Mason EGHolmström ENilsson U2017-11-062017-11-062017Mason EG, Holmström E, Nilsson U (2017). Using hybrid physiological/mensurational modelling to predict site index of Pinus sylvestris L. in Sweden: a pilot study. Scandinavian Journal of Forest Research. 1-8.0282-75811651-1891http://hdl.handle.net/10092/14591Precision 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 with a standard error of 3.7 m. A new model was constructed using a fitting subset of the data, employing the sum of mean monthly estimates of photosynthetically active radiation modified by local monthly climatic conditions as a primary independent variable. The best model used a day-time temperature modifier to calculate potential radiation use efficiency. Modifiers for vapour pressure deficit and soil water did not add significantly to the model. Elevation and distance to the sea added small but significant improvements to the predictions. Phytometer indicators of nutritional fertility also slightly improved the fit. The final model had a standard error of 2.06 m for predictions of site index that ranged from 18-30 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.enSite indexMensurationTree physiologyEcophysiologyScots pineJournal Article2017-07-18Fields of Research::30 - Agricultural, veterinary and food sciences::3007 - Forestry sciences::300707 - Forestry management and environmentFields of Research::30 - Agricultural, veterinary and food sciences::3007 - Forestry sciences::300708 - Forestry product quality assessmentFields of Research::31 - Biological sciences::3103 - Ecology::310303 - Ecological physiologyhttps://doi.org/10.1080/02827581.2017.1348539