Development of a multi-factor model for predicting the effects of ambient ozone on the biomass of white clover

Results are presented from the UN/ECE ICP Vegetation (International Coopera tive Programme on effects of air pollution on natural vegetation and crops) experiments in which ozone(O-3)-resistant (NC-R) and -sensitive (NC-S) clo nes of white clover (Trifolium repens cv. Regal) were exposed to ambient O- 3 episodes at 14 sites in eight European countries in 1996, 1997 and 1998. The plants were grown according to a standard protocol, and the forage was harvested every 28 days for 4-5 months per year by excision 7 cm above the soil surface. Biomass ratio (NC-S/NC-R) was related to the climatic and pol lutant conditions at each site using multiple linear regression (MLR) and a rtificial neural networks (ANNs), Twenty-one input parameters [e.g. AOT40, 7-h mean O-3 concentration, daylight vapour pressure deficit (VPD), daily m aximum temperature] were considered individually and in combination with th e aim of developing a model with high r(2) and simple structure that could be used to predict biomass change in white clover. MLR models were generall y more complex, and performed less well for unseen data than non-linear ANN models. The ANN model with the best performance had five inputs with an r( 2) value of 0.84 for the training data, and 0.71 for previously unseen data . Two inputs to the model described the O-3 conditions (AOT40 and 24-h mean for O-3), two described temperature (daylight mean and 24-h mean temperatu re), and the fifth input appeared to be differentiating between semi-urban and rural sites (NO concentration at 17:00). Neither VPD nor harvest interv al was an important component of the model. The model predicted that a 5% r eduction in biomass ratio was associated with AOT40s in the range 0.9-1.7 p pm.h (mu l l(-1) h) accumulated over 28 days, with plants being most sensit ive in conditions of low NOx, medium-range temperature, and high 24-h mean O-3 concentration. (C) 2000 Elsevier Science Ltd. All rights reserved.