Significance of bedrock as a site factor determining nutritional status and growth of maritime pine
Relationships between soil properties, foliar nutrients and growth were studied in 128 plots of Pinus pinaster established in soil over different types of bedrock in Galicia (NW Spain). Plots were classified into the following groups of bedrocks according to geological maps and samples: granitic roc...
| Autores: | , , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2014 |
| País: | España |
| Recursos: | Universidad de Santiago de Compostela (USC) |
| Repositorio: | Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela |
| Idioma: | inglés |
| OAI Identifier: | oai:minerva.usc.gal:10347/40776 |
| Acesso em linha: | https://hdl.handle.net/10347/40776 |
| Access Level: | acceso abierto |
| Palavra-chave: | Bedrock Nutrition Growth Maritime pine |
| Resumo: | Relationships between soil properties, foliar nutrients and growth were studied in 128 plots of Pinus pinaster established in soil over different types of bedrock in Galicia (NW Spain). Plots were classified into the following groups of bedrocks according to geological maps and samples: granitic rocks, quaternary sediments, quartzite and sandstone, slates and phyllites, biotitic schists, micaschists, gneiss and migmatites. Bedrock type significantly influenced exchangeable Ca, total N, soil depth, foliar N, P, Ca, K and Mg and site index. Bedrock was also related to elevation, temperature and slope, as a result of the distribution and geomorphology. Soils developed from biotitic schists, gneiss, migmatites and granitic rocks were the most favourable for tree growth. The poorest growth and most severe nutrient deficiencies were observed in soils developed from quaternary sediments, mica schists, phyllites and slates, quartzite and sandstone. Two regression models were developed to predict site index: a complete model explained 52% of the total variation in site index, and a model for granitic rocks explained 53% of the variation. Both indicated the importance of soil depth, elevation and foliar K and Ca as predictive variables. |
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