Understanding and modelling the dynamics of data point clouds of relative growth rate and plant size


Relative growth rates (RGR) have both intrigued and irritated many plant scientists since they were proposed as characteristics of growth performance in the early 20th century. Particularly, the common trend of RGR to decrease with increasing size, also referred to as ontogenetic drift, has given rise to many debates and much criticism. In this study, we showed that, with plants that germinated at the same time, it is common to obtain a linear relationship between RGR and size for each survey year which – when pulled together in one graph – eventually form a system of cascading elliptical point clouds over time. This system of data point clouds reflects the well-known exponential decline of RGR with size, the aforementioned ontogenetic drift. Using 12 individualtree time series of Pinus radiata in Chile we studied the ontogenetic drift based on a new spatially explicit explanatory model allowing the reconstruction of individual-tree RGR trajectories. Favourable environmental conditions enforced the RGR decline over size and accelerated growth dynamics. Less favourable environmental conditions reduced the strength of the ontogenetic drift and slowed down growth. We also found that the model parameter estimates were more precise the stronger the RGR decline over size. Both, interpretable model parameters and evaluation characteristics, described the ontogenetic drift well. Interestingly, the slopes of the semimajor axes of the RGR-size data ellipses changed signs precisely at the time when smaller trees ceased to dominate population growth and larger trees started to contribute disproportionately to the overall growth processes.

Forest Ecology and Management, 529: 120652. https://doi.org/10.1016/j.foreco.2022.120652