The present study examines variations in the timing of flowering between populations of Iberian Poaceae species using pollen data from 12 sites in Spain. The spatial variation in pollen season start-date for any given year was around 1 month; year-on-year differences at any given site ranged around 1.5 months. The spatial variation in the pollen season peak-date was smaller, at around 15 days, while the year-on-year variation for the peak-date at a given site was never greater than 20 days. Two process-based models were developed, one to predict the start-date and the other the peak-date of the grass pollen season. These models take into account the effects of temperature, photoperiod and water availability on the timing of grass flowering in Spain. Apart from predicting the pollen-season start and peak dates, the models provide information on (i) the Poaceae response to weather-related factors, (ii) the period during which these factors affect grass growth, and (iii) the relationship between photoperiod, temperature and water availability for flowering grasses. Internal validation showed that the models accounted for 45% of the variance in start-date and 68% of the variance in peak-date. External validation was performed for 2006 and 2007 at all sites: the root mean square error for the actual and predicted dates was around 4 days for the start-date and 6 for the peak-date. Analysis of the model estimates showed that a single model parameter set for all Spain, taking into account different bioclimatic factors, could be sufficient to account for the variability of the Poaceae pollen season across space and time. © 2008 Elsevier B.V. All rights reserved.
|Journal||Agricultural and Forest Meteorology|
|Publication status||Published - 1 Feb 2009|
García-Mozo, H., Galán, C., Belmonte, J., Bermejo, D., Candau, P., Díaz de la Guardia, C., Elvira, B., Gutiérrez, M., Jato, V., Silva, I., Trigo, M. M., Valencia, R., & Chuine, I. (2009). Predicting the start and peak dates of the Poaceae pollen season in Spain using process-based models. Agricultural and Forest Meteorology, 149(2), 256-262. https://doi.org/10.1016/j.agrformet.2008.08.013