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Analysis","monthly_downloads":272,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](http://www.repostatus.org/badges/latest/active.svg)](http://www.repostatus.org/#active)\n[![R-CMD-check](https://github.com/trotsiuk/r3PG/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/trotsiuk/r3PG/actions/workflows/R-CMD-check.yaml)\n[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/r3PG)](https://cran.r-project.org/package=r3PG)\n[![](https://cranlogs.r-pkg.org/badges/grand-total/r3PG)](https://cran.r-project.org/package=r3PG)\n[![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)\n\n\n\n## Purpose\n\n`r3PG` provides an implementation of the Physiological Processes Predicting Growth ([3-PG](https://3pg.forestry.ubc.ca)) model (Landsberg \u0026 Waring, 1997), which simulate forest growth and productivity. The `r3PG` serves as a flexible and easy-to-use interface for the `3-PGpjs` (Sands, 2010) and the `3-PGmix` (Forrester \u0026 Tang, 2016) model written in `Fortran`. The package enables fast and easy interaction with the model, and the `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.\n\n## Usage\n\nBelow is a basic example, for more extended examples please visit package [vignette](https://htmlpreview.github.io/?https://github.com/trotsiuk/r3PG/blob/master/vignettes/r3PG-ReferenceManual.html).\n\nThe main function is `run_3PG()` which returns all 108 simulated variables for each species at a monthly time-step, either as a 4-dimentional array or a long format data frame.\n\n```r\nlibrary(r3PG)\nout_3PG \u003c- run_3PG(\n  site        = d_site, \n  species     = d_species, \n  climate     = d_climate, \n  thinning    = d_thinning,\n  parameters  = d_parameters, \n  size_dist   = d_sizeDist,\n  settings    = list(light_model = 2, transp_model = 2, phys_model = 2, \n                height_model = 1, correct_bias = 0, calculate_d13c = 0),\n  check_input = TRUE, df_out = TRUE)\n\nhead( out_3PG )\n```\n\nTo visualize the output:\n``` r\nlibrary(dplyr)\nlibrary(ggplot2)\n\nsel_var \u003c- c('biom_stem', 'biom_foliage', 'biom_root')\n\nout_3PG %\u003e%\n  filter( variable %in% sel_var ) %\u003e%\n  ggplot( aes(date, value, color = species) ) +\n  geom_line() +\n  facet_wrap(~variable, scales = 'free') +\n  theme_classic()\n```\n\nIf you prefer to use data stored in `Excell`, you can use the following example. Data to reproduce this example are stored in [data-raw/internal_data/data.input.xlsx](https://github.com/trotsiuk/r3PG/blob/master/data-raw/).\n\n``` r\nlibrary(readxl)\n\nf_loc \u003c- 'data.input.xlsx'\n\nrun_3PG(\n  site        = read_xlsx(f_loc, 'site'),\n  species     = read_xlsx(f_loc, 'species'),\n  climate     = read_xlsx(f_loc, 'climate'),\n  thinning    = read_xlsx(f_loc, 'thinning'),\n  parameters  = read_xlsx(f_loc, 'parameters'), \n  size_dist   = read_xlsx(f_loc, 'sizeDist'),\n  settings    = list(light_model = 2, transp_model = 2, phys_model = 2, \n                height_model = 1, correct_bias = 0, calculate_d13c = 0),\n  check_input = TRUE, df_out = TRUE)\n```\n\n## Installation \n\n### Stable release\n\n`r3PG` is available for instalation from [CRAN](https://cran.r-project.org/web/packages/r3PG/index.html) \n\n```r\ninstall.packages(\"r3PG\")\n```\n\n### Development release\n\nTo install the current (development) version from the repository, run the following command:\n\n```r\nif(!require(devtools)){install.packages(devtools)}\ndevtools::install_github(repo = \"trotsiuk/r3PG\", build_vignettes = T)\n```\n\nThe unit test status of the master (development) branch is [![R-CMD-check](https://github.com/trotsiuk/r3PG/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/trotsiuk/r3PG/actions/workflows/R-CMD-check.yaml)\n\n## Other 3-PG implementations in R\n\nWe would like to acknowledge that r3PG is not the only 3-PG implementations in R. We are aware of the following other packages:\n\n| Maintainer          | Source |\n| ------------------- | ------ |\n| Daniel M. Griffith  | https://github.com/griffithdan/r3PG |\n| Georgios Xenakis    | https://github.com/drGeorgeXenakis/fr3PGD |\n| Francesco Minunno   | https://github.com/checcomi/threePGN-package |\n| Quinn Thomas        | https://github.com/EcoDynForecast/DAPPER |\n\nWe explain in a recent publication ([Trotsiuk et al, 2020](https://doi.org/10.1111/2041-210X.13474)) how these r3PG packages differs and / or improves over these. \n\n## Issues, suggestions, contributions\n\nPlease submit issues, bugs and suggestions in the dedicated [page](https://github.com/trotsiuk/r3PG/issues). Contribution and improvements are always welcome!\n\n## Author and contact\n\n[Volodymyr Trotsiuk; ](volodymyr.trotsiuk@wsl.ch)\n[Florian Hartig; ](mailto:florian.hartig@biologie.uni-regensburg.de)\n[David I. Forrester](mailto:david.forrester@wsl.ch)\n\n\n## Citation\nTrotsiuk, V., Hartig, F., Forrester, D.I. (2020). r3PG – an R package for simulating forest growth using the 3-PG process-based model. Methods Ecol. Evol., 11, 1470–1475. https://doi.org/10.1111/2041-210X.13474\n\n\n## References\n\nForrester, D. I., \u0026 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. https://doi.org/10.1016/j.ecolmodel.2015.07.010\n\nLandsberg, J. J., \u0026 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. https://doi.org/10.1016/S0378-1127(97)00026-1\n\nSands, P. J. (2010). 3PGpjs user manual. Retrieved from https://3pg.sites.olt.ubc.ca/files/2014/04/3PGpjs_UserManual.pdf\n\nTrotsiuk, V., Hartig, F., Cailleret, M., Babst, F., Forrester, D. I., Baltensweiler, A., … Schaub, M. (2020). Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion. Global Change Biology, 26(4), 2463–2476. https://doi.org/10.1111/gcb.15011\n\nForrester, D. I., Hobi M. L., Mathys A. S., Stadelmann G., Trotsiuk V. (2021). Calibration of the process-based model 3-PG for major central European tree species. 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