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.
| Original language | English |
|---|---|
| Pages (from-to) | 4040-4059 |
| Number of pages | 20 |
| Journal | Global Change Biology |
| Volume | 27 |
| Issue number | 17 |
| Early online date | 28 Apr 2021 |
| DOIs | |
| Publication status | Published - Sept 2021 |
Bibliographical note
Publisher Copyright:© 2021 John Wiley & Sons Ltd
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
Funding
AMV was supported by Nordenskiöld-samfundet, The Finnish Cultural Foundation, Alfred Kordelin Foundation, Väisälä fund, and Jenny and Antti Wihuri Foundation. AMV and ML were also funded by the Academy of Finland (grant 286950). JA acknowledges the funding by Academy of Finland (grants 33761, 337552), while AL acknowledges strategic research funding by the Academy of Finland for SOMPA project (grants 312912 and 325680). TT was funded by the Swedish National Space Board (SNSB Dnr 95/16). BR was supported by the NASA Carbon Cycle Science and Arctic-Boreal Vulnerability Experiment programs (ABoVE grant NNX17AE13G), SMN by NASA ABoVE (grant NNX15AT81A) and JDW by NNX15AT81A and NASA NIP grant NNH17ZDA001N. AMV, BR, SN, and JDW were also funded by the Gordon and Betty Moore foundation (grant #8414). EAGS acknowledges NSF Research, Synthesis, and Knowledge Transfer in a Changing Arctic: Science Support for the Study of Environmental Arctic Change (grant #1331083) and NSF PLR Arctic System Science Research Networking Activities (Permafrost Carbon Network: Synthesizing Flux Observations for Benchmarking Model Projections of Permafrost Carbon Exchange; grant #1931333). JK acknowledges NSF grant 1203583, DZ NSF 1204263 and 1702797 and WO NSF 1204263, and 1702798. WO and DZ further acknowledge NOAA NA16SEC4810008, NASA NNX-15AT74A and NNX16AF94A, EU Horizon 2020 727890, and UK NERC NE/P002552/1. HK, MU, and HI were funded by Arctic Challenge for Sustainability II grant JPMXD1420318865, and EH and PL by Natural Sciences and Engineering Research Council. MG acknowledges European Commission (INTAROS project, H2020-BG-09-2016, project 727890) and ESE NSF grants DEB-1636476, AON 856864, 1304271, 0632264, and 1107892, and the US Geological Survey. MM was funded by Academy of Finland (grant 317054) and MM and PJM were funded by the EU 6th Framework Programme project CARBO-North (grant 036993). AMV was supported by Nordenskiöld‐samfundet, The Finnish Cultural Foundation, Alfred Kordelin Foundation, Väisälä fund, and Jenny and Antti Wihuri Foundation. AMV and ML were also funded by the Academy of Finland (grant 286950). JA acknowledges the funding by Academy of Finland (grants 33761, 337552), while AL acknowledges strategic research funding by the Academy of Finland for SOMPA project (grants 312912 and 325680). TT was funded by the Swedish National Space Board (SNSB Dnr 95/16). BR was supported by the NASA Carbon Cycle Science and Arctic‐Boreal Vulnerability Experiment programs (ABoVE grant NNX17AE13G), SMN by NASA ABoVE (grant NNX15AT81A) and JDW by NNX15AT81A and NASA NIP grant NNH17ZDA001N. AMV, BR, SN, and JDW were also funded by the Gordon and Betty Moore foundation (grant #8414). EAGS acknowledges NSF Research, Synthesis, and Knowledge Transfer in a Changing Arctic: Science Support for the Study of Environmental Arctic Change (grant #1331083) and NSF PLR Arctic System Science Research Networking Activities (Permafrost Carbon Network: Synthesizing Flux Observations for Benchmarking Model Projections of Permafrost Carbon Exchange; grant #1931333). JK acknowledges NSF grant 1203583, DZ NSF 1204263 and 1702797 and WO NSF 1204263, and 1702798. WO and DZ further acknowledge NOAA NA16SEC4810008, NASA NNX‐15AT74A and NNX16AF94A, EU Horizon 2020 727890, and UK NERC NE/P002552/1. HK, MU, and HI were funded by Arctic Challenge for Sustainability II grant JPMXD1420318865, and EH and PL by Natural Sciences and Engineering Research Council. MG acknowledges European Commission (INTAROS project, H2020‐BG‐09‐2016, project 727890) and ESE NSF grants DEB‐1636476, AON 856864, 1304271, 0632264, and 1107892, and the US Geological Survey. MM was funded by Academy of Finland (grant 317054) and MM and PJM were funded by the EU 6th Framework Programme project CARBO‐North (grant 036993). CB and CV were funded by the EU FP7‐ENV project PAGE21 (grant 282700) and CB, CV, and PJM by the Nordic Center of Excellence project DEFROST. CB was further funded by the Academy of Finland (grant 314630), and CV by Academy of Finland (grant 332196). BE acknowledges Danish National Research Foundation (CENPERM DNRF100) and FJWP Research Council of Norway (Winterproof, grant 274711) and Swedish Research Council (WinterGap, project 2017‐05268). JC was funded by FORMAS (grant 942‐2015‐49). VLSL and CE were funded by the Natural Sciences and Engineering Research Council and MP by FORMAS #2016‐01289. JJ was funded by the Swedish Forest Society Foundation (2018‐485‐Steg 2 2017) and SFO by NSF grants PLR1504381 and PLR1836898. MST acknowledges Office of Biological and Environmental Research, DOE Office of Science; SJP the Korean government (NRF‐2021M1A5A1065425,KOPRI‐PN21011); and NC the Korean government (MSIP) (NRF‐2018R1D1A1B07047778 and NRF‐2021M1A5A1065679). HS was funded by Netherlands Earth System Science Centre (NESSC), and IM by Academy of Finland Flagship funding (project 337549) and ICOS‐Finland by University of Helsinki funding. RP was funded by Humboldt Fellowship for Experienced Researchers, MBN by Swedish Research Council, contract #2018‐03966 and the national research infrastructures SITES and ICOS, funded by VR and partner institutes, and ELB by Greenland Research Council grant number 80.35, financed by the “Danish Program for Arctic Research”. OS was supported through the Canada Research Chairs and Natural Sciences and Engineering Research Council Discovery Grants programs. The authors would also like to acknowledge Liangzhi Chen for his help with the literature review. Funding for the CO flux synthesis workshop was provided by the Arctic Data Center. 2
| Funders | Funder number |
|---|---|
| Nordenskiöld-samfundet | |
| Suomen Kulttuurirahasto | |
| Biological and Environmental Research | |
| Danmarks Grundforskningsfond | |
| Nordenskiöld‐samfundet | |
| Jenny ja Antti Wihurin Rahasto | |
| Natural Sciences and Engineering Research Council of Canada | |
| Canada Research Chairs | |
| national research infrastructures SITES | |
| Alfred Kordelinin Säätiö | |
| Office of Science | NRF‐2021M1A5A1065425, KOPRI‐PN21011 |
| Gordon and Betty Moore Foundation | 8414, 1331083, 1931333, DZ NSF 1204263, 1702798, 1702797, 1203583, WO NSF 1204263 |
| U.S. Geological Survey | 317054 |
| National Oceanic and Atmospheric Administration | NNX16AF94A, NNX-15AT74A, NA16SEC4810008 |
| European Commission | 282700 |
| FJWP Research Council of Norway | 274711 |
| Netherlands Earth System Science Centre | 337549 |
| Greenland Research Council | 80.35 |
| Horizon 2020 Framework Programme | 851181, 727890 |
| Svenska Forskningsrådet Formas | 2016‐01289, 942‐2015‐49 |
| National Science Foundation | 1107892 |
| Natural Environment Research Council | JPMXD1420318865, NE/P002552/1 |
| Swedish National Space Agency | SNSB Dnr 95/16 |
| EU Horizon | 2020 727890 |
| INTAROS | H2020‐BG‐09‐2016 |
| Academy of Finland | 337552, 33761, 286950, 312912, 325680 |
| NASA ABoVE | NNH17ZDA001N, NNX15AT81A |
| Helsingin Yliopisto | 2018‐03966 |
| Ministry of Science, ICT and Future Planning | NRF‐2021M1A5A1065679, NRF‐2018R1D1A1B07047778 |
| Skogssällskapet | 2018‐485‐Steg 2 2017, PLR1836898, PLR1504381 |
| Japan Society for the Promotion of Science | 20H00640 |
| ESE NSF | DEB‐1636476, 1304271, AON 856864, 0632264 |
| Vetenskapsrådet | 2017‐05268 |
| Sixth Framework Programme | 036993 |
| EU FP7‐ENV | 332196, 314630 |
| CENPERM | DNRF100 |
| National Aeronautics and Space Administration | NNX17AE13G |
Keywords
- Arctic
- CO balance
- empirical
- greenhouse gas
- land
- permafrost
- remote sensing
