Plant ecologists have recognized the importance of solar radiation for decades but have difficulty measuring it on plots. Proxies recorded on the ground or geographical information system (GIS) indices processed with a digital elevation model (DEM) have generally been used. Here we compare the efficiency of different methods of estimating spatially distributed topographic solar radiation, from the simplest ones (proxies based on slope, and sine or cosine transformed values of aspect) to more elaborate ones using a GIS program suited to calculations of monthly clear sky and overcast solar radiation. We used a 50-metre DEM to estimate solar radiation with these different methods for the whole of France (550 000 km²). Radiation indices were compared with ground measurements from meteorological stations and used to model the distribution of silver fir (Abies alba), sycamore (Acer pseudoplatanus), and downy oak (Quercus pubescens), forest species known to be sensitive to light. Results show that sine and cosine of aspect, combined or not with slope, are inefficient at simulating solar radiation over large areas. Solar radiation, calculated for clear sky and especially including cloud cover, is more relevant, leading respectively to an R² of 0.46 and 0.78 between measured and predicted annual radiation. Calculation with cloud cover appears to be the most efficient index for improving distribution models for the three species studied. Slope and aspect transformations are less efficient than the GIS calculations, but the difference between these proxies decreased on a local scale. Using both with GIS solar radiation, cosine of aspect, with or without interaction with slope, slightly improves distribution models on a local scale, but this effect attenuates with increase in area studied. We conclude that the effect of proxies studied is scale-dependent, but GIS-based calculation including cloudiness variability is more appropriate than topographic proxies or clear sky models in estimating solar radiation and improving the efficiency of plant distribution models.