Evaluation of the INTERCOM model for predicting growth of forest herbs

The ecophysiological model INTERCOM was evaluated for its suitability in predicting the growth of perennial forest herbs. A field experiment was conducted to obtain data on photosynthesis and growth parameters of two spring flowering understorey geophytes. Results were used to parameterize the model and its performance was evaluated using the average normalized difference (AE) between predicted and observed biomass and the leaf area index. The model was assumed to provide accurate simulations if the AE was smaller than 0.4. Adjusting the photosynthetic intensity parameters in the model to reflect observed changes in photosynthesis throughout the growing period resulted in the accurate prediction of Scilla bifolia and Arum maculatum biomass (AE=0.13 and AE=0.021, respectively) and LAI (AE=-0.16 and AE=-0.08, respectively). Ecophysiological models may be useful tools for predicting the biomass accumulation of forest understorey species in response to varying environmental conditions, which could be useful for monitoring forest ecosystem health