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r3PG – An r package for simulating forest growth using the 3‐PG process‐based model
Author(s) -
Trotsiuk Volodymyr,
Hartig Florian,
Forrester David I.
Publication year - 2020
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.13474
Subject(s) - fortran , computer science , sensitivity (control systems) , tree (set theory) , evergreen , process (computing) , implementation , r package , bayesian probability , climate change , data mining , ecology , programming language , artificial intelligence , mathematics , biology , mathematical analysis , electronic engineering , engineering
Process‐based forest models (PBMs) are important tools for quantifying forest growth and vulnerability, particularly under climate change. The 3‐PG model (Physiological Processes Predicting Growth) is one of the most widely used forest growth simulators for this purpose worldwide. Here, we present r3PG , a new Fortran implementation of 3‐PG, wrapped into an r package. r3PG can simulate monospecific as well as mixtures of evergreen and deciduous tree species in even‐aged or uneven‐aged stands. The combination of Fortran functions with an r interface makes the model extremely fast. This facilitates the use of r3PG for extensive computer experiments and sensitivity analysis. We demonstrate this in a case study including (a) single model runs; (b) a sensitivity analysis and a full Bayesian calibration of the model and (c) spatial simulations of forest growth across Switzerland. r3PG is faster and easier to use than previous implementations of 3‐PG in visual basic. We believe that this will make 3‐PG even more useful and popular for ecologists and climate change scientists.