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Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems. [ABSTRACT FROM AUTHOR]

Complex dynamic models of carbon and nitrogen are often used to investigate the consequences of climate change on agricultural production and greenhouse gas emissions from agriculture. These models require high temporal resolution input data regarding the timing of field operations. This paper describes the Timelines model, which predicts the timelines of key field operations across Europe. The evaluation of the model suggests that it is broadly capable of simulating the timing of field operations for a range of arable crops at different locations. Systematic variations in the date of harvesting and in the timing of the first application of N fertiliser to winter crops need to be corrected and the prediction of soil workability and traffcability might enable the prediction of ploughing and applications of solid manure in preparation for spring crops. The data concerning the thermal time thresholds for sowing and harvesting underlying the model should be updated and extended to a wider range of crops. [ABSTRACT FROM AUTHOR]

We use a soil carbon (C) model (RothC), driven by a range of climate models for a range of climate scenarios to examine the impacts of future climate on global soil organic carbon (SOC) stocks. The results suggest an overall global increase in global SOC stocks by 2100 under all scenarios, but with a different extent of increase among the climate model and emissions scenarios. Projected land use changes are also simulated, but have relatively small impacts at the global scale. Whether soils gain or lose SOC depends upon the balance between C inputs and decomposition. Changes in net primary production (NPP) change C inputs to the soil, whilst decomposition usu ally increases under warmer temperatures, but can also be slowed by decreased soil moisture. Underlying the global trend of increasing SOC under future climate is a complex pattern of regional SOC change. SOC losses are projected to occur in northern latitudes where higher SOC decomposition rates due to higher temperatures are not balanced by increased NPP, whereas in tropical regions, NPP increases override losses due to higher SOC decomposition. The spatial heterogeneity in the response of SOC to changing climate shows how delicately balanced the competing gain and loss processes are, with subtle changes in temperature, moisture, soil type and land use, interacting to determine whether SOC increases or decreases in the future. Our results suggest that we should stop asking the general question of whether SOC stocks will increase or decrease under future climate since there is no single answer. Instead, we should focus on improving our prediction of the factors that determine the size and direction of change, and the land management practices that can be implemented to protect and enhance SOC stocks. [ABSTRACT FROM AUTHOR]

Crop varieties and management practices such as planting and harvest dates, irrigation, and fertilization have important effects on the water and carbon fluxes over croplands, and lack or inaccuracy of this information may cause large uncertainties in hydraulic and carbon modeling. Yet the magnitude of uncertainties has not been investigated in detail. This paper provides a comprehensive assessment of the performances of a process-based ecosystem model called ORCHIDEE-STICS (a coupled model between generic ecosystem model ORCHIDEE and the crop growth model STICS), against eddy-covariance observations of CO2 and H2O fluxes at five European maize cultivation sites. The results show that ORCHIDEE-STICS has a good potential to simulate energy, water vapor and carbon dioxide fluxes from maize croplands on a daily basis. The model explains 23-75% of the observed daily net ecosystem exchange (NEE) variance at five sites, and 26-79% of the latent heat flux (LE) variance. Similarly, 34-83% of the variance in observed gross primary productivity (GPP) is accounted for by the model. However, only 3-81% of the variance of observed terrestrial ecosystem respiration (TER) is explained. Therefore, simulating TER is shown to be much more difficult than GPP. We conclude that structural deficiencies of the model in the determination of LAI and TER are the main sources of errors in simulating carbon dioxide and water vapor fluxes. A group of sensitivity analyses, by setting different crop variety, nitrogen fertilization, irrigation, and planting date, indicate that any of these factors is able to cause more than 15% change in simulated NEE although the response of these fluxes to management parameters is site-dependent. Varying management practice in the model is shown to affect not only the daily values of NEE and LE, but also the total seasonal cumulative values, and therefore the annual carbon and water budgets. However, LE is found to be less sensitive to management practices than NEE. Multi-site evaluation of the model and sensitivity analysis with respect to management practices performed in this research provide important insights on the model errors for estimating carbon and water vapor fluxes over European croplands. [ABSTRACT FROM AUTHOR]

Soil organic carbon plays a major role in the global carbon budget, and can act as a source or a sink of atmospheric carbon, whereby it can influence the course of climate change. Changes in soil organic soil stocks (SOCS) are now taken into account in international negotiations regarding climate change. Consequently, developing sampling schemes and models for estimating the spatial distribution of SOCS is a priority. The French soil monitoring network has been established on a 16 km×16 km grid and the first sampling campaign has recently been completed, providing circa 2200 measurements of stocks of soil organic carbon, obtained through an in situ composite sampling, uniformly distributed over the French territory. We calibrated a boosted regression tree model on the observed stocks, modelling SOCS as a function of other variables such as climatic parameters, vegetation net primary productivity, soil properties and land use. The calibrated model was evaluated through cross-validation and eventually used for estimating SOCS for the whole of metropolitan France. Two other models were calibrated on forest and agricultural soils separately, in order to assess more precisely the influence of pedo-climatic variables on soil organic carbon for such soils. The boosted regression tree model showed good predictive ability, and enabled quantification of relationships between SOCS and pedo-climatic variables (plus their in teractions) over the French territory. These relationship strongly depended on the land use, and more specifically differed between forest soils and cultivated soil. The total estimate of SOCS in France was 3.260±0.872 PgC for the first 30 cm. It was compared to another estimate, based on the previously published European soil organic carbon and bulk density maps, of 5.303 PgC. We demonstrate that the present estimate might better represent the actual SOCS distributions of France, and consequently that the previously published approach at the European level greatly overestimates SOCS. [ABSTRACT FROM AUTHOR]

The long-term carbon balance (NBP) of grasslands is estimated by combining scarce multi-year eddy-covariance observations at ecosystem observation sites where information on carbon inputs and harvesting removals is available. Following accounting for carbon leached to rivers, we estimated grasslands to be net carbon sinks of 74±10 g C m-2 yr-1. Uncertainties arise from the small number of sites and the short measurement period. Only 11 sites, out of a total of 20 grassland sites in Europe where eddy covariance systems are installed, were set-up for estimating NBP. These 11 selected sites are representative of intensive management practice and we lack information on disturbance history, such as plowing. This suggests that the grassland NBP estimate is likely biased towards overestimating the sink, compared to the European average. Direct measurements of Net Primary Productivity (NPP) are not possible in grasslands given permanent biomass removal by grazing and mowing, uncertainties in rhizodeposition and production of volatile organic carbon compounds lost to the atmosphere. Therefore, the grassland process-based ecosystem model PASIM was used to estimate the spatial-temporal distribution of NPP, providing a European average value of 750±150 g C across extensively grazed, intensively grazed pastures, and forage production systems. In Europe the NPP of grasslands seems higher than that of croplands and forests. The carbon sequestration efficiency of grasslands, defined as the ratio of NBP to NPP, amounts to 0.09±0.10. Therefore, per unit of carbon input, grasslands sequester 3-4 times more carbon in the soil than forests do, making them a good candidate for managing onsite carbon sinks. When using the 100 yr greenhouse warming potential for CH4 and N2O, their emissions due to management of grasslands together offset roughly 70-80% of the carbon sink. Uncertainties on the European grassland greenhouse gas balance, including CO2, CH4 and N2O fluxes are likely to be reduced in the near future, with data being collected from more sites, and improved up-scaling methods. [ABSTRACT FROM AUTHOR]