BIOMASS (version 2.1.11)

computeE: Retrieving Chave's environmental index

Description

Extract the Chave et al. 2014's environmental index thanks to the coordinates of the data. The function is time-consuming at its first use as it downloads a raster in a folder (see Details). However, as soon as the raster is downloaded once, the function then runs fast.

Usage

computeE(coord)

Value

The function returns E, the environmental index computed thanks to the Chave et al 2014's formula as a single value or a vector.

Arguments

coord

Coordinates of the site(s), a matrix/dataframe with two columns (e.g. cbind(longitude, latitude)) (see examples).

Localisation

Cache path discovery protocol

1. BIOMASS.cache option set to an existing folder

2. existing user data folder rappdirs::user_data_dir()

   • On Linux : ~/.local/share/R/BIOMASS

   • On Mac OS X : ~/Library/Application Support/R/BIOMASS

   • On Windows 7 up to 10 : C:\\Users\\<username>\\AppData\\Local\\R\\BIOMASS

   • On Windows XP : C:\\Documents and Settings\\<username>\\Data\\R\\BIOMASS

3. fallback to R session tempdir

Author

Jerome CHAVE, Maxime REJOU-MECHAIN, Ariane TANGUY, Arthur PERE

Details

The Chave's environmental index, E, has been shown to be an important covariable in the diameter-height relationship for tropical trees. It is calculated as: $$E = 1.e-3 * (0.178 * TS - 0.938 * CWD - 6.61 * PS)$$ where TS is temperature seasonality as defined in the Worldclim dataset (bioclimatic variable 4), CWD is the climatic water deficit (in mm/yr, see Chave et al. 2014) and PS is the precipitation seasonality as defined in the Worldclim dataset (bioclimatic variable 15).

The E index is extracted from a raster file (2.5 arc-second resolution, or ca. 5 km) available at http://chave.ups-tlse.fr/pantropical_allometry.htm

References

Chave et al. (2014) Improved allometric models to estimate the aboveground biomass of tropical trees, Global Change Biology, 20 (10), 3177-3190

Examples

# One study site
lat <- 4.08
long <- -52.68
coord <- cbind(long, lat)
# \donttest{
E <- computeE(coord)
# }

# Several study sites (here three sites)
long <- c(-52.68, -51.12, -53.11)
lat <- c(4.08, 3.98, 4.12)
coord <- cbind(long, lat)
# \donttest{
E <- computeE(coord)
# }