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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Water resources research 2021-05, Vol.57 (5), p.n/a
Hauptverfasser: Fernández Castro, Bieito, Chmiel, Hannah Elisa, Minaudo, Camille, Krishna, Shubham, Perolo, Pascal, Rasconi, Serena, Wüest, Alfred
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page n/a
container_issue 5
container_start_page
container_title Water resources research
container_volume 57
creator Fernández Castro, Bieito
Chmiel, Hannah Elisa
Minaudo, Camille
Krishna, Shubham
Perolo, Pascal
Rasconi, Serena
Wüest, Alfred
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
fullrecord <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_03297700v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2532144574</sourcerecordid><originalsourceid>FETCH-LOGICAL-a4022-a4131b36f899599f55e8d7fe88acc46faeaaa4dd2148bbda65f3b00f0d4d1a6d3</originalsourceid><addsrcrecordid>eNp9kMlKA0EQhhtRMC43H6DBk2C0t1n6KDEaIS4ExWNTma6Jo8m0ds-oufkIPqNPYuuIeJKCqqL46q-FkB3ODjgT-lAwwW4nMRO5XCE9rpXqZzqTq6THmJJ9LnW2TjZCuGeMqyTNeqS68tUC_JJCbekFNnRYuLAMDS7olXe2LZrK1bSqKdAx-BlG_4D0uIJZ7QJaeuLdgo6q2d3H2_sEg5u33w2Xr8sZ1vQcIbQeF1g3YYuslTAPuP0TN8nNyfB6MOqPL0_PBkfjPigmRPRc8qlMy1zrROsySTC3WYl5DkWh0hIQAJS1gqt8OrWQJqWcMlYyqyyH1MpNstfp3sHcPHbXGQeVGR2NzVeNSaGzjLFnHtndjn307qnF0Jh71_o6rmdEIuMIlWQqUvsdVXgXgsfyV5Yz8_V48_fxEZcd_lLNcfkva24ng4lIoslP9LqFew</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2532144574</pqid></control><display><type>article</type><title>Primary and Net Ecosystem Production in a Large Lake Diagnosed From High‐Resolution Oxygen Measurements</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Wiley-Blackwell AGU Digital Library</source><source>Wiley Online Library All Journals</source><creator>Fernández Castro, Bieito ; Chmiel, Hannah Elisa ; Minaudo, Camille ; Krishna, Shubham ; Perolo, Pascal ; Rasconi, Serena ; Wüest, Alfred</creator><creatorcontrib>Fernández Castro, Bieito ; Chmiel, Hannah Elisa ; Minaudo, Camille ; Krishna, Shubham ; Perolo, Pascal ; Rasconi, Serena ; Wüest, Alfred</creatorcontrib><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><identifier>ISSN: 0043-1397</identifier><identifier>EISSN: 1944-7973</identifier><identifier>DOI: 10.1029/2020WR029283</identifier><language>eng</language><publisher>Washington: John Wiley &amp; 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 &amp; 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 ; Chmiel, Hannah Elisa ; Minaudo, Camille ; Krishna, Shubham ; Perolo, Pascal ; Rasconi, Serena ; Wüest, Alfred</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a4022-a4131b36f899599f55e8d7fe88acc46faeaaa4dd2148bbda65f3b00f0d4d1a6d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Analytical methods</topic><topic>Aquatic ecosystems</topic><topic>Autotrophy</topic><topic>Biodiversity and Ecology</topic><topic>Biological activity</topic><topic>Blooms</topic><topic>Carbon</topic><topic>Carbon cycle</topic><topic>Depth</topic><topic>diel oxygen method</topic><topic>Dissolved oxygen</topic><topic>Dynamics</topic><topic>Ecosystem management</topic><topic>Ecosystems</topic><topic>Environmental Sciences</topic><topic>internal motions</topic><topic>Lake Geneva</topic><topic>Lakes</topic><topic>Mathematical analysis</topic><topic>Mesotrophic lakes</topic><topic>Metabolic rate</topic><topic>Metabolism</topic><topic>Organic matter</topic><topic>Oxygen</topic><topic>Primary production</topic><topic>Resolution</topic><topic>Sampling</topic><topic>Sampling methods</topic><topic>Sampling techniques</topic><topic>spectral analysis</topic><topic>Temporal variability</topic><topic>Temporal variations</topic><topic>Variability</topic><topic>Vertical advection</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><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><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Water resources research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fernández Castro, Bieito</au><au>Chmiel, Hannah Elisa</au><au>Minaudo, Camille</au><au>Krishna, Shubham</au><au>Perolo, Pascal</au><au>Rasconi, Serena</au><au>Wüest, Alfred</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Primary and Net Ecosystem Production in a Large Lake Diagnosed From High‐Resolution Oxygen Measurements</atitle><jtitle>Water resources research</jtitle><date>2021-05</date><risdate>2021</risdate><volume>57</volume><issue>5</issue><epage>n/a</epage><issn>0043-1397</issn><eissn>1944-7973</eissn><abstract>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</abstract><cop>Washington</cop><pub>John Wiley &amp; 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>
fulltext fulltext
identifier ISSN: 0043-1397
ispartof Water resources research, 2021-05, Vol.57 (5), p.n/a
issn 0043-1397
1944-7973
language eng
recordid cdi_hal_primary_oai_HAL_hal_03297700v1
source Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Wiley-Blackwell AGU Digital Library; Wiley Online Library All Journals
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
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T17%3A58%3A15IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Primary%20and%20Net%20Ecosystem%20Production%20in%20a%20Large%20Lake%20Diagnosed%20From%20High%E2%80%90Resolution%20Oxygen%20Measurements&rft.jtitle=Water%20resources%20research&rft.au=Fern%C3%A1ndez%20Castro,%20Bieito&rft.date=2021-05&rft.volume=57&rft.issue=5&rft.epage=n/a&rft.issn=0043-1397&rft.eissn=1944-7973&rft_id=info:doi/10.1029/2020WR029283&rft_dat=%3Cproquest_hal_p%3E2532144574%3C/proquest_hal_p%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2532144574&rft_id=info:pmid/&rfr_iscdi=true