Desarrollo y validación de modelos no lineales de altura-diámetro para cuatro especies de la Amazonia peruana

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The relationship between tree height and diameter is fundamental in growth and forest productivity models, as well as in understanding stand dynamics. In this study, twenty models were evaluated to predict the total height of four forest species using diameter at breast height: Dipteryx ferrea, Am­...

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Detalles Bibliográficos
Autor: Flores Bendezú, Ymber
Formato: artículo
Fecha de Publicación:2015
Institución:Universidad Nacional Agraria La Molina
Repositorio:Revistas - Universidad Nacional Agraria La Molina
Lenguaje:español
OAI Identifier:oai:revistas.lamolina.edu.pe:article/2243
Enlace del recurso:https://revistas.lamolina.edu.pe/index.php/rfp/article/view/2243
Nivel de acceso:acceso abierto
Materia:allometric models
total height
Dipteryx ferrea
Handroanthus serratifolius
forest plantation
modelos alométricos
altura total
plantación forestal
Descripción
Sumario:The relationship between tree height and diameter is fundamental in growth and forest productivity models, as well as in understanding stand dynamics. In this study, twenty models were evaluated to predict the total height of four forest species using diameter at breast height: Dipteryx ferrea, Am­ burana acreana, Handroanthus serratifolius, and Parkia nitida. For D. ferrea, the most suitable models were Rational, Exponential Association 2, Weibull, Hossfeld IV, and Loetsch, with the Rational model standing out for its high performance in criteria such as the correlation coefficient (r) and standard error (SE). For A. acreana, the Hossfeld model was the most efficient, followed by Logistic Power and Hoerl, excelling in r, R², and root mean square error (RMSE), although the Hoerl model showed significant differences compared to the other models. For H. serratifolius, the most appropriate models were Gompertz, Rational, and MMF, with MMF showing the best performance in R² and RMSE, though no significant differences were found between the models in height prediction. Finally, for P. nitida, the Hoerl and Exponential Association 2 models were the most effective, with the latter standing out for its lower standard error and RMSE. In general, no significant differences were found between the best-performing models regarding the observed total height (p ≥ 0.05).
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