Novel sampling and modeling approaches for studying soils during and after wildfires

Abstract

Wildfire transforms soil physical, chemical, and biological properties. These changes are integral soil processes in fire-prone terrestrial ecosystems around the world. Although methods for estimating fire energy and impacts aboveground have progressed in recent decades, there remain major challenges in characterizing soil heating and associated effects belowground. Overcoming these challenges is crucial for understanding how fire influences soil carbon storage, biogeochemical cycling, and ecosystem recovery after fires. The work in chapter one explores nitrogen (N) cycling in soils from a case study on the Walker Fire in Northern California, 2019. Previous work has shown that N cycling is transformed by fire but variability in the magnitude and direction of those changes makes generalizing between and within fires challenging. These studies are often complicated by the lack of prefire samples and verified control areas that did not burn. In this case study, I analyzed N cycling in samples from immediately prefire, immediately postfire, and up to nine months after the fire, in both burned and control areas. The burned sampling locations ranged from low to extreme severity. I found that in this system, fire severity and soil moisture interact to control levels of N cycling and availability. These synergistic effects would have been difficult to discern with traditional sampling designs that rely on postfire measurements and space-for-time substitutions to approximate prefire conditions because of the uncertainties inherent from spatial heterogeneity. This work increases our understanding of factors driving N cycling in Sierra Nevada forests and suggests that, when possible, this sampling design should be employed to study future fires. Chapter two proposes a model for soil heating during wildfires. Previous work has shown that the extent and duration of soil heating determines the immediate fire effects on soils. However, measuring soil temperatures during fires is logistically complicated. The resulting dearth of temperature data makes elucidating mechanisms and direct relationships between heating and fire effects challenging. In this chapter, I describe and validate a new field method, called iStakes, that addresses many of the current constraints in measuring soil temperatures. I also explain and validate a modelling framework I designed, called SheFire, which can predict soil temperature over time across soil depths during wildfires. The modeling framework also includes functions to summarize soil heating in a variety of manners and extends soil heating to biological impacts with functions that model soil organism survival at different soil depths. I use data from a case study to demonstrate the utility of iStakes and SheFire. This field method and model make studying the direct effects of fire on soil more streamlined and will help researchers characterize belowground processes that are transformed by fire

    Similar works