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Stone circles: form and soil kinematics.

Bernard Hallet1

  • 1Quaternary Research Center, Department of Earth and Space Sciences, University of Washington, Seattle, WA, USA. hallet@uw.edu

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Summary

Frost-related processes create distinct soil patterns in polar and alpine regions. This study documents 20 years of soil motion within these self-organizing, geometric formations, aiding model assessment.

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Area of Science:

  • Geosciences
  • Cryospheric Science
  • Soil Science

Background:

  • Distinct surface patterns, such as sorted circles, are common in polar and alpine soils where ground temperatures fluctuate around 0°C.
  • These patterns represent striking examples of abiotic self-organization in nature, driven by physical processes.

Purpose of the Study:

  • To outline the interplay of frost-related physical processes responsible for the spontaneous formation of soil patterns.
  • To present unique, long-term data on subsurface soil rotational motion and surface displacement within sorted circles.
  • To facilitate the assessment of numerical models for sorted circle development through field observations.

Main Methods:

  • Field monitoring of subsurface soil rotational motion and surface displacement over 20 years.
  • Observation of well-developed sorted circles characterized by geometric regularity and gravel ridges.
  • Utilizing recent numerical models to guide and interpret field observations.

Main Results:

  • Documentation of ongoing soil rotational motion and surface displacement within sorted circles.
  • Confirmation of the link between frost-related physical processes and pattern formation.
  • Data suitable for assessing the assumptions and parameters of numerical sorted circle development models.

Conclusions:

  • Frost-related physical processes are key drivers of self-organized soil pattern formation in cold environments.
  • Long-term field data provide crucial insights for validating and refining numerical models of sorted circle development.
  • Synergistic studies combining field observations and numerical modeling hold significant potential for advancing our understanding of these phenomena.