Plants possess an enormous phenotypic plasticity and can divert growth substrates and hence growth activity between growing plant modules in a very flexible way, allowing them to react efficiently to fluctuations in environmental parameters. They can increase the root:shoot ratio when light intensity reaching the shoot increases (Walter and Nagel 2006) or when nutrient availability decreases (Scheible et al. 1997; Walter et al. 2003a). The ability of plants to alter the direction of growth by differential redistribution of growth activity across the growth zone of an organ when reacting towards gradients of nutrient concentration, light or gravity has fascinated plant biologists for a long time (Darwin 1880; Perrin 2005). Since the fitness of a plant is strongly increased by dynamic growth reactions towards dynamically changing environmental parameters, plants and organs with diverse growth reactions have evolved in different ecological niches.

When comparing the reaction patterns of leaves and roots, one has to consider that the heterogeneity of environmental conditions to which those organs are exposed, differs strongly. This difference has led to different basic patterns of growth dynamics in leaves and roots. The steady rotation of day and night phases accompanied by strong differences in temperature and humidity during 24 h has led to a huge diel variation of relative growth rate in leaves, even if environmental factors other than light are kept constant. In contrast to this, roots of a wide variety of species grow continually throughout 24 h. Yet, since roots are not used to buffer strong variations of environmental factors, they modulate their growth rates strongly and rapidly in reaction to singular changes of temperature (Pahlavanian and Silk 1988; Walter et al. 2002b), water availability (Fan and Neumann 2004), nutrient availability (Walter et al. 2003a) or light intensity (Nagel et al. 2006).

The control of growth processes is regulated on a number of system levels, ranging from biomechanical constraints (Niklas 1999) via transcriptional control in roots (Birnbaum et al. 2003; Bassani et al. 2004) and leaves (Train-otti et al. 2004; Matsubara et al. 2006; Ainsworth et al. 2006) to regulation by long-distance signals (Heckenberger et al. 1998). In which way environmental stimuli are affecting this regulatory network has to be investigated more intensely in future studies to understand plant performance in fluctuating environmental situations. Models of cellular behavior in the context of growing organs and of plant architecture will help to gain insight into mechanisms of plant development. Supported by such models, the connection between patterns of gene expression and plant architecture is currently being revealed (Prusinkiewicz 2004; Coen et al. 2004).

The investigation of the interaction of heterogeneities of different environmental parameters with dynamic growth patterns will lead to an improved understanding of past, present and future plant behavior. This in turn will help us to understand evolutionary processes, to breed and design optimal crop plants for different environmental scenarios and to assess, how plant ecosystems will react to global climate change.

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