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Open Access Publications from the University of California

Depth-Resolved Physicochemical Characteristics of Active Layer and Permafrost Soils in an Arctic Polygonal Tundra Region

  • Author(s): Wu, Y
  • Ulrich, C
  • Kneafsey, T
  • Lopez, R
  • Chou, C
  • Geller, J
  • McKnight, K
  • Dafflon, B
  • Soom, F
  • Peterson, J
  • Hubbard, S
  • et al.

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©2018. The Authors. Permafrost physicochemical parameters play a key role in controlling the response of permafrost carbon to climate change. We studied the physicochemical parameters of permafrost in an Arctic tundra region to evaluate (1) how soil parameters vary with depth and whether and how they are interrelated, (2) whether and how permafrost soil differs from its overlaying active layer, and (3) whether soil property-depth relationships are different across geomorphic features (e.g., low, flat, and high centered polygons). We also explored the possible biogeochemical processes that led to these soil characteristics and how they may affect biogeochemical reactions upon permafrost thaw. We observed (1) consistent relationships between soil property and depth and between major parameters, (2) large contrasts of key soil parameters between active layer and permafrost, indicative of potentially different response of the permafrost carbon to warming when compared to the active layer, and (3) a correlation between soil hydraulic conductivity and topographic features that impacts soil hydrologic processes. Our analysis suggests that the permafrost has a marine-derived chemical signature that differs from the active layer and shapes the physicochemical fingerprints of the different geomorphic features. Specifically, we revealed the unique signatures of the high center polygons, indicative of possible microbial activity at depth (>1 m). Our study suggested consistent key soil parameter-depth correlations while demonstrating complex lateral and vertical variabilities. These results are valuable for identifying approaches to upscale point-based measurements and for improving model parameterization to predict permafrost carbon behavior and feedback under future climate.

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