Forecasting phenology under global warming

Inés Ibáñez, Richard B. Primack, Abraham J. Miller-Rushing, Elizabeth Ellwood, Hiroyoshi Higuchi, Sang Don Lee, Hiromi Kobori, John A. Silander

Research output: Contribution to journalArticlepeer-review

192 Scopus citations

Abstract

As a consequence of warming temperatures around the world, spring and autumn phenologies have been shifting, with corresponding changes in the length of the growing season. Our understanding of the spatial and interspecific variation of these changes, however, is limited. Not all species are responding similarly, and there is significant spatial variation in responses even within species. This spatial and interspecific variation complicates efforts to predict phenological responses to ongoing climate change, but must be incorporated in order to build reliable forecasts. Here, we use a long-term dataset (1953-2005) of plant phenological events in spring (flowering and leaf out) and autumn (leaf colouring and leaf fall) throughout Japan and South Korea to build forecasts that account for these sources of variability. Specifically, we used hierarchical models to incorporate the spatial variability in phenological responses to temperature to then forecast species' overall and site-specific responses to global warming. We found that for most species, spring phenology is advancing and autumn phenology is getting later, with the timing of events changing more quickly in autumn compared with the spring. Temporal trends and phenological responses to temperature in East Asia contrasted with results from comparable studies in Europe, where spring events are changing more rapidly than are autumn events. Our results emphasize the need to study multiple species at many sites to understand and forecast regional changes in phenology.

Original languageEnglish
Pages (from-to)3247-3260
Number of pages14
JournalPhilosophical Transactions of the Royal Society B: Biological Sciences
Volume365
Issue number1555
DOIs
StatePublished - 12 Oct 2010

Keywords

  • Climate change
  • East Asia, global warming
  • Growing season, hierarchical bayes
  • Plant phenology

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