Olives are one of the largest crops in the Mediterranean region, especially in Andalusia, in southern Spain. A thermal model has been developed for forecasting the start of the olive tree pollen season at five localities in Andalusia: Cordoba, Priego, Jaen, Granada and Malaga using airborne pollen and meteorological data from 1982 to 2001. Threshold temperatures varied between 5 degrees C and 12.5 degrees C depending on bio-geographical characteristics. The external validity of the results was tested using the data for the year 2002 as an independent variable and it confirmed the model's accuracy with only a few days difference from predicted values. All the localities had increasingly earlier start dates during the study period. This could confirm that olive flower phenology can be considered as a sensitive indicator of the effects of climate fluctuations in the Mediterranean area. The theoretical impact of the predicted climatic warming on the olive's flowering phenology at the end of the century is also proposed by applying Regional Climate Model data. A general advance, from 1 to 3 weeks could be expected, although this advance will be more pronounced in mid-altitude inland areas.

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Olive oil is a major economic resource of the Mediterranean region. Olive crop management can be improved by models that forecast the variable reproductive biology of olive tree. However, the processes controlling olive harvest are complex on large scales. Here, we study the parameters that influence olive fruit production for developing accurate forecasting models. Seventeen aerobiological sampling points have monitored olive pollen grains in Spain, Italy and Tunisia from 1993 to 2012. Six crop models have been developed at two provinces and country scales. The modelling has been done in two steps: (1) typification and (2) modelling by partial least square regression. Results show that higher pollen indexes and water availability during spring are related to an increase of final fruit production in all the studied area. Higher pollen indexes are also positively correlated with air temperature during early spring and autumn. Furthermore, a decrease of fruit production is related with increasing air temperature during winter and summer. To conclude, we have designed accurate models that allow accurate predictions of olive production.