LPJ-GUESS is a process-based dynamic vegetation-terrestrial ecosystem model designed for regional or global studies. Models of this kind are commonly known as dynamic global vegetation models (DGVMs). Given data on regional climate conditions and atmospheric carbon dioxide concentrations, it can predict structural, compositional and functional properties of the native ecosystems of major climate zones of the Earth.

Outputs include vegetation composition and cover in terms of major species or plant functional types (PFTs), biomass and soil organic matter carbon pools, leaf area index (LAI), net primary production (NPP), net ecosystem carbon balance, carbon emissions from wildfires, biogenic volatile organic compounds (BVOCs), evapotranspiration, runoff, and nitrogen pools and fluxes. The latest version (4.1) includes further outputs and functionalities such as methane emissions, soil nitrogen chemistry, permafrost dynamics, and a new wildfire model.

LPJ-GUESS stands for Lund-Potsdam-Jena General Ecosystem Simulator. The model was originally developed by Ben Smith of Lund University in a collaboration also involving the Potsdam Institute for Climate Impact Research and the Max-Planck Institute for Biogeochemistry. Over the years, many people from institutes around the world have contributed to the testing, refinement and further development of the model.

The source code of the research version of the LPJ-GUESS model, as well as an educational version of LPJ-GUESS (Windows executable, no source code), are available for download.