computeE: Retrieving Chave's environmental index
In ArthurPERE/biomass: Estimating Aboveground Biomass and Its Uncertainty in Tropical Forests

Description Usage Arguments Details Value Localisation Author(s) References Examples

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.

1	computeE(coord)

coord

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

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

The function returns E, the environmental index computed thanks to the Chave et al 2014's formula.

The localisation of the folder is :

On Linux : ~/.local/share/BIOMASS
On Mac OS X : ~/Library/Application Support/BIOMASS
On Windows 7 up to 10 : C:\Users\<username>\AppData\Local\BIOMASS\BIOMASS
On Windows XP : C:\Documents and Settings\<username>\Data\BIOMASS\BIOMASS

See this function for more information : rappdirs::user_data_dir()

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

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

# One study site
lat <- 4.08
long <- -52.68
coord <- cbind(long, lat)
## Not run: 
E <- computeE(coord)

## End(Not run)

# 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)
## Not run: 
E <- computeE(coord)

## End(Not run)