The development of single clones of the seagrass Cymodocea nodosa was analysed using a growth model based on the formation of structures limited by diffusive aggregation. The model implemented the measured clonal growth rules (i.e. rhizome elongation and branching rates, branching angle, and spacer length between consecutive shoots) and shoot mortality rate for C. nodosa at Alfacs Bay (Spain). The simulated patches increased their size nonlinearly with time displaying two different domains of growth. Young patches showed a rapid increase with time of the length of rhizome network and the number of living shoots, which depended on rhizome branching rate, and increased the radial patch size (Rg) algebraically with the number of living shoots as R g ∝ NsI/Df, being Df the fractal dimension of the patch structure. Patches older than 4 years increased the production of rhizome network and the number of living shoots much more slowly, while their radial patch size behaved as Rg ∝ N s0.5 resulting from an internal patch compactation. Moreover, the linear growth rate of the simulated patches changed up to 30 fold during patch development, increasing with increasing patch size until patches reached an intermediate size. The modelled patch development was found to closely reproduce the observed patch structure for the species at the Alfacs Bay (Spain). Hence, the growth of C. nodosa patches initially proceeds with a growth mode controlled by the branching pattern (branching frequency and angle) of the species, producing sparse and elongated patches. Once patches exceed 4-5 years of age and contained >500 shoots, becoming dense and circular, they shift to a growth model typical of compact structures. These results explain previously unaccounted evidence of the emergence of nonlinear patch growth from simple clonal growth rules, and highlight the importance of branching frequency and angles as critical determinants of the space occupation rate of seagrasses and probably other clonal plants.
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics