Articles | Volume 16, issue 14
https://doi.org/10.5194/gmd-16-4113-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-4113-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
20 Jul 2023
Development and technical paper |
| 20 Jul 2023
| 20 Jul 2023
Modelling the terrestrial nitrogen and phosphorus cycle in the UVic ESCM
Makcim L. De Sisto
CORRESPONDING AUTHOR
Earth Sciences, St. Francis Xavier University, Antigonish, NS, Canada
Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL, Canada
Andrew H. MacDougall
Earth Sciences, St. Francis Xavier University, Antigonish, NS, Canada
Nadine Mengis
Research Unit Biogeochemical Modelling, GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
Sophia Antoniello
Earth Sciences, St. Francis Xavier University, Antigonish, NS, Canada
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Cited articles
Archer, D.:
A data-driven model of the global calcite lysocline, Global Biogeochem. Cy., 10, 511–526, https://doi.org/10.1029/96GB01521, 1996. a
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., Krasting, J. P., Law, R. M., Lawrence, D. M., Lenton, A., Lindsay, K., Pongratz, J., Raddatz, T., Séférian, R., Tachiiri, K., Tjiputra, J. F., Wiltshire, A., Wu, T., and Ziehn, T.:
Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models, Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, 2020. a
Bitz, C. M., Holland, M. M., Weaver, A. J., and Eby, M.:
Simulating the ice-thickness distribution in a coupled, J. Geophys. Res., 106, 2441–2463, https://doi.org/10.1029/1999JC000113, 2001. a
Bonan, G. B. and Levis, S.:
Quantifying carbon-nitrogen feedbacks in the Community Land Model (CLM4), Geophys. Res. Lett., 37, 2261–2282, 2010. a
Braghiere, R. K., Fisher, J. B., Fisher, R. A., Shi, M., Steidinger, B. S., Sulman, B. N., Soudzilovskaia, N. A., Yang, X., Liang, J., Peay, K. G., Crowther, T. W., and Phillips, R. P.:
Mycorrhizal distributions impact global patterns of carbon and nutrient cycling. Geophysical Research Letters, 48, e2021GL094514, https://doi.org/10.1029/2021GL094514, 2021. a
Braghiere, R. K., Fisher, J. B., Allen, K., Brzostek, E., Shi, M., Yang, X., Ricciuto, D. M., Fisher, R. A., Zhu, Q., and Phillips, R. P.:
Modeling global carbon costs of plant nitrogen and phosphorus acquisition, J. Adv. Model. Earth Sy., 14, e2022MS003204, https://doi.org/10.1029/2022MS003204, 2022. a, b
Chen, X., Dunfield, K., Fraser, T. D., Wakelin, S., Richardson, A., and Condron, L. M.:
Soil biodiversity and biogeochemical function in managed ecosystems, Soil Res., 58, 1–20, https://doi.org/10.1071/SR19067, 2019. a
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.:
The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011. a
Collier, N., Hoffman, F. M., Lawrence, D. M., Keppel-Aleks, G., Koven, C. D., Riley, W. J., Mu, M., and Randerson, J. T.:
The International Land Model Benchmarking (ILAMB) System: Design, Theory, and Implementation, J. Adv. Model. Earth Sy., 10, 2731–2754, https://doi.org/10.1029/2018MS001354, 2018. a
Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K., and Paul, E.:
The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter?, Glob. Change Biol., 19, 988–995, https://doi.org/10.1111/gcb.12113, 2013. a
Cox, P., Huntingford, C., and Harding, J.:
A canopy conductance and photosynthesis model for use in a GCM land surface scheme, J. Hydrol., 212–213, 79–94, https://doi.org/10.1016/S0022-1694(98)00203-0, 1998. a
Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Lo Vullo, E., Solazzo, E., Monforti-Ferrario, F., Olivier, J., and Vignati, E.:
EDGAR v6.0 Greenhouse Gas Emissions, European Commission, Joint Research Centre (JRC) [data set], http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b (last access: 15 January 2023), 2021. a, b, c
Cross, A. F and Schlesinger, W. H.:
A literature review and evaluation of the Hedley fractionation: applications to the biogeochemical cycle of soil phosphorus in natural ecosystems, Geoderma, 64, 197–214, 1995. a
Davidson, E.,Keller, M, Erickson, H., Verchot, L., and Veldkamp, E.:
Testing a conceptual model of soil emissions of nitrous and nitric oxides: using two functions based on soil nitrogen availability and soil water content, the hole-in-the-pipe model characterizes a large fraction of the observed variation of nitric oxide and nitrous oxide emissions from soils, AIBS Bulletin, 50, 667–680, 2000. a
Davies-Barnard, T. and Friedlingstein, P.:
The global distribution of biological nitrogen fixation in terrestrial natural ecosystems, Global Biogeochem. Cy., 34, e2019GB006387, https://doi.org/10.1029/2019GB006387, 2020. a
De Sisto, M.: Modelling the terrestrial nitrogen and phosphorus cycle in the UVic ESCM, V1, Borealis [code, data set], https://doi.org/10.5683/SP3/GXYZKU, 2022. a
Dynarski, K. A., Morford, S. L., Mitchell, S. A., and Houlton, B. Z.:
Bedrock nitrogen weathering stimulates biological nitrogen fixation, Ecology, 100, 1–10, 2019. a
Eisele, K., Schimel, D., Kapustka, L., Parton, W.:
Effects of available P and N:P ratios on non-symbioticdinitrogen fixation in tall grass prairie soils, Oecologia, 79, 471–474, 1989. a
Firestone, M. and Davidson, E.:
Microbiological basis of NO and N2O production and consumption in soil. Exchange of trace gases between terrestrial ecosystems and the atmosphere, Wiley, 47, 7–21, 1989. a
Fisher, J., Badgley, G., and Blyth, E.:
Global nutrient limitation in terrestrial vegetation, Global Biogeochem. Cy., 6, GB3007, https://doi.org/10.1029/2011GB004252, 2012. a
Fleischer, K., Dolman, A. J., van der Molen, M. K., Rebel, K. T., Erisman, J. W., Wassen, M. J., Pak, B., Lu, X., Rammig, A., and Wang, Y.:
Nitrogen deposition maintains a positive effect on terrestrial carbon sequestration in the 21st century despite growing phosphorus limitation at regional scales, Global Biogeochem. Cy., 33, 810–824, https://doi.org/10.1029/2018GB005952, 2019. a
Fowler, D., Coyle, M., Skiba, U., Sutton, M. A., Cape, J. N., Reis, S., Sheppard, L. J., Jenkins, A., Grizzetti, B., Galloway, J. N., Vitousek, P., Leach, A., Bouwman, A. F., Butterbach-Bahl, K., Dentener, F., Stevenson, D., Amann, M., and Voss, M.:
The global nitrogen cycle in the twenty-first century, Philos. T. Roy. Soc. B, 368, 20130164, https://doi.org/10.1098/rstb.2013.0164, 2013. a, b, c
Gedney, N. and Cox, P.:
The sensitivity of global climate model simulations to the representation of soil moisture heterogeneity, J Hydrometeorol., 4, 1265–1275, 2003. a
Global Soil Data Task Group:
Global Soil Data Products CD-ROM Contents (IGBP-DIS), Oak Ridge National Laboratory Distributed Active Archive Center [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/565, 2014. a
Goll, D. S., Brovkin, V., Parida, B. R., Reick, C. H., Kattge, J., Reich, P. B., van Bodegom, P. M., and Niinemets, Ü.:
Nutrient limitation reduces land carbon uptake in simulations with a model of combined carbon, nitrogen and phosphorus cycling, Biogeosciences, 9, 3547–3569, https://doi.org/10.5194/bg-9-3547-2012, 2012. a, b, c, d, e
Goll, D. S., Vuichard, N., Maignan, F., Jornet-Puig, A., Sardans, J., Violette, A., Peng, S., Sun, Y., Kvakic, M., Guimberteau, M., Guenet, B., Zaehle, S., Penuelas, J., Janssens, I., and Ciais, P.:
A representation of the phosphorus cycle for ORCHIDEE (revision 4520), Geosci. Model Dev., 10, 3745–3770, https://doi.org/10.5194/gmd-10-3745-2017, 2017. a, b, c, d, e, f, g, h, i
Hartmann, J. and Moosdorf, N.:
The new global lithological map database GLiM: a representation of rock properties at the Earth surface, Geochem. Geophy. Geosy., 13, 1–37, https://doi.org/10.1029/2012GC004370, 2012. a
Haverd, V., Smith, B., Nieradzik, L., Briggs, P. R., Woodgate, W., Trudinger, C. M., Canadell, J. G., and Cuntz, M.:
A new version of the CABLE land surface model (Subversion revision r4601) incorporating land use and land cover change, woody vegetation demography, and a novel optimisation-based approach to plant coordination of photosynthesis, Geosci. Model Dev., 11, 2995–3026, https://doi.org/10.5194/gmd-11-2995-2018, 2018. a
He, X., Augusto, L., Goll, D. S., Ringeval, B., Wang, Y., Helfenstein, J., Huang, Y., Yu, K., Wang, Z., Yang, Y., and Hou, E.:
Global patterns and drivers of soil total phosphorus concentration, Earth Syst. Sci. Data, 13, 5831–5846, https://doi.org/10.5194/essd-13-5831-2021, 2021. a, b, c, d, e, f, g, h
Hedley, M. and Stewart, J.:
Method to measure microbial phosphate in soils, Soil Biol. Biochem., 14, 377–385, 1982. a
Hungate, B., Dukes, J., Shaw, M, Luo, Y., and Field, C.:
Nitrogen and Climate Change, Science (NY), 302, 1512–3, https://doi.org/10.1126/science.1091390, 2003. a
IPCC:
Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Pörtner, H.-O., Roberts, D. C., Tignor, M., Poloczanska, E. S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B., Cambridge University Press, https://doi.org/10.1017/9781009325844.001, 2022. a
Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., CampsValls, G., Papale, D., Schwalm, C., Tramontana, G., and Reichstein, M.:
The FLUXCOM ensemble of global landatmosphere energy fluxes, Scientific Data, 6, 74, https://doi.org/10.1038/s41597-019-0076-8, in press, 2019. a, b
Keller, D. P., Feng, E. Y., and Oschlies, A.:
Potential climate engineering effectiveness and side effects during a high carbon dioxide-emission scenario, Nat. Commun., 5, 1–11, https://doi.org/10.1038/ncomms4304, 2014. a
Kvale, K., Prowe, A. E. F., Chien, C. T., Landolfi, A., and Oschlies, A.:
Zooplankton grazing of microplastic can accelerate global loss of ocean oxygen, Nat. Commun., 12, 2358, https://doi.org/10.1038/s41467-021-22554-w, 2021. a
Lampitt, R. and Achterberg, E., Anderson, R., Hughes, J., Iglesias, M., Kelly, B., Lucas, M., Popova, E., Sanders, R., Shepherd, J., Smythe, D., and Yool, A.:
Ocean fertilization: a potential meansof geoengineering?, Philos. T. R. Soc. A, 366, 3919–3945, https://doi.org/10.1098/rsta.2008.0139, 2008.
Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C., Bonan, G., Collier, N., Ghimire, B., Kampenhout, L., Kennedy, D., Kluzek, E., Lawrence, P., Li, F., Li, H., Lombardozzi, D, Riley, W., Sacks, W., Shi, M., Vertenstein, M., and Zeng, X.:
The Community Land Model version 5: Description of new features, benchmarking, and impact of forcing uncertainty, J. Adv. Model. Earth Sy., 11, 4245–4287, https://doi.org/10.1029/2018MS001583, 2019. a
Le Quéré, C., Andrew, R. M., Friedlingstein, P., Sitch, S., Hauck, J., Pongratz, J., Pickers, P. A., Korsbakken, J. I., Peters, G. P., Canadell, J. G., Arneth, A., Arora, V. K., Barbero, L., Bastos, A., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Doney, S. C., Gkritzalis, T., Goll, D. S., Harris, I., Haverd, V., Hoffman, F. M., Hoppema, M., Houghton, R. A., Hurtt, G., Ilyina, T., Jain, A. K., Johannessen, T., Jones, C. D., Kato, E., Keeling, R. F., Goldewijk, K. K., Landschützer, P., Lefèvre, N., Lienert, S., Liu, Z., Lombardozzi, D., Metzl, N., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S., Neill, C., Olsen, A., Ono, T., Patra, P., Peregon, A., Peters, W., Peylin, P., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rocher, M., Rödenbeck, C., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Steinhoff, T., Sutton, A., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F. N., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., Wright, R., Zaehle, S., and Zheng, B.:
Global Carbon Budget 2018, Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, 2018. a, b, c
Li, S., Lü, S., Liu, Y., Gao, Y., and Ao, Y.:
Variations and trends of terrestrial NPP and its relation to climate change in the 10 CMIP5 models, J. Earth Syst. Sci., 124, 395–403, https://doi.org/10.1007/s12040-015-0545-1, 2015. a
MacDougall, A. H.:
The oceanic origin of path-independent carbon budgets, Sci. Rep.-UK, 7, 10373, https://doi.org/10.1038/s41598-017-10557-x, 2017. a
MacDougall, A. H., Avis, C. A., and Weaver, A. J.:
Significant contribution to climate warming from the permafrost carbon feedback, Nat. Geosci., 5, 719–721, 2012. a
Machado, C. and Furlani, A.:
KINETICS OF PHOSPHORUS UPTAKE AND ROOT MORPHOLOGY OF LOCAL AND IMPROVED VARIETIES OF MAIZE, Sci. Agric. (Piracicaba, Braz.), 61, 69–76, 2004. a
Malhi, Y., Baldocchi, D. D., and Jarvis, P. G.:
The carbon balance of tropical, temperate and boreal forests, Plant Cell Environ., 22, 715–740, 1999. a
Martius, C.:
Density, humidity, and nitrogen content of dominant wood species of floodplain forests (varzea) in Amazonia, Holz Roh. Werkst., 50, 300–303, 1992. a
Matthews, H. and Caldeira, K.:
Stabilizing climate requires near-zero emissions, Geophys. Res. Lett., 35, L04705, https://doi.org/10.1029/2007GL032388, 2008. a
Matthews, H. and Weaver, A.:
Committed climate warming, Nat. Geosci., 3, 142–143, https://doi.org/10.1038/ngeo813, 2010. a
Matthews, H., Gillett, N., Stott, P., and Zickfeld, K.:
The proportionality of global warming to cumulative carbon emissions, Nature, 459, 829–832, https://doi.org/10.1038/nature08047, 2009. a
McGill, W. and Cole, C.:
Comparative aspects of cycling of organic C, N, S, and P through soil organic matter, Geoderma, 26, 267–286, 1981. a
Meissner, K. J., Weaver, A. J., Matthews, H. D., and Cox, P. M.:
The role of land surface dynamics in glacial inception: a study with the UVic Earth System Model, Clim. Dynam., 21, 515–537, https://doi.org/10.1007/s00382-003-0352-2, 2003. a
Meissner, K. J., McNeil, B. I., Eby, M., and Wiebe, E. C.:
The importance of the terrestrial weathering feedback for multi-millennial coral reef habitat recovery, Global Biogeochem. Cy., 26, 1–20, https://doi.org/10.1029/2011GB004098, 2012. a
Menge D., Hedin, L., and Pacala S.:
Nitrogen and Phosphorus Limitation over Long-Term Ecosystem Development in Terrestrial Ecosystems, PLOS ONE, 7, e42045, https://doi.org/10.1371/journal.pone.0042045, 2012. a
Mengis, N., Partanen, A. I., Jalbert, J., and Matthews, H. D.:
1.5 ∘C carbon budget dependent on carbon cycle uncertainty and future non-CO2 forcing, Sci. Rep.-UK, 8, 5831, https://doi.org/10.1038/s41598-018-24241-1, 2018. a
Mengis, N., Keller, D. P., MacDougall, A. H., Eby, M., Wright, N., Meissner, K. J., Oschlies, A., Schmittner, A., MacIsaac, A. J., Matthews, H. D., and Zickfeld, K.:
Evaluation of the University of Victoria Earth System Climate Model version 2.10 (UVic ESCM 2.10), Geosci. Model Dev., 13, 4183–4204, https://doi.org/10.5194/gmd-13-4183-2020, 2020. a, b, c, d, e, f, g, h, i, j, k
Montenegro, A., Brovkin, V., Eby, M., Archer, D., and Weaver, A. J.:
Long term fate of anthropogenic carbon, Geophys. Res. Lett., 34, L19707, https://doi.org/10.1029/2007GL030905, 2007. a
Myhre, G., Stocker, F., Qin, D., Plattner, G, Tignor,M., Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. (Eds.): Anthropogenic and natural radiative forcing. Working Group I Contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report Climate Change 2013: The Physical Science Basis, Cambridge University Press, ISBN 9781107057991, 2013. a
Nakhavali, M. A., Mercado, L. M., Hartley, I. P., Sitch, S., Cunha, F. V., di Ponzio, R., Lugli, L. F., Quesada, C. A., Andersen, K. M., Chadburn, S. E., Wiltshire, A. J., Clark, D. B., Ribeiro, G., Siebert, L., Moraes, A. C. M., Schmeisk Rosa, J., Assis, R., and Camargo, J. L.:
Representation of the phosphorus cycle in the Joint UK Land Environment Simulator (vn5.5_JULES-CNP) , Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, 2022. a, b, c, d, e
Nzotungicimpaye, C.-M., Zickfeld, K., MacDougall, A. H., Melton, J. R., Treat, C. C., Eby, M., and Lesack, L. F. W.:
WETMETH 1.0: a new wetland methane model for implementation in Earth system models, Geosci. Model Dev., 14, 6215–6240, https://doi.org/10.5194/gmd-14-6215-2021, 2021. a
Olander, L. and Vitousek, P.:
Regulation of soil phosphatase and chitinase activity by N and P availability, Biogeochemistry, 49, 175–190, 2000. a
Pacanowski, R. C.:
MOM 2 Documentation, users guide and reference manual, GFDL Ocean Group Technical Report 3, Geophys, Fluid Dyn. Lab., Princet. Univ., Princeton, NJ, 1995. a
Pahlow, M., Chien, C.-T., Arteaga, L. A., and Oschlies, A.:
Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 1: Implementation and model behaviour, Geosci. Model Dev., 13, 4663–4690, https://doi.org/10.5194/gmd-13-4663-2020, 2020. a
Poulter, B., MacBean, N., Hartley, A., Khlystova, I., Arino, O., Betts, R., Bontemps, S., Boettcher, M., Brockmann, C., Defourny, P., Hagemann, S., Herold, M., Kirches, G., Lamarche, C., Lederer, D., Ottlé, C., Peters, M., and Peylin, P.:
Plant functional type classification for earth system models: results from the European Space Agency's Land Cover Climate Change Initiative, Geosci. Model Dev., 8, 2315–2328, https://doi.org/10.5194/gmd-8-2315-2015, 2015. a, b, c
Reed, S. C., Townsend, A. R., Davidson, E. A., and Cleveland, C.:
Stoichiometric patterns in foliar nutrient resorption across multiple scales, New Phytol., 196, 173–180, https://doi.org/10.1111/j.1469-8137.2012.04249.x, 2012. a
Reich, P. B. and Oleksyn, J.:
Global patterns of plant leaf N and P in relation to temperature and latitude, P. Natl Acad. Sci. USA, 101, 11001–11006, https://doi.org/10.1073/pnas.0403588101, 2004. a, b
Ryan, P. R., Dessaux, Y., Thomashow, L. S., and Weller, D. M.:
Rhizosphere engineering and management for sustainable agriculture, Plant Soil, 321, 363–383, https://doi.org/10.1007/s11104-009-0001-6, 2009. a
Schlesinger, W. H.:
Biogeochemistry: An Analysis of Global Change, Academic Press, San Diego, USA, 588 pp., ISBN-10 0-12-625155-X, 1997. a
Shi, M., Fisher, J. B., Brzostek, E. R., and Phillips, R. P.:
Carbon cost of plant nitrogen acquisition: global carbon cycle impact from an improved plant nitrogen cycle in the Community Land Model, Glob. Change Biol., 22, 1299–1314, 2016. a
Spafford, L. and MacDougall, A. H.:
Validation of terrestrial biogeochemistry in CMIP6 Earth system models: a review, Geosci. Model Dev., 14, 5863–5889, https://doi.org/10.5194/gmd-14-5863-2021, 2021. a, b
Thornton, P., Lamarque, J., Rosenbloom, N., and Mahowald, N.:
Influence of carbon-nitrogen cycle coupling on land model response to CO2 fertilization and climate variability, Global Biogeochem. Cy., 21, GB4018, https://doi.org/10.1029/2006GB002868, 2007. a
Thum, T., Caldararu, S., Engel, J., Kern, M., Pallandt, M., Schnur, R., Yu, L., and Zaehle, S.:
A new model of the coupled carbon, nitrogen, and phosphorus cycles in the terrestrial biosphere (QUINCY v1.0; revision 1996), Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, 2019. a
Tian, H., Xu, R., Canadell, J. G., Thompson, R. L., Winiwarter, W., Suntharalingam, P., Davidson, E. A., Ciais, P., Jackson, R. B., Janssens-Maenhout, G., Prather, M. J., Regnier, P., Pan, N., Pan, S., Peters, G. P., Shi, H., Tubiello, F. N., Zaehle, S., Zhou, F., Arneth, A., Battaglia, G., Berthet, S., Bopp, L., Bouwman, A. F., Buitenhuis, E. T., Chang, J., Chipperfield, M. P., Dangal, S. R. S., Dlugokencky, E., Elkins, J. W., Eyre, B. D., Fu, B., Hall, B., Ito, A., Joos, F., Krummel, P. B., Landolfi, A., Laruelle, G. G., Lauerwald, R., Li, W., Lienert, S., Maavara, T., MacLeod, M., Millet, D. B., Olin, S., Patra, P. K., Prinn, R. G., Raymond, P. A., Ruiz, D. J., van der Werf, G. R., Vuichard, N., Wang, J., Weiss, R. F., Wells, K. C., Wilson, C., Yang, J., and Yao, Y.:
A comprehensive quantification of global nitrous oxide sources and sinks, Nature, 586, 248–256, https://doi.org/10.1038/s41586-020-2780-0, 2020. a, b
Tokarska, K. B., Zickfeld, K., and Rogelj, J.:
Path independence of carbon budgets when meeting a stringent global mean temperature target after an overshoot, Earths Future, 7, 1283–1295, https://doi.org/10.1029/2019EF001312, 2019. a
Van Oijen, M., Barcza, Z., Confalonieri, R., Korhonen, P., Kroel-Dulay, G., Lellei-Kovács, E., Louarn, G., Louault, F., Martin, R., Moulin, T., Movedi, E., Picon-Cochard, C., Rolinski, S., Viovy, N., Wirth, S., and Bellocchi, G.:
Incorporating Biodiversity into Biogeochemistry Models to Improve Prediction of Ecosystem Services in Temperate Grasslands: Review and Roadmap, Agronomy, 10, 259, https://doi.org/10.3390/agronomy10020259, 2020. a
Vitousek, P. M., Porder, S., Houlton, B. Z., and Chadwick, O. A.:
Terrestrial phosphorus limitation: mechanisms, implications, and nitrogen–phosphorus interactions, Ecol. Appl., 20, 5–15, https://doi.org/10.1890/08-0127.1, 2010. a, b
Wagg, C., Bender, S., Widmer, F., and Van der Heijden, M.:
Soil biodiversity and soil community composition determine ecosystem multifunctionality, P. Natl. Acad. Sci. USA, 111, 5266–5270, https://doi.org/10.1073/pnas.1320054111, 2014. a
Walker, A., Beckerman, A., Gu, L., Kattge, J., Cernusak, L., Domingues, T., Scales, J., Wohlfahrt, G., Wullschleger, S., and Woodward, I.:
The relationship of leaf photosynthetic traits – Vcmax and Jmax – to leaf nitrogen, leaf phosphorus, and specific leaf area: A meta-analysis and modeling study, Ecol. Evol., 4, 3218–3235, 2014. a
Walker, T. and Syers, J.:
The fate of phosphorus during pedogenesis, Geoderma, 15, 1–19, https://doi.org/10.1016/0016-7061(76)90066-5, 1976. a
Wang, Y., Ciais, P., Goll, D., Huang, Y., Luo, Y., Wang, Y.-P., Bloom, A. A., Broquet, G., Hartmann, J., Peng, S., Penuelas, J., Piao, S., Sardans, J., Stocker, B. D., Wang, R., Zaehle, S., and Zechmeister-Boltenstern, S.:
GOLUM-CNP v1.0: a data-driven modeling of carbon, nitrogen and phosphorus cycles in major terrestrial biomes, Geosci. Model Dev., 11, 3903–3928, https://doi.org/10.5194/gmd-11-3903-2018, 2018. a, b, c, d, e
Wang, Z., Tian, H., Yang, J., Shi, H., Pan, S., Yao, Y., Banger, K., and Yang, Q.:
Coupling of phosphorus processes with carbon and nitrogen cycles in the dynamic land ecosystem model: Model structure, parameterization, and evaluation in tropical forests, J. Adv. Model. Earth Sy., 12, e2020MS002123, https://doi.org/10.1029/2020MS002123, 2020. a, b, c
Weaver, A. J., Eby, M., Wiebe, E. C., Bitz, C. M., Duffy, P. B., Ewen, T. L., Fanning, A. F., Holland, M. M., MacFadyen, A., Matthews, H. D., Meissner, K. J., Saenko, O., Schmittner, A., Wang, H. X., and Yoshimori, M.:
The UVic Earth System Climate Model: Model description, climatology, and applications to past, present and future climates, Atmos. Ocean, 39, 361–428, 2001. a
Weber, S.:
The utility of Earth system Models of Intermediate Complexity (EMICs), WIREs Clim. Change, 1, 243–252, https://doi.org/10.1002/wcc.24, 2010. a
Wieder, W., Cleveland, C., Smith, W., and Todd, K.:
Future productivity and carbon storage limited by terrestrial nutrient availability, Nat. Geosci., 8, 441–444, https://doi.org/10.1038/ngeo2413, 2015. a
Xu-Ri and Prentice, I. C.:
Terrestrial nitrogen cycle simulation with a dynamic global vegetation model, Glob. Change Biol., 14, 1745–1764, 2008. a
Yang, G., Wagg, C., Veresoglou, S. D., Hempel, S., and Rillig, M. C.:
How soil biota drive ecosystem stability, Trends Plant Sci., 23, 1057–1067, https://doi.org/10.1016/j.tplants.2018.09.007, 2018. a
Yang, X., Ricciuto, D. M., Thornton, P. E., Shi, X., Xu, M., Hoffman, F., and Norby, R. J.:
The effects of phosphorus cycle dynamics on carbon sources and sinks in the Amazon region: a modeling study using ELM v1, J. Geophys. Res.-Biogeo., 124, 3686–3698, https://doi.org/10.1029/2019JG005082, 2019. a
Zaehle, S., Friend, A. D., Friedlingstein, P., Dentener, F., Peylin, P., and Schulz, M.:
Carbon and nitrogen cycle dynamics in the OCN land surface model: 2. Role of the nitrogen cycle in the historical terrestrial carbon balance, Global Biogeochem. Cy., 24, GB1006, https://doi.org/10.1029/2009GB003522, 2010. a, b, c, d
Zaehle, S., Medlyn, B. E., de Kauwe, M. G., Walker, A. P., Dietze, M. C., Hickler, T., Luo, Y., Wang, Y. P., El-Masri, B., Thornton, P., Jain, A., Wang, S., Warlind, D., Weng, E., Parton, W., Iversen, C. M., Gallet-Budynek, A., Mccarthy, H., Finzi,A.,Hanson, P., Colin I., Oren R., and Norby, R.:
Evaluation of 11 terrestrial carbon-nitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment studies, New Phytol., 202, 803–822, https://doi.org/10.1111/nph.12697, 2014. a
Zickfeld, K., Eby, M., Matthews, H. D., and Weaver, A. J.:
Setting cumulative emissions targets to reduce the risk of dangerous climate change, P. Natl. Acad. Sci. USA, 106, 16129–16134, https://doi.org/10.1073/pnas.0805800106, 2009. a
Ziehn, T., Chamberlain, M., Law, R., Lenton, A., Bodman, R., Dix, M., Stevens L., Wang, Y., and Srbinovsky, J.:
The Australian Earth System Model: ACCESS-ESM1.5, Journal of Southern Hemisphere Earth Systems Science, 70, 193–214, 2020. a
Short summary
In this study, we developed a nitrogen and phosphorus cycle in an intermediate-complexity Earth system climate model. We found that the implementation of nutrient limitation in simulations has reduced the capacity of land to take up atmospheric carbon and has decreased the vegetation biomass, hence, improving the fidelity of the response of land to simulated atmospheric CO2 rise.
In this study, we developed a nitrogen and phosphorus cycle in an intermediate-complexity Earth...
