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ABSTRACT

We compared linear regression with a diffusion-based model for N2O flux estimation using non-steady-state chamber gas concentrations from a long-term study of N cycling in a managed grass pasture on sandy soil in southern Texas. Of 2224 chamber deployments, 449 met criteria established for using the diffusion-based model, which yielded flux estimates that averaged 54% larger than linear regression (n = 3). Although they represented only about 20% of all chamber deployments, this group included most of the data with greatest influence on the magnitude and dynamics of total N2O exchange at our site; e.g., of the 263 fluxes >10 g N ha–1 d–1, 192 (or 73%) were included. Apparently, application of a linear model to nonlinear chamber concentration data represents a potentially serious source of measurement bias that may influence not only summary statistics for the experiment, but also larger scale budgets based partially or wholly on those data.

Received for publication October 13, 1994.