Additive biomass equations for pine species of forest plantations of Durango, Mexico

Statistical analysis between three weighted additive biomass equations are presented forplanted pine species typical of the coniferous forests of the Western Sierra Madre mountain range ofDurango, Mexico. Statistical and graphical analyses were used to select the best single and multipleindividual b...

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Detalles Bibliográficos
Autores: José de Jesús Graciano Luna, Nicolás González, Virginia Dale, Bernard Parresol, José de Jesús Návar
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2004
País:México
Institución:Universidad Autónoma de Nuevo León
Repositorio:Redalyc-UANL
OAI Identifier:oai:redalyc.org:61710202
Acceso en línea:https://www.redalyc.org/articulo.oa?id=61710202
Access Level:acceso abierto
Palabra clave:Agrociencias
cooperi
durangensis
engelmannii
Biomass additivity
seemingly unrelated regression
Descripción
Sumario:Statistical analysis between three weighted additive biomass equations are presented forplanted pine species typical of the coniferous forests of the Western Sierra Madre mountain range ofDurango, Mexico. Statistical and graphical analyses were used to select the best single and multipleindividual biomass component equation. Linear equations better fitted the biomass components.Therefore, three linear additive procedures were tested: (i) the conventional, (ii) a harmonization, and(iii) the seemingly-unrelated regression in two types of equations of component biomass estimationusing both simple regression and multiple regression techniques. These tests were performed at twoscales: (a) each of three pine species and (b) all three species. For both the simple linear and bestmultiple regression equation, the seemingly-unrelated equations provided more precise biomasscomponent estimates, with tendencies consistent with the conventional non-additive non-linear regressionprocedures, and provided average biomass component estimates when equations were appliedto a data set of 23 sample quadrants.