A Practical Approach for Uncertainty Quantification of High Frequency Soil Respiration Using Forced Diffusion Chambers

Abstract:

This presentation examines the sources of uncertainty for the Forced Diffusion (FD) chamber soil respiration (R_s) measurement technique, and demonstrates a protocol for uncertainty quantification that could be appropriate with any soil flux technique. Here, we sought to quantify and compare the three primary sources of uncertainty in R_s: (1) instrumentation error, (2) scaling error, defined as spatial variability of R_s across an ecosystem, and (3) random error, defined as the temporal variability of R_s at a single location, under a narrow temperature, moisture, and time range. In laboratory studies, we found that FD instrumentation error remained constant as R_s increased. In field studies from five North American ecosystems, we found that as R_s increased from winter to peak growing season, scaling error increased by about 50% of average R_s, and random error was about 40% of average R_s. Random error, which is the residual temporal variability left unexplained by soil temperature and moisture, not only scales with soil flux, but scales in a consistent way (same slope) across ecosystems. Our findings are consistent with previous findings for both soil fluxes and eddy covariance fluxes across other Northern temperate ecosystems that showed random error scales linearly with flux magnitude with a slope of ~0.2. Although the mechanistic basis for this scaling is unknown, is a suggestive of a broadly applicable rule for the scaling of flux error. Also consistent with previous studies, we found the random error of FD follows a Laplace (double-exponential) rather than a normal (Gaussian) distribution.