Parkin, Tim (USDA-ARS, National Soil Tilth Lab., 2150 Pammel Dr., Ames, IA, 50011; Phone: 515-294-6888; Email: parkin@nstl.gov)

Filling Data Gaps in Soil Respiration Measurements using Autocorrelation

T.B. Parkin *, T.C. Kaspar

Field respiration measurements are commonly performed using chambers placed on the soil surface at periodic intervals.� Calculation of cumulative CO₂ flux over time is then estimated by linear interpolation between measurement points.� Because soil CO₂ fluxes often exhibit pulses following rainfall events or other pertubations (i.e. tillage), measurements at infrequent intervals may fail to adequately characterize the temporal flux dynamics.� If this occurs biased estimates of� cumulative CO₂ loss may be obtained.�� This paper explores the use of autocorrelation analysis to improve interpolation between measurement points,� and thus, improve estimates of cumulative CO₂ flux from soil respiration.� An automated chambers was used to measure soil CO₂ fluxes at hourly intervals from a fallow soil from April 16 through Sept. 5,�� 2001.� All the hourly measurements were then used to compute cumulative CO₂ flux from the site.� This value was used as the best estimate of cumulative CO₂ flux.� Two interpolation techniques (linear interpolation and autocorrelation analysis) were then tested with regard to well they provided estimates of cumulative CO₂ flux relative to the best estimate.� In this analysis the population of hourly chamber fluxes was subsampled by selecting individual hourly flux measurments at intervals ranging from 1 d to 20 d.� The two interpolation techniques were then applied and a cumulative flux for each technique was calculated.� We observed that there was no difference in the two interpolation techniques when sampling interval was 4 d or less. However, as sampling interval was increased beyond 4 d the variance associated with estimates obtained by linear interpolation increased, however, the variances associated with the autocorrelation estimates were substantially less and remained relatively constant.� Additional evaluations are being conducted to refine the autocorrelation technique