Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm
- Autores
- Oleksy, Isabella A.; Solomon, Christopher T.; Jones, Stuart E.; Olson, Carly; Bertolet, Brittni L.; Adrian, Rita; Bansal, Sheel; Baron, Jill S.; Brothers, Soren; Chandra, Sudeep; Chou, Hsiu-Mei; Colom Montero, William; Culpepper, Joshua; de Eyto, Elvira; Farragher, Matthew J.; Hilt, Sabine; Holeck, Kristen T.; Kazanjian, Garabet; Klaus, Marcus; Klug, Jennifer; Köhler, Jan; Laas, Alo; Lundin, Erik; Parkes, Alice H.; Rose, Kevin C.; Rustam, Lars G.; Rusak, James; Scordo, Facundo; Vanni, Michael J.; Verburg, Piet; Weyhenmeyer, Gesa A.
- Año de publicación
- 2024
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. In lakes, pelagic gross primary productivity (GPP) is strongly controlled by inputs of nutrients and dissolved organic matter. Although past studies have developed process models of this nutrient-color paradigm (NCP), broad empirical tests of these models are scarce. We used data from 58 globally distributed, mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. The model includes three state variables–dissolved phosphorus, terrestrial dissolved organic carbon (DOC), and phytoplankton biomass–and generates realistic predictions for equilibrium rates of pelagic GPP. We calibrated our model using a Bayesian data assimilation technique on a subset of lakes where DOC and total phosphorus (TP) loads were known. We then asked how well the calibrated model performed with a larger set of lakes. Revised parameter estimates from the updated model aligned well with existing literature values. Observed GPP varied nonlinearly with both inflow DOC and TP concentrations in a manner consistent with increasing light limitation as DOC inputs increased and decreasing nutrient limitation as TP inputs increased. Furthermore, across these diverse lake ecosystems, model predictions of GPP were highly correlated with observed values derived from high-frequency sensor data. The GPP predictions using the updated parameters improved upon previous estimates, expanding the utility of a process model with simplified assumptions for water column mixing. Our analysis provides a model structure that may be broadly useful for understanding current and future patterns in lake primary production.
Fil: Oleksy, Isabella A.. University of Colorado; Estados Unidos
Fil: Solomon, Christopher T.. Cary Institute Of Ecosystem Studies; Estados Unidos
Fil: Jones, Stuart E.. University of Notre Dame; Estados Unidos
Fil: Olson, Carly. University of Nebraska; Estados Unidos
Fil: Bertolet, Brittni L.. University of California at Irvine; Estados Unidos
Fil: Adrian, Rita. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; Alemania
Fil: Bansal, Sheel. United States Geological Survey; Estados Unidos
Fil: Baron, Jill S.. United States Geological Survey; Estados Unidos
Fil: Brothers, Soren. University of Toronto; Canadá
Fil: Chandra, Sudeep. University of Nevada; Estados Unidos
Fil: Chou, Hsiu-Mei. National Center For High Performance Computing; China
Fil: Colom Montero, William. Uppsala Universitet; Suecia
Fil: Culpepper, Joshua. York University; Estados Unidos
Fil: de Eyto, Elvira. Marine Institute; Irlanda
Fil: Farragher, Matthew J.. University Of Maine; Estados Unidos
Fil: Hilt, Sabine. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; Alemania
Fil: Holeck, Kristen T.. Cornell University; Estados Unidos
Fil: Kazanjian, Garabet. American University Of Armenia; Armenia
Fil: Klaus, Marcus. Swedish University Of Agricultural Sciences; Suecia
Fil: Klug, Jennifer. Fairfield University; Estados Unidos
Fil: Köhler, Jan. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; Alemania
Fil: Laas, Alo. Estonian University Of Life Sciences; Estonia
Fil: Lundin, Erik. Swedish Polar Research Secretariate; Suecia
Fil: Parkes, Alice H.. Université Du Québec; Canadá
Fil: Rose, Kevin C.. Rensselaer Polytechnic Institute; Estados Unidos
Fil: Rustam, Lars G.. Cornell University; Estados Unidos
Fil: Rusak, James. Queens University. Department Of Biology; Canadá
Fil: Scordo, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Geografía y Turismo; Argentina
Fil: Vanni, Michael J.. Miami University; Estados Unidos
Fil: Verburg, Piet. Victoria University Of Wellington; Nueva Zelanda
Fil: Weyhenmeyer, Gesa A.. Uppsala Universitet; Suecia - Materia
-
LAKE
PRIMARY PRODUCTIVITY
NUTRIENT CONTROL
ENVIRONMENTAL CHANGE
PROCESS MODEL - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/277389
Ver los metadatos del registro completo
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Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigmOleksy, Isabella A.Solomon, Christopher T.Jones, Stuart E.Olson, CarlyBertolet, Brittni L.Adrian, RitaBansal, SheelBaron, Jill S.Brothers, SorenChandra, SudeepChou, Hsiu-MeiColom Montero, WilliamCulpepper, Joshuade Eyto, ElviraFarragher, Matthew J.Hilt, SabineHoleck, Kristen T.Kazanjian, GarabetKlaus, MarcusKlug, JenniferKöhler, JanLaas, AloLundin, ErikParkes, Alice H.Rose, Kevin C.Rustam, Lars G.Rusak, JamesScordo, FacundoVanni, Michael J.Verburg, PietWeyhenmeyer, Gesa A.LAKEPRIMARY PRODUCTIVITYNUTRIENT CONTROLENVIRONMENTAL CHANGEPROCESS MODELhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. In lakes, pelagic gross primary productivity (GPP) is strongly controlled by inputs of nutrients and dissolved organic matter. Although past studies have developed process models of this nutrient-color paradigm (NCP), broad empirical tests of these models are scarce. We used data from 58 globally distributed, mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. The model includes three state variables–dissolved phosphorus, terrestrial dissolved organic carbon (DOC), and phytoplankton biomass–and generates realistic predictions for equilibrium rates of pelagic GPP. We calibrated our model using a Bayesian data assimilation technique on a subset of lakes where DOC and total phosphorus (TP) loads were known. We then asked how well the calibrated model performed with a larger set of lakes. Revised parameter estimates from the updated model aligned well with existing literature values. Observed GPP varied nonlinearly with both inflow DOC and TP concentrations in a manner consistent with increasing light limitation as DOC inputs increased and decreasing nutrient limitation as TP inputs increased. Furthermore, across these diverse lake ecosystems, model predictions of GPP were highly correlated with observed values derived from high-frequency sensor data. The GPP predictions using the updated parameters improved upon previous estimates, expanding the utility of a process model with simplified assumptions for water column mixing. Our analysis provides a model structure that may be broadly useful for understanding current and future patterns in lake primary production.Fil: Oleksy, Isabella A.. University of Colorado; Estados UnidosFil: Solomon, Christopher T.. Cary Institute Of Ecosystem Studies; Estados UnidosFil: Jones, Stuart E.. University of Notre Dame; Estados UnidosFil: Olson, Carly. University of Nebraska; Estados UnidosFil: Bertolet, Brittni L.. University of California at Irvine; Estados UnidosFil: Adrian, Rita. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; AlemaniaFil: Bansal, Sheel. United States Geological Survey; Estados UnidosFil: Baron, Jill S.. United States Geological Survey; Estados UnidosFil: Brothers, Soren. University of Toronto; CanadáFil: Chandra, Sudeep. University of Nevada; Estados UnidosFil: Chou, Hsiu-Mei. National Center For High Performance Computing; ChinaFil: Colom Montero, William. Uppsala Universitet; SueciaFil: Culpepper, Joshua. York University; Estados UnidosFil: de Eyto, Elvira. Marine Institute; IrlandaFil: Farragher, Matthew J.. University Of Maine; Estados UnidosFil: Hilt, Sabine. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; AlemaniaFil: Holeck, Kristen T.. Cornell University; Estados UnidosFil: Kazanjian, Garabet. American University Of Armenia; ArmeniaFil: Klaus, Marcus. Swedish University Of Agricultural Sciences; SueciaFil: Klug, Jennifer. Fairfield University; Estados UnidosFil: Köhler, Jan. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; AlemaniaFil: Laas, Alo. Estonian University Of Life Sciences; EstoniaFil: Lundin, Erik. Swedish Polar Research Secretariate; SueciaFil: Parkes, Alice H.. Université Du Québec; CanadáFil: Rose, Kevin C.. Rensselaer Polytechnic Institute; Estados UnidosFil: Rustam, Lars G.. Cornell University; Estados UnidosFil: Rusak, James. Queens University. Department Of Biology; CanadáFil: Scordo, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Geografía y Turismo; ArgentinaFil: Vanni, Michael J.. Miami University; Estados UnidosFil: Verburg, Piet. Victoria University Of Wellington; Nueva ZelandaFil: Weyhenmeyer, Gesa A.. Uppsala Universitet; SueciaWiley2024-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/277389Oleksy, Isabella A.; Solomon, Christopher T.; Jones, Stuart E.; Olson, Carly; Bertolet, Brittni L.; et al.; Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm; Wiley; Journal of Geophysical Research: Biogeosciences; 129; 12; 12-2024; 1-152169-89532169-8961CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JG008140info:eu-repo/semantics/altIdentifier/doi/10.1029/2024JG008140info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-12-23T14:13:42Zoai:ri.conicet.gov.ar:11336/277389instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-12-23 14:13:43.222CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| dc.title.none.fl_str_mv |
Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm |
| title |
Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm |
| spellingShingle |
Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm Oleksy, Isabella A. LAKE PRIMARY PRODUCTIVITY NUTRIENT CONTROL ENVIRONMENTAL CHANGE PROCESS MODEL |
| title_short |
Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm |
| title_full |
Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm |
| title_fullStr |
Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm |
| title_full_unstemmed |
Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm |
| title_sort |
Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm |
| dc.creator.none.fl_str_mv |
Oleksy, Isabella A. Solomon, Christopher T. Jones, Stuart E. Olson, Carly Bertolet, Brittni L. Adrian, Rita Bansal, Sheel Baron, Jill S. Brothers, Soren Chandra, Sudeep Chou, Hsiu-Mei Colom Montero, William Culpepper, Joshua de Eyto, Elvira Farragher, Matthew J. Hilt, Sabine Holeck, Kristen T. Kazanjian, Garabet Klaus, Marcus Klug, Jennifer Köhler, Jan Laas, Alo Lundin, Erik Parkes, Alice H. Rose, Kevin C. Rustam, Lars G. Rusak, James Scordo, Facundo Vanni, Michael J. Verburg, Piet Weyhenmeyer, Gesa A. |
| author |
Oleksy, Isabella A. |
| author_facet |
Oleksy, Isabella A. Solomon, Christopher T. Jones, Stuart E. Olson, Carly Bertolet, Brittni L. Adrian, Rita Bansal, Sheel Baron, Jill S. Brothers, Soren Chandra, Sudeep Chou, Hsiu-Mei Colom Montero, William Culpepper, Joshua de Eyto, Elvira Farragher, Matthew J. Hilt, Sabine Holeck, Kristen T. Kazanjian, Garabet Klaus, Marcus Klug, Jennifer Köhler, Jan Laas, Alo Lundin, Erik Parkes, Alice H. Rose, Kevin C. Rustam, Lars G. Rusak, James Scordo, Facundo Vanni, Michael J. Verburg, Piet Weyhenmeyer, Gesa A. |
| author_role |
author |
| author2 |
Solomon, Christopher T. Jones, Stuart E. Olson, Carly Bertolet, Brittni L. Adrian, Rita Bansal, Sheel Baron, Jill S. Brothers, Soren Chandra, Sudeep Chou, Hsiu-Mei Colom Montero, William Culpepper, Joshua de Eyto, Elvira Farragher, Matthew J. Hilt, Sabine Holeck, Kristen T. Kazanjian, Garabet Klaus, Marcus Klug, Jennifer Köhler, Jan Laas, Alo Lundin, Erik Parkes, Alice H. Rose, Kevin C. Rustam, Lars G. Rusak, James Scordo, Facundo Vanni, Michael J. Verburg, Piet Weyhenmeyer, Gesa A. |
| author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
LAKE PRIMARY PRODUCTIVITY NUTRIENT CONTROL ENVIRONMENTAL CHANGE PROCESS MODEL |
| topic |
LAKE PRIMARY PRODUCTIVITY NUTRIENT CONTROL ENVIRONMENTAL CHANGE PROCESS MODEL |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 |
| dc.description.none.fl_txt_mv |
Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. In lakes, pelagic gross primary productivity (GPP) is strongly controlled by inputs of nutrients and dissolved organic matter. Although past studies have developed process models of this nutrient-color paradigm (NCP), broad empirical tests of these models are scarce. We used data from 58 globally distributed, mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. The model includes three state variables–dissolved phosphorus, terrestrial dissolved organic carbon (DOC), and phytoplankton biomass–and generates realistic predictions for equilibrium rates of pelagic GPP. We calibrated our model using a Bayesian data assimilation technique on a subset of lakes where DOC and total phosphorus (TP) loads were known. We then asked how well the calibrated model performed with a larger set of lakes. Revised parameter estimates from the updated model aligned well with existing literature values. Observed GPP varied nonlinearly with both inflow DOC and TP concentrations in a manner consistent with increasing light limitation as DOC inputs increased and decreasing nutrient limitation as TP inputs increased. Furthermore, across these diverse lake ecosystems, model predictions of GPP were highly correlated with observed values derived from high-frequency sensor data. The GPP predictions using the updated parameters improved upon previous estimates, expanding the utility of a process model with simplified assumptions for water column mixing. Our analysis provides a model structure that may be broadly useful for understanding current and future patterns in lake primary production. Fil: Oleksy, Isabella A.. University of Colorado; Estados Unidos Fil: Solomon, Christopher T.. Cary Institute Of Ecosystem Studies; Estados Unidos Fil: Jones, Stuart E.. University of Notre Dame; Estados Unidos Fil: Olson, Carly. University of Nebraska; Estados Unidos Fil: Bertolet, Brittni L.. University of California at Irvine; Estados Unidos Fil: Adrian, Rita. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; Alemania Fil: Bansal, Sheel. United States Geological Survey; Estados Unidos Fil: Baron, Jill S.. United States Geological Survey; Estados Unidos Fil: Brothers, Soren. University of Toronto; Canadá Fil: Chandra, Sudeep. University of Nevada; Estados Unidos Fil: Chou, Hsiu-Mei. National Center For High Performance Computing; China Fil: Colom Montero, William. Uppsala Universitet; Suecia Fil: Culpepper, Joshua. York University; Estados Unidos Fil: de Eyto, Elvira. Marine Institute; Irlanda Fil: Farragher, Matthew J.. University Of Maine; Estados Unidos Fil: Hilt, Sabine. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; Alemania Fil: Holeck, Kristen T.. Cornell University; Estados Unidos Fil: Kazanjian, Garabet. American University Of Armenia; Armenia Fil: Klaus, Marcus. Swedish University Of Agricultural Sciences; Suecia Fil: Klug, Jennifer. Fairfield University; Estados Unidos Fil: Köhler, Jan. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; Alemania Fil: Laas, Alo. Estonian University Of Life Sciences; Estonia Fil: Lundin, Erik. Swedish Polar Research Secretariate; Suecia Fil: Parkes, Alice H.. Université Du Québec; Canadá Fil: Rose, Kevin C.. Rensselaer Polytechnic Institute; Estados Unidos Fil: Rustam, Lars G.. Cornell University; Estados Unidos Fil: Rusak, James. Queens University. Department Of Biology; Canadá Fil: Scordo, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Geografía y Turismo; Argentina Fil: Vanni, Michael J.. Miami University; Estados Unidos Fil: Verburg, Piet. Victoria University Of Wellington; Nueva Zelanda Fil: Weyhenmeyer, Gesa A.. Uppsala Universitet; Suecia |
| description |
Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. In lakes, pelagic gross primary productivity (GPP) is strongly controlled by inputs of nutrients and dissolved organic matter. Although past studies have developed process models of this nutrient-color paradigm (NCP), broad empirical tests of these models are scarce. We used data from 58 globally distributed, mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. The model includes three state variables–dissolved phosphorus, terrestrial dissolved organic carbon (DOC), and phytoplankton biomass–and generates realistic predictions for equilibrium rates of pelagic GPP. We calibrated our model using a Bayesian data assimilation technique on a subset of lakes where DOC and total phosphorus (TP) loads were known. We then asked how well the calibrated model performed with a larger set of lakes. Revised parameter estimates from the updated model aligned well with existing literature values. Observed GPP varied nonlinearly with both inflow DOC and TP concentrations in a manner consistent with increasing light limitation as DOC inputs increased and decreasing nutrient limitation as TP inputs increased. Furthermore, across these diverse lake ecosystems, model predictions of GPP were highly correlated with observed values derived from high-frequency sensor data. The GPP predictions using the updated parameters improved upon previous estimates, expanding the utility of a process model with simplified assumptions for water column mixing. Our analysis provides a model structure that may be broadly useful for understanding current and future patterns in lake primary production. |
| publishDate |
2024 |
| dc.date.none.fl_str_mv |
2024-12 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/277389 Oleksy, Isabella A.; Solomon, Christopher T.; Jones, Stuart E.; Olson, Carly; Bertolet, Brittni L.; et al.; Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm; Wiley; Journal of Geophysical Research: Biogeosciences; 129; 12; 12-2024; 1-15 2169-8953 2169-8961 CONICET Digital CONICET |
| url |
http://hdl.handle.net/11336/277389 |
| identifier_str_mv |
Oleksy, Isabella A.; Solomon, Christopher T.; Jones, Stuart E.; Olson, Carly; Bertolet, Brittni L.; et al.; Controls on lake pelagic primary productivity: Formalizing the nutrient‐color paradigm; Wiley; Journal of Geophysical Research: Biogeosciences; 129; 12; 12-2024; 1-15 2169-8953 2169-8961 CONICET Digital CONICET |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
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info:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JG008140 info:eu-repo/semantics/altIdentifier/doi/10.1029/2024JG008140 |
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info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/2.5/ar/ |
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openAccess |
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https://creativecommons.org/licenses/by/2.5/ar/ |
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application/pdf application/pdf |
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Wiley |
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Wiley |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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13.075124 |