espace_nicheOv Niche Overlap

Function evaluates niche overlap between the two species for which the occurrence density grid was computed

Usage

espace_nicheOv(
  z1,
  z2,
  iter = 100,
  equivalency = FALSE,
  similarity = TRUE,
  logger = NULL
)

Arguments

z1

ecospat niche object for species 1 from espace_occDens.

z2

ecospat niche object for species 2 from espace_occDens.

iter

numeric. Number of iterations.

equivalency

logical. Whether to run equivalency test. Default is FALSE.

similarity

logical. Whether to run similarity test. Default is TRUE.

logger

Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL.

Value

A list of 4 elements if all is set to TRUE. Elements are overlap (Schoener's D), USE (ecospat.niche.dyn.index), equiv and simil.

Details

The niche overlap quantification is based on the occurrence densities and the densities of environmental conditions available in the background extent that are estimated in the module Occurrence Density Grid. The function computes 4 different things; Schoener's D, unfilling, stability, expansion indices (Guisan et al. 2014 TREE), and tests for niche equivalency and niche similarity.

See also

espace_pca espace_occDens ecospat.niche.overlap ecospat.niche.dyn.index ecospat.niche.equivalency.test ecospat.niche.similarity.test

Author

Jamie Kass <jamie.m.kass@gmail.com>

Olivier Broennimann <olivier.broennimann@unil.ch>

Examples

if (FALSE) { # \dontrun{
sp.name1 <- "Bassaricyon_alleni"
sp.name2 <- "Bassaricyon_neblina"
envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc",
                                           package = "wallace"),
                      pattern = ".tif$", full.names = TRUE),
                      rasName = list.files(system.file("extdata/wc",
                                           package = "wallace"),
                      pattern = ".tif$", full.names = FALSE))

occs.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni.csv",
                    package = "wallace"))
occs.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina.csv",
                    package = "wallace"))

bgPts.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv",
                     package = "wallace"))
bgPts.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina_bgPoints.csv",
                     package = "wallace"))

occsExt.z1 <- raster::extract(envs, occs.z1[, c("longitude", "latitude")])
occsExt.z2 <- raster::extract(envs, occs.z2[, c("longitude", "latitude")])
bgExt.z1 <- raster::extract(envs, bgPts.z1[, c("longitude", "latitude")])
bgExt.z2 <- raster::extract(envs, bgPts.z2[, c("longitude", "latitude")])
pcaZ <- espace_pca(sp.name1, sp.name2,
                   occsExt.z1, occsExt.z2,
                   bgExt.z1, bgExt.z2)
occDens <- espace_occDens(sp.name1, sp.name2, pcaZ)
nicheOv <- espace_nicheOv(z1 = occDens[[sp.name1]],
                          z2 = occDens[[sp.name2]],
                          iter = 100, equivalency = TRUE,
                          similarity = TRUE)
} # }