CENFA: departure – R documentation

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departure

Climatic departure

Description

This function quantifies the amount of change between historical and future climate conditions inside a species' habitat.

Usage

departure(x, y, s.dat, ...)

## S4 method for signature 'GLdeparture,missing,cnfa'
departure(x, s.dat, filename = "", ...)

## S4 method for signature 'GLdeparture,missing,Spatial'
departure(x, s.dat, field, fun = "last", filename = "", ...)

## S4 method for signature 'Raster,Raster,cnfa'
departure(
  x,
  y,
  s.dat,
  center = TRUE,
  scale = TRUE,
  filename = "",
  progress = FALSE,
  parallel = FALSE,
  n = 1,
  ...
)

## S4 method for signature 'Raster,Raster,Spatial'
departure(
  x,
  y,
  s.dat,
  center = TRUE,
  scale = TRUE,
  filename = "",
  progress = FALSE,
  parallel = FALSE,
  n = 1,
  ...
)

Arguments

`x`	Raster* object, typically a brick or stack of historical climate raster layers or a brick of absolute differences (see Details)
`y`	Raster* object, future climate values with the same layers as `x`
`s.dat`	SpatialPolygons*, sf, or cnfa object detailing species presence
`...`	Additional arguments for `clusterR`
`filename`	character. Optional filename to save the Raster* output to file. If this is not provided, a temporary file will be created for large `x`
`field`	field of `s.dat` that specifies presence. This is equivalent to the `field` argument of `raster::rasterize`. Options are 'first', 'last' (default), and 'count'
`fun`	function or character. Determines what values to assign to cells with multiple spatial features, similar to the `fun` argument in `rasterize`
`center`	logical. If `TRUE` then the values of `x` and `y` will be centered on the means of the historical climate data
`scale`	logical. If `TRUE` then the values of `x` and `y` will be scaled by the sds of the historical climate data
`progress`	logical. If `TRUE`, messages and progress bar will be printed
`parallel`	logical. If `TRUE` then multiple cores are utilized
`n`	numeric. Optional number of CPU cores to utilize for parallel processing

Details

For comparisons of multiple species in the same study area, it is much more efficient to first construct a Raster* object of absolute differences between the historical and future values, so that the differences do not need to be recalculated for each species. This can be achieved with by passing x and y to the difRaster function, and then passing the results to the departure function.

When only one Raster* object is supplied, it is assumed that x is a Raster* object containing the absolute differences of a historical and future dataset.

Value

Returns an S4 object of class departure with the following slots:

call: Original function call
df: Departure factor. Vector of length p that describes the amount of departure between future and historical conditions for each climate variable
departure: Magnitude of the departure factor
g.cov: p x p historical global covariance matrix
ras: RasterBrick of climate departures, with p layers
weights: Raster layer of weights used for departure calculation

References

Rinnan, D. Scott and Lawler, Joshua. Climate-niche factor analysis: a spatial approach to quantifying species vulnerability to climate change. Ecography (2019): doi:10.1111/ecog.03937.

Examples

dep1 <- departure(x = climdat.hist, y = climdat.fut, s.dat = ABPR, field = "CODE")

# using difRaster as an initial step
# for multi-species comparison

gld <- GLdeparture(x = climdat.hist, y = climdat.fut)
dep2 <- departure(x = gld, s.dat = ABPR, field = "CODE")

# same results either way
all.equal(dep1@df, dep2@df)

CENFA

Climate and Ecological Niche Factor Analysis

v1.1.0

GPL (>= 3)

Authors

D. Scott Rinnan

Initial release

2020-02-15