10 Jul 2024

Seasonal Variation in Near-Surface Seasonally Thawed Active Layer and Permafrost Soil Microbial Communities

Abstract: Understanding how soil microbes respond to permafrost thaw is critical to predicting the implications of climate change for soil processes. However, our knowledge of microbial responses to warming is mainly based on laboratory thaw experiments, and field sampling in warmer months when sites are more accessible. In this study, we sampled a depth profile through seasonally thawed active layer and permafrost in the Imnavait Creek Watershed, Alaska, USA over the growing season from summer to late fall. Amplicon sequencing showed that bacterial and fungal communities differed in composition across both sampling depths and sampling months. Surface communities were most variable while those from the deepest samples, which remained frozen throughout our sampling period, showed little to no variation over time. However, community variation was not explained by trace metal concentrations, soil nutrient content, pH, or soil condition (frozen/thawed), except insofar as those measurements were correlated with depth. Our results highlight the importance of collecting samples at multiple times throughout the year to capture temporal variation, and suggest that data from across the annual freeze-thaw cycle might help predict microbial responses to permafrost thaw.

25 Jun 2020

PUBLICATION NOTICE: A Generalized Approach for Modeling Creep of Snow Foundations

ABSTRACT:  When an external load is applied, snow will continue to deform in time, or creep, until the load is removed. When using snow as a foundation material, one must consider the time-dependent nature of snow mechanics to understand its long-term structural performance. In this work, we develop a general approach for predicting the creep behavior of snow. This new approach spans the primary (nonlinear) to secondary (linear) creep regimes. Our method is based on a uniaxial rheological Burgers model and is extended to three dimensions. We parameterize the model with density- and temperature-dependent constants that we calculate from experimental snow creep data. A finite element implementation of the multiaxial snow creep model is derived, and its inclusion in an ABAQUS user material model is discussed. We verified the user material model against our analytical snow creep model and validated our model against additional experimental data sets. The results show that the model captures the creep behavior of snow over various time scales, temperatures, densities, and external loads. By furthering our ability to more accurately predict snow foundation movement, we can help prevent unexpected failures and extend the useful lifespan of structures that are constructed on snow.