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Seasonality, density dependence, and spatial population synchrony.

Pedro G Nicolau1, Rolf A Ims2, Sigrunn H Sørbye1

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Season-specific density dependence significantly shapes population synchrony. Accounting for this and climate change impacts helps disentangle ecological dynamics and predict future population trends.

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Area of Science:

  • Ecology
  • Population Dynamics
  • Climate Change Research

Background:

  • Spatial population synchrony is key to understanding ecological dynamics.
  • Climate change impacts on populations are a growing research focus.
  • Seasonality and density dependence influence local populations, but their role in large-scale synchrony is understudied.

Purpose of the Study:

  • To develop a protocol for analyzing season and context-specific density dependence in population synchrony.
  • To elucidate the roles of deterministic and stochastic factors in population synchrony.
  • To investigate the impact of climate warming on population dynamics.

Main Methods:

  • Developed an analytical protocol to account for season-specific density dependence.
  • Applied the protocol to seasonal (spring and fall) rodent population time-series data.
  • Differentiated between deterministic (season-specific density dependence) and stochastic (weather events) synchrony drivers.

Main Results:

  • Season-specific density dependence is a major driver of population synchrony.
  • Mild winter weather events, amplified by climate warming, directly and indirectly impact vole populations.
  • The Moran effect is enhanced by these weather events.

Conclusions:

  • Seasonally sampled data and appropriate models can disentangle climate change impacts on population synchrony.
  • Understanding season-specific density dependence is crucial for predicting ecological responses to warming.
  • The developed protocol offers a framework for analyzing complex population dynamics under environmental change.