An analysis of the dynamic response of stomatal conductance to a reduction in humidity over leaves of Cedrella odorata


  • 1 The SRIV algorithm is particularly appropriate for this kind of analysis, as it is based on a special ‘instrumental variable’ technique, which includes adaptive prefiltering of the IO data. This ensures that the identification and estimation analysis is very robust to noise on the experimental data, and works particularly well if the input stimuli are step (or impulsive) in form, as in the present study.

Correspondence: A. J.Jarvis. E-mail:


Single leaves of 3-month-old Cedrella odorata seedlings were exposed to a step reduction in the ambient dew point. The resultant time series of dynamic variations in leaf surface water vapour concentration, leaf surface water vapour concentration gradient, transpiration rate and stomatal conductance to water vapour, are analysed using the data-based mechanistic (DBM) modelling methodology of Young (e.g. Young & Lees 1992; Minchin et al. 1996 ). It is shown that the identified second-order, dynamic model between transpiration rate (as the input) and stomatal conductance (as the output) provides an appropriate, physiologically meaningful, description of the system. In particular, the dynamic relationship between these two variables is remarkably linear and can be resolved in terms of two parallel, first-order, subsystems; a model which complements the results of Cowan (1977) for cotton. The model is also compared with the recently published simulation model of Haefner, Buckley & Mott (1997).