[1] Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, interannual and spatial variability of soil respiration as affected by water availability, temperature, and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g., leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical nonlinear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content, and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and intersite variability of soil respiration with a mean absolute error of 0.82 mmol m À2 s À1. The parameterized model exhibits the following principal properties: (1) At a relative amount of upper-layer soil water of 16% of field capacity, half-maximal soil respiration rates are reached. (2) The apparent temperature sensitivity of soil respiration measured as Q 10 varies between 1 and 5 depending on soil temperature and water content. (3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly timescale, we employed the approach by Raich et al. [2002] that used monthly precipitation and air temperature to globally predict soil respiration (T&P model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the intersite variability, regardless of whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 17, NO. 4, 1104, doi:10.1029/2003GB002035, 2003 15 -1 index. Thus, for a monthly timescale, we developed a simple T&P&LAI model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time step model and explained 50% of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index. Before application at the continental or global scale, this approach should be further tested in boreal, cold-temperate, and tropical biomes as well as for non-woody vegetation.INDEX TERMS: 1615 Global...

[1] We present a two-criteria inverse modeling approach to analyze the effects of seasonal drought on ecosystem gas exchange at three Mediterranean sites. The three sites include two nearly monospecific Quercus ilex L. forests, one on karstic limestone (Puéchabon), the other on fluvial sand with access to groundwater (Castelporziano), and a typical multispecies shrubland on limestone (Arca di Noè). A canopy gas exchange model Process Pixel Net Ecosystem Exchange (PROXEL NEE ), which contains the Farquhar photosynthesis model coupled to stomatal conductance via the Ball-Berry model, was inverted in order to estimate the seasonal time course of canopy parameters from hourly values of ecosystem gross carbon uptake and transpiration. It was shown that an inverse estimation of leaf-level parameters was impossible when optimizing against ecosystem H 2 O or CO 2 fluxes alone (unidentifiable parameters). In contrast, a criterion that constrained the optimization against both H 2 O and CO 2 fluxes yielded stable estimates of leaf-level parameters. Two separate model inversions were implemented to test two alternative hypotheses about the response to drought: a reduction in active leaf area as a result of patchy stomatal closure or a change in photosynthetic capacities. In contrast to a previously tested hypothesis of classical (uniform) stomatal control, both hypotheses were equally able to describe the seasonality of carbon uptake and transpiration on all three sites, with a decline during the drought and recovery after autumn rainfall. Large reductions of up to 80%, in either active leaf area or photosynthetic capacities, were necessary to describe the observed carbon and water fluxes at the end of the drought period. With a threshold-type relationship, soil water content was an excellent predictor of these changes. With the drought-dependent parameter changes included, the canopy model explains 80-90% of the variance of hourly gross CO 2 uptake (root mean squared error (RMSE): 1.1-2.6 mmol m À2 s À1 ) and 70-80% of the variance of hourly transpiration (RMSE: 0.02-0.03 mm h À1 ) at all sites. In addition to drought effects, changes in leaf photosynthetic activity not related to water availability, i.e., high spring activity, were detected through the inverse modeling approach. Moreover, our study exemplifies a kind of multiconstraint inverse modeling that can be profitably used for calibrating ecosystem models that are meant for global applications with ecosystem flux data.

Models and observational strategies of carbon exchange need to take into account synoptic and mesoscale transport for correct interpretation of the relation between surface fluxes and atmospheric concentration gradients.A dequate quantification of the geographical distribution of sources and sinks of C02 is still a major task with considerable implications for both our understanding of the global climate and the possible opportunities to mitigate climate change. Atmospheric measurements of C02 mixing ratios at a number of locations around the globe have helped significantly to quantify the source-sink distribu-AFFILIATIONS: DOLMAN, TOLK, AND

Water-use efficiency (WUE) has been recognized as an important characteristic of vegetation productivity in various natural scientific disciplines for decades, but only recently at the ecosystem level, where different ways exist to characterize water-use efficiency. Hence, the objective of this research was (a) to systematically compare different ways of calculating ecosystem water-use efficiency (WUEe) from eddy-covariance measurements, (b) quantify the diurnal, seasonal and interannual variability of WUEe in relation to meteorological conditions, and (c) analyse between-site variability of WUEe as affected by vegetation type and climatic conditions, across sites in European forest ecosystems. Day-to-day variability of gross primary productivity (GPP) and evapotranspiration (ET) were more strongly coupled than net ecosystem production (NEP) and ET, obviously because NEP also depends on the respiration that is not heavily coupled to water fluxes. However, the slope of daytime NEP versus ET (mNEP) from half-hourly measurements of a single day may also be used as a WUEe-estimate giving very similar results to those of the GPP-ET slope (mGPP), since the diurnal variation is dominated by GPP. Since ET is the sum of transpiration (linked to GPP) and evaporation from wet vegetation and soil surfaces (not linked to GPP) we expected that WUEe is increasing when days after rain are excluded from the analysis. However only very minor changes were found, justifying an analysis of WUEe related to vegetation type. In most of the studied ecosystems the instantaneous WUEGPP was quite sensitive to diurnally varying meteorological conditions and tended to decline from the morning to the afternoon by more than 50% because of increasing vapour pressure deficits (VPD). Seasonally, WUEGPP increased with a rising monthly precipitation sum and rising average monthly temperatures up to a threshold of 11, 14 and 18°C in boreal, temperate and Mediterranean ecosystems, respectively. Across all sites, the highest monthly WUEGPP-values were detected at times of positive anomalies of summer-precipitation. During drought periods with high temperatures, high VPD, little precipitation and low soil water content, the water-use efficiency of gross carbon uptake (WUEGPP) tended to decrease in all forest types because of a stronger decline of GPP compared to ET. However the largest variation of growing season WUEGPP was found between-sites and significantly related to vegetation type: WUEGPP was highest in ecosystems dominated by deciduous trees ranging from 5.0 g CO₂ kg H₂O−1 for temperate broad-leaved deciduous forests (TD), to 4.5 for temperate mixed forests (TM), 3.5 for temperate evergreen conifers (TC), 3.4 for Mediterranean broad-leaved deciduous forests (MD), 3.3 for Mediterranean broad-leaved evergreen forests (Mbeg), 3.1 for Mediterranean evergreen conifers (MC), 2.9 for boreal evergreen conifers (BC) and only 1.2 g CO₂ kg H₂O−1 for a boreal wetland site (BT). Although vegetation type and meteoro...

Aflatoxin (AF) contamination in maize is of worldwide importance. Aspergillus flavus and A. parasiticus are the principal fungi responsible for AF production. Based on the current literature, AFs are not considered a problem in wheat and rice at harvest and no data were found on aspergilliwheat/rice interactions in the field. Data on the effects influencing the development of A. flavus and A. parasiticus on maize and maize kernel at harvest were collected; however data on A. parasiticus and AFB 2 -G 1 -G 2 were not sufficient for further use in predictive modelling. Thus, a model was developed to predict the risk of AFB 1 contamination, due to A. flavus, in maize at harvest and further adapted to wheat and rice as host crops. The Joint Research Centre of the EC provided a database with mean daily temperatures during emergence, flowering and harvesting of maize, wheat and rice. Meteorological data (temperature, relative humidity and rain) obtained from the LARS weather generator, were used as input for the modelling of crop phenology and A. flavus behaviour. The output was designed at a 50 x 50 km scale over the European territory and generated over 100 years, in three different climate scenarios (present and A2 and B2 storylines, or + 2 °C and + 5 °C scenarios, proposed by the Intergovernmental Panel on Climate Change). Predictions showed a reduction in season length and an advance in flowering and harvest dates leading to an enlargement of the crop growing areas towards north EU, mainly for maize and rice, because earlier ripening could occur in these areas. The risk of A. flavus contamination was expected to increase in maize, both in the + 2 °C and + 5 °C scenarios, to be very low in wheat and to be absent in rice. Results were discussed and recommendations were made on data collection and prevention measures on AF risks.