Statistical upscaling of ecosystem CO <sub>2</sub> fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties
Anna‐Maria Virkkala, Juha Aalto, Brendan M. Rogers, Torbern Tagesson, Claire C. Treat, Susan M. Natali, Jennifer D. Watts, Stefano Potter, Aleksi Lehtonen, Marguerite Mauritz, Edward A. G. Schuur, John Kochendorfer, Donatella Zona, Walter C. Oechel, Hideki Kobayashi, Elyn Humphreys, Mathias Goeckede, Hiroki Iwata, Peter M. Lafleur, E. S. Euskirchen, Stef Bokhorst, Maija E. Marushchak, Pertti J. Martikainen, Bo Elberling, Carolina Voigt, Christina Biasi, Oliver Sonnentag, Frans‐Jan W. Parmentier, Masahito Ueyama, Gerardo Celis, Vincent L. St. Louis, Craig A. Emmerton, Matthias Peichl, Jinshu Chi, Järvi Järveoja, Mats B. Nilsson, Steven F. Oberbauer, Margaret Torn, Sang‐Jong Park, A. J. Dolman, Ivan Mammarella, Namyi Chae, Rafael Poyatos, Efrèn López‐Blanco, Torben R. Christensen, Min Jung Kwon, Torsten Sachs, David Holl, Miska Luoto, Anna‐Maria Virkkala, Juha Aalto, Brendan M. Rogers, Torbern Tagesson, Claire C. Treat, Susan M. Natali, Jennifer D. Watts, Stefano Potter, Aleksi Lehtonen, Marguerite Mauritz, Edward A. G. Schuur, John Kochendorfer, Donatella Zona, Walter C. Oechel, Hideki Kobayashi, Elyn Humphreys, Mathias Goeckede, Hiroki Iwata, Peter M. Lafleur, E. S. Euskirchen, Stef Bokhorst, Maija E. Marushchak, Pertti J. Martikainen, Bo Elberling, Carolina Voigt, Christina Biasi, Oliver Sonnentag, Frans‐Jan W. Parmentier, Masahito Ueyama, Gerardo Celis, Vincent L. St. Louis, Craig A. Emmerton, Matthias Peichl, Jinshu Chi, Järvi Järveoja, Mats B. Nilsson, Steven F. Oberbauer, Margaret Torn, Sang‐Jong Park, A. J. Dolman, Ivan Mammarella, Namyi Chae, Rafael Poyatos, Efrèn López‐Blanco, Torben R. Christensen, Min Jung Kwon, Torsten Sachs, David Holl, Miska Luoto
Abstract
The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.- Cite:
- Anna‐Maria Virkkala, Juha Aalto, Brendan M. Rogers, Torbern Tagesson, Claire C. Treat, Susan M. Natali, Jennifer D. Watts, Stefano Potter, Aleksi Lehtonen, Marguerite Mauritz, Edward A. G. Schuur, John Kochendorfer, Donatella Zona, Walter C. Oechel, Hideki Kobayashi, Elyn Humphreys, Mathias Goeckede, Hiroki Iwata, Peter M. Lafleur, et al.. 2021. Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties. Global Change Biology, Volume 27, Issue 17, 27(17):4040–4059.
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@article{Virkkala-2021-Statistical,
title = "Statistical upscaling of ecosystem CO {\textless}sub{\textgreater}2{\textless}/sub{\textgreater} fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties",
author = {Virkkala, Anna‐Maria and
Aalto, Juha and
Rogers, Brendan M. and
Tagesson, Torbern and
Treat, Claire C. and
Natali, Susan M. and
Watts, Jennifer D. and
Potter, Stefano and
Lehtonen, Aleksi and
Mauritz, Marguerite and
Schuur, Edward A. G. and
Kochendorfer, John and
Zona, Donatella and
Oechel, Walter C. and
Kobayashi, Hideki and
Humphreys, Elyn and
Goeckede, Mathias and
Iwata, Hiroki and
Lafleur, Peter M. and
Euskirchen, E. S. and
Bokhorst, Stef and
Marushchak, Maija E. and
Martikainen, Pertti J. and
Elberling, Bo and
Voigt, Carolina and
Biasi, Christina and
Sonnentag, Oliver and
Parmentier, Frans‐Jan W. and
Ueyama, Masahito and
Celis, Gerardo and
Louis, Vincent L. St. and
Emmerton, Craig A. and
Peichl, Matthias and
Chi, Jinshu and
J{\"a}rveoja, J{\"a}rvi and
Nilsson, Mats B. and
Oberbauer, Steven F. and
Torn, Margaret and
Park, Sang‐Jong and
Dolman, A. J. and
Mammarella, Ivan and
Chae, Namyi and
Poyatos, Rafael and
L{\'o}pez‐Blanco, Efr{\`e}n and
Christensen, Torben R. and
Kwon, Min Jung and
Sachs, Torsten and
Holl, David and
Luoto, Miska and
Virkkala, Anna‐Maria and
Aalto, Juha and
Rogers, Brendan M. and
Tagesson, Torbern and
Treat, Claire C. and
Natali, Susan M. and
Watts, Jennifer D. and
Potter, Stefano and
Lehtonen, Aleksi and
Mauritz, Marguerite and
Schuur, Edward A. G. and
Kochendorfer, John and
Zona, Donatella and
Oechel, Walter C. and
Kobayashi, Hideki and
Humphreys, Elyn and
Goeckede, Mathias and
Iwata, Hiroki and
Lafleur, Peter M. and
Euskirchen, E. S. and
Bokhorst, Stef and
Marushchak, Maija E. and
Martikainen, Pertti J. and
Elberling, Bo and
Voigt, Carolina and
Biasi, Christina and
Sonnentag, Oliver and
Parmentier, Frans‐Jan W. and
Ueyama, Masahito and
Celis, Gerardo and
Louis, Vincent L. St. and
Emmerton, Craig A. and
Peichl, Matthias and
Chi, Jinshu and
J{\"a}rveoja, J{\"a}rvi and
Nilsson, Mats B. and
Oberbauer, Steven F. and
Torn, Margaret and
Park, Sang‐Jong and
Dolman, A. J. and
Mammarella, Ivan and
Chae, Namyi and
Poyatos, Rafael and
L{\'o}pez‐Blanco, Efr{\`e}n and
Christensen, Torben R. and
Kwon, Min Jung and
Sachs, Torsten and
Holl, David and
Luoto, Miska},
journal = "Global Change Biology, Volume 27, Issue 17",
volume = "27",
number = "17",
year = "2021",
publisher = "Wiley",
url = "https://gwf-uwaterloo.github.io/gwf-publications/G21-100001",
doi = "10.1111/gcb.15659",
pages = "4040--4059",
abstract = "The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990{--}2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990{--}2015, although uncertainty remains high.",
}
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<abstract>The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.</abstract>
<identifier type="citekey">Virkkala-2021-Statistical</identifier>
<identifier type="doi">10.1111/gcb.15659</identifier>
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<url>https://gwf-uwaterloo.github.io/gwf-publications/G21-100001</url>
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%0 Journal Article %T Statistical upscaling of ecosystem CO \textlesssub\textgreater2\textless/sub\textgreater fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties %A Virkkala, Anna‐Maria %A Aalto, Juha %A Rogers, Brendan M. %A Tagesson, Torbern %A Treat, Claire C. %A Natali, Susan M. %A Watts, Jennifer D. %A Potter, Stefano %A Lehtonen, Aleksi %A Mauritz, Marguerite %A Schuur, Edward A. G. %A Kochendorfer, John %A Zona, Donatella %A Oechel, Walter C. %A Kobayashi, Hideki %A Humphreys, Elyn %A Goeckede, Mathias %A Iwata, Hiroki %A Lafleur, Peter M. %A Euskirchen, E. S. %A Bokhorst, Stef %A Marushchak, Maija E. %A Martikainen, Pertti J. %A Elberling, Bo %A Voigt, Carolina %A Biasi, Christina %A Sonnentag, Oliver %A Parmentier, Frans‐Jan W. %A Ueyama, Masahito %A Celis, Gerardo %A Louis, Vincent L. St. %A Emmerton, Craig A. %A Peichl, Matthias %A Chi, Jinshu %A Järveoja, Järvi %A Nilsson, Mats B. %A Oberbauer, Steven F. %A Torn, Margaret %A Park, Sang‐Jong %A Dolman, A. J. %A Mammarella, Ivan %A Chae, Namyi %A Poyatos, Rafael %A López‐Blanco, Efrèn %A Christensen, Torben R. %A Kwon, Min Jung %A Sachs, Torsten %A Holl, David %A Luoto, Miska %J Global Change Biology, Volume 27, Issue 17 %D 2021 %V 27 %N 17 %I Wiley %F Virkkala-2021-Statistical %X The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high. %R 10.1111/gcb.15659 %U https://gwf-uwaterloo.github.io/gwf-publications/G21-100001 %U https://doi.org/10.1111/gcb.15659 %P 4040-4059
Markdown (Informal)
[Statistical upscaling of ecosystem CO <sub>2</sub> fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties](https://gwf-uwaterloo.github.io/gwf-publications/G21-100001) (Virkkala et al., GWF 2021)
- Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties (Virkkala et al., GWF 2021)
ACL
- Anna‐Maria Virkkala, Juha Aalto, Brendan M. Rogers, Torbern Tagesson, Claire C. Treat, Susan M. Natali, Jennifer D. Watts, Stefano Potter, Aleksi Lehtonen, Marguerite Mauritz, Edward A. G. Schuur, John Kochendorfer, Donatella Zona, Walter C. Oechel, Hideki Kobayashi, Elyn Humphreys, Mathias Goeckede, Hiroki Iwata, Peter M. Lafleur, et al.. 2021. Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties. Global Change Biology, Volume 27, Issue 17, 27(17):4040–4059.