Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling
The Arctic is warming at twice the rate of the global mean. This warming could further stimulate methane (CH _4 ) emissions from northern wetlands and enhance the greenhouse impact of this region. Arctic wetlands are extremely heterogeneous in terms of geochemistry, vegetation, microtopography, and...
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ftdoajarticles:oai:doaj.org/article:02f194f0e71342388aaf51c11cbb3f8a 2023-09-05T13:17:02+02:00 Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling Kassandra Reuss-Schmidt Peter Levy Walter Oechel Craig Tweedie Cathy Wilson Donatella Zona 2019-01-01T00:00:00Z https://doi.org/10.1088/1748-9326/ab4d32 https://doaj.org/article/02f194f0e71342388aaf51c11cbb3f8a EN eng IOP Publishing https://doi.org/10.1088/1748-9326/ab4d32 https://doaj.org/toc/1748-9326 doi:10.1088/1748-9326/ab4d32 1748-9326 https://doaj.org/article/02f194f0e71342388aaf51c11cbb3f8a Environmental Research Letters, Vol 14, Iss 12, p 125010 (2019) eddy covariance footprint modelling heterogeneity permafrost wetlands Arctic Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 article 2019 ftdoajarticles https://doi.org/10.1088/1748-9326/ab4d32 2023-08-13T00:37:22Z The Arctic is warming at twice the rate of the global mean. This warming could further stimulate methane (CH _4 ) 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 CH _4 fluxes can differ dramatically within the metre scale. Eddy covariance (EC) is one of the most useful methods for estimating CH _4 fluxes 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 CH _4 emissions becomes even more challenging, confounding efforts to reduce uncertainty in baseline CH _4 emissions from these landscapes. In this study, we evaluated the effect of footprint variability on CH _4 fluxes 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 CH _4 fluxes, 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 CH _4 fluxes, 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 km ^2 domain 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 ... Article in Journal/Newspaper Arctic north slope permafrost Thermokarst Tundra Alaska Directory of Open Access Journals: DOAJ Articles Arctic Environmental Research Letters 14 12 125010 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
eddy covariance footprint modelling heterogeneity permafrost wetlands Arctic Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 |
spellingShingle |
eddy covariance footprint modelling heterogeneity permafrost wetlands Arctic Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 Kassandra Reuss-Schmidt Peter Levy Walter Oechel Craig Tweedie Cathy Wilson Donatella Zona Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling |
topic_facet |
eddy covariance footprint modelling heterogeneity permafrost wetlands Arctic Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 |
description |
The Arctic is warming at twice the rate of the global mean. This warming could further stimulate methane (CH _4 ) 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 CH _4 fluxes can differ dramatically within the metre scale. Eddy covariance (EC) is one of the most useful methods for estimating CH _4 fluxes 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 CH _4 emissions becomes even more challenging, confounding efforts to reduce uncertainty in baseline CH _4 emissions from these landscapes. In this study, we evaluated the effect of footprint variability on CH _4 fluxes 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 CH _4 fluxes, 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 CH _4 fluxes, 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 km ^2 domain 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 ... |
format |
Article in Journal/Newspaper |
author |
Kassandra Reuss-Schmidt Peter Levy Walter Oechel Craig Tweedie Cathy Wilson Donatella Zona |
author_facet |
Kassandra Reuss-Schmidt Peter Levy Walter Oechel Craig Tweedie Cathy Wilson Donatella Zona |
author_sort |
Kassandra Reuss-Schmidt |
title |
Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling |
title_short |
Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling |
title_full |
Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling |
title_fullStr |
Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling |
title_full_unstemmed |
Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling |
title_sort |
understanding spatial variability of methane fluxes in arctic wetlands through footprint modelling |
publisher |
IOP Publishing |
publishDate |
2019 |
url |
https://doi.org/10.1088/1748-9326/ab4d32 https://doaj.org/article/02f194f0e71342388aaf51c11cbb3f8a |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic north slope permafrost Thermokarst Tundra Alaska |
genre_facet |
Arctic north slope permafrost Thermokarst Tundra Alaska |
op_source |
Environmental Research Letters, Vol 14, Iss 12, p 125010 (2019) |
op_relation |
https://doi.org/10.1088/1748-9326/ab4d32 https://doaj.org/toc/1748-9326 doi:10.1088/1748-9326/ab4d32 1748-9326 https://doaj.org/article/02f194f0e71342388aaf51c11cbb3f8a |
op_doi |
https://doi.org/10.1088/1748-9326/ab4d32 |
container_title |
Environmental Research Letters |
container_volume |
14 |
container_issue |
12 |
container_start_page |
125010 |
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1776198378375348224 |