Model calibration in unstressed conditions

J.-C. Calvet Agricultural and Forest Meteorology 103 2000 229–247 235 Soybean datasets, respectively. For the sake of clarity, only three classes of root-zone soil moisture were rep- resented in Figs. 1 and 2: dry, intermediate, and wet. As the distribution of soil moisture conditions differed from one experiment to the other, the classes’ bound- aries are not the same. While the classical decrease of g ′ s in response to increasing D ′ s is observed for both datasets, marked differences appear in the relative position of dry, intermediate, and wet points. In partic- ular, there is a clear dependence of g ′ s on the soil mois- ture class in Fig. 2 Soybean, while the results from MUREX show a more complex behaviour Fig. 1. These features are analysed in this paper in terms of stomatal response to soil water stress Section 5.

4. Model calibration in unstressed conditions

In order to assess the inter- and intra-specific vari- ability of the parameterisations of stomatal conduc- tance, both A–g s and T s -based Jarvis approaches were applied to the unstressed datasets. In many of the anal- ysed leaf-air exchange measurements, the response of g s to D s is clearly non-linear, and the formulation of the A–g s model is very efficient to simulate the non-linearity, provided appropriate values of g ∗ m and D ∗ max are used Jacobs et al., 1996; Calvet et al., 1998. 4.1. Interspecific variability The unstressed values of g ∗ m and D ∗ max displayed in Tables 2–4, were obtained using an optimisation technique consisting in minimising the RMS error between the simulated and the measured g s , for differ- ent values of D s . The optimal values of g ∗ m and D ∗ max were produced by an iterative, quasi-Newton algo- rithm. The same method was applied to the MUREX micrometeorological data Calvet et al., 1999, after computing estimates of g ′ s and D ′ s at the canopy level from observations of LAI, flux, air humidity and temperature, and surface temperature. The soybean field data of Olioso et al. 1996 were not employed to estimate unstressed parameters since most of the data were acquired during stressed conditions. The unstressed parameters r ∗ smin and α ∗ H of the Jarvis ap- proach were obtained by using the same optimisation procedure, and are also presented in Tables 2–4. Ta- bles 2–4 show that either g ∗ m and D ∗ max or r ∗ smin and α ∗ H , are extremely variable from one species to another. As far as the A–g s approach is concerned, C 4 plants present the highest values of g ∗ m , and woody plants the lowest values, while C 3 herbaceous plants occupy an intermediate position. Fig. 3 presents plots of the natural logarithm of g ∗ m and D ∗ max in unstressed con- ditions. While the pooled 63 studies do not present a particular correlation between lng ∗ m and lnD ∗ max , linear relationships are observed after separating C 3 from C 4 plants, and herbaceous from woody plants. The logarithmic equation lng ∗ m = a − b lnD ∗ max is statistically significant for C 4 plants and C 3 herba- ceous species only see Fig. 1, with values of a as 5.323 and 2.381, respectively, and values of b as 0.8929 and 0.6103, respectively with D ∗ max in g kg − 1 and g ∗ m in mm s − 1 . This result, obtained using the A–g s model, is also valid using the Jarvis approach not shown. Considering the natural logarithm of r ∗ smin − 1 and α ∗ H − 1 , the equation ln1000r ∗ smin = a −b ln1α ∗ H is statistically significant for the pooled C 4 plants and C 3 herbaceous species, with values of a and b as 4.135 and 0.5086, respectively with α ∗ H in g kg − 1 , and r ∗ smin in s m − 1 . 4.2. Intraspecific variability Interestingly, these parameters’ difference may oc- cur within the same plant species, also, suggesting that either the cultivar or the growing conditions may con- tribute to determine g ∗ m and D ∗ max . Table 5 summarises the results obtained for maize, rice, tobacco, bean, and sunflower. From the corresponding growing con- ditions listed in Table 5, the magnitude of D ∗ max seems to be correlated with the size of the pot in which the plant was grown: generally, the lowest value of D ∗ max obtained for a given plant species, corresponds to the smallest pots, that is, the lower potential extension of the roots. Concerning rice, it seems that another effect is at stake since the air-humidity growing conditions themselves may influence g ∗ m on the long term Ta- ble 5: for the same conditions of soil substrate, plants grown under humid air present a higher value of g ∗ m , while D ∗ max does not change.

5. The effect of soil water stress