Attractor of a neutral individual-based forest model captures spatiotemporal structure characteristics of a mature tropical forest
Issued Date
2025-02-01
Resource Type
ISSN
03043800
Scopus ID
2-s2.0-85213892820
Journal Title
Ecological Modelling
Volume
501
Rights Holder(s)
SCOPUS
Bibliographic Citation
Ecological Modelling Vol.501 (2025)
Suggested Citation
Dubois M.A., Allen M.A., Chanthorn W., Cournac L., Emmons L.H., Favier C., Riéra B. Attractor of a neutral individual-based forest model captures spatiotemporal structure characteristics of a mature tropical forest. Ecological Modelling Vol.501 (2025). doi:10.1016/j.ecolmodel.2024.111009 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/102793
Title
Attractor of a neutral individual-based forest model captures spatiotemporal structure characteristics of a mature tropical forest
Corresponding Author(s)
Other Contributor(s)
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 (LAI¯) against its standard deviation (σLAI). We find that each transect follows a trajectory in (σLAI,LAI¯)-space which is confined to an oval-shaped domain. A strong change is observed between 2000 and 2009, with lower LAI¯ and higher σLAI, 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.