From virtual plants to real communities: A review of modelling clonal growth

Clonal plants grow by the production of semi-autonomous modules (ramets), and form complex branching structures which may provide communication/resource flow channels between the units. These characteristic features have made clonal plants a challenging subject for spatial modelling. We review the advance of ideas and new directions in theoretical research since the last review (Oborny and Cain, 1997). We place clonal growth models into a general framework of spatial population dynamic models, comparing individual ramets of a clone with individuals in a non-clonal population. We discuss three specificities of clonal spreading: (1) ramets can be physiologically integrated through the network of branching structures; (2) formation of new ramets occurs by the growth of these branching structures which can be directional, following architectural rules; and (3) formation of new ramets can be adjusted to the environment by phenotypic plasticity. We review methods by which these traits have been implemented into models. We summarize model predictions, for the spatial structure and fitness of clonal plants, and link these predictions with existing empirical data. Emphasis is given to the contributions that theoretical studies could provide for experimental studies in the field. We emphasize the following recent major developments: (i) a much better understanding of emergent consequences of various clonal growth rules over broad spatial and temporal scales has been reached. (ii) Links have been found to other complex systems. For example, a key problem of integration vs. splitting of connecting structures has been shown to be closely related to a problem in percolation theory. (iii) Interactions between physiological integration, architectural growth and plastic responses have been demonstrated; research on these interactions has generally shown a large degree of contingency in the effects of these traits. Finally, we outline some areas for future research.