Assessing forest soil disturbance and headwater stream restoration in managed northeastern U.S. forests

Sophia Katerina Larson

doi:10.17918/00011512

The health of harvested forest systems depends heavily on the condition of their forest soils and headwater streams, but methods used to monitor and restore these resources have received limited quantitative evaluation. Harvesting (logging) trees in U.S. Forest systems must be conducted in a sustainable manner so that forest regrowth and long-term ecosystem functions are maintained. This dissertation presents three studies which address this gap across two forested ecosystems. The first two assess the U.S. Forest Service Soil Disturbance Monitoring Protocol (FSDMP) as a predictor of soil physical and chemical properties in post-timber harvested areas within the Green Mountain National Forest, Vermont. In the first study, a field-based exploration, soil, and forest floor samples were collected across all four FSDMP disturbance classes at three study sites, yielding 107 soil cores and 390 subsamples. The FSDMP disturbance class was a reliable predictor of soil properties across all study areas, with consistent declines from low to high disturbance classes for bulk density, forest floor organic carbon, and total nitrogen. Soil organic carbon showed no consistent response to FSDMP class disturbance, while soil nitrogen did, but only at the most severe FSDMP class. Instead of the continuous four-class disturbance gradient used in the current FSDMP, an alternative framework is proposed here to simplify the FSDMP. Findings from this work support the alternative two-group class framework, with one FSDMP class showing low disturbance and the other showing high disturbance. The second study was a modeling-based effort that identified predictors of FSDMP class assignments drawn from over one thousand FSDMP survey points between 2015-2022. FSDMP field-collected indicators were found to be the main drivers of FSDMP class assignment, specifically topsoil displacement and surface compaction. Site geomorphic characteristics from SOLUS100, including depth to bedrock and rock fragment content, were significant predictors across all disturbance classes. In addition, the type of timber harvesting used was also a significant predictor throughout all FSDMP classes. This suggests that sites with certain geomorphic characteristics and harvesting methods are predisposed to higher disturbance risk. Pre-harvest geomorphic characterization may help identify higher-risk sites before timber harvesting operations begin. The third study examined the biogeochemical response of chop-and-drop restoration in forested headwater streams. A multi-scale field sampling design was used that included groups of chop-and-drop structures at the reach and individual scale. Beaver pond systems were then used as a comparison. The study captured variation at the reach and individual scales; however, the chop-and-drop structures did not produce consistent downstream dissolved carbon or nutrient results. Low-flow conditions during the reach scale sampling may have further limited chop-and-drop signal detectability. The two- to six-year-old chop-and-drop structures in this study lacked the organic matter, anaerobic conditions, and hydrologic connectivity that beaver pond signals reflect - conditions that take decades, not years, to develop. Long established beaver pond systems within the same watersheds showed significant downstream carbon and nutrient patterns across nearly all six analytes. These studies highlight the importance of long-term forest ecosystem monitoring and the expectations for what early-stage disturbance and restoration can detect in managed U.S. northeastern forest ecosystems.

Assessing forest soil disturbance and headwater stream restoration in managed northeastern U.S. forests

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Assessing forest soil disturbance and headwater stream restoration in managed northeastern U.S. forests

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