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Phylogenetic estimates of species-level phenology improve ecological forecasting

Author

Listed:
  • Ignacio Morales-Castilla

    (University of Alcalá)

  • T. J. Davies

    (University of British Columbia
    University of British Columbia)

  • Geoffrey Legault

    (University of British Columbia)

  • D. M. Buonaiuto

    (Harvard University
    Arnold Arboretum of Harvard University
    University of Massachusetts–Amherst)

  • Catherine J. Chamberlain

    (Harvard University
    Arnold Arboretum of Harvard University
    The Nature Conservancy)

  • Ailene K. Ettinger

    (Arnold Arboretum of Harvard University
    The Nature Conservancy of Washington)

  • Mira Garner

    (University of British Columbia)

  • Faith A. M. Jones

    (University of British Columbia
    Swedish University of Agricultural Sciences)

  • Deirdre Loughnan

    (University of British Columbia)

  • William D. Pearse

    (Imperial College London)

  • Darwin S. Sodhi

    (University of British Columbia)

  • E. M. Wolkovich

    (University of British Columbia
    Harvard University
    Arnold Arboretum of Harvard University)

Abstract

The ability to adapt to climate change requires accurate ecological forecasting. Current forecasts, however, have failed to capture important variability in biological responses, especially across species. Here we present a new method using Bayesian hierarchical phylogenetic models and show that species-level differences are larger than the average differences between cues. Applying our method to phenological experiments manipulating temperature and day length we show an underlying phylogenetic structure in plant phenological responses to temperature cues, whereas responses to photoperiod appear weaker, more uniform across species and less phylogenetically constrained. We thus illustrate how a focus on certain clades can bias prediction, but that predictions may be improved by integrating information on phylogeny to better estimate species-level responses. Our approach provides an advance in ecological forecasting, with implications for predicting the impacts of climate change and other anthropogenic forces on ecosystems.

Suggested Citation

  • Ignacio Morales-Castilla & T. J. Davies & Geoffrey Legault & D. M. Buonaiuto & Catherine J. Chamberlain & Ailene K. Ettinger & Mira Garner & Faith A. M. Jones & Deirdre Loughnan & William D. Pearse & , 2024. "Phylogenetic estimates of species-level phenology improve ecological forecasting," Nature Climate Change, Nature, vol. 14(9), pages 989-995, September.
  • Handle: RePEc:nat:natcli:v:14:y:2024:i:9:d:10.1038_s41558-024-02102-2
    DOI: 10.1038/s41558-024-02102-2
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