Measurements of CO<sub>2</sub> exchange with an automated chamber system throughout the year: challenges in measuring night-time respiration on porous peat soil

Abstract

Abstract. We built an automatic chamber system to measure greenhouse gas (GHG) exchange in forested peatland ecosystems. We aimed to build a system robust enough which would work throughout the year and could measure through a changing snowpack in addition to producing annual GHG fluxes by integrating the measurements without the need of using models. The system worked rather well throughout the year, but it was not service free. Gap filling of data was still necessary. We observed problems in carbon dioxide (CO2) respiration flux estimation during calm summer nights, when a CO2 concentration gradient from soil/moss system to atmosphere builds up. Chambers greatly overestimated the night-time respiration. This was due to the disturbance caused by the chamber to the soil-moss CO2 gradient and consequent initial pulse of CO2 to the chamber headspace. We tested different flux calculation and measurement methods to solve this problem. The estimated flux was strongly dependent on (1) the starting point of the fit after closing the chamber, (2) the length of the fit, (3) the type of the fit (linear and polynomial), (4) the speed of the fan mixing the air inside the chamber, and (5) atmospheric turbulence (friction velocity, u*). The best fitting method (the most robust, least random variation) for respiration measurements on our sites was linear fitting with the period of 120–240 s after chamber closure. Furthermore, the fan should be adjusted to spin at minimum speed to avoid the pulse-effect, but it should be kept on to ensure mixing. If night-time problems cannot be solved, emissions can be estimated using daytime data from opaque chambers.

Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

“…The reason is the higher temporal resolution of AC-derived C budgets, displaying daily C losses and gains. Observed crop-dependent differences in NECB are in accordance with Kutsch et al (2010), Jans et al (2010), Hollinger et al (2005) and Verma et al (2005), for example, who reported comparable EC-derived C balances for, inter alia, maize, sorghum and alfalfa.…”

“…As a result, sensitive measurement techniques are required to precisely assess short-term temporal and small-scale (10-30 m) spatial dynamics in SOC (Batjes and van Wesemael, 2015). To date, the assessment of SOC has typically been based on two methods, namely (i) destructive, repeated soil inventories through soil resampling and (ii) non-destructive determination of net ecosystem C balance (NCEB) by measurements of gaseous C exchange, C import and C export (Leifeld et al, 2011;Smith et al, 2010).…”

“…By contrast, the NECB (Smith et al, 2010) -used as a proxy for temporal dynamics of SOC -can be easily derived through the eddy covariance (EC) technique, representing a common approach to obtaining gaseous C exchange (Alberti et al, 2010;Leifeld et al, 2011;Skinner and Dell, 2015). However, C fluxes based on EC measurements are integrated over a larger, changing footprint area (several hectares).…”

“…On the one hand, flux measurements of the same spatial entity avoid the mixing of spatial and temporal variability, as done in the case of point measurements from repeated soil inventories. On the other hand, AC measurements combine the advantages of EC and manual chamber systems because they not only increase the temporal resolution compared to manual chambers but also allow for the detection of small-scale spatial differences and treatment comparisons regarding the gaseous C exchange (Koskinen et al, 2014).…”

A simple calculation algorithm to separate high-resolution CH<sub>4</sub> flux measurements into ebullition- and diffusion-derived components

“…eddy covariance (EC) measurements), allow for high-temporal-resolution records of CH 4 emissions (Schrier-Uijl et al, 2011;Wille et al, 2008). Recently, a growing number of experimental GHG studies have employed automatic chambers (ACs) (Koskinen et al, 2014;Lai et al, 2014;Ramos et al, 2006), which can provide flux data with an enhanced temporal resolution and capture short-term temporal (e.g. diurnal) dynamics.…”