4.7 Article

Modelling cold hardening and dehardening in timothy. Sensitivity analysis and Bayesian model comparison

Journal

AGRICULTURAL AND FOREST METEOROLOGY
Volume 150, Issue 12, Pages 1529-1542

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.agrformet.2010.08.001

Keywords

Modelling; Frost tolerance; Timothy; Bayesian calibration; Sensitivity analysis

Funding

  1. Norwegian Research council

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Timothy (Phleum pratense L) is the most important forage grass in Scandinavia and it is therefore highly interesting to study how it will perform in a changing climate. In order to model winter survival, the dynamics of hardening and dehardening must be simulated with satisfactory precision. We investigated an early timothy frost tolerance model (LT50 model), and an LT50 model for winter wheat. Based on the assumption that timothy has no vernalization requirement, unlike winter wheat, but does have the ability to adapt to cold temperatures in a process linked to stage of development, two alternative versions of the winter wheat model were also constructed. In total, these four candidate models were calibrated by a Bayesian approach for the timothy cultivar Engmo. The candidate models were validated using independent observations on LT50 in timothy at different locations reflecting differences in climate. A sensitivity analysis, using the Morris method, to identify important model parameters suggested that there is a connection between frost tolerance and stage of plant development, even if there is no vernalization requirement. The simplified winter wheat model was selected as the best candidate model for LT50 in timothy based on model selection criteria and its ability to capture the hardening and dehardening processes. The results from the Bayesian calibration suggest that there are no major regional differences in Norway calling for regional calibration. However, cultivar-specific calibration is probably required, since there are hardy and less hardy cultivars within the same species. A functional LT50 model would allow risk assessments to be made of future winter survival using specifically tailored and downscaled climate scenarios. (C) 2010 Elsevier B.V. All rights reserved.

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