Predicting forest site productivity in temperate lowland from forest floor, soil and litterfall characteristics using boosted regression trees

Aims The aim of this study is on the one hand to identify the most determining variables predicting the site productivity of pedunculate oak, common beech and Scots pine in temperate lowland forests of Flanders; and on the other hand to test whether the accuracy of site productivity models based exc...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Plant and soil 2012-05, Vol.354 (1-2), p.157-172
Hauptverfasser:	Aertsen, Wim, Kint, Vincent, De Vos, Bruno, Deckers, Jozef, Van Orshoven, Jos, Muys, Bart
Format:	Artikel
Sprache:	eng
Schlagworte:	Agricultural productivity Agronomy. Soil science and plant productions Animal, plant and microbial ecology Biological and medical sciences Biomedical and Life Sciences Decomposing organic matter Ecology Ecosystem models Ecosystems Environmental aspects Forest dynamics Forest floor Forest litter Forest management Forest practices Forest soils Forestry research Fundamental and applied biological sciences. Psychology General agronomy. Plant production Humus Life Sciences Modeling Nitrogen Pine trees Pinus sylvestris Plant Physiology Plant populations Plant Sciences Prediction models Productivity Regression analysis Regular Article Soil depth Soil ecology Soil horizons Soil science Soil Science & Conservation Soil-plant relationships. Soil fertility Soil-plant relationships. Soil fertility. Fertilization. Amendments Soils Terrestrial ecosystems Trees Vegetation
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!