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Sensitivity of migratory connectivity estimates to spatial sampling design.

Stephen H Vickers1, Aldina M A Franco2, James J Gilroy2

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Statistical methods for migratory connectivity, like Mantel correlations, are sensitive to sampling design. Biased sampling can lead to inaccurate connectivity estimates, especially in populations with low connectivity.

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Mantel testMigrationMigratory connectivityMigratory spreadSampling bias

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Area of Science:

  • Ecology
  • Conservation Biology
  • Quantitative Biology

Background:

  • Statistical methods are widely used to assess migratory connectivity.
  • However, their sensitivity to spatial sampling designs and scales of inference is often overlooked.

Purpose of the Study:

  • To examine biases and imprecision in Mantel correlations due to various sampling designs.
  • To understand how spatial sampling affects the accuracy of migratory connectivity estimates.

Main Methods:

  • Simulated migratory populations under diverse sampling regimes.
  • Analysis of Mantel correlations, a common method for quantifying migratory connectivity.

Main Results:

  • Mantel correlations are highly dependent on spatial sampling scale and configuration.
  • Contiguous sampling can underestimate connectivity, while discrete sampling may overestimate it.
  • Bias severity increases with lower true population connectivity; accuracy improves with more, evenly spread sampling sites.

Conclusions:

  • Mantel statistics can introduce significant bias and imprecision in migratory connectivity inferences.
  • Researchers should limit inferences to their sampling extent, increase site numbers, and use caution with small sample sizes.