Abstract Rising winter temperatures jeopardize the fruit yield of trees that require a prolonged and sufficiently cold winter to flower. Predicting the exact risk to different crop varieties is the first step in mitigating the harmful effects of climate change. This work focused on olive (Olea europaea) – a traditional crop in the Mediterranean basin whose flowering depends on the sufficiency of cold periods and the lack of warm ones during the preceding winter. Yet, a satisfactory quantitative model forecasting its expected flowering under natural temperature conditions is still lacking. The effect of different temperature regimes on olive flowering level and flowering-gene expression was empirically tested. A modified ‘dynamic model’ describing the response of a putative flowering factor to the temperature signal was constructed. The crucial component of the model was an unstable intermediate, produced and degraded at temperature-dependent rates. The model accounts for both the number of cold and warm hours but also for their sequence. Empirical flowering and temperature data were applied to fit the model parameters, applying numerical constrained optimization techniques; the model outcomes were successfully validated. The model accurately predicted low-to-moderate flowering under winters with warm periods and properly accounted for the effects of warm periods during winter.
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