Effects of foliar nutrients and environmental factors on site productivity in Pinus pinaster Ait. stands in Asturias (NW Spain)
[EN] Background: The effects of foliar nutrients and environmental variables on site productivity in Maritime pine (Pinus pinaster Ait.) stands in Asturias (NW Spain) were studied. Methods: Site productivity was evaluated by means of site index. The environmental characteristics considered included...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2011 |
| País: | España |
| Institución: | Universidad de León |
| Repositorio: | BULERIA. Repositorio Institucional de la Universidad de León |
| OAI Identifier: | oai:buleria.unileon.es:10612/25449 |
| Acceso en línea: | https://annforsci.biomedcentral.com/articles/10.1007/s13595-011-0047-5 https://hdl.handle.net/10612/25449 |
| Access Level: | acceso abierto |
| Palabra clave: | Ingeniería agrícola CHAID procedure Environmental factors Foliar nutrients Parametric regression Pinus pinaster Site index 3102 Ingeniería Agrícola |
| Sumario: | [EN] Background: The effects of foliar nutrients and environmental variables on site productivity in Maritime pine (Pinus pinaster Ait.) stands in Asturias (NW Spain) were studied. Methods: Site productivity was evaluated by means of site index. The environmental characteristics considered included physiographic, edaphic and climatic variables. Two different statistical analyses were carried out to determine the key factors affecting site productivity: the CHAID procedure and parametric regression techniques. Results: The regression trees obtained by applying the CHAID algorithm separately to each type of variable revealed the order of importance of the environmental factors. In addition, the variables corresponding to the first level of branches of the CHAID regression trees were consistent with those identified by parametric regression. According to the parametric regression model, a physical soil characteristic (soil depth) and a climatic characteristic (mean summer temperature) were the most important variables for explaining site productivity in the region. Foliar concentrations of phosphorus and elevation were not significant factors in the parametric regression analysis (although considered key factors when foliar nutrients and physiographic variables were analyzed separately). Conclusion: Although the percentage variability in SI explained by the best parametric model was not very high (45%), the model is parsimonious and provides robust estimates of the spatial distribution of this variable. The results obtained provide further information about the ecology of this species in Asturias, and represent an important tool in forest management, especially for afforested areas. © INRA and Springer Science+Business Media B.V. 2011. |
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