We used the hypothesized bi-component origin of CH
4 emissions in relation to the timing of snowmelt to describe flux patterns at different arctic tundra sites. Finding the statistical distributions of the seasonal flux patterns using only the day of snowmelt is useful to explore site differences and potentially upscale fluxes to areas where no measurements exist. The underlying hypothesis based on slow and fast-turnover carbon could not be tested with our dataset, so alternative explanations remain possible. For example, CH
4 fluxes could originate from one dominating source, and surface fluxes could primarily be a result of the seasonal patterns of soil temperature and water table rather than differences in substrate. The sharp rise of emissions after snowmelt at Zackenberg could also stem from stored organic acids or gases that were produced in the previous summer. Many such mechanisms could, however, still be captured with the temporal separation model proposed here or a variation thereof. Therefore, even when the underlying drivers are different, our statistical breakdown would remain useful to describe spatial and temporal patterns in CH
4 fluxes. While Mastepanov et al. (
2013) treated individual chambers as replicates and derived the flux pattern from mean values and standard deviations, the present study analyzed each chamber individually using a temporal separation into three-components. The choice of Gaussian functions for each component was intended to give a simple description with a minimal number of fitting parameters, so the model did not explicitly represent the mechanisms underlying the suggested hypothesis. Therefore, this model may not resolve the exact shape and integral of the individual seasonal components, as indicated by the mismatches seen in Fig.
2. However, the model’s simplicity leads to numerically robust and intuitive results with three clearly distinguished peaks, which allowed us to investigate the peak center positions at Zackenberg. The results indicate a significant dependence between the timing of the first peak (component A) and day of snowmelt with an average lag of 31.4 days, supporting the findings by Mastepanov et al. (
2013). The timing of the second peak (component B)—hypothesized to stem from root exudates of plants—was independent of the day of snowmelt. The center of component B occurred between approximately DOY 210 and 240 (cf. Fig.
3b), which coincides with the typical time of maximum CO
2 uptake fluxes in this wetland (Nordstroem et al.
2001; Mastepanov et al.
2013). This match further supports the bi-component hypothesis, because root exudates are expected to correlate with plant growth as measured by CO
2 fluxes (Ström et al.
2003). In a nearby heath ecosystem, the plant dynamics later in the growing season have been shown to depend more on incoming sunlight than the timing of snowmelt (Lund et al.
2012). Therefore, a strong dependence between component B and the day of snowmelt is not expected, which follows our hypothesis. After confirming the earlier findings at the Zackenberg site, the same analysis was performed on data from the two sites at Kobbefjord and Adventdalen. The fluxes at these sites, however, showed no clear presence of three seasonal components, so a correlation of the first component with the date of snowmelt did not exist. These differences between the three sites suggest quite different dominating processes behind the CH
4 emissions. At Kobbefjord, for example, the growing season CH
4 flux has one strongly expressed component (cf. Fig.
4d), which bears a resemblance to component B because of its large width. This site features no permafrost, so despite the seasonal ground freezing, the physical mechanisms proposed to lie behind the autumn CH
4 burst cannot be at work (Mastepanov et al.
2008,
2013; Pirk et al.
2015). However, we cannot fully exclude the presence of this flux component at Kobbefjord, because our measurements never continued long enough into the freeze-in period (November–December). Component A might well be present at this site, but could be masked by a shoulder of the much larger component B. The dominance of the component B would be in line with the finding that the total growing season CH
4 emission at Kobbefjord appears linearly related to the total growing degree days per season (cf. Fig.
5b). At Zackenberg, in contrast, this relation cannot be seen, possibly because component A is much more pronounced than it is at Kobbefjord.
At Adventdalen, where permafrost is present, the CH
4 autumn burst (flux component C) was observed, as suggested by the physical mechanism. Similar autumnal flux patterns with significant contributions to the CH
4 budget were reported from permafrost-underlain tundra in Alaska (Sturtevant et al.
2012; Zona et al.
2016). The short observation history in Adventdalen and gaps in the data, however, prevent a detailed analysis of this peak, leaving this task for future studies. Flux component A was either small or irregular compared to Zackenberg, which could be related to climatic differences during wintertime. At Zackenberg, despite the proximity to the sea (which is ice-covered for a large part of the year), the climate is stable and continental. Wintertime air temperature typically varies between −10 and −30 °C. In combination with the relatively thick snow cover of up to 1.3 m at the site (Pedersen et al.
2016), the harsh conditions lead to a constant soil temperature, which is low enough to suppress microbial decomposition processes until the soil starts to thaw (around the day of snowmelt). Adventdalen, on the other hand, has a maritime climate with changeable weather in wintertime. Air temperature can rise above 0 °C in episodic warm spells in the autumn, winter, and spring. Together with the relatively thin snow cover of about 20–30 cm, which can melt and refreeze repeatedly, this leads to a strongly varying soil temperature and episodic warming of the top of the permafrost. CH
4 attributed to type A decomposition, therefore, may have escaped to the atmosphere before complete snowmelt in May, and was not captured by our measurements. Thus, flux component B is predominant at this site during the growing season. Furthermore, due to the polygonal ground pattern in Adventdalen and the associated differences in soil wetness, the flux magnitude varies strongly on small spatial scales. The overall interannual temperature variations as quantified by the total growing degree days are relatively small (cf. Fig.
5b) and explain little of the interannual variations of CH
4 emissions.
Arctic winter precipitation is both observed and projected to change with climate warming, affecting snow cover differently depending on the season and region within the Arctic (Callaghan et al.
2011b; Derksen and Brown
2012). Arctic coastal regions (such as our sites) are likely to experience strong decreases of snow cover duration due to an earlier snowmelt in spring (Callaghan et al.
2011b), which would prolong the growing season. At each of our three sites, there was no indication that an earlier snowmelt would increase the total seasonal amount of emitted CH
4 (cf. Fig.
5a). This finding is in line with Oberbauer et al. (
1998), who observed no statistically significant difference in total CH
4 emissions in a snow removal experiment in Alaskan tundra. Variations of the wintertime snow thickness, on the other hand, were found to increase CH
4 emission, largely as a response to soil warming (Blanc-Betes et al.
2016). So it could be argued that the shorter growing season could be compensated by typically higher soil temperature (higher CH
4 fluxes) in years with a thick, long-lasting snowpack (Stiegler et al.
2016). Reciprocally, an earlier snowmelt can in part be due to less wintertime precipitation, which in turn leads to a lower water table position upon melt in summertime and therefore lower CH
4 fluxes. Note, however, that these interannual differences can in the long term be overruled by climate warming and potential permafrost thawing, which is expected to increase both CH
4 and CO
2 emissions (Schädel et al.
2016).