Attractor of a neutral individual-based forest model captures spatiotemporal structure characteristics of a mature tropical forest

Abstract

Like other ecosystems, a forest never reaches a static equilibrium (climax), but ends up on a stochastic attractor, as a few dynamical systems approaches have shown. Here, we follow a tropical evergreen South American forest in French Guyana, which has not been anthropically perturbed for around 200 years, and then only in minor ways (and there have been no large scale perturbations since around 500 years ago). This study presents both experimental data and a modelling approach. Our data consists of measurements of the leaf area index (LAI) at high resolution along thirteen 512 m-long transects in July of 2000, 2009, and 2018. For each transect we plot the mean LAI ($\overline{\mathrm{LAI}}$) against its standard deviation (${\sigma }_{\mathrm{LAI}}$). We find that each transect follows a trajectory in $({\sigma }_{\mathrm{LAI}},\overline{\mathrm{LAI}})$-space which is confined to an oval-shaped domain. A strong change is observed between 2000 and 2009, with lower $\overline{\mathrm{LAI}}$ and higher ${\sigma }_{\mathrm{LAI}}$, on average, hinting at temporal environmental degradation. However, the average values over all transects in 2018 show a quasi-return to the 2000 values. This is explained by a rainfall deficit in 2009, but does not exclude the possibility of a systematic drift in the future. In the modelling part, we improved upon the very simple cellular automata type model used in previous work by incorporating a more realistic description of tree life and death, and it successfully reproduces the dynamic behaviour of the real forest. The fact that such a simple model gives a very good description of the forest behaviour is strong evidence for the efficacy of a dynamical systems approach to the understanding of real forest ecosystem dynamics.