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LPJ-GUESS

A process-based dynamic vegetation-terrestrial ecosystem model

Potential natural vegetation simulated by the dynamic vegetation model LPJ-GUESS for a grid cell located in Lund.
Potential natural vegetation simulated by the dynamic vegetation model LPJ-GUESS for a grid cell located in Lund.

LPJ-GUESS, initially developed in the late 1990s, is a product of collaboration between Lund University in Sweden, the Potsdam Institute for Climate Impact Research, and the Max Planck Institute for Biogeochemistry in Jena, Germany. The model was designed to simulate the dynamics of vegetation in response to environmental changes, including climate, land use, and atmospheric CO2 concentrations. Over the years, LPJ-GUESS has undergone several iterations, with continuous refinements and enhancements to incorporate new scientific findings and improve its predictive capabilities. Its development has been driven by the growing need for robust tools to assess the impacts of climate change and human activities on terrestrial ecosystems. LPJ-GUESS has become a widely used tool in the fields of ecology, biogeography, and climate science, contributing significantly to our understanding of the Earth's vegetation dynamics.

LPJ-GUESS, standing for 'Lund-Potsdam-Jena General Ecosystem Simulator', is a dynamic global vegetation model renowned for its process- and individual-based approach. This model simulates the growth, distribution, and interactions of various plant functional types across the globe, accounting for factors such as climate, soil properties, land use, and atmospheric CO2 concentrations. LPJ-GUESS integrates advanced algorithms to simulate ecological processes, including vegetation dynamics, carbon and water cycling, and land-atmosphere interactions. Its comprehensive framework allows researchers to investigate complex ecological questions and assess the potential impacts of environmental changes on terrestrial ecosystems at both regional and global scales. Through its versatility and robustness, LPJ-GUESS continues to be a valuable tool for informing policy decisions and advancing our understanding of Earth's biosphere.

See profile in the LU research portal

 

Main model development papers

Smith, B., Prentice, I.C. & Sykes, M.T. 2001. Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecology & Biogeography 10: 621-637.

Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J. & Zaehle, S. 2014. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences 11: 2027-2054.

Olin, S., Schurgers, G., Lindeskog, M., Wårlind, D., Smith, B., Bodin, P., Holmér, J. & Arneth, A. 2015. Modelling the response of yields and tissue C:N to changes in atmospheric CO2 and N management in the main wheat regions of western Europe. Biogeosciences 12: 2489-2515.

Lindeskog, M., Smith, B., Lagergren, F., Sycheva, E., Ficko, A., Pretzsch, H. & Rammig, A. 2021. Accounting for forest management in the estimation of forest carbon balance using the dynamic vegetation model LPJ-GUESS (v4.0, r9710): implementation and evaluation of simulations for Europe. Geoscientific Model Development 14: 6071–6112.

Martín Belda, D., Anthoni, P., Wårlind, D., Olin, S., Schurgers, G., Tang, J., Smith, B. & Arneth, A. 2022. LPJGUESS/LSMv1.0: a next-generation land surface model with high ecological realism. Geoscientific Model Development 15: 6709–6745.

A pdf listing LPJ-GUESS publications is available here (0.65 MB).

Contact

Johan Nord and Stefan Olin 

lpj-guess [at] nateko [dot] lu [dot] se (lpj-guess[at]nateko[dot]lu[dot]se)