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Using model analysis to unveil hidden patterns in tropical forest structures

Picard N., Mortier F., Ploton P., Liang J., Derroire G., Bastin J.F., Ayyappan N., Bénédet F., Boyemba Bosela F., Clark C.J., Crowther T.W., Engone Obiang N.L., Forni E., Harris D., Ngomanda A., Poulsen J.R., Sonké B., Couteron P., Gourlet-Fleury S.. 2021. Frontiers in Ecology and Evolution, 9 : 13 p..

DOI: 10.5281/zenodo.4338387

DOI: 10.3389/fevo.2021.599200

When ordinating plots of tropical rain forests using stand-level structural attributes such as biomass, basal area and the number of trees in different size classes, two patterns often emerge: a gradient frompoorly to highly stocked plots and high positive correlations between biomass, basal area and the number of large trees. These patterns are inherited from the demographics (growth, mortality and recruitment) and size allometry of trees and tend to obscure other patterns, such as site differences among plots, that would be more informative for inferring ecological processes. Using data from 133 rain forest plots at nine sites for which site differences are known, we aimed to filter out these patterns in forest structural attributes to unveil a hidden pattern. Using a null model framework, we generated the anticipated pattern inherited from individual allometric patterns. We then evaluated deviations between the data (observations) and predictions of the null model. Ordination of the deviations revealed site differences that were not evident in the ordination of observations. These sites differences could be related to different histories of large-scale forest disturbance. By filtering out patterns inherited from individuals, our model analysis provides more information on ecological processes.

Mots-clés : modèle végétal; parcelle; forêt tropicale humide; allométrie; structure du peuplement; type forestier (composition botanique); modélisation; république centrafricaine; cameroun; congo; république démocratique du congo; inde; gabon; guyane française; france

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