International Journal of Biometeorology

, Volume 56, Issue 1, pp 153–164 | Cite as

Bayesian calibration of the Unified budburst model in six temperate tree species

  • Yongshuo H. Fu
  • Matteo Campioli
  • Gaston Demarée
  • Alex Deckmyn
  • Rafiq Hamdi
  • Ivan A. Janssens
  • Gaby Deckmyn
Original Paper

Abstract

Numerous phenology models developed to predict the budburst date of trees have been merged into one Unified model (Chuine, 2000, J. Theor. Biol. 207, 337–347). In this study, we tested a simplified version of the Unified model (Unichill model) on six woody species. Budburst and temperature data were available for five sites across Belgium from 1957 to 1995. We calibrated the Unichill model using a Bayesian calibration procedure, which reduced the uncertainty of the parameter coefficients and quantified the prediction uncertainty. The model performance differed among species. For two species (chestnut and black locust), the model showed good performance when tested against independent data not used for calibration. For the four other species (beech, oak, birch, ash), the model performed poorly. Model performance improved substantially for most species when using site-specific parameter coefficients instead of across-site parameter coefficients. This suggested that budburst is influenced by local environment and/or genetic differences among populations. Chestnut, black locust and birch were found to be temperature-driven species, and we therefore analyzed the sensitivity of budburst date to forcing temperature in those three species. Model results showed that budburst advanced with increasing temperature for 1–3 days °C−1, which agreed with the observed trends. In synthesis, our results suggest that the Unichill model can be successfully applied to chestnut and black locust (with both across-site and site-specific calibration) and to birch (with site-specific calibration). For other species, temperature is not the only determinant of budburst and additional influencing factors will need to be included in the model.

Keywords

Tree budburst Phenology Bayesian calibration Unichill model 

Supplementary material

484_2011_408_MOESM1_ESM.doc (18 kb)
ESM 1Online Resource (DOC 18 kb)

Reference

  1. Baldocchi DD, Wilson KB (2001) Modelling CO2 and water vapour exchange of a temperate broadleaved forest across hourly to decadal time scales. Ecol Model 142:155–184CrossRefGoogle Scholar
  2. Cannell MGR, Smith RI (1983) Thermal time, chill days and prediction of budburst in Picea-Sitchensis. J Appl Ecol 20:951–963CrossRefGoogle Scholar
  3. Chen X (1994) Untersuchung zur zeitlich-räumlichen Ähnlichkeit von phänologischen und klimatologischen Parametern in Westdeutschland und zum Einfluß geooekologischer Faktoren auf die phänologische Entwicklung imGebiet des Taunus, Ber Dtsch Wetterdienst 189, Offenbacham MainGoogle Scholar
  4. Chuine I (2000) A unified model for budburst of trees. J Theor Biol 207:337–347CrossRefGoogle Scholar
  5. Chuine I, Kramer K, Hänninen H (2003) Plant development models. In: Schwartz MD (ed) Phenology: an integrative environmental science. Kluwer, Dordrecht, pp 305–333Google Scholar
  6. Cleland EE, Chuine I, Menzel A, Mooney HA, Schwartz MD (2007) Shifting plant phenology in response to global change. Trends Ecol Evol 22:357–365CrossRefGoogle Scholar
  7. Demarée GR, Chuine I (2006) A concise history of the phenological observations at the Royal Meteorological Institute of Belgium. In: Actes du ESF exploratory workshop. Phenology and agroclimatology. Volos, Greece 21-23 Sep 2006Google Scholar
  8. Demarée GR, Rutishauser T (2009) Origins of the word “phenology”, Eos Trans. AGU 90(34), doi:10.1029/2009EO340004
  9. Falusi M, Calamassi R (1990) Bud dormancy in beech (Fagus sylvatica L.), Effect of chilling and photoperiod on dormancy release of beech seedlings. Tree Physiol 6:429–438Google Scholar
  10. Friedel MH, Nelson DJ, Sparrow AD, Kinloch JE, Maconochie JR (1993) What induces central Australian arid zone trees and shrubs to flower and fruit Australian. Aust J Bot 41:307–319CrossRefGoogle Scholar
  11. Hänninen H (1990) Modelling bud dormancy release in trees from cool and temperate regions. Acta For Fenn 213:1–47Google Scholar
  12. Hänninen H, Beuker E, Johnsen O, Leinonen I, Murray M, Sheppard L, Skroppa T (2001) Impacts of climate change on cold hardiness of conifers. In: Bigras FJ, Colombo SJ (eds) Conifer cold hardiness. Kluwer, Dordrecht, pp 305–333Google Scholar
  13. Heide OM (1993) Daylength and thermal time responses of budburst during dormancy release in some northern deciduous trees. Physiol Plant 88:531–540CrossRefGoogle Scholar
  14. Kobayashi KD, Fuchigami LH, English MJ (1982) Modelling temperature requirements for rest development in Cornus-Sericea. J Am Soc Hortic Sci 107:914–918Google Scholar
  15. Kramer K (1994) A modeling analysis of the effects of climatic warming on the probability of spring frost damage to tree species in the Netherlands and Germany. Plant Cell Environ 17:367–377CrossRefGoogle Scholar
  16. Landsberg JJ (1974) Apple fruit bud development and growth analysis and an empirical model. Ann Bot 38:1013–1023Google Scholar
  17. Lavender DP (1981) Environment and shoot growth of woody plants. Oregon State Univ For Res Lab Res Paper 45Google Scholar
  18. Linkosalo T, Lechowicz MJ (2006) Twilight far-red treatment advances leaf bud burst of silver birch (Betula pendula). Tree Physiol 26:1249–1256CrossRefGoogle Scholar
  19. Linkosalo T, Lappalainen HK, Hari P (2008) A comparison of phenological models of leaf bud burst and flowering of boreal trees using independent observations. Tree Physiol 28:1873–1882CrossRefGoogle Scholar
  20. Matsumoto K, Ohta T, Irasawa M, Nakamura T (2003) Climate change and extension of the Ginkgo biloba L. growing season in Japan. Glob Change Biol 9:1634–1642CrossRefGoogle Scholar
  21. Menzel A (2002) Phenology: Its importance to the global change community - An editorial comment. Clim Change 54:379–385CrossRefGoogle Scholar
  22. Murray MB, Cannell MGR, Smith RI (1989) Date of budburst of 15 tree species in Britain following climatic warming. J Appl Ecol 26:693–700CrossRefGoogle Scholar
  23. Nelson EA, Lavender DP (1979) The chilling requirement of western hemlock seedlings. For Sci 25:485–490Google Scholar
  24. Nizinski J, Saugier B (1988) A model of leaf budding and development for a mature Quercus forest. J Appl Ecol 25:643–652CrossRefGoogle Scholar
  25. Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (2007) Climate Change: Impacts, Adapation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University PressGoogle Scholar
  26. Partanen J, Koski V, Hänninen H (1998) Effects of photoperiod and temperature on the timing of bud burst in Norway spruce (Picea abies). Tree Physiol 18:811–816Google Scholar
  27. Phillips OL, Lewis SL, Baker TR, Chao KJ, Higuchi N (2008) The changing Amazon forest. Philos Trans R Soc Lond B 363:1819–1827CrossRefGoogle Scholar
  28. Piao SL, Ciais P, Friedlingstein P, Peylin P, Reichstein M, Luyssaert S, Margolis H, Fang JY, Barr A, Chen A et al (2008) Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature 451:49–52CrossRefGoogle Scholar
  29. Robert C, Casella G (2004) Monte Carlo statistical methods. Springer, New YorkGoogle Scholar
  30. Rotzer T (1996) A new kind of phenology- and water balance-maps of Bavaria in regard to possible future climate change. Dissertation, Technical University, MunchenGoogle Scholar
  31. Rotzer T, Chmielewski FM (2001) Phenological maps of Europe. Clim Res 18:249–257CrossRefGoogle Scholar
  32. Samish RM (1954) Dormancy in woody plants. Annu Rev Plant Physiol 5:183–204CrossRefGoogle Scholar
  33. Schnelle F (1955) Pflanzen-Phänologie. Geest and Portig, LeipzigGoogle Scholar
  34. Seiwa K (1999) Changes in leaf phenology are dependent on tree height in Acer mono, a deciduous broad-leaved tree. Ann Bot 83:355–361CrossRefGoogle Scholar
  35. Snyder RL, Spano D, Duce P, Cesaraccio C (2001) Temperature data for phenological models. Int J Biometeorol 45:178–183CrossRefGoogle Scholar
  36. Sparks TH, Menzel A, Stenseth NC (2009) European cooperation in plant phenology. Clim Res 39:175–177CrossRefGoogle Scholar
  37. Van Dongen S (2006) Prior specification in Bayesian statistics: three cautionary tales. J Theor Biol 242:90–100CrossRefGoogle Scholar
  38. Van Oijen M, Rougier J, Smith R (2005) Bayesian calibration of process-based forest models: bridging the gap between models and data. Tree Physiol 25:915–927Google Scholar
  39. Vegis A (1964) Dormancy in higher plants. Annu Rev Plant Physiol 15:185–224CrossRefGoogle Scholar
  40. Vitasse Y, Delzon S, Dufrêne E, Pontailler JY, Louvet JM, Kremer A, Michalet R (2009) Leaf phenology sensitivity to temperature in European trees: do within-species populations exhibit similar responses? Agric For Meteorol 149:735–744CrossRefGoogle Scholar
  41. Wareing PF (1969) The control of bud dormancy in seed plants. In: Woolhouse HW (ed) Dormancy and survival. Symposia of the society for experimental biology 23:241-262Google Scholar
  42. Wielgolaski FE (2001) Phenological modifications in plants by various edaphic factors. Int J Biometeorol 45:196–202CrossRefGoogle Scholar

Copyright information

© ISB 2011

Authors and Affiliations

  • Yongshuo H. Fu
    • 1
  • Matteo Campioli
    • 1
  • Gaston Demarée
    • 2
  • Alex Deckmyn
    • 2
  • Rafiq Hamdi
    • 2
  • Ivan A. Janssens
    • 1
  • Gaby Deckmyn
    • 1
  1. 1.Department of BiologyUniversity of AntwerpenWilrijkBelgium
  2. 2.Royal MeteorologicalInstitute of BelgiumBrusselsBelgium

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