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A practical approach for uncertainty quantification of high‐frequency soil respiration using Forced Diffusion chambers
Author(s) -
Lavoie Martin,
Phillips C. L.,
Risk David
Publication year - 2015
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1002/2014jg002773
Subject(s) - eddy covariance , scaling , statistics , flux (metallurgy) , mathematics , environmental science , observational error , covariance , diffusion , range (aeronautics) , soil respiration , atmospheric sciences , standard deviation , random field , soil science , soil water , ecosystem , physics , ecology , chemistry , geometry , biology , organic chemistry , materials science , composite material , thermodynamics
This paper 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, which stems from the spatial variability of R s ; and (3) random error, which arises from stochastic or unpredictable variation in environmental drivers and was quantified from repeated observations 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, random error increased linearly with average flux by about 40% of average R s . Random error not only scales with soil flux but scales in a consistent way (same slope) across ecosystems. Scaling error, measured at one site, similarly increased linearly with average R s , by about 50% of average R s . 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 of random error is unknown, it is suggestive of a broadly applicable rule for predicting flux random error. Also consistent with previous studies, we found the random error of FD follows a Laplace (double‐exponential) rather than a normal (Gaussian) distribution.