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Spatiotemporal connectivity dynamics in spatially structured populations.

Joseph Drake1,2, Xavier Lambin3, Chris Sutherland1,4

  • 1Department of Environmental Conservation, University of Massachusetts-Amherst, Amherst, MA, USA.

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|July 24, 2022
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Summary
This summary is machine-generated.

Dynamic connectivity, not static, is crucial for understanding metapopulation persistence. Accounting for temporal changes in landscape connectivity and patch occupancy improves ecological models and predictions.

Keywords:
BayesianSPOMcolonization-extinctionmammalpopulation dynamicsspatially realistic metapopulation modelstochastic patch occupancy modelstructural connectivity

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Area of Science:

  • Ecology
  • Population Dynamics
  • Spatial Ecology

Background:

  • Landscape connectivity is key to population persistence but often treated as static.
  • Traditional connectivity measures overlook spatiotemporal population dynamics.
  • Dynamic connectivity, reflecting real-time landscape and population states, offers a more accurate approach.

Purpose of the Study:

  • To test if dynamic connectivity improves spatially explicit occupancy models.
  • To compare static vs. dynamic connectivity metrics in describing metapopulation dynamics.
  • To investigate the impact of temporal variability in connectivity on population persistence.

Main Methods:

  • Utilized a long-term occupancy dataset of water voles (Arvicola amphibius).
  • Developed and compared occupancy models with static and dynamic connectivity metrics.
  • Incorporated temporally varying connectivity based on dynamic patch occupancy states.

Main Results:

  • Demographic weighting using patch occupancy dynamics significantly improved metapopulation models.
  • Temporal variability in connectivity measures is essential for accurately describing population dynamics.
  • Static connectivity assumptions lead to highly variable and potentially inaccurate predictions of metapopulation capacity.

Conclusions:

  • Recognizing and incorporating spatiotemporal variation in connectivity is vital for ecological applications.
  • Dynamic connectivity, linked to ecological state variables, provides superior insights into metapopulation dynamics.
  • Future connectivity modeling should embrace temporal dynamics for more robust predictions.