Background: Species’ life history and population dynamics are strongly shaped by the longevity of individuals, but lifespan is one of the least accessible demographic traits, particularly in clonal plants. Continuous vegetative reproduction of genets enables persistence despite low or no sexual reproduction, affecting genet turnover rates and population stability. Therefore, the longevity of clonal plants is of high biological interest, but still relatively poorly known.
Scope: Here, we critically review the present knowledge on the longevity of clonal plants and discuss its importance for population persistence. Direct lifespan measurements such as growth-ring analysis in woody plants are relatively easy to perform, although, for many clonal plants, these methods are not adequate due to the variable growth pattern of ramets and difficult genet identification. For several years now, indirect methods are being applied where genet size and annual shoot increments are used to estimate genet age. These methods are often based on molecular techniques, which are non-invasive and allow precise and spatial genet detection. Moreover, such methods allow the investigation of genet size and age structures of populations, a crucial issue for understanding their viability and persistence. However, indirect estimates of clonal longevity are impeded because the process of aging in clonal plants is still poorly understood and because their size and age are not always well correlated. Alternative estimators for genet lifespan such as somatic mutations have recently been suggested.
Conclusions: The empirical knowledge on the longevity of clonal species has considerably increased during the last few years. Maximum age estimates are an indicator of population persistence, but not sufficient to evaluate turn over rates and the ability of long-lived clonal plants to enhance community stability and ecosystem resilience. In order to understand the dynamics of populations it will be necessary in the future to measure genet size and age structure, not only lifespans of single individuals, and to use such data for modelling of genet dynamics.