Pos E., Coelho L. D., Lima D. D., Salomao R. P., Amaral I. L., Matos F. D. D., Castilho C. V., Phillips O. L., Guevara J. E., Carim M. D. V., Lopez D. C., Magnusson W. E., Wittmann F., Irume M. V., Martins M. P., Sabatier Daniel, Guimaraes J. R. D., Molino Jean-François, Banki O. S., Piedade M. T. F., Pitman N. C. A., Mendoza A. M., Ramos J. F., Hawes J. E., Almeida E. J., Barbosa L. F., Cavalheiro L., dos Santos M. C. V., Luize B. G., Novo Emmd, Vargas P. N., Silva T. S. F., Venticinque E. M., Manzatto A. G., Reis N. F. C., Terborgh J., Casula K. R., Coronado E. N. H., Montero J. C., Marimon B. S., Marimon-Junior B., Feldpausch T. R., Duque A., Baraloto C., Arboleda N. C., Engel Julien, et al. (2023). Unraveling Amazon tree community assembly using Maximum Information Entropy : a quantitative analysis of tropical forest ecology. Scientific Reports - Nature, 13 (1), [11 p.]. ISSN 2045-2322.
Titre du document
Unraveling Amazon tree community assembly using Maximum Information Entropy : a quantitative analysis of tropical forest ecology
Année de publication
2023
Auteurs
Pos E., Coelho L. D., Lima D. D., Salomao R. P., Amaral I. L., Matos F. D. D., Castilho C. V., Phillips O. L., Guevara J. E., Carim M. D. V., Lopez D. C., Magnusson W. E., Wittmann F., Irume M. V., Martins M. P., Sabatier Daniel, Guimaraes J. R. D., Molino Jean-François, Banki O. S., Piedade M. T. F., Pitman N. C. A., Mendoza A. M., Ramos J. F., Hawes J. E., Almeida E. J., Barbosa L. F., Cavalheiro L., dos Santos M. C. V., Luize B. G., Novo Emmd, Vargas P. N., Silva T. S. F., Venticinque E. M., Manzatto A. G., Reis N. F. C., Terborgh J., Casula K. R., Coronado E. N. H., Montero J. C., Marimon B. S., Marimon-Junior B., Feldpausch T. R., Duque A., Baraloto C., Arboleda N. C., Engel Julien, et al.
Source
Scientific Reports - Nature, 2023,
13 (1), [11 p.] ISSN 2045-2322
In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020]
;
Sciences du milieu [021]
;
Etudes, transformation, conservation du milieu naturel [082]
Description Géographique
AMAZONIE ; ZONE TROPICALE
Localisation
Fonds IRD [F B010087744]
Identifiant IRD
fdi:010087744
