Articles | Volume 21, issue 16
https://doi.org/10.5194/bg-21-3735-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/bg-21-3735-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Aug 2024
Research article |
| 23 Aug 2024
| 23 Aug 2024
Optimizing the terrestrial ecosystem gross primary productivity using carbonyl sulfide (COS) within a two-leaf modeling framework
Huajie Zhu
International Institute for Earth System Science, Nanjing University, Nanjing, China
Xiuli Xing
Department of Environmental Science and Engineering, Fudan University, Shanghai, China
Mousong Wu
CORRESPONDING AUTHOR
International Institute for Earth System Science, Nanjing University, Nanjing, China
Weimin Ju
International Institute for Earth System Science, Nanjing University, Nanjing, China
Fei Jiang
International Institute for Earth System Science, Nanjing University, Nanjing, China
Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China
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Cited articles
Abadie, C., Maignan, F., Remaud, M., Ogée, J., Campbell, J. E., Whelan, M. E., Kitz, F., Spielmann, F. M., Wohlfahrt, G., Wehr, R., Sun, W., Raoult, N., Seibt, U., Hauglustaine, D., Lennartz, S. T., Belviso, S., Montagne, D., and Peylin, P.: Global modelling of soil carbonyl sulfide exchanges, Biogeosciences, 19, 2427–2463, https://doi.org/10.5194/bg-19-2427-2022, 2022.
Abadie, C., Maignan, F., Remaud, M., Kohonen, K.-M., Sun, W., Kooijmans, L., Vesala, T., Seibt, U., Raoult, N., Bastrikov, V., Belviso, S., and Peylin, P.: Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations, J. Geophys. Res.-Biogeo., 128, e2023JG007407, https://doi.org/10.1029/2023JG007407, 2023.
Asaf, D., Rotenberg, E., Tatarinov, F., Dicken, U., Montzka, S. A., and Yakir, D.: Ecosystem photosynthesis inferred from measurements of carbonyl sulphide flux, Nat. Geosci., 6, 186–190, 2013.
Badger, M. R. and Price, G. D.: The role of carbonic anhydrase in photosynthesis, Annu Rev. Plant Biol., 45, 369–392, 1994.
Ball, J. T., Woodrow, I. E., and Berry, J. A.: A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions, in: Progress in Photosynthesis Research: Volume 4 Proceedings of the VIIth International Congress on Photosynthesis Providence, Rhode Island, USA, August 10–15, 1986, edited by: Biggins, J., Springer Netherlands, Dordrecht, 221–224, https://doi.org/10.1007/978-94-017-0519-6_48, 1987.
Bao, S., Ibrom, A., Wohlfahrt, G., Koirala, S., Migliavacca, M., Zhang, Q., and Carvalhais, N.: Narrow but robust advantages in two-big-leaf light use efficiency models over big-leaf light use efficiency models at ecosystem level, Agr. Forest Meteorol., 326, 109185, https://doi.org/10.1016/j.agrformet.2022.109185, 2022.
Berry, J., Wolf, A., Campbell, J. E., Baker, I., Blake, N., Blake, D., Denning, A. S., Kawa, S. R., Montzka, S. A., Seibt, U., Stimler, K., Yakir, D., and Zhu, Z.: A coupled model of the global cycles of carbonyl sulfide and CO2: A possible new window on the carbon cycle, J. Geophys Res.-Biogeo., 118, 842–852, https://doi.org/10.1002/jgrg.20068, 2013.
Beven, K. and Binley, A.: The future of distributed models: model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.
Beven, K. and Binley, A.: GLUE: 20 years on, Hydrol. Process., 28, 5897–5918, 2014.
Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, J. Hydrol., 249, 11–29, 2001.
Blankenship, R. E.: Molecular mechanisms of photosynthesis, John Wiley & Sons, https://doi.org/10.1002/9780470758472, 2021.
Blasone, R.-S., Vrugt, J. A., Madsen, H., Rosbjerg, D., Robinson, B. A., and Zyvoloski, G. A.: Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling, Adv. Water Resour., 31, 630–648, 2008.
Bonan, G. B.: A biophysical surface energy budget analysis of soil temperature in the boreal forests of interior Alaska, Water Resour. Res., 27, 767–781, 1991.
Bonan, G. B., Lawrence, P. J., Oleson, K. W., Levis, S., Jung, M., Reichstein, M., Lawrence, D. M., and Swenson, S. C.: Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data, J. Geophys. Res.-Biogeo., 116, G02014, https://doi.org/10.1029/2010JG001593, 2011.
Borgonovo, E.: A new uncertainty importance measure, Reliab. Eng. Syst. Safe., 92, 771–784, 2007.
Canadell, J. G., Mooney, H. A., Baldocchi, D. D., Berry, J. A., Ehleringer, J. R., Field, C. B., Gower, S. T., Hollinger, D. Y., Hunt, J. E., Jackson, R. B., Running, S. W., Shaver, G. R., Steffen, W., Trumbore, S. E., Valentini, R., and Bond, B. Y.: Commentary: Carbon Metabolism of the Terrestrial Biosphere: A Multitechnique Approach for Improved Understanding, Ecosystems, 3, 115–130, https://doi.org/10.1007/s100210000014, 2000.
Chen, B., Wang, P., Wang, S., Ju, W., Liu, Z., and Zhang, Y.: Simulating canopy carbonyl sulfide uptake of two forest stands through an improved ecosystem model and parameter optimization using an ensemble Kalman filter, Ecol. Model., 475, 110212, https://doi.org/10.1016/j.ecolmodel.2022.110212, 2023.
Chen, J., Liu, J., Cihlar, J., and Goulden, M.: Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications, Ecol. Model., 124, 99–119, 1999.
Chen, J. M., Mo, G., Pisek, J., Liu, J., Deng, F., Ishizawa, M., and Chan, D.: Effects of foliage clumping on the estimation of global terrestrial gross primary productivity, Global Biogeochem. Cy., 26, GB1019, https://doi.org/10.1029/2010GB003996, 2012.
Chen, J. M., Ju, W., Ciais, P., Viovy, N., Liu, R., Liu, Y., and Lu, X.: Vegetation structural change since 1981 significantly enhanced the terrestrial carbon sink, Nat. Commun., 10, 4259, https://doi.org/10.1038/s41467-019-12257-8, 2019.
Cho, A., Kooijmans, L. M. J., Kohonen, K.-M., Wehr, R., and Krol, M. C.: Optimizing the carbonic anhydrase temperature response and stomatal conductance of carbonyl sulfide leaf uptake in the Simple Biosphere model (SiB4), Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, 2023.
Commane, R., Meredith, L. K., Baker, I. T., Berry, J. A., Munger, J. W., Montzka, S. A., Templer, P. H., Juice, S. M., Zahniser, M. S., and Wofsy, S. C.: Seasonal fluxes of carbonyl sulfide in a midlatitude forest, P. Natl. Acad. Sci. USA, 112, 14162–14167, 2015.
Commane, R., Wofsy, S., and Weir, R.: Fluxes of Carbonyl Sulfide at Harvard Forest EMS Tower since 2010 ver 4, Environmental Data Initiative [data set], https://doi.org/10.6073/pasta/7ed7b4d1fc7ad303998e76143a3b279a, 2016.
De Pury, D. and Farquhar, G.: Simple scaling of photosynthesis from leaves to canopies without the errors of big-leaf models, Plant Cell Environ., 20, 537–557, 1997.
Evans, J. R., Caemmerer, S., Setchell, B. A., and Hudson, G. S.: The relationship between CO2 transfer conductance and leaf anatomy in transgenic tobacco with a reduced content of Rubisco, Functional Plant Biology, 21, 475–495, 1994.
Fang, H., Baret, F., Plummer, S., and Schaepman-Strub, G.: An overview of global leaf area index (LAI): Methods, products, validation, and applications, Rev. Geophys., 57, 739–799, 2019.
Farquhar, G. D., von Caemmerer, S. v., and Berry, J. A.: A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149, 78–90, 1980.
Gan, Y., Duan, Q., Gong, W., Tong, C., Sun, Y., Chu, W., Ye, A., Miao, C., and Di, Z.: A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model, Environ. Modell. Softw., 51, 269–285, 2014.
Gu, L., Baldocchi, D., Verma, S. B., Black, T., Vesala, T., Falge, E. M., and Dowty, P. R.: Advantages of diffuse radiation for terrestrial ecosystem productivity, J. Geophys. Res.-Atmos., 107, ACL 2-1–ACL 2-23, 2002.
Harvard University: FLUXNET2015 US-Ha1 Harvard Forest EMS Tower (HFR1), FLUXNET [data set], https://doi.org/10.18140/FLX/1440071, 2020.
Haynes, K., Baker, I., and Denning, S.: Simple biosphere model version 4.2 (SiB4) technical description, Colorado State University, Fort Collins, CO, USA, 2020.
He, H., Jansson, P.-E., Svensson, M., Meyer, A., Klemedtsson, L., and Kasimir, Å.: Factors controlling Nitrous Oxide emission from a spruce forest ecosystem on drained organic soil, derived using the CoupModel, Ecol. Model., 321, 46–63, 2016.
He, Q., Ju, W., Dai, S., He, W., Song, L., Wang, S., Li, X., and Mao, G.: Drought risk of global terrestrial gross primary productivity over the last 40 years detected by a remote sensing-driven process model, J. Geophys. Res.-Biogeo., 126, e2020JG005944, 2021.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023.
Hilton, T. W., Whelan, M. E., Zumkehr, A., Kulkarni, S., Berry, J. A., Baker, I. T., Montzka, S. A., Sweeney, C., Miller, B. R., and Elliott Campbell, J.: Peak growing season gross uptake of carbon in North America is largest in the Midwest USA, Nat. Clim. Change, 7, 450–454, 2017.
Houska, T., Multsch, S., Kraft, P., Frede, H.-G., and Breuer, L.: Monte Carlo-based calibration and uncertainty analysis of a coupled plant growth and hydrological model, Biogeosciences, 11, 2069–2082, https://doi.org/10.5194/bg-11-2069-2014, 2014.
Hu, L., Montzka, S. A., Kaushik, A., Andrews, A. E., Sweeney, C., Miller, J., Baker, I. T., Denning, S., Campbell, E., Shiga, Y. P., Tans, P., Siso, M. C., Crotwell, M., McKain, K., Thoning, K., Hall, B., Vimont, I., Elkins, J. W., Whelan, M. E., and Suntharalingam, P.: COS-derived GPP relationships with temperature and light help explain high-latitude atmospheric CO2 seasonal cycle amplification, P. Natl. Acad. Sci., 118, e2103423118, https://doi.org/10.1073/pnas.2103423118, 2021.
Ibrom, A. and Pilegaard, K.: FLUXNET2015 DK-Sor Soroe, FLUXNET2015 [data set], https://doi.org/10.18140/FLX/1440155, 2020.
Iwanaga, T., Usher, W., and Herman, J.: Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses, Socio-Environmental Systems Modelling, 4, 18155–18155, 2022.
Jackson, R. B., Canadell, J., Ehleringer, J. R., Mooney, H. A., Sala, O. E., and Schulze, E.-D.: A global analysis of root distributions for terrestrial biomes, Oecologia, 108, 389–411, 1996.
Ju, W., Chen, J. M., Black, T. A., Barr, A. G., Liu, J., and Chen, B.: Modelling multi-year coupled carbon and water fluxes in a boreal aspen forest, Agr. Forest Meteorol., 140, 136–151, 2006.
Ju, W., Gao, P., Wang, J., Zhou, Y., and Zhang, X.: Combining an ecological model with remote sensing and GIS techniques to monitor soil water content of croplands with a monsoon climate, Agr. Water Manage., 97, 1221–1231, 2010.
Karu, E., Li, M., Ernle, L., Brenninkmeijer, C. A., Lelieveld, J., and Williams, J.: Carbonyl Sulfide (OCS) in the upper troposphere/Lowermost stratosphere (UT/LMS) region: Estimates of lifetimes and fluxes, Geophys. Res. Lett., 50, e2023GL105826, https://doi.org/10.1029/2023GL105826, 2023.
Kattge, J., Knorr, W., Raddatz, T., and Wirth, C.: Quantifying photosynthetic capacity and its relationship to leaf nitrogen content for global-scale terrestrial biosphere models, Glob. Change Biol., 15, 976–991, 2009.
Kesselmeier, J., Teusch, N., and Kuhn, U.: Controlling variables for the uptake of atmospheric carbonyl sulfide by soil, J. Geophys. Res.-Atmos., 104, 11577–11584, 1999.
Knauer, J., Zaehle, S., De Kauwe, M. G., Haverd, V., Reichstein, M., and Sun, Y.: Mesophyll conductance in land surface models: effects on photosynthesis and transpiration, Plant J., 101, 858–873, 2020.
Koffi, E. N., Rayner, P. J., Norton, A. J., Frankenberg, C., and Scholze, M.: Investigating the usefulness of satellite-derived fluorescence data in inferring gross primary productivity within the carbon cycle data assimilation system, Biogeosciences, 12, 4067–4084, https://doi.org/10.5194/bg-12-4067-2015, 2015.
Kohonen, K.-M., Kolari, P., Kooijmans, L. M. J., Chen, H., Seibt, U., Sun, W., and Mammarella, I.: Towards standardized processing of eddy covariance flux measurements of carbonyl sulfide, Atmos. Meas. Tech., 13, 3957–3975, https://doi.org/10.5194/amt-13-3957-2020, 2020.
Kohonen, K.-M., Dewar, R., Tramontana, G., Mauranen, A., Kolari, P., Kooijmans, L. M. J., Papale, D., Vesala, T., and Mammarella, I.: Intercomparison of methods to estimate gross primary production based on CO2 and COS flux measurements, Biogeosciences, 19, 4067–4088, https://doi.org/10.5194/bg-19-4067-2022, 2022a.
Kohonen, K.-M., Tramontana, G., and Kolari, P.: Dataset for “Intercomparison of methods to estimate gross primary production based on CO2 and COS flux measurements”, Zenodo [data set], https://doi.org/10.5281/zenodo.6940750, 2022b.
Kooijmans, L. M., Sun, W., Aalto, J., Erkkilä, K.-M., Maseyk, K., Seibt, U., Vesala, T., Mammarella, I., and Chen, H.: Influences of light and humidity on carbonyl sulfide-based estimates of photosynthesis, P. Natl. Acad. Sci. USA, 116, 2470–2475, 2019.
Kooijmans, L. M. J., Cho, A., Ma, J., Kaushik, A., Haynes, K. D., Baker, I., Luijkx, I. T., Groenink, M., Peters, W., Miller, J. B., Berry, J. A., Ogée, J., Meredith, L. K., Sun, W., Kohonen, K.-M., Vesala, T., Mammarella, I., Chen, H., Spielmann, F. M., Wohlfahrt, G., Berkelhammer, M., Whelan, M. E., Maseyk, K., Seibt, U., Commane, R., Wehr, R., and Krol, M.: Evaluation of carbonyl sulfide biosphere exchange in the Simple Biosphere Model (SiB4), Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, 2021.
Lasslop, G., Migliavacca, M., Bohrer, G., Reichstein, M., Bahn, M., Ibrom, A., Jacobs, C., Kolari, P., Papale, D., Vesala, T., Wohlfahrt, G., and Cescatti, A.: On the choice of the driving temperature for eddy-covariance carbon dioxide flux partitioning, Biogeosciences, 9, 5243–5259, https://doi.org/10.5194/bg-9-5243-2012, 2012.
Launois, T., Peylin, P., Belviso, S., and Poulter, B.: A new model of the global biogeochemical cycle of carbonyl sulfide – Part 2: Use of carbonyl sulfide to constrain gross primary productivity in current vegetation models, Atmos. Chem. Phys., 15, 9285–9312, https://doi.org/10.5194/acp-15-9285-2015, 2015.
Liu, J., Chen, J., Cihlar, J., and Park, W.: A process-based boreal ecosystem productivity simulator using remote sensing inputs, Remote Sens. Environ., 62, 158–175, 1997.
Liu, R., Liu, Y., and Chen, J.: GLOBMAP global Leaf Area Index since 1981 (Version 3.0), Zenodo [data set], https://doi.org/10.5281/zenodo.4700264, 2021.
Liu, Y., Liu, R., and Chen, J. M.: Retrospective retrieval of long-term consistent global leaf area index (1981–2011) from combined AVHRR and MODIS data, J. Geophys. Res.-Biogeo., 117, G04003, https://doi.org/10.1029/2012JG002084, 2012.
Liu, Y., Xiao, J., Ju, W., Zhou, Y., Wang, S., and Wu, X.: Water use efficiency of China's terrestrial ecosystems and responses to drought, Sci. Rep.-UK, 5, 13799, https://doi.org/10.1038/srep13799, 2015.
Liu, Z., Zhou, Y., Ju, W., and Gao, P.: Simulation of soil water content in farm lands with the BEPS ecological model, Transactions of the Chinese Society of Agricultural Engineering, 27, 67–72, 2011.
Lloyd, J. and Taylor, J. A.: On the Temperature Dependence of Soil Respiration, Funct. Ecol., 8, 315–323, https://doi.org/10.2307/2389824, 1994.
Lu, X., Wang, Y.-P., Ziehn, T., and Dai, Y.: An efficient method for global parameter sensitivity analysis and its applications to the Australian community land surface model (CABLE), Agr. Forest Meteorol., 182, 292–303, 2013.
Lu, X., Croft, H., Chen, J. M., Luo, Y., and Ju, W.: Estimating photosynthetic capacity from optimized Rubisco–chlorophyll relationships among vegetation types and under global change, Enviro. Res. Lett., 17, 014028, https://doi.org/10.1088/1748-9326/ac444d, 2022.
Luo, X., Chen, J. M., Liu, J., Black, T. A., Croft, H., Staebler, R., He, L., Arain, M. A., Chen, B., Mo, G., Gonsamo, A., and McCaughey, H.: Comparison of Big-Leaf, Two-Big-Leaf, and Two-Leaf Upscaling Schemes for Evapotranspiration Estimation Using Coupled Carbon-Water Modeling, J. Geophys. Res-Biogeo., 123, 207–225, https://doi.org/10.1002/2017JG003978, 2018.
Luo, Y.: Terrestrial carbon–cycle feedback to climate warming, Annu. Rev. Ecol. Evol. S., 38, 683–712, 2007.
Ma, J., Kooijmans, L. M. J., Cho, A., Montzka, S. A., Glatthor, N., Worden, J. R., Kuai, L., Atlas, E. L., and Krol, M. C.: Inverse modelling of carbonyl sulfide: implementation, evaluation and implications for the global budget, Atmos. Chem. Phys., 21, 3507–3529, https://doi.org/10.5194/acp-21-3507-2021, 2021.
Ma, J., Remaud, M., Peylin, P., Patra, P., Niwa, Y., Rodenbeck, C., Cartwright, M., Harrison, J. J., Chipperfield, M. P., Pope, R. J., Wilson, C., Belviso, S., Montzka, S. A., Vimont, I., Moore, F., Atlas, E. L., Schwartz, E., and Krol, M. C.: Intercomparison of Atmospheric Carbonyl Sulfide (TransCom-COS): 2. Evaluation of Optimized Fluxes Using Ground-Based and Aircraft Observations, J. Geophys. Res.-Atmos., 128, e2023JD039198, https://doi.org/10.1029/2023JD039198, 2023.
Ma, R., Xiao, J., Liang, S., Ma, H., He, T., Guo, D., Liu, X., and Lu, H.: Pixel-level parameter optimization of a terrestrial biosphere model for improving estimation of carbon fluxes with an efficient model–data fusion method and satellite-derived LAI and GPP data, Geosci. Model Dev., 15, 6637–6657, https://doi.org/10.5194/gmd-15-6637-2022, 2022.
MacBean, N., Bacour, C., Raoult, N., Bastrikov, V., Koffi, E. N., Kuppel, S., Maignan, F., Ottlé, C., Peaucelle, M., Santaren, D., and Peylin, P.: Quantifying and Reducing Uncertainty in Global Carbon Cycle Predictions: Lessons and Perspectives From 15 Years of Data Assimilation Studies With the ORCHIDEE Terrestrial Biosphere Model, Global Biogeochem. Cy., 36, e2021GB007177, https://doi.org/10.1029/2021GB007177, 2022.
Maignan, F., Abadie, C., Remaud, M., Kooijmans, L. M. J., Kohonen, K.-M., Commane, R., Wehr, R., Campbell, J. E., Belviso, S., Montzka, S. A., Raoult, N., Seibt, U., Shiga, Y. P., Vuichard, N., Whelan, M. E., and Peylin, P.: Carbonyl sulfide: comparing a mechanistic representation of the vegetation uptake in a land surface model and the leaf relative uptake approach, Biogeosciences, 18, 2917–2955, https://doi.org/10.5194/bg-18-2917-2021, 2021.
Mammarella, I., Keronen, P., Kolari, P., Launiainen, S., Pumpanen, J., Rannik, Ü., Siivola, E., Levula, J., Pohja, T., and Vesala, T.: FLUXNET2015 FI-Hyy Hyytiala, FLUXNET2015 [data set], https://doi.org/10.18140/FLX/1440158, 2020.
Medlyn, B. E., Badeck, F.-W., De Pury, D. G. G., Barton, C. V. M., Broadmeadow, M., Ceulemans, R., De Angelis, P., Forstreuter, M., Jach, M. E., Kellomäki, S., Laitat, E., Marek, M., Philippot, S., Rey, A., Strassemeyer, J., Laitinen, K., Liozon, R., Portier, B., Roberntz, P., Wang, K., and Jstbid, P. G.: Effects of elevated [CO2] on photosynthesis in European forest species: a meta-analysis of model parameters, Plant Cell Environ., 22, 1475–1495, https://doi.org/10.1046/j.1365-3040.1999.00523.x, 1999.
Medlyn, B. E., Dreyer, E., Ellsworth, D., Forstreuter, M., Harley, P. C., Kirschbaum, M. U. F., Le Roux, X., Montpied, P., Strassemeyer, J., Walcroft, A., Wang, K., and Loustau, D.: Temperature response of parameters of a biochemically based model of photosynthesis. II. A review of experimental data, Plant Cell Environ., 25, 1167–1179, https://doi.org/10.1046/j.1365-3040.2002.00891.x, 2002.
Migliavacca, M., El-Madany, T. S., Carrara, A., Reichstein, M., and ICOS Ecosystem Thematic Centre: Drought-2018 ecosystem eddy covariance flux product from Majadas del Tietar North, ICOS [data set], https://doi.org/10.18160/FDSD-GVRS, 2020.
Miner, G. L., Bauerle, W. L., and Baldocchi, D. D.: Estimating the sensitivity of stomatal conductance to photosynthesis: a review, Plant Cell Environ., 40, 1214–1238, 2017.
Mo, X., Chen, J. M., Ju, W., and Black, T. A.: Optimization of ecosystem model parameters through assimilating eddy covariance flux data with an ensemble Kalman filter, Ecol. Model., 217, 157–173, 2008.
Montzka, S., Calvert, P., Hall, B., Elkins, J., Conway, T., Tans, P., and Sweeney, C.: On the global distribution, seasonality, and budget of atmospheric carbonyl sulfide (COS) and some similarities to CO2, J. Geophys. Res.-Atmos., 112, D09302, https://doi.org/10.1029/2006JD007665, 2007.
Moradkhani, H., Hsu, K. L., Gupta, H., and Sorooshian, S.: Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter, Water Resour. Res., 41, W05012, https://doi.org/10.1029/2004WR003604, 2005.
Mu, X. and Chen, Y.: The physiological response of photosynthesis to nitrogen deficiency, Plant Physiol. Bioch., 158, 76–82, 2021.
Munger, J. W.: AmeriFlux FLUXNET-1F US-Ha1 Harvard Forest EMS Tower (HFR1), AmeriFlux AMP [data set], https://doi.org/10.17190/AMF/1871137, 2022.
Ogée, J., Sauze, J., Kesselmeier, J., Genty, B., Van Diest, H., Launois, T., and Wingate, L.: A new mechanistic framework to predict OCS fluxes from soils, Biogeosciences, 13, 2221–2240, https://doi.org/10.5194/bg-13-2221-2016, 2016.
Pignon, C. P., Jaiswal, D., McGrath, J. M., and Long, S. P.: Loss of photosynthetic efficiency in the shade. An Achilles heel for the dense modern stands of our most productive C4 crops?, J. Exp. Bot., 68, 335–345, 2017.
Plischke, E., Borgonovo, E., and Smith, C. L.: Global sensitivity measures from given data, Eur. J. Oper. Res., 226, 536–550, 2013.
Protoschill-Krebs, G., Wilhelm, C., and Kesselmeier, J.: Consumption of carbonyl sulphide (COS) by higher plant carbonic anhydrase (CA), Atmos. Environ., 30, 3151–3156, 1996.
Raines, C. A.: The Calvin cycle revisited, Photosynth. Res., 75, 1–10, 2003.
Rastogi, B., Berkelhammer, M., Wharton, S., Whelan, M. E., Itter, M. S., Leen, J. B., Gupta, M. X., Noone, D., and Still, C. J.: Large uptake of atmospheric OCS observed at a moist old growth forest: Controls and implications for carbon cycle applications, J. Geophys. Res.-Biogeo., 123, 3424–3438, 2018a.
Rastogi, B., Berkelhammer, M., Wharton, S., Whelan, E. M., Itter, S. M., Leen, B. J., Gupta, X. M., Noone, D., and Still, C. J.: Large uptake of atmospheric OCS observed at a moist old growth forest: Controls and implications for carbon cycle applications (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.1422820, 2018b.
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grünwald, T., Havránková, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-M., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and Valentini, R.: On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm, Glob. Change Biol., 11, 1424–1439, https://doi.org/10.1111/j.1365-2486.2005.001002.x, 2005.
Remaud, M., Chevallier, F., Maignan, F., Belviso, S., Berchet, A., Parouffe, A., Abadie, C., Bacour, C., Lennartz, S., and Peylin, P.: Plant gross primary production, plant respiration and carbonyl sulfide emissions over the globe inferred by atmospheric inverse modelling, Atmos. Chem. Phys., 22, 2525–2552, https://doi.org/10.5194/acp-22-2525-2022, 2022.
Remaud, M., Ma, J., Krol, M., Abadie, C., Cartwright, M. P., Patra, P., Niwa, Y., Rodenbeck, C., Belviso, S., Kooijmans, L., Lennartz, S., Maignan, F., Chevallier, F., Chipperfield, M. P., Pope, R. J., Harrison, J. J., Vimont, I., Wilson, C., and Peylin, P.: Intercomparison of Atmospheric Carbonyl Sulfide (TransCom-COS; Part One): Evaluating the Impact of Transport and Emissions on Tropospheric Variability Using Ground-Based and Aircraft Data, J. Geophys. Res.-Atmos., 128, e2022JD037817, https://doi.org/10.1029/2022JD037817, 2023.
Rogers, A.: The use and misuse of Vc,max in Earth System Models, Photosynth. Res., 119, 15–29, 2014.
Rogers, A., Medlyn, B. E., Dukes, J. S., Bonan, G., von Caemmerer, S., Dietze, M. C., Kattge, J., Leakey, A. D. B., Mercado, L. M., Niinemets, Ü., Prentice, I. C., Serbin, S. P., Sitch, S., Way, D. A., and Zaehle, S.: A roadmap for improving the representation of photosynthesis in Earth system models, New Phytol., 213, 22–42, https://doi.org/10.1111/nph.14283, 2017.
Ryu, Y., Jiang, C., Kobayashi, H., and Detto, M.: MODIS-derived global land products of shortwave radiation and diffuse and total photosynthetically active radiation at 5 km resolution from 2000, Remote Sens. Environ., 204, 812–825, 2018.
Sage, R. F. and Pearcy, R. W.: The nitrogen use efficiency of C3 and C4 plants: II. Leaf nitrogen effects on the gas exchange characteristics of Chenopodium album (L.) and Amaranthus retroflexus (L.), Plant Physiol., 84, 959–963, 1987.
Sambridge, M. and Mosegaard, K.: Monte Carlo methods in geophysical inverse problems, Rev. Geophys., 40, 3–1-3-29, 2002.
Sandoval-Soto, L., Stanimirov, M., von Hobe, M., Schmitt, V., Valdes, J., Wild, A., and Kesselmeier, J.: Global uptake of carbonyl sulfide (COS) by terrestrial vegetation: Estimates corrected by deposition velocities normalized to the uptake of carbon dioxide (CO2), Biogeosciences, 2, 125–132, https://doi.org/10.5194/bg-2-125-2005, 2005.
Sargsyan, K., Safta, C., Najm, H. N., Debusschere, B. J., Ricciuto, D., and Thornton, P.: Dimensionality reduction for complex models via Bayesian compressive sensing, Int. J. Uncertain. Quan., 4, 63–93, https://doi.org/10.1615/Int.J.UncertaintyQuantification.2013006821, 2014.
Schwalm, C. R., Williams, C. A., Schaefer, K., Anderson, R., Arain, M. A., Baker, I., Barr, A., Black, T. A., Chen, G., Chen, J. M., Ciais, P., Davis, K. J., Desai, A., Dietze, M., Dragoni, D., Fischer, M. L., Flanagan, L. B., Grant, R., Gu, L., Hollinger, D., Izaurralde, R. C., Kucharik, C., Lafleur, P., Law, B. E., Li, L., Li, Z., Liu, S., Lokupitiya, E., Luo, Y., Ma, S., Margolis, H., Matamala, R., McCaughey, H., Monson, R. K., Oechel, W. C., Peng, C., Poulter, B., Price, D. T., Riciutto, D. M., Riley, W., Sahoo, A. K., Sprintsin, M., Sun, J., Tian, H., Tonitto, C., Verbeeck, H., and Verma, S. B.: A model-data intercomparison of CO2 exchange across North America: Results from the North American Carbon Program site synthesis, J. Geophys. Res.-Biogeo., 115, G00H05, https://doi.org/10.1029/2009JG001229, 2010.
Seibt, U., Kesselmeier, J., Sandoval-Soto, L., Kuhn, U., and Berry, J. A.: A kinetic analysis of leaf uptake of COS and its relation to transpiration, photosynthesis and carbon isotope fractionation, Biogeosciences, 7, 333–341, https://doi.org/10.5194/bg-7-333-2010, 2010.
Shaw, D. C., Franklin, J. F., Bible, K., Klopatek, J., Freeman, E., Greene, S., and Parker, G. G.: Ecological setting of the Wind River old-growth forest, Ecosystems, 7, 427–439, 2004.
Smith, B., Knorr, W., Widlowski, J.-L., Pinty, B., and Gobron, N.: Combining remote sensing data with process modelling to monitor boreal conifer forest carbon balances, Forest Ecol. Manag., 255, 3985–3994, 2008.
Spielmann, F. M., Wohlfahrt, G., Hammerle, A., Kitz, F., Migliavacca, M., Alberti, G., Ibrom, A., El-Madany, T. S., Gerdel, K., Moreno, G., Kolle, O., Karl, T., Peressotti, A., and Delle Vedove, G.: Gross Primary Productivity of Four European Ecosystems Constrained by Joint CO2 and COS Flux Measurements, Geophys. Res. Lett., 46, 5284–5293, https://doi.org/10.1029/2019GL082006, 2019a.
Spielmann, F. M., Wohlfahrt, G., Hammerle, A., Kitz, F., Migliavacca, M., Alberti, G., Ibrom, A., El-Madany, T., Gerdel, K., Moreno, G., Kolle, O., Karl, T., Peressotti, A., and Delle Vedove, G.: Dataset for “Gross primary productivity of four European ecosystems constrained by joint CO2 and COS flux measurements” In Geophysical Research Letters (1.0.0), Zenodo [data set], https://doi.org/10.5281/zenodo.3406990, 2019b.
Staudt, K., Falge, E., Pyles, R. D., Paw U, K. T., and Foken, T.: Sensitivity and predictive uncertainty of the ACASA model at a spruce forest site, Biogeosciences, 7, 3685–3705, https://doi.org/10.5194/bg-7-3685-2010, 2010.
Stimler, K., Montzka, S. A., Berry, J. A., Rudich, Y., and Yakir, D.: Relationships between carbonyl sulfide (COS) and CO2 during leaf gas exchange, New Phytol., 186, 869–878, 2010.
Stimler, K., Berry, J. A., and Yakir, D.: Effects of carbonyl sulfide and carbonic anhydrase on stomatal conductance, Plant Physiol., 158, 524–530, 2012.
Sun, W., Maseyk, K., Lett, C., and Seibt, U.: A soil diffusion–reaction model for surface COS flux: COSSM v1, Geosci. Model Dev., 8, 3055–3070, https://doi.org/10.5194/gmd-8-3055-2015, 2015.
Sun, W., Kooijmans, L. M. J., Maseyk, K., Chen, H., Mammarella, I., Vesala, T., Levula, J., Keskinen, H., and Seibt, U.: Soil fluxes of carbonyl sulfide (COS), carbon monoxide, and carbon dioxide in a boreal forest in southern Finland, Atmos. Chem. Phys., 18, 1363–1378, https://doi.org/10.5194/acp-18-1363-2018, 2018.
Sun, W., Berry, J. A., Yakir, D., and Seibt, U.: Leaf relative uptake of carbonyl sulfide to CO2 seen through the lens of stomatal conductance–photosynthesis coupling, New Phytol., 235, 1729–1742, 2022.
Tang, J. and Zhuang, Q.: A global sensitivity analysis and Bayesian inference framework for improving the parameter estimation and prediction of a process-based Terrestrial Ecosystem Model, Journal of Geophys. Res.-Atmos., 114, D15303, https://doi.org/10.1029/2009JD011724, 2009.
Tonkin, M. and Doherty, J.: Calibration-constrained Monte Carlo analysis of highly parameterized models using subspace techniques, Water Resour. Res., 45, W00B10, https://doi.org/10.1029/2007WR006678, 2009.
Vesala, T., Kohonen, K.-M., Kooijmans, L. M. J., Praplan, A. P., Foltýnová, L., Kolari, P., Kulmala, M., Bäck, J., Nelson, D., Yakir, D., Zahniser, M., and Mammarella, I.: Long-term fluxes of carbonyl sulfide and their seasonality and interannual variability in a boreal forest, Atmos. Chem. Phys., 22, 2569–2584, https://doi.org/10.5194/acp-22-2569-2022, 2022.
Wang, J., Jiang, F., Wang, H., Qiu, B., Wu, M., He, W., Ju, W., Zhang, Y., Chen, J. M., and Zhou, Y.: Constraining global terrestrial gross primary productivity in a global carbon assimilation system with OCO-2 chlorophyll fluorescence data, Agr. Forest Meteorol., 304, 108424, https://doi.org/10.1016/j.agrformet.2021.108424, 2021.
Wang, S., Ibrom, A., Bauer-Gottwein, P., and Garcia, M.: Incorporating diffuse radiation into a light use efficiency and evapotranspiration model: An 11-year study in a high latitude deciduous forest, Agr. Forest Meteorol., 248, 479–493, 2018.
Wehr, R., Commane, R., Munger, J. W., McManus, J. B., Nelson, D. D., Zahniser, M. S., Saleska, S. R., and Wofsy, S. C.: Dynamics of canopy stomatal conductance, transpiration, and evaporation in a temperate deciduous forest, validated by carbonyl sulfide uptake, Biogeosciences, 14, 389–401, https://doi.org/10.5194/bg-14-389-2017, 2017.
Wharton, S.: AmeriFlux BASE US-Wrc Wind River Crane Site, AmeriFlux AMP [data set], https://doi.org/10.17190/AMF/1246114, 2016.
Whelan, M. E., Hilton, T. W., Berry, J. A., Berkelhammer, M., Desai, A. R., and Campbell, J. E.: Carbonyl sulfide exchange in soils for better estimates of ecosystem carbon uptake, Atmos. Chem. Phys., 16, 3711–3726, https://doi.org/10.5194/acp-16-3711-2016, 2016.
Whelan, M. E., Lennartz, S. T., Gimeno, T. E., Wehr, R., Wohlfahrt, G., Wang, Y., Kooijmans, L. M. J., Hilton, T. W., Belviso, S., Peylin, P., Commane, R., Sun, W., Chen, H., Kuai, L., Mammarella, I., Maseyk, K., Berkelhammer, M., Li, K.-F., Yakir, D., Zumkehr, A., Katayama, Y., Ogée, J., Spielmann, F. M., Kitz, F., Rastogi, B., Kesselmeier, J., Marshall, J., Erkkilä, K.-M., Wingate, L., Meredith, L. K., He, W., Bunk, R., Launois, T., Vesala, T., Schmidt, J. A., Fichot, C. G., Seibt, U., Saleska, S., Saltzman, E. S., Montzka, S. A., Berry, J. A., and Campbell, J. E.: Reviews and syntheses: Carbonyl sulfide as a multi-scale tracer for carbon and water cycles, Biogeosciences, 15, 3625–3657, https://doi.org/10.5194/bg-15-3625-2018, 2018.
Whelan, M. E., Shi, M., Sun, W., Vries, L. K. d., Seibt, U., and Maseyk, K.: Soil carbonyl sulfide (OCS) fluxes in terrestrial ecosystems: an empirical model, J. Geophys. Res.-Biogeo., 127, e2022JG006858, https://doi.org/10.1029/2022JG006858, 2022.
Wohlfahrt, G., Brilli, F., Hörtnagl, L., Xu, X., Bingemer, H., Hansel, A., and Loreto, F.: Carbonyl sulfide (COS) as a tracer for canopy photosynthesis, transpiration and stomatal conductance: potential and limitations, Plant Cell Environ., 35, 657–667, 2012.
Wohlfahrt, G., Hammerle, A., and Hörtnagl, L.: FLUXNET2015 AT-Neu Neustift, FLUXNET [data set], https://doi.org/10.18140/FLX/1440121, 2020.
Woodward, F. I., Smith, T. M., and Emanuel, W. R.: A global land primary productivity and phytogeography model, Global Biogeochem. Cy., 9, 471–490, 1995.
Wu, M., Ran, Y., Jansson, P.-E., Chen, P., Tan, X., and Zhang, W.: Global parameters sensitivity analysis of modeling water, energy and carbon exchange of an arid agricultural ecosystem, Agr. Forest Meteorol., 271, 295–306, 2019.
Wu, M., Tan, X., Wu, J., Huang, J., Jansson, P.-E., and Zhang, W.: Coupled water transport and heat flux in seasonally frozen soils: uncertainties identification in multi-site calibration, Environ. Earth Sci., 79, 524, https://doi.org/10.1007/s12665-020-09262-2, 2020.
Xiao, Z., Liang, S., Wang, J., Xiang, Y., Zhao, X., and Song, J.: Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance, IEEE T. Geosci. Remote, 54, 5301–5318, https://doi.org/10.1109/TGRS.2016.2560522, 2016 (data available at: https://doi.org/10.12041/geodata.GLASS_LAI_MODIS(0.05D).ver1.db).
Xing, X., Wu, M., Zhang, W., Ju, W., Tagesson, T., He, W., Wang, S., Wang, J., Hu, L., Yuan, S., Zhu, T., Wang, X., Ran, Y., Li, S., Wang, C., and Jiang, F.: Modeling China's terrestrial ecosystem gross primary productivity with BEPS model: Parameter sensitivity analysis and model calibration, Agr. Forest Meteorol., 343, 109789, https://doi.org/10.1016/j.agrformet.2023.109789, 2023.
Yi, D. H., Kim, D. W., and Park, C. S.: Parameter identifiability in Bayesian inference for building energy models, Energ. Buildings, 198, 318–328, 2019.
Yuan, W., Liu, S., Zhou, G., Zhou, G., Tieszen, L. L., Baldocchi, D., Bernhofer, C., Gholz, H., Goldstein, A. H., Goulden, M. L., Hollinger, D. Y., Hu, Y., Law, B. E., Stoy, P. C., Vesala, T., and Wofsy, S. C.: Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes, Agr. Forest Meteorol., 143, 189–207, https://doi.org/10.1016/j.agrformet.2006.12.001, 2007.
Zaehle, S., Sitch, S., Smith, B., and Hatterman, F.: Effects of parameter uncertainties on the modeling of terrestrial biosphere dynamics, Global Biogeochem. Cy., 19, GB3020, https://doi.org/10.1029/2004GB002395, 2005.
Zhu, H., Wu, M., Jiang, F., Vossbeck, M., Kaminski, T., Xing, X., Wang, J., Ju, W., and Chen, J. M.: Assimilation of Carbonyl Sulfide (COS) fluxes within the adjoint-based data assimilation system–Nanjing University Carbon Assimilation System (NUCAS v1.0), EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1955, 2023.
Zierl, B.: A water balance model to simulate drought in forested ecosystems and its application to the entire forested area in Switzerland, J. Hydrol., 242, 115–136, 2001.
Short summary
Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across ecosystems with the Biosphere-atmosphere Exchange Process Simulator (BEPS), which was developed for simulating the canopy COS uptake under its state-of-the-art two-leaf modeling framework. Our results showcased the efficacy of COS in improving model prediction and reducing prediction uncertainty of GPP and enhanced insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across...
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