Comparison of models for daily light partitioning in multispecies canopies

A simulation model of light partitioning in horizontally homogeneous multis pecies canopies is proposed. The model is based on the Kubelka-Munk equatio ns (KM) applied to a mixture of N vegetation components. Only two hemispher ical fluxes, i.e. downwards and upwards, are considered. The exact solution of KM equations was then simplified in such a way that the model can be ea sily extended to multispecies canopies including several vegetation layers. The simplified KM model (KMS) was compared to two other light models deali ng with mixed canopies: the more detailed model SIRASCA [Sinoquet, H., Moul ia, B., Gastal, F., Bonhomme, R., Varlet-Grancher, C., 1990. Modeling the r adiative balance of the components of a well-mixed canopy: application to a white clover-tall fescue mixture. Acta Oecol. 11, 469-486], and the simple r model ERIN [Wallace, J.S., 1997. Evaporation and radiation interception b y neighbouring plants. Q. J. R. Meteorol. Sec. 123, 1885-1905]. All three m odels were applied to theoretical two-species monolayer canopies, and to ac tual mixed canopies, the geometry of which was retrieved from the literatur e. In the PAR waveband, the model KMS gave simulation results very similar to those of SIRASCA in case of contrasted canopy structures. In conditions of high leaf and soil scattering, deviations between SIRASCA and KMS output s were higher and reached maximum values of -0.08 for erectophile species. Comparison between SIRASCA and ERIN outputs showed that ERIN largely undere stimated light competition in a two-component canopy in several conditions, due to light partitioning only based on height differences between compone nts. Simulations also showed the significant effect of the vertical distrib ution of leaf area on light partitioning in the case of mixtures where comp onents had equal or different heights. Finally it appears that the model KM S could be a candidate for inclusion in growth models for multispecies cano pies, since all KMS parameters have physical meaning and it is very easy to implement. (C) 2000 Elsevier Science B.V. All rights reserved.