Additive biomass equations for pine species of forest plantations of Durango, Mexico
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| Format: | Artículo científico |
| Langue: | en |
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Instituto de Ecología, A.C.
2004
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| _version_ | 1876456149107081216 |
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| author | José de Jesús Graciano Luna |
| author_facet | José de Jesús Graciano Luna |
| contents | Additive biomass equations for pine species of forest plantations of Durango, Mexico José de Jesús Graciano Luna Nicolás González Virginia Dale Bernard Parresol José de Jesús Návar Agrociencias cooperi durangensis engelmannii Biomass additivity seemingly unrelated regression 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. 2004 artículo científico 1405-0471 https://www.redalyc.org/articulo.oa?id=61710202 en http://www.redalyc.org/revista.oa?id=617 Madera y Bosques application/pdf Instituto de Ecología, A.C. Madera y Bosques (México) Num.2 Vol.10 |
| format | Artículo científico |
| id | redalyc_61710202 |
| institution | Redalyc |
| language | en |
| publishDate | 2004 |
| publisher | Instituto de Ecología, A.C. |
| spellingShingle | Additive biomass equations for pine species of forest plantations of Durango, Mexico José de Jesús Graciano Luna Agrociencias cooperi durangensis engelmannii Biomass additivity seemingly unrelated regression Additive biomass equations for pine species of forest plantations of Durango, Mexico José de Jesús Graciano Luna Nicolás González Virginia Dale Bernard Parresol José de Jesús Návar Agrociencias cooperi durangensis engelmannii Biomass additivity seemingly unrelated regression 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. 2004 artículo científico 1405-0471 https://www.redalyc.org/articulo.oa?id=61710202 en http://www.redalyc.org/revista.oa?id=617 Madera y Bosques application/pdf Instituto de Ecología, A.C. Madera y Bosques (México) Num.2 Vol.10 |
| title | Additive biomass equations for pine species of forest plantations of Durango, Mexico |
| topic | Agrociencias cooperi durangensis engelmannii Biomass additivity seemingly unrelated regression |
| url | https://www.redalyc.org/articulo.oa?id=61710202 |