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Comparison of soil respiration methods in a mid-latitude deciduous forest

Wayson, C.A., Randolph, J.C., Hanson, P.J., Grimmond, C.S.B., Schmid, H.P.
Biogeochemistry 2006 v.80 no.2 pp. 173-189
carbon dioxide, deciduous forests, ecosystem respiration, eddy covariance, forest ecosystems, growing season, models, net ecosystem production, researchers, soil respiration, soil temperature, soil water, spring
In forest ecosystems the single largest respiratory flux influencing net ecosystem productivity (NEP) is the total soil CO₂ efflux; however, it is difficult to make measurements of this flux that are accurate at the ecosystem scale. We examined patterns of soil CO₂ efflux using five different methods: auto-chambers, portable gas analyzers, eddy covariance along and two models parameterized with the observed data. The relation between soil temperature and soil moisture with soil CO₂ effluxes are also investigated, both inter-annually and seasonally, using these observations/results. Soil respiration rates (R soil) are greatest during the growing season when soil temperatures are between 15 and 25 °C, but some soil CO₂ efflux occurs throughout the year. Measured soil respiration was sensitive to soil temperature, particularly during the spring and fall. All measurement methods produced similar annual estimates. Depending on the time of the year, the eddy covariance (flux tower) estimate for ecosystem respiration is similar to or slightly lower than estimates of annual soil CO₂ efflux from the other methods. As the eddy covariance estimate includes foliar and stem respiration which the other methods do not; it was expected to be larger (perhaps 15-30%). The auto-chamber system continuously measuring soil CO₂ efflux rates provides a level of temporal resolution that permits investigation of short- to longer term influences of factors on these efflux rates. The expense of building and maintaining an auto chamber system may not be necessary for those researchers interested in estimating R soil annually, but auto-chambers do allow the capture of data from all seasons needed for model parameterization.