Articles | Volume 11, issue 7
Geosci. Model Dev., 11, 2789–2812, 2018

Special issue: The Lund–Potsdam–Jena managed Land (LPJmL) dynamic...

Geosci. Model Dev., 11, 2789–2812, 2018
Model description paper
12 Jul 2018
Model description paper | 12 Jul 2018

Implementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0)

Werner von Bloh et al.

Related authors

Variable tree rooting strategies are key for modelling the distribution, productivity and evapotranspiration of tropical evergreen forests
Boris Sakschewski, Werner von Bloh, Markus Drüke, Anna Amelia Sörensson, Romina Ruscica, Fanny Langerwisch, Maik Billing, Sarah Bereswill, Marina Hirota, Rafael Silva Oliveira, Jens Heinke, and Kirsten Thonicke
Biogeosciences, 18, 4091–4116,,, 2021
Short summary
CM2Mc-LPJmL v1.0: biophysical coupling of a process-based dynamic vegetation model with managed land to a general circulation model
Markus Drüke, Werner von Bloh, Stefan Petri, Boris Sakschewski, Sibyll Schaphoff, Matthias Forkel, Willem Huiskamp, Georg Feulner, and Kirsten Thonicke
Geosci. Model Dev., 14, 4117–4141,,, 2021
Short summary
Global cotton production under climate change – Implications for yield and water consumption
Yvonne Jans, Werner von Bloh, Sibyll Schaphoff, and Christoph Müller
Hydrol. Earth Syst. Sci., 25, 2027–2044,,, 2021
Short summary
Improving the LPJmL4-SPITFIRE vegetation–fire model for South America using satellite data
Markus Drüke, Matthias Forkel, Werner von Bloh, Boris Sakschewski, Manoel Cardoso, Mercedes Bustamante, Jürgen Kurths, and Kirsten Thonicke
Geosci. Model Dev., 12, 5029–5054,,, 2019
Short summary
Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0-tillage)
Femke Lutz, Tobias Herzfeld, Jens Heinke, Susanne Rolinski, Sibyll Schaphoff, Werner von Bloh, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 12, 2419–2440,,, 2019
Short summary

Related subject area

Using terrestrial laser scanning to constrain forest ecosystem structure and functions in the Ecosystem Demography model (ED2.2)
Félicien Meunier, Sruthi M. Krishna Moorthy, Marc Peaucelle, Kim Calders, Louise Terryn, Wim Verbruggen, Chang Liu, Ninni Saarinen, Niall Origo, Joanne Nightingale, Mathias Disney, Yadvinder Malhi, and Hans Verbeeck
Geosci. Model Dev., 15, 4783–4803,,, 2022
Short summary
A map of global peatland extent created using machine learning (Peat-ML)
Joe R. Melton, Ed Chan, Koreen Millard, Matthew Fortier, R. Scott Winton, Javier M. Martín-López, Hinsby Cadillo-Quiroz, Darren Kidd, and Louis V. Verchot
Geosci. Model Dev., 15, 4709–4738,,, 2022
Short summary
Implementation and evaluation of the unified stomatal optimization approach in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES)
Qianyu Li, Shawn P. Serbin, Julien Lamour, Kenneth J. Davidson, Kim S. Ely, and Alistair Rogers
Geosci. Model Dev., 15, 4313–4329,,, 2022
Short summary
ECOSMO II(CHL): a marine biogeochemical model for the North Atlantic and the Arctic
Veli Çağlar Yumruktepe, Annette Samuelsen, and Ute Daewel
Geosci. Model Dev., 15, 3901–3921,,, 2022
Short summary
Water Ecosystems Tool (WET) 1.0 – a new generation of flexible aquatic ecosystem model
Nicolas Azaña Schnedler-Meyer, Tobias Kuhlmann Andersen, Fenjuan Rose Schmidt Hu, Karsten Bolding, Anders Nielsen, and Dennis Trolle
Geosci. Model Dev., 15, 3861–3878,,, 2022
Short summary

Cited articles

Arneth, A., Sitch, S., Pongratz, J., Stocker, B. D., Ciais, P., Poulter, B., Bayer, A. D., Bondeau, A., Calle, L., Chini, L. P., Gasser, T., Fader, M., Friedlingstein, P., Kato, E., Li, W., Lindeskog, M., Nabel, J. E. M. S., Pugh, T. A. M., Robertson, E., Viovy, N., Yue, C., and Zaehle, S.: Historical carbon dioxide emissions caused by land-use changes are possibly larger than assumed, Nat. Geosci., 10, 79–84,, 2017. a
Arnold, J. G., Kiniry, J. R., Williams, J. R., Haney, E. B., and Neitsch, S. L.: Soil and water assessment tool input/output documentation version 2012, Texas Water Resources Institute, College Station, Texas, 2012. a
Ascott, M. J., Gooddy, D. C., Wang, L., Stuart, M. E., Lewis, M. A., Ward, R. S., and Binley, A. M.: Global patterns of nitrate storage in the vadose zone, Nat. Comm., 8, 1416,, 2017. a
Atkin, O., Schortemeyer, M., McFarlane, N., and Evans, J.: The response of fast- and slow-growing Acacia species to elevated atmospheric CO2: an analysis of the underlying components of relative growth rate, Oecologica, 120, 544–554,, 1999. a
Baker, T. R., Phillips, O. L., Laurance, W. F., Pitman, N. C. A., Almeida, S., Arroyo, L., DiFiore, A., Erwin, T., Higuchi, N., Killeen, T. J., Laurance, S. G., Nascimento, H., Monteagudo, A., Neill, D. A., Silva, J. N. M., Malhi, Y., López Gonzalez, G., Peacock, J., Quesada, C. A., Lewis, S. L., and Lloyd, J.: Do species traits determine patterns of wood production in Amazonian forests?, Biogeosciences, 6, 297–307,, 2009. a
Short summary
The dynamics of the terrestrial carbon cycle are of central importance for Earth system science. Nutrient limitations, especially from nitrogen, are important constraints on vegetation growth and the terrestrial carbon cycle. We extended the well-established global vegetation, hydrology, and crop model LPJmL with a nitrogen cycle. We find significant improvement in global patterns of crop productivity. Regional differences in crop productivity can now be largely reproduced by the model.