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We estimated daily use of stored water by Scots pine (Pinus sylvestris L.) trees growing in a temperate climate with the ANAFORE model (ANAlysis of FORest Ecosystems) and compared the simulation results with sap flow measurements. The original model was expanded with a dynamic water flow and storage model that simulates sap flow dynamics in an individual tree. ANAFORE was able to accurately simulate diurnal patterns of measured sap flow under microclimatic conditions that differ from those of the calibration period. Strong relationships were found between stored water use and several tree characteristics (diameter at breast height, sapwood area, leaf area), but not with tree height. Relative to transpiration, stored water use varied over time (between less than 1% and 44% of daily transpiration). On days when transpiration was high, trees were more dependent on stored water, indicating that the contribution of internal water to transpiration is not a constant in the water budget of trees. [ABSTRACT FROM AUTHOR]

Soil CO2 efflux (SR) is the second largest carbon flux on earth. We investigated the driving factors of the seasonal change and short-distance spatial variation in SR in a short-rotation plantation of willow (Salix viminalis Orm). Total annual SR ranged from 723 to 1149 g Cm-2 year-1. Both an exponential and a logistic model were fitted to the data, with soil temperature at a depth of 5 cm as the independent variable. The R² values for individual sampling points ranged from 0.83 to 0.95 and from 0.85 to 0.93 for the exponential and logistic models, respectively, indicating that soil temperature largely determined the seasonal variation in SR. Modeled soil SR at 10°C ranged from 1.22 to 1.95 µmol m-2 s-1, whereas modeled annual Q10 values were between 3.31 and 6.13. These high Q10 values were attributed to the absence of drought during the study in 2005. When the coefficients of the general SR models were replaced by linear dependencies on soil and vegetation- related characteristics, the resulting spatially explicit exponential and logistic SR models explained 85 and 86%, respectively, of the variability within the dataset. The analysis indicated that soil carbon concentration, leaf area index, soil pH and root biomass caused differences in SR at the short distances considered in this study. However, incorporating information on variables considered to account for spatial variability in the model did not result in a higher R² compared with a simple temperature function. When the general SR models were applied to independent datasets from the same plantation, the logistic model provided a better fit than the exponential model when drought occurred. Drought greatly reduced the annual Q10 values of SR. [ABSTRACT FROM AUTHOR]