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Predictability in community dynamics.

Benjamin Blonder1,2, Derek E Moulton3, Jessica Blois4

  • 1Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY, UK.

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Summary
This summary is machine-generated.

Community composition can respond to climate change with varying time lags. Complex dynamics, including memory effects and alternate states, are possible and may hinder future predictions.

Keywords:
Alternate stateschaosclimate changecommunity assemblycommunity climatecommunity response diagramdisequilibriumhysteresislagmemory effects

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Area of Science:

  • Ecology
  • Climate Change Science
  • Ecological Modeling

Background:

  • The relationship between community composition and climate change is fundamental to ecological understanding.
  • Existing models often assume no or simple time lags in community responses.
  • Disequilibrium ecology highlights the importance of time delays in ecological tracking.

Purpose of the Study:

  • To investigate the spectrum of temporal dynamics in community responses to climate change.
  • To develop methods for assessing complex community dynamics beyond simple lag hypotheses.
  • To understand the implications of these dynamics for ecological prediction.

Main Methods:

  • Development of graphical and analytical methods to assess community dynamics.
  • Modeling of ecological scenarios to explore lag effects.
  • Analysis of the relationship between past climate, community states, and future predictions.

Main Results:

  • Community responses to climate change can exhibit a wide range of time lags, from none to complex.
  • Complex dynamics, including memory effects and potential for alternate unstable states, can arise even in simple models.
  • The presence of complex dynamics complicates predictions of future community states.

Conclusions:

  • Complex community dynamics in response to climate change may be more common than previously assumed.
  • Accurate prediction of future community states often requires detailed historical climate and community data.
  • Even with extensive historical data, predicting future community states can remain challenging due to complex dynamics.