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Bayesian comparison of six different temperature-based budburst models for four temperate tree species

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  • Fu, Yongshuo H.
  • Campioli, Matteo
  • Van Oijen, Marcel
  • Deckmyn, Gaby
  • Janssens, Ivan A.

Abstract

Phenology models are tools to analyze changes in the timing and duration of the growing season. During the past three decades different budburst models have been developed, but, so far, no consensus model has been found to accurately predict budburst date across different tree species. The aim of this study was to estimate the performance of six different temperature-driven models of leaf budburst (thermal time, thermal period fixed, sequential, parallel, alternating, unified) for four temperate tree species in Belgium (birch, chestnut, oak, beech). The models were parameterized using a Bayesian approach. The performance of these models was compared using Bayesian model comparison (BMC) and root mean square error (RMSE).

Suggested Citation

  • Fu, Yongshuo H. & Campioli, Matteo & Van Oijen, Marcel & Deckmyn, Gaby & Janssens, Ivan A., 2012. "Bayesian comparison of six different temperature-based budburst models for four temperate tree species," Ecological Modelling, Elsevier, vol. 230(C), pages 92-100.
    • Handle: RePEc:eee:ecomod:v:230:y:2012:i:c:p:92-100
    DOI: 10.1016/j.ecolmodel.2012.01.010
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    References listed on IDEAS

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    1. Tuomi, Mikko & Vanhala, Pekka & Karhu, Kristiina & Fritze, Hannu & Liski, Jari, 2008. "Heterotrophic soil respiration—Comparison of different models describing its temperature dependence," Ecological Modelling, Elsevier, vol. 211(1), pages 182-190.
    2. Ben D. MacArthur & Richard O. C. Oreffo, 2005. "Bridging the gap," Nature, Nature, vol. 433(7021), pages 19-19, January.
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    1. Olsson, Cecilia & Bolmgren, Kjell & Lindström, Johan & Jönsson, Anna Maria, 2013. "Performance of tree phenology models along a bioclimatic gradient in Sweden," Ecological Modelling, Elsevier, vol. 266(C), pages 103-117.
    2. Yun, Kyungdahm & Hsiao, Jennifer & Jung, Myung-Pyo & Choi, In-Tae & Glenn, D. Michael & Shim, Kyo-Moon & Kim, Soo-Hyung, 2017. "Can a multi-model ensemble improve phenology predictions for climate change studies?," Ecological Modelling, Elsevier, vol. 362(C), pages 54-64.

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