B.V. All rights reserved.
    Detecting the critical periods that underpin interannual fluctuations in the carbon balance of European forests
    Maire, G. Le; Delpierre, N. ; Ciais, P. ; Reichstein, M. ; Moors, E.J. - \ 2010
    Journal of Geophysical Research: Biogeosciences 115 (2010)115. - ISSN 2169-8953 - 16 p.
    global vegetation model - net ecosystem exchange - young beech forest - boreal forest - deciduous forest - co2 exchange - dioxide exchange - central germany - pine forest - long-term
    The interannual variability of CO2 exchange by forest ecosystems in Europe was analyzed at site and regional scales by identifying critical periods that contributed to interannual flux anomalies. Critical periods were defined as periods in which monthly and annual flux anomalies were correlated. The analysis was first conducted at seven European forest flux tower sites with contrasting species and climatic conditions. Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE), a generic process-based model, represented fairly well most features of the critical period patterns and their climate drivers at the site scale. Simulations at the scale of European forests were performed with ORCHIDEE integrated at a 0.25° spatial resolution. The spatial and temporal distributions of critical periods for canopy photosynthesis, ecosystem respiration, and net ecosystem exchange (NEE) as well as their underlying climate drivers were analyzed. The interannual variability in gross primary productivity (GPP) was explained by critical periods during spring and summer months. In contrast, the interannual variability in total ecosystem respiration (TER) was explained by critical periods occurring throughout the year. A latitudinal contrast between southern and northern Europe was observed in the distributions of critical periods for GPP and TER. The critical periods were positively controlled by temperature in northern Europe and by soil water availability in southern Europe. More importantly, the latitudinal transition between temperature-driven and water-driven critical periods for GPP varied from early spring to late summer. Such a distinct seasonal regime of critical periods was less clearly defined for TER and NEE. Overall, the critical periods associated with NEE variations and their meteorological drivers followed those associated with GPP.
    Variability in carbon exchange of European croplands
    Moors, E.J. ; Jacobs, C.M.J. ; Jans, W.W.P. ; Supit, I. ; Werners, S.E. ; Kutsch, W.L. ; Elbers, J.A. ; Kruijt, B. - \ 2010
    Agriculture, Ecosystems and Environment 139 (2010)3. - ISSN 0167-8809 - p. 325 - 335.
    netto ecosysteem uitwisseling - kooldioxide - emissie - landbouwgrond - gewasproductie - variatie - europa - net ecosystem exchange - carbon dioxide - emission - agricultural land - crop production - variation - europe - agricultural soils - net carbon - sequestration - forests - respiration - ecosystems - fluxes - model
    The estimated net ecosystem exchange (NEE) of CO2 based on measurements at 17 flux sites in Europe for 45 cropping periods showed an average loss of -38 gC m-2 per cropping period. The cropping period is defined as the period after sowing or planting until harvest. The variability taken as the standard deviation of these cropping periods was 251 gC m-2. These numbers do not include lateral inputs such as the carbon content of applied manure, nor the carbon exchange out of the cropping period. Both are expected to have a major effect on the C budget of high energy summer crops such as maize. NEE and gross primary production (GPP) can be estimated by crop net primary production based on inventories of biomass at these sites, independent of species and regions. NEE can also be estimated by the product of photosynthetic capacity and the number of days with the average air temperature >5 °C. Yield measured at these sites or reported at the NUTS2 level dataset of EUROSTAT is a relatively poor predictor of NEE. To investigate the difference in the variability in CO2 emissions of different crops at the same location and to compare this variation with the variation of the same crop at different locations and with the inter-annual variation the measured dataset at the flux sites was extended with simulated data. These simulations show that the variability in carbon exchange is determined by: firstly the choice of crop and the location and to a lesser extent by the yearly differences in climate.
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