The closed chamber technique is widely used to measure the exchange of
methane (

To understand the role of wetlands within the global carbon cycle, accurate
estimations of the fluxes of methane (

Also, the temporal increase might appear to saturate because the vertical
concentration gradient between the soil and the chamber headspace lessens as
a result of accumulation in the chamber. This effect was theoretically
described using diffusion theory by

The choice of flux model can be one of the largest sources of uncertainty for
chamber flux measurements

Here, we aim to improve the understanding of the processes leading to
curvilinear concentration time series of chamber flux measurements and
quantify differences between flux estimates derived from different models. We
hypothesize that the curvature of the concentration time series is in part
caused by systematic effects of the closed chamber technique, and that these
are related to the environmental site conditions. Such an analysis can only
be meaningful if random experimental uncertainties are kept to a minimum. We
achieve this by using data from high-resolution automatic chamber systems
installed to monitor

Two examples of

Site overview, from north to south. Temperature and precipitation are average values of measurements by the closest weather station in the period 1961–1990 (1958–1987 for Zackenberg).

The five study sites are all situated in peat-forming wetlands where the
water table is typically close to the soil surface. Table

All field sites are equipped with a similar automatic chamber system based on

At Stordalen there are nine transparent chambers that are activated for
18 min at a time. This results in a 3 h cycle (one 18 min slot is
used as a control with ambient air). The chamber closure time is 5 min,
between minute 10 and 15 of each measurement. The construction of the
chambers is different from the other sites. The entire chamber is lifted off
plots with short canopies (

Examples of the recorded data are shown in Fig.

The air temperature (

The linear model assumes a constant concentration change, i.e.,

We extend the linear model of Eq. (

The non-steady-state diffusive flux estimator (NDFE) model

These models are optimized against the measured concentrations with a
least-squares algorithm based on the Levenberg–Marquardt algorithm. The
values of all other variables entering the flux calculation (

We compare the curvilinear flux estimates derived from the fixed 3 min
window of the flux measurement to flux estimates calculated from the same raw
data in other studies. Different versions of the linear regression method
(cf. Eq.

At Zackenberg, a linear regression to the initial, most-linear, part of the
gas concentration curve was applied by careful visual inspection of each
measurement

At Stordalen, the algorithm first block-averages the raw data to 15 s
resolution and then calculates eight sequential 2.25 min long fits starting
every 15 s

For Adventdalen (the most recent site) we did not have independently calculated reference fluxes. Instead, we applied linear regression to the same 3 min time window which was used for the curvilinear models. Consequently, Adventdalen yields the direct comparison between linear and curvilinear flux estimates, without additional effects of the fit window choice or block averaging.

Results of chamber 6 at Zackenberg.

Example histograms of the relationship between reference and
exponential flux estimates for all chambers of Zackenberg.

Summary statistics of all chambers. Temporal variability is
expressed as daily standard deviation divided by daily mean (not shown for

Figure

Unlike in the NDFE model, curvature (

Curvature parameter

An alternative way to quantify the differences between two flux models (for
example reference and exponential) is to assume a constant ratio, i.e.,

We analyzed the dependency of the curvature parameter of the exponential
model

Example of curvature correlation

Example
of

By subtracting the low PAR baseline from the curvature difference we can
isolate the PAR-dependent signal in the curvature. Under conditions where
photosynthesis is limited by

Another way of verifying the partitioned fluxes derived from the curvatures
is to compare

Note that the

We analyzed short time series of concentrations of automatic chamber

The NDFE model, however, exemplifies that flux estimates can be overestimated and noisy when the assumptions of a process-based model are violated. The NDFE model should only be applied with outmost care, i.e., only if the analyst is sure that the altered gas concentration gradient is indeed the main reason for curvilinear concentration changes, such as it might be in controlled laboratory experiments or computer simulations. Direct measurements of the gas concentration at different depths in the soil under a chamber could in future studies quantify to what extent the concentration gradient is really altered by the presence of the chamber.

It is moreover important that the used flux estimator is suitable for the
resolution at which the primary gas concentrations are measured. The
measurement precision in the present study was high enough for both time and
concentration to perform an analysis of curvilinear behavior, and relevant
information contained therein could be extracted. We have shown that the
simultaneous measurement of

The research leading to these results has received funding from the European Community's Seventh Framework Program (FP7) under grants 238366, 262693 and 282700, the Nordic Centers of Excellence DEFROST and eSTICC, as well as the GeoBasis programs supported by the Danish Energy Agency. Edited by: S. M. Noe