Data analysis in plant physiology: are we missing the reality?

In plant physiology, data analysis is based on the comparison of mean values. In this perspective, variability around the mean value has no significance per se, but only for estimating statistical significance of the difference between two mean values. Another approach to variability is proposed here, derived from the difference between redundant and deterministic patterns of regulation in their capacity to buffer noise. From this point of view, analysis of variability enables the investigation of the level of redundancy of a regulation pattern, and even allows us to study its modifications. As an example, this method is used to investigate the effect of brassinosteroids (BSs) during vegetative growth in Sorghum bicolor. It is shown that, at physiological concentrations, BSs modulate the network of regulation without affecting the mean value. Thus, it is concluded that the physiological effect of BSs cannot be revealed by comparison of mean values. This example illustrates how a part of the reality (in this case, the most relevant one) is hidden by the classical methods of comparison between mean values. The proposed tools of analysis open new perspectives in understanding plant development and the nonlinear processes involved in its regulation. They also ask for a redefinition of fundamental concepts in physiology, such as growth regulator, optimality, stress and adaptation.