The Arctic is warming at twice the rate of the global mean. This warming could further stimulate methane (CH4) emissions from northern wetlands and enhance the greenhouse impact of this region. Arctic wetlands are extremely heterogeneous in terms of geochemistry, vegetation, microtopography, and hydrology, and therefore CH4fluxes can differ dramatically within the metre scale. Eddy covariance (EC) is one of the most useful methods for estimating CH4fluxes in remote areas over long periods of time. However, when the areas sampled by these EC towers (i.e. tower footprints) are by definition very heterogeneous, due to encompassing a variety of environmental conditions and vegetation types, modelling environmental controls of CH4emissions becomes even more challenging, confounding efforts to reduce uncertainty in baseline CH4emissions from these landscapes. In this study, we evaluated the effect of footprint variability on CH4fluxes from two EC towers located in wetlands on the North Slope of Alaska. The local domain of each of these sites contains well developed polygonal tundra as well as a drained thermokarst lake basin. We found that the spatiotemporal variability of the footprint, has a significant influence on the observed CH4fluxes, contributing between 3% and 33% of the variance, depending on site, time period, and modelling method. Multiple indices were used to define spatial heterogeneity, and their explanatory power varied depending on site and season. Overall, the normalised difference water index had the most consistent explanatory power on CH4fluxes, though generally only when used in concert with at least one other spatial index. The spatial bias (defined here as the difference between the mean for the 0.36 km2domain around the tower and the footprint-weighted mean) was between ∣51∣% and ∣18∣% depending on the index. This study highlights the need for footprint modelling to infer the representativeness of the carbon fluxes measured by EC towers in these highly heterogeneous tundra ecosystems, and the need to evaluate spatial variability when upscaling EC site-level data to a larger domain.
The atmospheric methane (CH4) concentration, a potent greenhouse gas, is on the rise once again, making it critical to understand the controls on CH4emissions. In Arctic tundra ecosystems, a substantial part of the CH4budget originates from the cold season, particularly during the “zero curtain” (ZC), when soil remains unfrozen around 0 °C. Due to the sparse data available at this time, the controls on cold season CH4emissions are poorly understood. This study investigates the relationship between the fall ZC and CH4emissions using long‐term soil temperature measurements and CH4fluxes from four eddy covariance (EC) towers in northern Alaska. To identify the large‐scale implication of the EC results, we investigated the temporal change of terrestrial CH4enhancements from the National Oceanic and Atmospheric Administration monitoring station in Utqiaġvik, AK, from 2001 to 2017 and their association with the ZC. We found that the ZC is extending later into winter (2.6 ± 0.5 days/year from 2001 to 2017) and that terrestrial fall CH4enhancements are correlated with later soil freezing (0.79 ± 0.18‐ppb CH4day−1unfrozen soil). ZC conditions were associated with consistently higher CH4fluxes than after soil freezing across all EC towers during the measuring period (2013–2017). Unfrozen soil persisted after air temperature was well below 0 °C suggesting that air temperature has poor predictive power on CH4fluxes relative to soil temperature. These results imply that later soil freezing can increase CH4loss and that soil temperature should be used to model CH4emissions during the fall.more » « less
- Award ID(s):
- NSF-PAR ID:
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Biogeosciences
- Page Range / eLocation ID:
- p. 2595-2609
- Medium: X
- Sponsoring Org:
- National Science Foundation
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