Presentation_1_Identifying Drivers Behind Spatial Variability of Methane Concentrations in East Siberian Ponds.pdf
Waterbody methane emissions per area are negatively correlated with the size of the emitting waterbody. Thus, ponds, defined here as having an area smaller than 8 · 10 4 m 2 , contribute out of proportion to the aquatic methane budget compared to the total area they cover and compared to other water...
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ftfrontimediafig:oai:figshare.com:article/14314805 2023-05-15T15:18:51+02:00 Presentation_1_Identifying Drivers Behind Spatial Variability of Methane Concentrations in East Siberian Ponds.pdf Zoé Rehder Anna Zaplavnova Lars Kutzbach 2021-03-26T05:06:37Z https://doi.org/10.3389/feart.2021.617662.s001 https://figshare.com/articles/presentation/Presentation_1_Identifying_Drivers_Behind_Spatial_Variability_of_Methane_Concentrations_in_East_Siberian_Ponds_pdf/14314805 unknown doi:10.3389/feart.2021.617662.s001 https://figshare.com/articles/presentation/Presentation_1_Identifying_Drivers_Behind_Spatial_Variability_of_Methane_Concentrations_in_East_Siberian_Ponds_pdf/14314805 CC BY 4.0 CC-BY Solid Earth Sciences Climate Science Atmospheric Sciences not elsewhere classified Exploration Geochemistry Inorganic Geochemistry Isotope Geochemistry Organic Geochemistry Geochemistry not elsewhere classified Igneous and Metamorphic Petrology Ore Deposit Petrology Palaeontology (incl. Palynology) Structural Geology Tectonics Volcanology Geology not elsewhere classified Seismology and Seismic Exploration Glaciology Hydrogeology Natural Hazards Quaternary Environments Earth Sciences not elsewhere classified Evolutionary Impacts of Climate Change ponds methane polygonal tundra permafost spatial variability Lena river delta ice-wedge polygons waterbodies Text Presentation 2021 ftfrontimediafig https://doi.org/10.3389/feart.2021.617662.s001 2021-03-31T22:59:36Z Waterbody methane emissions per area are negatively correlated with the size of the emitting waterbody. Thus, ponds, defined here as having an area smaller than 8 · 10 4 m 2 , contribute out of proportion to the aquatic methane budget compared to the total area they cover and compared to other waterbodies. However, methane concentrations in and methane emissions from ponds show more spatial variability than larger waterbodies. We need to better understand this variability to improve upscaling estimates of freshwater methane emissions. In this regard, the Arctic permafrost landscape is an important region, which, besides carbon-rich soils, features a high pond density and is exposed to above-average climatic warming. We studied 41 polygonal-tundra ponds in the Lena River Delta, northeast Siberia. We collected water samples at different locations and depths in each pond and determined methane concentrations using gas chromatography. Additionally, we collected information on the key properties of the ponds to identify drivers of surface water methane concentrations. The ponds can be categorized into three geomorphological types with distinct differences in drivers of methane concentrations: polygonal-center ponds, ice-wedge ponds and larger merged polygonal ponds. All ponds are supersaturated in methane, but ice-wedge ponds exhibit the highest surface water concentrations. We find that ice-wedge ponds feature a strong stratification due to consistently low bottom temperatures. This causes surface concentrations to mainly depend on wind speed and on the amount of methane that has accumulated in the hypolimnion. In polygonal-center ponds, high methane surface concentrations are mostly determined by a small water depth. Apart from the influence of water depth on mixing speed, water depth controls the overgrown fraction, the fraction of the pond covered by vascular plants. The plants provide labile substrate to the methane-producing microbes. This link can also be seen in merged polygonal ponds, which furthermore show ... Conference Object Arctic Climate change Ice lena river permafrost Tundra wedge* Siberia Frontiers: Figshare Arctic High Pond ENVELOPE(-57.148,-57.148,50.500,50.500) |
institution |
Open Polar |
collection |
Frontiers: Figshare |
op_collection_id |
ftfrontimediafig |
language |
unknown |
topic |
Solid Earth Sciences Climate Science Atmospheric Sciences not elsewhere classified Exploration Geochemistry Inorganic Geochemistry Isotope Geochemistry Organic Geochemistry Geochemistry not elsewhere classified Igneous and Metamorphic Petrology Ore Deposit Petrology Palaeontology (incl. Palynology) Structural Geology Tectonics Volcanology Geology not elsewhere classified Seismology and Seismic Exploration Glaciology Hydrogeology Natural Hazards Quaternary Environments Earth Sciences not elsewhere classified Evolutionary Impacts of Climate Change ponds methane polygonal tundra permafost spatial variability Lena river delta ice-wedge polygons waterbodies |
spellingShingle |
Solid Earth Sciences Climate Science Atmospheric Sciences not elsewhere classified Exploration Geochemistry Inorganic Geochemistry Isotope Geochemistry Organic Geochemistry Geochemistry not elsewhere classified Igneous and Metamorphic Petrology Ore Deposit Petrology Palaeontology (incl. Palynology) Structural Geology Tectonics Volcanology Geology not elsewhere classified Seismology and Seismic Exploration Glaciology Hydrogeology Natural Hazards Quaternary Environments Earth Sciences not elsewhere classified Evolutionary Impacts of Climate Change ponds methane polygonal tundra permafost spatial variability Lena river delta ice-wedge polygons waterbodies Zoé Rehder Anna Zaplavnova Lars Kutzbach Presentation_1_Identifying Drivers Behind Spatial Variability of Methane Concentrations in East Siberian Ponds.pdf |
topic_facet |
Solid Earth Sciences Climate Science Atmospheric Sciences not elsewhere classified Exploration Geochemistry Inorganic Geochemistry Isotope Geochemistry Organic Geochemistry Geochemistry not elsewhere classified Igneous and Metamorphic Petrology Ore Deposit Petrology Palaeontology (incl. Palynology) Structural Geology Tectonics Volcanology Geology not elsewhere classified Seismology and Seismic Exploration Glaciology Hydrogeology Natural Hazards Quaternary Environments Earth Sciences not elsewhere classified Evolutionary Impacts of Climate Change ponds methane polygonal tundra permafost spatial variability Lena river delta ice-wedge polygons waterbodies |
description |
Waterbody methane emissions per area are negatively correlated with the size of the emitting waterbody. Thus, ponds, defined here as having an area smaller than 8 · 10 4 m 2 , contribute out of proportion to the aquatic methane budget compared to the total area they cover and compared to other waterbodies. However, methane concentrations in and methane emissions from ponds show more spatial variability than larger waterbodies. We need to better understand this variability to improve upscaling estimates of freshwater methane emissions. In this regard, the Arctic permafrost landscape is an important region, which, besides carbon-rich soils, features a high pond density and is exposed to above-average climatic warming. We studied 41 polygonal-tundra ponds in the Lena River Delta, northeast Siberia. We collected water samples at different locations and depths in each pond and determined methane concentrations using gas chromatography. Additionally, we collected information on the key properties of the ponds to identify drivers of surface water methane concentrations. The ponds can be categorized into three geomorphological types with distinct differences in drivers of methane concentrations: polygonal-center ponds, ice-wedge ponds and larger merged polygonal ponds. All ponds are supersaturated in methane, but ice-wedge ponds exhibit the highest surface water concentrations. We find that ice-wedge ponds feature a strong stratification due to consistently low bottom temperatures. This causes surface concentrations to mainly depend on wind speed and on the amount of methane that has accumulated in the hypolimnion. In polygonal-center ponds, high methane surface concentrations are mostly determined by a small water depth. Apart from the influence of water depth on mixing speed, water depth controls the overgrown fraction, the fraction of the pond covered by vascular plants. The plants provide labile substrate to the methane-producing microbes. This link can also be seen in merged polygonal ponds, which furthermore show ... |
format |
Conference Object |
author |
Zoé Rehder Anna Zaplavnova Lars Kutzbach |
author_facet |
Zoé Rehder Anna Zaplavnova Lars Kutzbach |
author_sort |
Zoé Rehder |
title |
Presentation_1_Identifying Drivers Behind Spatial Variability of Methane Concentrations in East Siberian Ponds.pdf |
title_short |
Presentation_1_Identifying Drivers Behind Spatial Variability of Methane Concentrations in East Siberian Ponds.pdf |
title_full |
Presentation_1_Identifying Drivers Behind Spatial Variability of Methane Concentrations in East Siberian Ponds.pdf |
title_fullStr |
Presentation_1_Identifying Drivers Behind Spatial Variability of Methane Concentrations in East Siberian Ponds.pdf |
title_full_unstemmed |
Presentation_1_Identifying Drivers Behind Spatial Variability of Methane Concentrations in East Siberian Ponds.pdf |
title_sort |
presentation_1_identifying drivers behind spatial variability of methane concentrations in east siberian ponds.pdf |
publishDate |
2021 |
url |
https://doi.org/10.3389/feart.2021.617662.s001 https://figshare.com/articles/presentation/Presentation_1_Identifying_Drivers_Behind_Spatial_Variability_of_Methane_Concentrations_in_East_Siberian_Ponds_pdf/14314805 |
long_lat |
ENVELOPE(-57.148,-57.148,50.500,50.500) |
geographic |
Arctic High Pond |
geographic_facet |
Arctic High Pond |
genre |
Arctic Climate change Ice lena river permafrost Tundra wedge* Siberia |
genre_facet |
Arctic Climate change Ice lena river permafrost Tundra wedge* Siberia |
op_relation |
doi:10.3389/feart.2021.617662.s001 https://figshare.com/articles/presentation/Presentation_1_Identifying_Drivers_Behind_Spatial_Variability_of_Methane_Concentrations_in_East_Siberian_Ponds_pdf/14314805 |
op_rights |
CC BY 4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.3389/feart.2021.617662.s001 |
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1766349024598687744 |