Olive phenology as a sensitive indicator of future climatic warming in the Mediterranean

Olive phenology as a sensitive indicator of future climatic warming in the Mediterranean Experimental and modelling work suggests a strong dependence of olive flowering date on spring temperatures. Since airborne pollen concentrations reflect the flowering phenology of olive populations within a radius of 50 km, they may be a sensitive regional indicator of climatic warming. We assessed this potential sensitivity with phenology models fitted to flowering dates inferred from maximum airborne pollen data. Of four models tested, a thermal time model gave the best fit for Montpellier, France, and was the most effective at the regional scale, providing reasonable predictions for 10 sites in the western Mediterranean. This model was forced with replicated future temperature simulations for the western Mediterranean from a coupled ocean‐atmosphere general circulation model (GCM). The GCM temperatures rose by 4·5 °C between 1990 and 2099 with a 1% per year increase in greenhouse gases, and modelled flowering date advanced at a rate of 6·2 d per °C. The results indicated that this long‐term regional trend in phenology might be statistically significant as early as 2030, but with marked spatial variation in magnitude, with the calculated flowering date between the 1990s and 2030s advancing by 3–23 d. Future monitoring of airborne olive pollen may therefore provide an early biological indicator of climatic warming in the Mediterranean. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Plant Cell & Environment Wiley

Olive phenology as a sensitive indicator of future climatic warming in the Mediterranean

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Publisher
Wiley
Copyright
"Copyright © 2000 Wiley Subscription Services, Inc., A Wiley Company"
ISSN
0140-7791
eISSN
1365-3040
DOI
10.1046/j.1365-3040.2000.00584.x
Publisher site
See Article on Publisher Site

Abstract

Experimental and modelling work suggests a strong dependence of olive flowering date on spring temperatures. Since airborne pollen concentrations reflect the flowering phenology of olive populations within a radius of 50 km, they may be a sensitive regional indicator of climatic warming. We assessed this potential sensitivity with phenology models fitted to flowering dates inferred from maximum airborne pollen data. Of four models tested, a thermal time model gave the best fit for Montpellier, France, and was the most effective at the regional scale, providing reasonable predictions for 10 sites in the western Mediterranean. This model was forced with replicated future temperature simulations for the western Mediterranean from a coupled ocean‐atmosphere general circulation model (GCM). The GCM temperatures rose by 4·5 °C between 1990 and 2099 with a 1% per year increase in greenhouse gases, and modelled flowering date advanced at a rate of 6·2 d per °C. The results indicated that this long‐term regional trend in phenology might be statistically significant as early as 2030, but with marked spatial variation in magnitude, with the calculated flowering date between the 1990s and 2030s advancing by 3–23 d. Future monitoring of airborne olive pollen may therefore provide an early biological indicator of climatic warming in the Mediterranean.

Journal

Plant Cell & EnvironmentWiley

Published: Jul 1, 2000

Keywords: ; ; ; ;

References

  • Thermal time, chill days and prediction of budburst in Picea sitchensis.
    Cannell, M.G.R.; Smith, R.I.
  • Problem Solving: A Statistician’s Guide.
    Chatfield, C.
  • Fitting models predicting dates of flowering of temperate‐zone trees using simulated annealing.
    Chuine, I.; Cour, P.; Rousseau, D.D.
  • Inflorescence formation in olive as influenced by low temperature, photoperiod, and leaf area.
    Hackett, W.P.; Hartmann, H.T.
  • Genetic structure and patterns of genetic variation among populations in eastern white spruce (Picea glauca).
    Li, P.; Beaulieu, J.; Bousquet, J.
  • Phenology and Seasonality Modelling.
    Lieth, H.
  • Adaptive variation in jack pine from north central Ontario determined by short‐term common garden tests.
    Van Niejenhuis, A.; Parker, W.H.
  • Genetic variation in the olive tree (Olea europaea L.) cultivated in Morocco.
    Ouazzani, N.; Lumaret, R.; Villemur, P.
  • The incidence of Olea pollen in Portugal in five consecutive years.
    Pinto da Silva, Q.G.

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