forestdynR

forestdynR is a package to calculate forest dynamics, including abundance, mortality and recruitment rates, basal area, and biomass. The function uses diameter at breast height (DBH) data to estimate forest dynamics over time.

1. INSTALLATION

You can install the package directly from GitHub using the devtools. Run the following command in R:

# Install devtools if you haven't already
install.packages('devtools')

# Install forestdynR from GitHub
devtools::install_github('https://github.com/higuchip/forestdynR.git')

#NOTE: To install this package from source on Windows, you must have the [Rtools](https://cran.rstudio.com/bin/windows/Rtools/) installed.

Or through CRAN, the official R repository. Run this command in R:

install.packages('forestdynR')

2. USAGE

2.1 DESCRIPTION

The forestdynR package accepts data that must have the following arguments:

Function Arguments: - forest_df: Data frame that must contain the following columns (not necessarily in this order):

• plot: Plot identification.
• spp: Species identification Species identification..
• DBH_1: Diameter at breast height (DBH) in year 1 (numeric values).
• DBH_2: Diameter at breast height (DBH) in year 2 (numeric values).

Important: - The columns DBH_1 and DBH_2 must contain numeric values; - You can add more columns, but columns plot, spp, DBH_1 and DBH_2must be present in the data frame, because the function uses the column names to do the calculation.

• inv_time: Represents the time between inventories, in years (e.g.: 5);

• coord: Geographic coordinates in the format c(longitude, latitude), with values in decimal degrees (e.g.: c(-50.17,-27.71));

• add_wd: Optional data frame with wood density values (g/cm3). The expected format is a data frame with three columns:

  • genus: Genus of the species;
  • species: Species identification (scientific name);
  • wd: Wood density (g/cm3).

  NOTE: The add_wd is NULL by default. If the argument is not provided, wood density will be estimated automatically using the getWoodDensity() function from the BIOMASS package, based on the wood density database by Zanne et al., (2009).

Example file: An example input file is available with the function, just call data(forest_df_example), and you will have access to the database presented in e.g. 1.

e.g.1: Example input file is available with the function:

[…]

• You can check that data set by running the command:

data(forest_df_example)

2.2 APPLYING THE FUNCTION

#Example of usage os the forestdybR function

library(forestdynR) # Load package
data(forest_df_example) # Load your dataset

dyn_object <- forest_dyn(forest_df_example, 5, c(-50.17,-27.71)) # Run the function

2.3 RETURN

The function returns a report containing the forest community dynamics, with abundance metrics, dynamic rates, basal area, and biomass by year. If you apply the example data (data(forest_df_example)) to the function, the result will be the same as shown in the e.g.2.

e.g.2: Function results

forest_dyn(forest_df, 5, c(-50.17,-27.71))
NA's were turned into 0
The reference dataset contains 16467 wood density values
Your taxonomic table contains 25 taxa

dyn_object$dynamics$n_plot

dyn_object$dynamics$n_species

dyn_object$dynamics$basal_area_plot

dyn_object$dynamics$basal_area_species

dyn_object$report_df

3. REFERENCES

• KORNING, J.; BALSLEV, H. Growth and mortality of trees in Amazonian tropical rain forest in Ecuador. Journal of Vegetation Science, v.5, n.1, p.77-86, 1994.
• OLIVEIRA FILHO, A. T. et a. Dinâmica da comunidade e populações arbóreas da borda e interior de um remanescente florestal na Serra da Mantiqueira, Minas Gerais, em um intervalo de cinco anos (1999-2004). Revista Brasileira de Botânica, v.30, n.1, p.149-161, 2007.
• SALAMI, B. et al. Influência de variáveis ambientais na dinâmica do componente arbóreo em um fragmento de Floresta Ombrófila Mista em Lages, SC. Scientia Forestalis, v.42, n.102, p.197-207, 2014.
• SHEIL, D.; DAVID, BURSLEM, D. F. R. P.; ALDER, D. The interpretation and misinterpretation of mortality rate measures. Journal of Ecology, v.83, n.2, p.331-333, 1995.
• SHEIL, D.; JENNINGS, S.; SAVILL, P. Long-term permanent plot observations of vegetation dynamics in Budongo, a Ugandan rain forest. Journal of Tropical Ecology, v.16, n.6, p.865-882, 2000.
• Zanne, A. E., et al. Global wood density database. Dryad, 2009.
• Chave et al. (2014) Improved allometric models to estimate the above ground biomass of tropical trees. Global Change Biology, 20 (10), 3177-3190
• REJOU-MECHAIN, M.; TANGUY, A.; PIPONIOT, C.; CHAVE, J.; HERAULT, B. BIOMASS: Estimating Above ground Biomass and Its Uncertainty in Tropical Forests. R package version 1.2. https://CRAN.R-project.org/package=BIOMASS

4. CONTRIBUTION

Contributions are welcome! Feel free to open issues or pull requests.

5. LICENSE

This package is licensed under the MIT License.

6. CONTACT

If you have any questions, feel free to reach out:

• Author: Pedro Higuchi

• Email: higuchip@gmail.com

• Co-author: Ana Carolina da Silva

• Email: carol_sil4@yahoo.com.br

• Co-author: Adam Slabadack

• Email: arslabadack@gmail.com