Multiscale computation of solar radiation for predictive vegetation modelling

Abstract

The recent development of large environmental databases allow the analysis of the ecological behaviour of species or communities over large territories. Solar radiation is a fundamental component of ecological processes, but is poorly used at this scale due to the lack of available data. Here we present a GIS program allowing to calculate solar radiation as well locally as at large scale, taking into account both topographical (slope, aspect, altitude, shadowing) and global (cloudiness and latitude) parameters. This model was applied to the whole of France (540 000 km2) for each month of the year, using only a 50-m digital elevation model (DEM), latitude values and cloudiness data. Solar radiation measured from 88 meteorological stations used for validation indicated a R 2 of 0.78 between measured and predicted annual radiation with better predictions for winter than for summer. Radiation values increase with altitude, and with slope for southern exposure, excepted in summer. They decrease with latitude, nebulosity, and slope for north, east, and west exposures. The effect of cloudiness is important, and reduces radiation by around 20% in winter and 10% in summer. Models of plant distribution were calculated for Abies alba, Acer pseudoplatanus, and Quercus pubescens, for France. The use of solar radiation improved modelling for the three species models directly or through the water balance variable. We conclude that models which incorporates both topographical and global variability of solar radiation can improve efficiency of large-scale models of plant distribution.