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r3PG

An R package for forest growth simulation using the 3-PG process-based model

https://github.com/trotsiuk/r3pg

Science Score: 39.0%

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    Found 12 DOI reference(s) in README
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    Low similarity (15.2%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

An R package for forest growth simulation using the 3-PG process-based model

Basic Info
Statistics
  • Stars: 29
  • Watchers: 4
  • Forks: 17
  • Open Issues: 3
  • Releases: 7
Created over 6 years ago · Last pushed 12 months ago
Metadata Files
Readme Changelog License

README.md

Project Status: Active – The project has reached a stable, usable state and is being actively developed. R-CMD-check CRAN_Status_Badge License: GPL v3

Purpose

r3PG provides an implementation of the Physiological Processes Predicting Growth (3-PG) model (Landsberg & 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 & 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.

Usage

Below is a basic example, for more extended examples please visit package vignette.

The 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.

```r library(r3PG) out3PG <- run3PG( site = dsite, species = dspecies, climate = dclimate, thinning = dthinning, parameters = dparameters, sizedist = dsizeDist, settings = list(lightmodel = 2, transpmodel = 2, physmodel = 2, heightmodel = 1, correctbias = 0, calculated13c = 0), checkinput = TRUE, df_out = TRUE)

head( out_3PG ) ```

To visualize the output: ``` r library(dplyr) library(ggplot2)

selvar <- c('biomstem', 'biomfoliage', 'biomroot')

out3PG %>% filter( variable %in% selvar ) %>% ggplot( aes(date, value, color = species) ) + geomline() + facetwrap(~variable, scales = 'free') + theme_classic() ```

If 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.

``` r library(readxl)

f_loc <- 'data.input.xlsx'

run3PG( site = readxlsx(floc, 'site'), species = readxlsx(floc, 'species'), climate = readxlsx(floc, 'climate'), thinning = readxlsx(floc, 'thinning'), parameters = readxlsx(floc, 'parameters'), sizedist = readxlsx(floc, 'sizeDist'), settings = list(lightmodel = 2, transpmodel = 2, physmodel = 2, heightmodel = 1, correctbias = 0, calculated13c = 0), checkinput = TRUE, dfout = TRUE) ```

Installation

Stable release

r3PG is available for instalation from CRAN

r install.packages("r3PG")

Development release

To install the current (development) version from the repository, run the following command:

r if(!require(devtools)){install.packages(devtools)} devtools::install_github(repo = "trotsiuk/r3PG", build_vignettes = T)

The unit test status of the master (development) branch is R-CMD-check

Other 3-PG implementations in R

We would like to acknowledge that r3PG is not the only 3-PG implementations in R. We are aware of the following other packages:

| Maintainer | Source | | ------------------- | ------ | | Daniel M. Griffith | https://github.com/griffithdan/r3PG | | Georgios Xenakis | https://github.com/drGeorgeXenakis/fr3PGD | | Francesco Minunno | https://github.com/checcomi/threePGN-package | | Quinn Thomas | https://github.com/EcoDynForecast/DAPPER |

We explain in a recent publication (Trotsiuk et al, 2020) how these r3PG packages differs and / or improves over these.

Issues, suggestions, contributions

Please submit issues, bugs and suggestions in the dedicated page. Contribution and improvements are always welcome!

Author and contact

Volodymyr Trotsiuk; Florian Hartig; David I. Forrester

Citation

Trotsiuk, 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

References

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. https://doi.org/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. https://doi.org/10.1016/S0378-1127(97)00026-1

Sands, P. J. (2010). 3PGpjs user manual. Retrieved from https://3pg.sites.olt.ubc.ca/files/2014/04/3PGpjs_UserManual.pdf

Trotsiuk, 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

Forrester, 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. European Journal of Forest Research, 140, 847-868. https://doi.org/10.1007/s10342-021-01370-3

Owner

  • Name: Trotsiuk Volodymyr
  • Login: trotsiuk
  • Kind: user
  • Location: Birmensdorf
  • Company: Swiss Federal Research Institute WSL

RESEARCHER and DATA SCIENTIST

GitHub Events

Total
  • Issues event: 3
  • Watch event: 2
  • Issue comment event: 8
  • Push event: 20
  • Create event: 4
Last Year
  • Issues event: 3
  • Watch event: 2
  • Issue comment event: 8
  • Push event: 20
  • Create event: 4

Committers

Last synced: 11 months ago

All Time
  • Total Commits: 211
  • Total Committers: 6
  • Avg Commits per committer: 35.167
  • Development Distribution Score (DDS): 0.455
Past Year
  • Commits: 27
  • Committers: 2
  • Avg Commits per committer: 13.5
  • Development Distribution Score (DDS): 0.074
Top Committers
Name Email Commits
trotsiuk v****k@g****m 115
Volodymyr Trotsiuk v****k@w****h 54
florianhartig f****g 28
Rasilgon r****n@g****m 11
trotsiuk t****k@r****h 2
trotsiuk t****k@r****l 1
Committer Domains (Top 20 + Academic)
rabota.wsl.ch: 1 wsl.ch: 1

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 83
  • Total pull requests: 21
  • Average time to close issues: 4 months
  • Average time to close pull requests: about 1 month
  • Total issue authors: 16
  • Total pull request authors: 4
  • Average comments per issue: 4.04
  • Average comments per pull request: 0.29
  • Merged pull requests: 18
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 3
  • Pull requests: 0
  • Average time to close issues: 6 months
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • florianhartig (25)
  • trotsiuk (23)
  • twest820 (9)
  • DavidForrester (6)
  • Rasilgon (6)
  • SebastianBr2 (3)
  • GakenouOF (2)
  • LisaHuelsmann (1)
  • ChaitraliGore (1)
  • Catarinaxa (1)
  • Alvertin83 (1)
  • JohannesOberpriller (1)
  • zhengjiji456 (1)
  • jm5233 (1)
  • issamyax (1)
Pull Request Authors
  • trotsiuk (13)
  • Rasilgon (5)
  • florianhartig (2)
  • JohannesOberpriller (1)
Top Labels
Issue Labels
enhancement (11) bug (9) question (7) documentation (5) help wanted (2)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 197 last-month
  • Total docker downloads: 7
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 7
  • Total maintainers: 1
cran.r-project.org: r3PG

Simulating Forest Growth using the 3-PG Model

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 197 Last month
  • Docker Downloads: 7
Rankings
Forks count: 5.3%
Stargazers count: 11.9%
Average: 27.1%
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Downloads: 53.0%
Maintainers (1)
volodymyr.trotsiuk@wsl.ch
Last synced: 10 months ago

Dependencies

.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
DESCRIPTION cran
  • R >= 3.5.0 depends
  • BayesianTools * suggests
  • R.rsp >= 0.40.0 suggests
  • dplyr * suggests
  • ggplot2 * suggests
  • knitr >= 1.15.1 suggests
  • rmarkdown >= 1.3 suggests
  • roxygen2 * suggests
  • sensitivity * suggests
  • testthat >= 1.0.2 suggests