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Trends and uncertainties in budburst projections of Norway spruce in Northern Europe

Author:
  • Cecilia Olsson
  • Stefan Olin
  • Johan Lindström
  • Anna Maria Jönsson
Publishing year: 2017-12-01
Language: English
Pages: 9954-9969
Publication/Series: Ecology and Evolution
Volume: 7
Issue: 23
Document type: Journal article
Publisher: Wiley-Blackwell

Abstract english

Budburst is regulated by temperature conditions, and a warming climate is associated with earlier budburst. A range of phenology models has been developed to assess climate change effects, and they tend to produce different results. This is mainly caused by different model representations of tree physiology processes, selection of observational data for model parameterization, and selection of climate model data to generate future projections. In this study, we applied (i) Bayesian inference to estimate model parameter values to address uncertainties associated with selection of observational data, (ii) selection of climate model data representative of a larger dataset, and (iii) ensembles modeling over multiple initial conditions, model classes, model parameterizations, and boundary conditions to generate future projections and uncertainty estimates. The ensemble projection indicated that the budburst of Norway spruce in northern Europe will on average take place 10.2 ± 3.7 days earlier in 2051–2080 than in 1971–2000, given climate conditions corresponding to RCP 8.5. Three provenances were assessed separately (one early and two late), and the projections indicated that the relationship among provenance will remain also in a warmer climate. Structurally complex models were more likely to fail predicting budburst for some combinations of site and year than simple models. However, they contributed to the overall picture of current understanding of climate impacts on tree phenology by capturing additional aspects of temperature response, for example, chilling. Model parameterizations based on single sites were more likely to result in model failure than parameterizations based on multiple sites, highlighting that the model parameterization is sensitive to initial conditions and may not perform well under other climate conditions, whether the change is due to a shift in space or over time. By addressing a range of uncertainties, this study showed that ensemble modeling provides a more robust impact assessment than would a single phenology model run.

Keywords

  • Evolutionary Biology
  • Climate Research
  • Bayesian inference
  • climate models
  • International Phenological Gardens
  • phenology models
  • Picea abies
  • provenance

Other

Published
  • ISSN: 2045-7758
E-mail: anna_maria [dot] jonsson [at] nateko [dot] lu [dot] se

Professor

Dept of Physical Geography and Ecosystem Science

+46 46 222 94 10

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Senior lecturer

Dept of Physical Geography and Ecosystem Science

+46 46 222 94 10

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Teaching staff

Dept of Physical Geography and Ecosystem Science

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Department of Physical Geography and Ecosystem Science
Lund University
Sölvegatan 12
S-223 62 Lund
Sweden

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