Runs the 3-PGpjs (monospecific, evenaged and evergreen forests) or 3-PGmix (deciduous, uneven-aged or mixed-species forests) model. For more details on parameters and structure of input visit prepare_input.
run_3PG(site, species, climate, thinning = NULL, parameters = NULL,
size_dist = NULL, settings = NULL, check_input = TRUE, df_out = TRUE)either a 4-dimentional array or a data.frame, depending on the parameter df_out. More details on the output is i_output
table as described in prepare_input containing the information about site conditions.
table as described in prepare_input containing the information about species level data. Each row corresponds to one species/cohort.
table as described in prepare_input containing the information about monthly values for climatic data. See also prepare_climate
table as described in prepare_input containing the information about thinnings. See also prepare_thinning
table as described in prepare_input containing the information about parameters to be modified. See also prepare_parameters
table as described in prepare_input containing the information about size distributions. See also prepare_sizeDist
a list as described in prepare_input with settings for the model.
logical if the input shall be checked for consistency. It will call prepare_input function.
logical if the output shall be long data.frame (TRUE) the 4-dimensional array (FALSE).
`r3PG` provides an implementation of the Physiological Processes Predicting Growth 3-PG model, which simulates forest growth and productivity. The `r3PG` serves as a flexible and easy-to-use interface for the `3-PGpjs` (monospecific, evenaged and evergreen forests) and the `3-PGmix` (deciduous, uneven-aged or mixed-species forests) model written in `Fortran`. The package, allows for fast and easy interaction with the model, and `Fortran` re-implementation facilitates computationally intensive sensitivity analysis and calibration. The user can flexibly switch between various options and submodules, to use the original `3-PGpjs` model version for monospecific, even-aged and evergreen forests and the `3-PGmix` model, which can also simulate multi-cohort stands (e.g. mixtures, uneven-aged) that contain deciduous species.
This implementation of 3-PG includes several major variants / modifications of the model in particular the ability to switch between 3-PGpjs (the more classic model version for monospecific stands) vs. 3-PGmix (a version for mixed stands), as well as options for bias corrections and \(\delta^13 C\) calculations (see parameters).
Forrester, D. I., 2020. 3-PG User Manual. Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland. 70 p. Available at the following web site: http://sites.google.com/site/davidforresterssite/home/projects/3PGmix/3pgmixdownload
Forrester, D. I., & Tang, X. (2016). Analysing the spatial and temporal dynamics of species interactions in mixed-species forests and the effects of stand density using the 3-PG model. Ecological Modelling, 319, 233–254. tools:::Rd_expr_doi("10.1016/j.ecolmodel.2015.07.010")
Landsberg, J. J., & Waring, R. H., 1997. A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology and Management, 95(3), 209–228. tools:::Rd_expr_doi("10.1016/S0378-1127(97)00026-1")
Sands, P. J., 2010. 3PGpjs user manual. Available at the following web site: https://3pg.sites.olt.ubc.ca/files/2014/04/3PGpjs_UserManual.pdf
prepare_input, prepare_parameters, prepare_sizeDist, prepare_thinning, prepare_climate
out <- run_3PG(
site = d_site,
species = d_species,
climate = d_climate,
thinning = d_thinning,
parameters = d_parameters,
size_dist = d_sizeDist,
settings = list(light_model = 2, transp_model = 2, phys_model = 2,
correct_bias = 1, calculate_d13c = 0),
check_input = TRUE, df_out = TRUE) # note that default is TRUE
str(out) # List output format
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