Skip to contents

Retrieving Chave's environmental index

Source: R/computeE.R
computeE.Rd

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)

Arguments

coord

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

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.

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

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

References

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

Author

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

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)
# }