Articles | Volume 19, issue 16
https://doi.org/10.5194/bg-19-3739-2022
https://doi.org/10.5194/bg-19-3739-2022
Research article
 | 
16 Aug 2022
Research article |  | 16 Aug 2022

Variability and uncertainty in flux-site-scale net ecosystem exchange simulations based on machine learning and remote sensing: a systematic evaluation

Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde

Related authors

Global dryland aridity changes indicated by atmospheric, hydrological, and vegetation observations at meteorological stations
Haiyang Shi, Geping Luo, Olaf Hellwich, Xiufeng He, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 27, 4551–4562, https://doi.org/10.5194/hess-27-4551-2023,https://doi.org/10.5194/hess-27-4551-2023, 2023
Short summary
Revisiting and attributing the global controls over terrestrial ecosystem functions of climate and plant traits at FLUXNET sites via causal graphical models
Haiyang Shi, Geping Luo, Olaf Hellwich, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Biogeosciences, 20, 2727–2741, https://doi.org/10.5194/bg-20-2727-2023,https://doi.org/10.5194/bg-20-2727-2023, 2023
Short summary
Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis
Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 26, 4603–4618, https://doi.org/10.5194/hess-26-4603-2022,https://doi.org/10.5194/hess-26-4603-2022, 2022
Short summary
A novel causal structure-based framework for comparing a basin-wide water–energy–food–ecology nexus applied to the data-limited Amu Darya and Syr Darya river basins
Haiyang Shi, Geping Luo, Hongwei Zheng, Chunbo Chen, Olaf Hellwich, Jie Bai, Tie Liu, Shuang Liu, Jie Xue, Peng Cai, Huili He, Friday Uchenna Ochege, Tim Van de Voorde, and Philippe de Maeyer
Hydrol. Earth Syst. Sci., 25, 901–925, https://doi.org/10.5194/hess-25-901-2021,https://doi.org/10.5194/hess-25-901-2021, 2021
Short summary

Related subject area

Biogeochemistry: Air - Land Exchange
Environmental controls of winter soil carbon dioxide fluxes in boreal and tundra environments
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Carolina Voigt, Nick Rutter, Paul Mann, Jean-Daniel Sylvain, and Alexandre Roy
Biogeosciences, 20, 5087–5108, https://doi.org/10.5194/bg-20-5087-2023,https://doi.org/10.5194/bg-20-5087-2023, 2023
Short summary
Origin of secondary fatty alcohols in atmospheric aerosols in a cool–temperate forest based on their mass size distributions
Yuhao Cui, Eri Tachibana, Kimitaka Kawamura, and Yuzo Miyazaki
Biogeosciences, 20, 4969–4980, https://doi.org/10.5194/bg-20-4969-2023,https://doi.org/10.5194/bg-20-4969-2023, 2023
Short summary
Sap flow and leaf gas exchange response to a drought and heatwave in urban green spaces in a Nordic city
Joyson Ahongshangbam, Liisa Kulmala, Jesse Soininen, Yasmin Frühauf, Esko Karvinen, Yann Salmon, Anna Lintunen, Anni Karvonen, and Leena Järvi
Biogeosciences, 20, 4455–4475, https://doi.org/10.5194/bg-20-4455-2023,https://doi.org/10.5194/bg-20-4455-2023, 2023
Short summary
Changes in biogenic volatile organic compound emissions in response to the El Niño–Southern Oscillation
Ryan Vella, Andrea Pozzer, Matthew Forrest, Jos Lelieveld, Thomas Hickler, and Holger Tost
Biogeosciences, 20, 4391–4412, https://doi.org/10.5194/bg-20-4391-2023,https://doi.org/10.5194/bg-20-4391-2023, 2023
Short summary
Rethinking the deployment of static chambers for CO2 flux measurement in dry desert soils
Nadav Bekin and Nurit Agam
Biogeosciences, 20, 3791–3802, https://doi.org/10.5194/bg-20-3791-2023,https://doi.org/10.5194/bg-20-3791-2023, 2023
Short summary

Cited articles

Abbasian, H., Solgi, E., Mohsen Hosseini, S., and Hossein Kia, S.: Modeling terrestrial net ecosystem exchange using machine learning techniques based on flux tower measurements, Ecol. Model., 466, 109901, https://doi.org/10.1016/j.ecolmodel.2022.109901, 2022. 
Adams, D. C., Gurevitch, J., and Rosenberg, M. S.: Resampling tests for meta analysis of ecological data, Ecology, 78, 1277–1283, 1997. 
Baldocchi, D. D.: Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future, Global Change Biol., 9, 479–492, https://doi.org/10.1046/j.1365-2486.2003.00629.x, 2003. 
Berryman, E. M., Vanderhoof, M. K., Bradford, J. B., Hawbaker, T. J., Henne, P. D., Burns, S. P., Frank, J. M., Birdsey, R. A., and Ryan, M. G.: Estimating soil respiration in a subalpine landscape using point, terrain, climate, and greenness data, J. Geophys. Res.-Biogeo., 123, 3231–3249, 2018. 
Borenstein, M., Hedges, L. V., Higgins, J. P., and Rothstein, H. R.: Introduction to meta-analysis, John Wiley & Sons, https://doi.org/10.1002/9780470743386, 2011. 
Download
Short summary
A number of studies have been conducted by using machine learning approaches to simulate carbon fluxes. We performed a meta-analysis of these net ecosystem exchange (NEE) simulations. Random forests and support vector machines performed better than other algorithms. Models with larger timescales had a lower accuracy. For different plant functional types (PFTs), there were significant differences in the predictors used and their effects on model accuracy.
Altmetrics
Final-revised paper
Preprint