The quantitative assessment of the benefits of physiological integration in clonal plants

A genet of a clonal plant often has ramets persistently interconnected by living tissue capable of supporting the exchange of materials. This condition is known as physiological integration. A quantitative framework is developed for the study of the fitness benefits of physiological integration in clonal plants in spatially heterogeneous environments. We argue that the relative growth rate of the genet is a suitable approximate measure of fitness. Fitness benefits of physiological integration are then measured by comparing genet relative growth rates between heterogeneous and homogeneous environmental conditions. Fitness benefit measures are derived for both exponential and non-exponential growth of genet (clonal) fragments and for equilibrium scenarios. For short time-scales and equilibrium scenarios, we show how the fitness benefit (at the level of the genet) can be decomposed into net benefits accruing at the level of the genet fragment, which can then be further analysed in terms of costs and benefits for the parent and offspring sections of a genet fragment. Applying these benefit measures to simple models of clonal plant growth shows that net benefits of physiological integration may disappear with time and become net costs when physiological integration occurs between strictly good and poor environments. Such time dependence is predicted to result from long-term dominance of total genet growth by genet fragments in good environments. Time dependence, however, would not necessarily occur when the various environments are not strictly good or bad but have complementary attributes. Similarly, net benefits would not necessarily be time-dependent under equilibrium growth scenarios. The net benefit measures derived here allow such time dependence to be assessed in an experimental setting. Although the quantitative methods developed here focus specifically on a common experimental design in which genet fragments are divided into sections subject to different environmental conditions, these methods extend to complex scenarios that might be justified by particular circumstances in the field.