exdet_univar: Exdet univariate: NT1 metric, univariate extrapolation risk...

In luismurao/ntbox: From Getting Biodiversity Data to Evaluating Species Distribution Models in a Friendly GUI Environment

Exdet univariate: NT1 metric, univariate extrapolation risk analysis for model transfer

Description

exdet_univa calculates NT1 metric.

Usage

exdet_univar(M_stack, G_stack, G_mold = NULL)

Arguments

M_stack	a RasterStack or a Matrix of variables representing the calibration area (M area in ENM context). If M_stack is matrix it should contain the values of environmental variables as get it from getValues function.
G_stack	a RasterStack or a Matrix of variables representing areas or scenarios to which models will be transferred. If G_stack is matrix it should contain the values of environmental variables as get it from getValues function.
G_mold	a Raster representing the extent of the projection area. This is only necessary when G_stack is of class matrix; G_mold will we use as a mold to save the NT1 values computed by exdet_univa function.

Details

The exdet univariate (exdet_univar) and multivariate (exdet_multvar) is calculated following: Mesgaran, M.B., Cousens, R.D. & Webber, B.L. (2014) Here be dragons: a tool for quantifying novelty due to covariate range and correlation change when projecting species distribution models. Diversity & Distributions, 20: 1147–1159, DOI: 10.1111/ddi.12209.

Examples

m_stack <- raster::stack(list.files(system.file("extdata",
                                    package = "ntbox"),
                                    pattern = "M_layers.tif$",
                                    full.names = TRUE))
g_stack <- raster::stack(list.files(system.file("extdata",
                                    package = "ntbox"),
                                    pattern = "G_layers.tif$",
                                    full.names = TRUE))

NT1 <- exdet_univar(M_stack = m_stack,
                    G_stack = g_stack,G_mold=NULL)
raster::plot(NT1)

luismurao/ntbox documentation built on April 3, 2024, 5:47 a.m.