One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models
Abstract Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land‐surface model (LSM) simulations during drought. However, systematic evaluations of both optimality‐based and alternative empirical formulations for...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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American Geophysical Union (AGU)
2022-04-01
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| Series: | Journal of Advances in Modeling Earth Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2021MS002761 |
| _version_ | 1828384552338325504 |
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| author | Manon E. B. Sabot Martin G. De Kauwe Andy J. Pitman Belinda E. Medlyn David S. Ellsworth Nicolas K. Martin‐StPaul Jin Wu Brendan Choat Jean‐Marc Limousin Patrick J. Mitchell Alistair Rogers Shawn P. Serbin |
| author_facet | Manon E. B. Sabot Martin G. De Kauwe Andy J. Pitman Belinda E. Medlyn David S. Ellsworth Nicolas K. Martin‐StPaul Jin Wu Brendan Choat Jean‐Marc Limousin Patrick J. Mitchell Alistair Rogers Shawn P. Serbin |
| author_sort | Manon E. B. Sabot |
| collection | DOAJ |
| description | Abstract Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land‐surface model (LSM) simulations during drought. However, systematic evaluations of both optimality‐based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimization approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviors differ in response to abiotic changes. We also evaluate the models against leaf‐level observations of gas‐exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361–3,286 mm yr−1. We find that models differ in how easily parameterized they are, due to: (a) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (b) low influence parameters, (c) sensitivities to environmental drivers. In both the idealized experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapor pressure deficit. For example, stomatal closure rates at high vapor pressure deficit range between −45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf‐gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses. |
| first_indexed | 2024-12-10T05:05:10Z |
| format | Article |
| id | doaj.art-8b820a3bed2d43009b0f52d9a5cd5843 |
| institution | Directory Open Access Journal |
| issn | 1942-2466 |
| language | English |
| last_indexed | 2024-12-10T05:05:10Z |
| publishDate | 2022-04-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Journal of Advances in Modeling Earth Systems |
| spelling | doaj.art-8b820a3bed2d43009b0f52d9a5cd58432022-12-22T02:01:17ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662022-04-01144n/an/a10.1029/2021MS002761One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global ModelsManon E. B. Sabot0Martin G. De Kauwe1Andy J. Pitman2Belinda E. Medlyn3David S. Ellsworth4Nicolas K. Martin‐StPaul5Jin Wu6Brendan Choat7Jean‐Marc Limousin8Patrick J. Mitchell9Alistair Rogers10Shawn P. Serbin11ARC Centre of Excellence for Climate Extremes Sydney NSW AustraliaARC Centre of Excellence for Climate Extremes Sydney NSW AustraliaARC Centre of Excellence for Climate Extremes Sydney NSW AustraliaHawkesbury Institute for the Environment Western Sydney University Penrith NSW AustraliaHawkesbury Institute for the Environment Western Sydney University Penrith NSW AustraliaINRAE URFM, Domaine Saint Paul Centre de Recherche PACA Avignon FranceSchool of Biological Sciences The University of Hong Kong Hong Kong ChinaHawkesbury Institute for the Environment Western Sydney University Penrith NSW AustraliaCEFE Université Montpellier CNRS EPHE IRD Paul Valéry University Montpellier 3 Montpellier FranceCSIRO Agriculture and Food Hobart TAS AustraliaDepartment of Environmental and Climate Sciences Brookhaven National Laboratory Upton NY USADepartment of Environmental and Climate Sciences Brookhaven National Laboratory Upton NY USAAbstract Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land‐surface model (LSM) simulations during drought. However, systematic evaluations of both optimality‐based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimization approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviors differ in response to abiotic changes. We also evaluate the models against leaf‐level observations of gas‐exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361–3,286 mm yr−1. We find that models differ in how easily parameterized they are, due to: (a) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (b) low influence parameters, (c) sensitivities to environmental drivers. In both the idealized experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapor pressure deficit. For example, stomatal closure rates at high vapor pressure deficit range between −45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf‐gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses.https://doi.org/10.1029/2021MS002761gas exchangeplant hydraulicsstomatal optimizationland‐surface modelsdroughtvapor pressure deficit |
| spellingShingle | Manon E. B. Sabot Martin G. De Kauwe Andy J. Pitman Belinda E. Medlyn David S. Ellsworth Nicolas K. Martin‐StPaul Jin Wu Brendan Choat Jean‐Marc Limousin Patrick J. Mitchell Alistair Rogers Shawn P. Serbin One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models Journal of Advances in Modeling Earth Systems gas exchange plant hydraulics stomatal optimization land‐surface models drought vapor pressure deficit |
| title | One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models |
| title_full | One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models |
| title_fullStr | One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models |
| title_full_unstemmed | One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models |
| title_short | One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models |
| title_sort | one stomatal model to rule them all toward improved representation of carbon and water exchange in global models |
| topic | gas exchange plant hydraulics stomatal optimization land‐surface models drought vapor pressure deficit |
| url | https://doi.org/10.1029/2021MS002761 |
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