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Harvard Forest REU Symposium Abstract 2023
- Title: Testing whether long-term soil collars are representative of stand-level soil respiration
- Author: Alassane Sow (Michigan State University)
- Abstract:
Measuring soil respiration over time is common across the Long Term Ecological Research network, and this long term record can be used to help investigate changing carbon sinks, or the impact of increased atmospheric CO2 and temperature on overall ecosystem function. Within two eastern hemlock stands (Tsuga canadensis L.) at Harvard Forest, soil respiration is continuously measured when the soil is not frozen. The paired hemlock stands are differentially infested by the Hemlock Wooly Adelgid, an invasive insect that sucks sap from hemlocks resulting in the loss of leaves and branches, and eventual death. Recording soil respiration in these plots can help predict how forest health correlates with its ability to be a carbon sink, and how soil respiration responds to forest succession. Since measurements began in 2015, mean daily soil respiration was consistently higher in the healthier stand. However, respiration is highly variable between chambers. The goal of this study is to investigate if variation within a stand confounds the results from comparison analyses between stands. In this study, 60 PVC collars (30 at each stand) were installed to measure finer-scale soil respiration around the permanent soil collars. The data was used in kriging interpolations to map respiration across the 16m2 plots surrounding the permanent soil respiration collars. Within each plot, we also conducted plant surveys to identify species presence and abundance. We found that placement of collars adjacent to live trees increased respiration rates. Microscale variations did not confound the results of comparison analysis but interpolation could be a powerful tool to choose best sampling locations. Our results emphasize that landscape variation can modify soil respiration rates and our ability to reliably scale plot-level data.
- Research Category: Soil Carbon and Nitrogen Dynamics; Ecological Informatics and Modelling
