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Research article - Peer-reviewed, 2018

Using hybrid physiological/mensurational modelling to predict site index of Pinus sylvestris L. in Sweden: a pilot study

Mason, Euan G.; Holmstrom, Emma; Nilsson, Urban


Precision and bias of a model designed to predict site index of Scots pine (P. sylvestris L.) from site variables in Sweden were tested using data from 1985 inventory plots. The model was biased and relatively imprecise (standard error = 3.7 m). A new model was constructed using a fitting subset of data, employing sums of mean monthly estimates of photosynthetically active radiation modified by local monthly climatic conditions as a primary independent variable. The best model used daytime temperature modifiers to calculate potential radiation-use efficiency. Modifiers for vapour pressure deficit and soil water did not improve the model. Elevation, distance to the sea, and phytometer indicators of nutritional fertility added small but significant improvements to the predictions. The final model had a standard error of 2.06 m for predictions of site index that ranged from 18 to 30 m at age 100. When applied to a validation subset of plots the model displayed a standard error of 2.09 m and very similar residual patterns to those observed during fitting. The new model represents a significant improvement over the older model, and further improvements may be feasible when historical climatic estimates and a higher resolution digital elevation model become available.


Site index; mensuration; tree physiology; ecophysiology; Scots pine

Published in

Scandinavian Journal of Forest Research
2018, Volume: 33, number: 2, pages: 147-154