Heat accumulation period in the Mediterranean region: phenological response of the olive in different climate areas (Spain, Italy and Tunisia)

Mendías, Carlos Salazar; Ruiz, L.; Fornaciari, Marco; Romano, Bruno; Galán, Carmen; Oteros, José; Dhiab, Ali Ben; Msallem, M.; Orlandi, Fabio

doi:10.1007/s00484-013-0666-7

Cited by 68 publications

(46 citation statements)

References 32 publications

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“…In this regard, Galán et al (2005) found different Tb values for accumulating thermal time until flowering in olive depending on the values of average air temperatures at different sites in Andalusia (Spain). Aguilera et al (2014) also reported over a wide latitudinal gradient from central Italy (43°N) to southern Tunisia (33°N) that more southerly olive populations had lower thermal time requirements than those in the north. It is possible that the warm temperatures in our area may have resulted in physiological changes within the tree and its buds that led to deviations from the DMA model calculations.…”

Section: Discussionmentioning

confidence: 82%

“…Expansion of olive production to lower than traditional latitudes requires information about the flowering response of different cultivars to key environmental factors such as temperature (Orlandi et al, 2010b;Aguilera et al, 2014). Because field trials in perennial A consideration not accounted for in the DMA model is whether a maximum threshold for thermal time accumulation to flowering exists after endodormancy release.…”

Section: Discussionmentioning

confidence: 99%

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Evaluation of olive flowering at low latitude sites in Argentina using a chilling requirement model

Aybar

Melo-Abreu

Searles

et al. 2015

Span. j. agric. res.

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Olive production has expanded significantly from the Mediterranean Basin into the New World over the last two decades. In some cases, cultivars of European origin have been introduced at a large commercial scale with little previous evaluation of potential productivity. The objective of this study was to evaluate whether a temperature-driven simulation model developed in the Mediterranean Basin to predict normal flowering occurrence and flowering date using cultivar-specific thermal requirements was suitable for the low latitude areas of Northwest Argentina. The model was validated at eight sites over several years and a wide elevation range (350–1200 m above mean sea level) for three cultivars (‘Arbequina’, ‘Frantoio’, ‘Leccino’) with potentially different chilling requirements. In ‘Arbequina’, normal flowering was observed at almost all sites and in all years, while normal flowering events in ‘Frantoio’ and ‘Leccino’ were uncommon. The model successfully predicted if flowering would be normal in 92% and 83% of the cases in ‘Arbequina’ and ‘Frantoio’, respectively, but was somewhat less successful in ‘Leccino’ (61%). When flowering occurred, the predicted flowering date was within ± 7 days of the observed date in 71% of the cases. Overall, the model results indicate that cultivar-specific simulation models may be used as an approximate tool to predict whether individual cultivars will be successful in new growing areas. In Northwest Argentina, the model could be used to identify cultivars to replace ‘Frantoio’ and ‘Leccino’ and to simulate global warming scenarios.

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Section: Discussionmentioning

confidence: 82%

Section: Discussionmentioning

confidence: 99%

Evaluation of olive flowering at low latitude sites in Argentina using a chilling requirement model

Aybar

Melo-Abreu

Searles

et al. 2015

Span. j. agric. res.

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“…High temperatures during the two months preceding budburst have a positive effect on the final fruit production. According to Aguilera et al (2013), the onset of the heat accumulation period usually occurs in the first two weeks of February, and a certain number of days are required to completely satisfy the olive tree biothermic requirements. The relationship between accumulation of temperature and future development of flowers and fruit might explain the inclusion of this variable in the forecasting models.…”

Section: Discussionmentioning

confidence: 99%

Forecasting olive crop yields based on long-term aerobiological data series and bioclimatic conditions for the southern Iberian Peninsula

Mendías

Valenzuela

2014

Span. j. agric. res.

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In the present study, bio-meteorological models for predicting olive-crop production in the southern Iberian Peninsula were developed. These covered a 16-year period: 1994-2009. The forecasting models were constructed using the partial least-squares regression method, taking the annual olive yield as the dependent variable, and both aerobiological and meteorological parameters as the independent variables. Two regression models were built for the prediction of crop production prior to the final harvest at two different times of the year: July and November. The percentage variance explained by the models was between 83% and 93%. Through these forecasting models, the main factors that influence olive-crop yield were identified. Pollen index and accumulated precipitation, especially as rain recorded during the pre-flowering months, were the most important parameters for providing an explanation of fluctuations in fruit production. The temperature recorded during the two months preceding budburst was another important variable, which showed positive effects on the final yield. The July model that provides accurate predictions of fruit production eight months prior to the final harvest is proposed as an optimal model to forecast fruit produced by olive trees in western Mediterranean areas.

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“…Both the onset of the heat accumulation period and the temperature threshold for the number of positive heat units might vary according to the climate of a determined geographical area. The threshold level was also reported to decrease towards the north (Aguilera et al, 2013). Altitude is the topographical factor that most influences olive local phenology and the major weather factors are temperature, rainfall, and solar radiation, which control plant evapotranspiration .…”

Section: Introductionmentioning

confidence: 99%

“…Several wider-area studies were also undertaken to aim at more general statistical characteristics of the season, e.g. Aguilera et al (2014Aguilera et al ( , 2013, Galan et al (2016).…”

Section: Introductionmentioning

confidence: 99%

Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook

et al. 2017

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Abstract. The paper presents the first modelling experiment of the European-scale olive pollen dispersion, analyses the quality of the predictions, and outlines the research needs. A 6-model strong ensemble of Copernicus Atmospheric Monitoring Service (CAMS) was run throughout the olive season of 2014, computing the olive pollen distribution. The simulations have been compared with observations in eight countries, which are members of the European Aeroallergen Network (EAN). Analysis was performed for individual models, the ensemble mean and median, and for a dynamically optimised combination of the ensemble members obtained via fusion of the model predictions with observations. The models, generally reproducing the olive season of 2014, showed noticeable deviations from both observations and each other. In particular, the season was reported to start too early by 8 days, but for some models the error mounted to almost 2 weeks. For the end of the season, the disagreement between the models and the observations varied from a nearly perfect match up to 2 weeks too late. A series of sensitivity studies carried out to understand the origin of the disagreements revealed the crucial role of ambient temperature and consistency of its representation by the meteorological models and heat-sum-based phenological model. In particular, a simple correction to the heat-sum threshold eliminated the shift of the start of the season but its validity in other years remains to be checked. The short-term features of the concentration time series were reproduced better, suggesting that the precipitation events and cold/warm spells, as well as the large-scale transport, were represented rather well. Ensemble averaging led to more robust results. The best skill scores were obtained with data fusion, which used the previous days' observations to identify the optimal weighting coefficients of the individual model forecasts. Such combinations were tested for the forecasting period up to 4 days and shown to remain nearly optimal throughout the whole period.

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Heat accumulation period in the Mediterranean region: phenological response of the olive in different climate areas (Spain, Italy and Tunisia)

Cited by 68 publications

References 32 publications

Evaluation of olive flowering at low latitude sites in Argentina using a chilling requirement model

Evaluation of olive flowering at low latitude sites in Argentina using a chilling requirement model

Forecasting olive crop yields based on long-term aerobiological data series and bioclimatic conditions for the southern Iberian Peninsula

Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook

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