rLPJGUESS
An R interface to the LPJ-GUESS vegetation model, with parallel runs on workstations and HPC clusters.
Cited 19 times on Google Scholar (as of 11 October 2026)
rLPJGUESS runs LPJ-GUESS, a dynamic global vegetation model, from within R instead of through its own configuration files. Calibration and sensitivity analysis need hundreds to thousands of model runs, so the package runs them in parallel: on a workstation via SOCK clusters, on HPC systems via MPI. Combined with a sampler such as BayesianTools, this makes Bayesian calibration of LPJ-GUESS feasible.
The package targets LPJ-GUESS 3.1. It is not on CRAN and can be installed from GitHub.
Authors: Maurizio Bagnara (maintainer), Florian Hartig, Ramiro Silveyra Gonzalez.
Paper describing rLPJGUESS
Widely cited work citing rLPJGUESS
The most-cited articles that cite rLPJGUESS or its paper, ranked by their own citation count in OpenAlex; the group's own papers are left out.
- A fundamental theorem for eco-environmental surface modelling and its applications
- Advancing simulations of water fluxes, soil moisture and drought stress by using the LWF-Brook90 hydrological model in R
- Regional carbon stock assessment and the potential effects of land cover change
- Parameter Estimation in Land Surface Models: Challenges and Opportunities With Data Assimilation and Machine Learning
- Heterogeneous impacts of human activities and climate change on transformed vegetation dynamics on the Qinghai-Tibet Plateau