diversity.predict: Makes a spacially explicit prediction of the occupancy of...

In DiversityOccupancy: Building Diversity Models from Multiple Species Occupancy Models

Description

This function takes an deiversityoccu object and predicts occupancy for all species in new data, either a data.frame or a rasterstack. It can also return a subset of the total area of a rasterstack, where diversity and occupancy/abundance are higher than the nth quantile.

Usage

diversity.predict(model, diverse, new.data, quantile.nth = 0.8, species,
  kml = TRUE, name = "Priority_Area.kml")

Arguments

model	A result from diversityoccu
diverse	A result from the model.diversity function.
new.data	a rasterstack, or a dataframe containing the same variables as the siteCovs variable in diversityoccu or batchoccu
quantile.nth	the nth quantile, over which is a goal to keep both diversity and selected species. default = NULL
species	a boolean vector of the species to take into acount
kml	if TRUE builds a kml file of the selected area and saves it in your working directry
name	the name of the kml file if kml is TRUE

Value

a data frame with predicted values, or a raster stack with predictions for each species, a raster for diversity and a raster with the area meeting the quantile criteria.

Author(s)

Derek Corcoran <[e-mail]>

See Also

diversityoccu

batchoccu

model.diversity

Examples

## Not run: 
#Load the data
data("IslandBirds")
data("Daily_Cov")
data("siteCov")
data("Birdstack")

#Model the abundance for  5 bat species and calculate alpha diversity from that

#Model the abundance for  5 bat species and calculate alpha diversity from that

BirdDiversity <-diversityoccu(pres = IslandBirds, sitecov = siteCov,
obscov = Daily_Cov,spp =  5, form = ~ Day + Wind + Time ~ Elev + Wetland + Upland)

#Select the best model that explains diversity using genetic algorithms
set.seed(123)
glm.Birdiversity <- model.diversity(BirdDiversity, method = "g")

# get the area where the first two bird species are most abundant
# and the diversity is high

library(rgdal)
Selected.area <- diversity.predict(model = BirdDiversity, diverse = glm.Birdiversity,
new.data = Birdstack, quantile.nth = 0.65, species =
c(TRUE, TRUE, FALSE, FALSE, FALSE))

Selected.area

## End(Not run)

DiversityOccupancy documentation built on May 2, 2019, 12:35 p.m.