Forecasting phenology: from species variability to community patterns

Authors

  • Jeffrey M. Diez,

    Corresponding author
    1. School of Natural Resources and the Environment, University of Michigan, Ann Arbor, MI 48109, USA
      E-mail: jeffdiez@gmail.com
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  • Inés Ibáñez,

    1. School of Natural Resources and the Environment, University of Michigan, Ann Arbor, MI 48109, USA
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  • Abraham J. Miller-Rushing,

    1. National Park Service, Schoodic Education and Research Center and Acadia National Park, Winter Harbor, ME 04693, USA
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  • Susan J. Mazer,

    1. Ecology, Evolution and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
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  • Theresa M. Crimmins,

    1. Office of Arid Lands Studies, University of Arizona, Tucson, AZ 85721, USA
    2. USA National Phenology Network, Tucson, AZ 85721, USA
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  • Michael A. Crimmins,

    1. Department of Soil, Water and Environmental Science, University of Arizona, PO Box 210038 Tucson, AZ 85721-0038, USA
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  • C. David Bertelsen,

    1. Herbarium, University of Arizona, PO Box 210036, University of Arizona, Tucson, AZ 85721-0036, USA
    2. School of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USA
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  • David W. Inouye

    1. Rocky Mountain Biological Laboratory, PO Box 519, Crested Butte, CO 81224, USA
    2. Department of Biology, University of Maryland, College Park, MD 20742-4415, USA
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E-mail: jeffdiez@gmail.com

Abstract

Ecology Letters (2012)

Abstract

Shifts in species’ phenology in response to climate change have wide-ranging consequences for ecological systems. However, significant variability in species’ responses, together with limited data, frustrates efforts to forecast the consequences of ongoing phenological changes. Herein, we use a case study of three North American plant communities to explore the implications of variability across levels of organisation (within and among species, and among communities) for forecasting responses to climate change. We show how despite significant variation among species in sensitivities to climate, comparable patterns emerge at the community level once regional climate drivers are accounted for. However, communities differ with respect to projected patterns of divergence and overlap among their species’ phenological distributions in response to climate change. These analyses and a review of hypotheses suggest how explicit consideration of spatial scale and levels of biological organisation may help to understand and forecast phenological responses to climate change.

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