Continental to global‐scale modeling of the carbon cycle using process‐based models is subject to large uncertainties. These uncertainties originate from the model structure and uncertainty in model ...forcing fields; however, little is known about their relative importance. A thorough understanding and quantification of uncertainties is necessary to correctly interpret carbon cycle simulations and guide further model developments. This study elucidates the effects of different state‐of‐the‐art land cover and meteorological data set options and biosphere models on simulations of gross primary productivity (GPP) over Europe. The analysis is based on (1) three different process‐oriented terrestrial biosphere models (Biome‐BGC, LPJ, and Orchidee) driven with the same input data and one model (Biome‐BGC) driven with (2) two different meteorological data sets (ECMWF and REMO), (3) three different land cover data sets (GLC2000, MODIS, and SYNMAP), and (4) three different spatial resolutions of the land cover (0.25° fractional, 0.25° dominant, and 0.5° dominant). We systematically investigate effects on the magnitude, spatial pattern, and interannual variation of GPP. While changing the land cover map or the spatial resolution has only little effect on the model outcomes, changing the meteorological drivers and especially the model results in substantial differences. Uncertainties of the meteorological forcings affect particularly strongly interannual variations of simulated GPP. By decomposing modeled GPP into their biophysical and ecophysiological components (absorbed photosynthetic active radiation (APAR) and radiation use efficiency (RUE), respectively) we show that differences of interannual GPP variations among models result primarily from differences of simulating RUE. Major discrepancies appear to be related to the feedback through the carbon‐nitrogen interactions in one model (Biome‐BGC) and water stress effects, besides the modeling of croplands. We suggest clarifying the role of nitrogen dynamics in future studies and revisiting currently applied concepts of carbon‐water cycle interactions regarding the representation of canopy conductance and soil processes.
It is not clear whether the changing climate in Europe will be favourable for crop yield in the future. In this study, we quantified the yield gap for the year 2000 and analyzed the sensitivity of ...the rain-fed potential yield of winter wheat to changes in temperature, precipitation, and CO₂ across Europe. The ecosystem model ANTHRO-BGC was used to simulate potential yields; actual winter wheat yield data together with modelled potential yields were used to calculate yield gap. Artificial climate scenarios for the main climate factors used in sensitivity studies were generated according to climate scenarios from the IPCC 4th Assessment Report (AR4). We found that there is currently a large yield gap in Eastern Europe (around 6 t ha⁻¹), whereas in a few developed countries in Western Europe the harvested yield approaches potential yield (around 2 t ha⁻¹). Sensitivity analysis indicates that the rain-fed potential yield could increase by about 14% in Europe, under the assumption that the changes in temperature and precipitation will be the same as those projected for 2050 from AR4, and that CO₂ will increase from 380 to 550 ppm. This increase in projected potential yield is mainly due to fertilization effects caused by increasing atmospheric CO₂ concentrations (15% yield increase), whereas the projected changes in temperature and precipitation will negatively (−1%) affect the rain-fed potential yield in Europe.
We analysed climate change impacts on the growth and natural mortality of forest tree species and forest carbon (C) balance along an elevation gradient extending from the Pannonian lowland to the ...West Carpathian Mountains (Central Europe). Norway sprucePicea abies, European beechFagus sylvatica, and oakQuercussp. were investigated for 2 future time periods: 2021–2050 and 2071–2100. The period 1961–1990 was used as reference. Forest growth simulations were based on the SIBYLA tree growth simulator (an empirical model), and C cycle-related simulations were performed using BIOME-BGC (a process-based biogeochemical model). Growth simulations indicated that climate change will substantially affect the growth of spruce and beech, but not of oak, in Central Europe. Growth of spruce and beech in their upper distribution ranges was projected to improve, while drought-induced production decline was projected at the species' receding edges. Beech was the only species projected to decline critically at lower elevations. C cycle simulations performed for the zone of ecological optima of the 3 tree species indicated that these forests are likely to remain net carbon dioxide sinks in the future, although the magnitude of their sequestration capacity will differ. Increasing nitrogen deposition and atmospheric carbon dioxide concentration were projected to greatly affect the forest C cycle. A multi-model assessment based on SIBYLA and BIOME-BGC simulations performed for the zone of ecological optima suggested that oak production will either remain the same as in the reference period or will increase. Future production of beech seems uncertain and might decline, while spruce production is likely to increase. The results also confirmed the value of multi-model approaches for assessing future forest development under climate change.
Information about the uncertainties associated with eddy covariance measurements of surface-atmosphere CO₂ exchange is needed for data assimilation and inverse analyses to estimate model parameters, ...validation of ecosystem models against flux data, as well as multi-site synthesis activities (e.g., regional to continental integration) and policy decision-making. While model residuals (mismatch between fitted model predictions and measured fluxes) can potentially be analyzed to infer data uncertainties, the resulting uncertainty estimates may be sensitive to the particular model chosen. Here we use 10 site-years of data from the CarboEurope program, and compare the statistical properties of the inferred random flux measurement error calculated first using residuals from five different models, and secondly using paired observations made under similar environmental conditions. Spectral analysis of the model predictions indicated greater persistence (i.e., autocorrelation or “memory”) compared to the measured values. Model residuals exhibited weaker temporal correlation, but were not uncorrelated white noise. Random flux measurement uncertainty, expressed as a standard deviation, was found to vary predictably in relation to the expected magnitude of the flux, in a manner that was nearly identical (for negative, but not positive, fluxes) to that reported previously for forested sites. Uncertainty estimates were generally comparable whether the uncertainty was inferred from model residuals or paired observations, although the latter approach resulted in somewhat smaller estimates. Higher order moments (e.g., skewness and kurtosis) suggested that for fluxes close to zero, the measurement error is commonly skewed and leptokurtic. Skewness could not be evaluated using the paired observation approach, because differencing of paired measurements resulted in a symmetric distribution of the inferred error. Patterns were robust and not especially sensitive to the model used, although more flexible models, which did not impose a particular functional form on relationships between environmental drivers and modeled fluxes, appeared to give the best results. We conclude that evaluation of flux measurement errors from model residuals is a viable alternative to the standard paired observation approach.
Long-term flux measurement sites are often characterized by a heterogeneous terrain, which disagrees with the fundamental theoretical assumptions for eddy-covariance measurements. An evaluation ...procedure to assess the influence of terrain heterogeneity on the data quality has been developed by Gockede et al. (2004), which combines existing quality assessment tools for flux measurements with analytic footprint modeling. In addition to micrometeorological input data, this approach requires information defining the land use structure and the roughness of the surrounding terrain. The aim of this study was to improve the footprint based site evaluation approach by using high-resolution land use maps derived by Landsat ETM+ and ASTER satellite data. The influence of the grid resolution of the maps on the results was examined, and four different roughness length classification schemes were tested. Due to numerical instabilities of the analytic footprint routine, as an additional footprint model a Lagrangian stochastic footprint routine (Rannik et al., 2003) was employed. Application of the approach on two German FLUXNET sites revealed only weak influence of the characteristics of the land use data when the land use structure was homogeneous. For a more heterogeneous site, use of the more detailed land use maps derived by remote sensing methods resulted in distinct differences indicating the potential of remote sensing for improving the flux measurement site evaluation. PUBLICATION ABSTRACT
Net primary productivity (NPP) represents the greatest annual carbon flux from the atmosphere to the biosphere, is an important component of seasonal fluctuations in atmospheric CO2concentrations, ...and is the most critical biotic component of the global carbon cycle. NPP measures products of major economic and social importance, such as crop yield and forest production. Given that global NPP can not be measured directly, model simulations must provide understanding of its global spatial and temporal dynamics. In this study, we used the biogeochemical model BIOME-BGC to simulate global terrestrial NPP and assessed relative importance of climatic controls (temperature, water availability, and radiation) in limiting NPP in the array of climatic combinations found globally. The degree of limitation on NPP by climatic controls was defined by using an empirical membership function. Results showed that temperature or water availability limited NPP over larger land areas (31% and 52%, respectively) than did radiation limitation (5%). Climatic controls appeared to be important in limiting productivity in most vegetation biomes, except for evergreen broadleaf forests. Nevertheless, there were areas of the globe (12%) where none of the climatic factors appeared to limit NPP. Our research has suggested that other environmental controls, such as nutrient availability or biological constraints, should then be considered. The wide distribution of NPP between zero and the upper boundary values in the correlation plots indicated that multivariate environmental balances, not single limiting factors, controlled biospheric productivity.
The viral particles (about 30 nm in diameter) that contain dsRNAs (2.0 and 6.3 kbp) encapsidated by a coat of protein were detected in a mycocin-secreting strain of Cystofilobasidium infirmominiatum ...isolated from plants in an oak forest (Moscow region). The mycocin with a molecular mass above 15 kDa is fungicidal (maximum activity at pH 4.5) and active mainly against some species of the Cystofilobasidiales and Filobasidiales (‘Cryptococcus aerius’ clade). Curing by incubation at elevated temperature resulted in the concomitant loss of dsRNAs and mycocinogenic activity, and cured derivatives became sensitive to the mycocin produced by the parent strain.
Soils represent the largest carbon pool in the terrestrial biosphere, and climate change might affect the main carbon fluxes associated with this pool. These fluxes are the production of aboveground ...litter and root litter, and decomposition of the soil organic matter (SOM) pool by soil microorganisms. Knowledge about the temperature sensitivity of the decomposition of different SOM fractions is crucial in order to understand how climate change might affect carbon storage in soils. In this study, the temperature sensitivity of the turnover times of three different SOM fractions (labile, intermediate, and stabilized) was investigated for 11 forest sites along a temperature gradient. Carbon-14 isotope analyses of the SOM fractions combined with a model provided estimates of their turnover times. The turnover times of the labile SOM fraction were not correlated with mean annual soil temperature. Therefore it was not possible to estimate temperature sensitivity for the labile SOM fraction. Given considerable evidence elsewhere for significant temperature sensitivities of labile SOM, lack of temperature sensitivity here most likely indicates limitations of the applied methodology for the labile SOM fraction. The turnover times of the intermediate and the stabilized SOM fractions were both correlated with mean annual soil temperatures. The temperature sensitivity of the stabilized SOM fraction was at least equal to that of the intermediate SOM fraction and possibly more than twice as high. A correction for confounding effects of soil acidity and clay content on the temperature sensitivities of the intermediate and stabilized SOM fractions was included in the analysis. The results as observed here for the three SOM fractions may have been influenced by (1) modeling assumptions for the estimation of SOM turnover times of leaf and needle longevities, constant annual carbon inputs, and steady-state SOM pools, (2) the occurrence of summer drought at some sites, (3) differences between sites in quality of the SOM fractions, or (4) the relatively small temperature range. Our results suggested that a 1°C increase in temperature could lead to decreases in turnover times of 4-11% and 8-16%, for the intermediate and stabilized SOM fractions, respectively.
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