Primary and Net Ecosystem Production in a Large Lake Diagnosed From High‐Resolution Oxygen Measurements
The rates of gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) provide quantitative information about the cycling of carbon and energy in aquatic ecosystems. In lakes, metabolic rates are often diagnosed from diel oxygen fluctuations recorded with high‐res...
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description | The rates of gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) provide quantitative information about the cycling of carbon and energy in aquatic ecosystems. In lakes, metabolic rates are often diagnosed from diel oxygen fluctuations recorded with high‐resolution sondes. This requires that the imprint of ecosystem metabolism can be separated from that of physical processes. Here, we quantified the vertical and temporal variability of the metabolic rates of a deep, large, mesotrophic lake (Lake Geneva, Switzerland–France) by using a 6‐month record (April–October 2019) of high‐frequency, depth‐resolved (0–30 m) dissolved oxygen measurements. Two new alternative methods (in the time and frequency domain) were used to filter low‐frequency basin‐scale internal motions from the oxygen signal. Both methods proved successful and yielded consistent metabolic estimates showing net autotrophy (NEP = GPP − R = 55 mmol m−2 day−1) over the sampling period and depth interval, with GPP (235 mmol m−2 day−1) exceeding R (180 mmol m−2 day−1). They also revealed significant temporal variability, with at least two short‐lived blooms occurring during calm periods, and a vertical partitioning of metabolism, with stronger diel cycles and positive NEP in the upper ∼10 m and negative NEP below, where the diel oxygen signal was dominated by internal motions. The proposed methods expand the range of applicability of the diel oxygen technique to large lakes hosting energetic, low‐frequency internal motions, offering new possibilities for unveiling the rich spatiotemporal metabolism dynamics in these systems.
Plain Language Summary
Quantifying the rates of production and degradation of organic matter is of fundamental importance for understanding the cycling of carbon in lakes and for assessing and managing the health of these ecosystems. Owing to the increased availability of high‐resolution sondes, this quantification is now frequently achieved by recording changes of oxygen concentration directly in free‐water, allowing for an unprecedented temporal coverage. In small, shallow, productive lakes, the application of this method is relatively straightforward because oxygen changes driven by biological processes are larger than vertical transport. Instead, large, deep lakes host large‐amplitude vertical motions, which can significantly impact the oxygen record, hindering the calculation of metabolic rates. In this study, we quantified the meta |
doi_str_mv | 10.1029/2020WR029283 |
format | Article |
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Plain Language Summary
Quantifying the rates of production and degradation of organic matter is of fundamental importance for understanding the cycling of carbon in lakes and for assessing and managing the health of these ecosystems. Owing to the increased availability of high‐resolution sondes, this quantification is now frequently achieved by recording changes of oxygen concentration directly in free‐water, allowing for an unprecedented temporal coverage. In small, shallow, productive lakes, the application of this method is relatively straightforward because oxygen changes driven by biological processes are larger than vertical transport. Instead, large, deep lakes host large‐amplitude vertical motions, which can significantly impact the oxygen record, hindering the calculation of metabolic rates. In this study, we quantified the metabolism of Lake Geneva during the productive period of 2019 with continuous oxygen measurements at different depths. To obtain reliable metabolic rates, we developed new analytical techniques allowing for the isolation of the biological signal. This study unveils the rich spatiotemporal metabolic dynamics of Lake Geneva, which would remain unnoticed with traditional sampling techniques, and provides new insights and mathematical tools for improving the application of the free‐water oxygen technique in large and energetic systems.
Key Points
Metabolic rates diagnosed with high‐resolution free‐water oxygen measurements in Lake Geneva
Two new methods proposed to filter the imprint of vertical dislocations that interferes with the diel oxygen signal
The summer metabolism of Lake Geneva is net autotrophic and shows both rich vertical structures and temporal dynamics</description><identifier>ISSN: 0043-1397</identifier><identifier>EISSN: 1944-7973</identifier><identifier>DOI: 10.1029/2020WR029283</identifier><language>eng</language><publisher>Washington: John Wiley & Sons, Inc</publisher><subject>Analytical methods ; Aquatic ecosystems ; Autotrophy ; Biodiversity and Ecology ; Biological activity ; Blooms ; Carbon ; Carbon cycle ; Depth ; diel oxygen method ; Dissolved oxygen ; Dynamics ; Ecosystem management ; Ecosystems ; Environmental Sciences ; internal motions ; Lake Geneva ; Lakes ; Mathematical analysis ; Mesotrophic lakes ; Metabolic rate ; Metabolism ; Organic matter ; Oxygen ; Primary production ; Resolution ; Sampling ; Sampling methods ; Sampling techniques ; spectral analysis ; Temporal variability ; Temporal variations ; Variability ; Vertical advection</subject><ispartof>Water resources research, 2021-05, Vol.57 (5), p.n/a</ispartof><rights>2021. The Authors.</rights><rights>2021. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Attribution</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a4022-a4131b36f899599f55e8d7fe88acc46faeaaa4dd2148bbda65f3b00f0d4d1a6d3</citedby><cites>FETCH-LOGICAL-a4022-a4131b36f899599f55e8d7fe88acc46faeaaa4dd2148bbda65f3b00f0d4d1a6d3</cites><orcidid>0000-0001-5137-6858 ; 0000-0001-7372-1181 ; 0000-0001-7797-854X ; 0000-0001-8311-1280 ; 0000-0003-0979-9595 ; 0000-0001-6667-8904 ; 0000-0001-7984-0368</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2020WR029283$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2020WR029283$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,1417,11514,27924,27925,45574,45575,46468,46892</link.rule.ids><backlink>$$Uhttps://hal.inrae.fr/hal-03297700$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Fernández Castro, Bieito</creatorcontrib><creatorcontrib>Chmiel, Hannah Elisa</creatorcontrib><creatorcontrib>Minaudo, Camille</creatorcontrib><creatorcontrib>Krishna, Shubham</creatorcontrib><creatorcontrib>Perolo, Pascal</creatorcontrib><creatorcontrib>Rasconi, Serena</creatorcontrib><creatorcontrib>Wüest, Alfred</creatorcontrib><title>Primary and Net Ecosystem Production in a Large Lake Diagnosed From High‐Resolution Oxygen Measurements</title><title>Water resources research</title><description>The rates of gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) provide quantitative information about the cycling of carbon and energy in aquatic ecosystems. In lakes, metabolic rates are often diagnosed from diel oxygen fluctuations recorded with high‐resolution sondes. This requires that the imprint of ecosystem metabolism can be separated from that of physical processes. Here, we quantified the vertical and temporal variability of the metabolic rates of a deep, large, mesotrophic lake (Lake Geneva, Switzerland–France) by using a 6‐month record (April–October 2019) of high‐frequency, depth‐resolved (0–30 m) dissolved oxygen measurements. Two new alternative methods (in the time and frequency domain) were used to filter low‐frequency basin‐scale internal motions from the oxygen signal. Both methods proved successful and yielded consistent metabolic estimates showing net autotrophy (NEP = GPP − R = 55 mmol m−2 day−1) over the sampling period and depth interval, with GPP (235 mmol m−2 day−1) exceeding R (180 mmol m−2 day−1). They also revealed significant temporal variability, with at least two short‐lived blooms occurring during calm periods, and a vertical partitioning of metabolism, with stronger diel cycles and positive NEP in the upper ∼10 m and negative NEP below, where the diel oxygen signal was dominated by internal motions. The proposed methods expand the range of applicability of the diel oxygen technique to large lakes hosting energetic, low‐frequency internal motions, offering new possibilities for unveiling the rich spatiotemporal metabolism dynamics in these systems.
Plain Language Summary
Quantifying the rates of production and degradation of organic matter is of fundamental importance for understanding the cycling of carbon in lakes and for assessing and managing the health of these ecosystems. Owing to the increased availability of high‐resolution sondes, this quantification is now frequently achieved by recording changes of oxygen concentration directly in free‐water, allowing for an unprecedented temporal coverage. In small, shallow, productive lakes, the application of this method is relatively straightforward because oxygen changes driven by biological processes are larger than vertical transport. Instead, large, deep lakes host large‐amplitude vertical motions, which can significantly impact the oxygen record, hindering the calculation of metabolic rates. In this study, we quantified the metabolism of Lake Geneva during the productive period of 2019 with continuous oxygen measurements at different depths. To obtain reliable metabolic rates, we developed new analytical techniques allowing for the isolation of the biological signal. This study unveils the rich spatiotemporal metabolic dynamics of Lake Geneva, which would remain unnoticed with traditional sampling techniques, and provides new insights and mathematical tools for improving the application of the free‐water oxygen technique in large and energetic systems.
Key Points
Metabolic rates diagnosed with high‐resolution free‐water oxygen measurements in Lake Geneva
Two new methods proposed to filter the imprint of vertical dislocations that interferes with the diel oxygen signal
The summer metabolism of Lake Geneva is net autotrophic and shows both rich vertical structures and temporal dynamics</description><subject>Analytical methods</subject><subject>Aquatic ecosystems</subject><subject>Autotrophy</subject><subject>Biodiversity and Ecology</subject><subject>Biological activity</subject><subject>Blooms</subject><subject>Carbon</subject><subject>Carbon cycle</subject><subject>Depth</subject><subject>diel oxygen method</subject><subject>Dissolved oxygen</subject><subject>Dynamics</subject><subject>Ecosystem management</subject><subject>Ecosystems</subject><subject>Environmental Sciences</subject><subject>internal motions</subject><subject>Lake Geneva</subject><subject>Lakes</subject><subject>Mathematical analysis</subject><subject>Mesotrophic lakes</subject><subject>Metabolic rate</subject><subject>Metabolism</subject><subject>Organic matter</subject><subject>Oxygen</subject><subject>Primary production</subject><subject>Resolution</subject><subject>Sampling</subject><subject>Sampling methods</subject><subject>Sampling techniques</subject><subject>spectral analysis</subject><subject>Temporal variability</subject><subject>Temporal variations</subject><subject>Variability</subject><subject>Vertical advection</subject><issn>0043-1397</issn><issn>1944-7973</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp9kMlKA0EQhhtRMC43H6DBk2C0t1n6KDEaIS4ExWNTma6Jo8m0ds-oufkIPqNPYuuIeJKCqqL46q-FkB3ODjgT-lAwwW4nMRO5XCE9rpXqZzqTq6THmJJ9LnW2TjZCuGeMqyTNeqS68tUC_JJCbekFNnRYuLAMDS7olXe2LZrK1bSqKdAx-BlG_4D0uIJZ7QJaeuLdgo6q2d3H2_sEg5u33w2Xr8sZ1vQcIbQeF1g3YYuslTAPuP0TN8nNyfB6MOqPL0_PBkfjPigmRPRc8qlMy1zrROsySTC3WYl5DkWh0hIQAJS1gqt8OrWQJqWcMlYyqyyH1MpNstfp3sHcPHbXGQeVGR2NzVeNSaGzjLFnHtndjn307qnF0Jh71_o6rmdEIuMIlWQqUvsdVXgXgsfyV5Yz8_V48_fxEZcd_lLNcfkva24ng4lIoslP9LqFew</recordid><startdate>202105</startdate><enddate>202105</enddate><creator>Fernández Castro, Bieito</creator><creator>Chmiel, Hannah Elisa</creator><creator>Minaudo, Camille</creator><creator>Krishna, Shubham</creator><creator>Perolo, Pascal</creator><creator>Rasconi, Serena</creator><creator>Wüest, Alfred</creator><general>John Wiley & Sons, Inc</general><general>American Geophysical Union</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7QL</scope><scope>7T7</scope><scope>7TG</scope><scope>7U9</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H94</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>M7N</scope><scope>P64</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0001-5137-6858</orcidid><orcidid>https://orcid.org/0000-0001-7372-1181</orcidid><orcidid>https://orcid.org/0000-0001-7797-854X</orcidid><orcidid>https://orcid.org/0000-0001-8311-1280</orcidid><orcidid>https://orcid.org/0000-0003-0979-9595</orcidid><orcidid>https://orcid.org/0000-0001-6667-8904</orcidid><orcidid>https://orcid.org/0000-0001-7984-0368</orcidid></search><sort><creationdate>202105</creationdate><title>Primary and Net Ecosystem Production in a Large Lake Diagnosed From High‐Resolution Oxygen Measurements</title><author>Fernández Castro, Bieito ; 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In lakes, metabolic rates are often diagnosed from diel oxygen fluctuations recorded with high‐resolution sondes. This requires that the imprint of ecosystem metabolism can be separated from that of physical processes. Here, we quantified the vertical and temporal variability of the metabolic rates of a deep, large, mesotrophic lake (Lake Geneva, Switzerland–France) by using a 6‐month record (April–October 2019) of high‐frequency, depth‐resolved (0–30 m) dissolved oxygen measurements. Two new alternative methods (in the time and frequency domain) were used to filter low‐frequency basin‐scale internal motions from the oxygen signal. Both methods proved successful and yielded consistent metabolic estimates showing net autotrophy (NEP = GPP − R = 55 mmol m−2 day−1) over the sampling period and depth interval, with GPP (235 mmol m−2 day−1) exceeding R (180 mmol m−2 day−1). They also revealed significant temporal variability, with at least two short‐lived blooms occurring during calm periods, and a vertical partitioning of metabolism, with stronger diel cycles and positive NEP in the upper ∼10 m and negative NEP below, where the diel oxygen signal was dominated by internal motions. The proposed methods expand the range of applicability of the diel oxygen technique to large lakes hosting energetic, low‐frequency internal motions, offering new possibilities for unveiling the rich spatiotemporal metabolism dynamics in these systems.
Plain Language Summary
Quantifying the rates of production and degradation of organic matter is of fundamental importance for understanding the cycling of carbon in lakes and for assessing and managing the health of these ecosystems. Owing to the increased availability of high‐resolution sondes, this quantification is now frequently achieved by recording changes of oxygen concentration directly in free‐water, allowing for an unprecedented temporal coverage. In small, shallow, productive lakes, the application of this method is relatively straightforward because oxygen changes driven by biological processes are larger than vertical transport. Instead, large, deep lakes host large‐amplitude vertical motions, which can significantly impact the oxygen record, hindering the calculation of metabolic rates. In this study, we quantified the metabolism of Lake Geneva during the productive period of 2019 with continuous oxygen measurements at different depths. To obtain reliable metabolic rates, we developed new analytical techniques allowing for the isolation of the biological signal. This study unveils the rich spatiotemporal metabolic dynamics of Lake Geneva, which would remain unnoticed with traditional sampling techniques, and provides new insights and mathematical tools for improving the application of the free‐water oxygen technique in large and energetic systems.
Key Points
Metabolic rates diagnosed with high‐resolution free‐water oxygen measurements in Lake Geneva
Two new methods proposed to filter the imprint of vertical dislocations that interferes with the diel oxygen signal
The summer metabolism of Lake Geneva is net autotrophic and shows both rich vertical structures and temporal dynamics</abstract><cop>Washington</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1029/2020WR029283</doi><tpages>24</tpages><orcidid>https://orcid.org/0000-0001-5137-6858</orcidid><orcidid>https://orcid.org/0000-0001-7372-1181</orcidid><orcidid>https://orcid.org/0000-0001-7797-854X</orcidid><orcidid>https://orcid.org/0000-0001-8311-1280</orcidid><orcidid>https://orcid.org/0000-0003-0979-9595</orcidid><orcidid>https://orcid.org/0000-0001-6667-8904</orcidid><orcidid>https://orcid.org/0000-0001-7984-0368</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analytical methods Aquatic ecosystems Autotrophy Biodiversity and Ecology Biological activity Blooms Carbon Carbon cycle Depth diel oxygen method Dissolved oxygen Dynamics Ecosystem management Ecosystems Environmental Sciences internal motions Lake Geneva Lakes Mathematical analysis Mesotrophic lakes Metabolic rate Metabolism Organic matter Oxygen Primary production Resolution Sampling Sampling methods Sampling techniques spectral analysis Temporal variability Temporal variations Variability Vertical advection |
title | Primary and Net Ecosystem Production in a Large Lake Diagnosed From High‐Resolution Oxygen Measurements |
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