ensemble.bioclim.graph: Graphs of bioclimatic ranges of species and climates

In BiodiversityR: Package for Community Ecology and Suitability Analysis

Graphs of bioclimatic ranges of species and climates

Description

The main graph function makes graphs that show mean, median, minimum, maximum and lower and upper limits for species or climates. The ensemble.bioclim.graph.data function creates input data, using ensemble.bioclim.object internally.

Usage

ensemble.bioclim.graph(graph.data = NULL, focal.var = NULL, 
    species.climates.subset = NULL, cols = NULL,
    var.multiply = 1.0, ref.lines = TRUE)

ensemble.bioclim.graph.data(
    x=NULL, p=NULL, fraction = 0.9, 
    species.climate.name="Species001_base", factors = NULL)

Arguments

graph.data	Input data with same variables as created by ensemble.bioclim.graph
focal.var	Bioclimatic variable to be plotted in the graph
species.climates.subset	Character vector with subset of names of species and climates to be plotted in the graph (if not provided, then all species and climates will be plotted).
cols	colours for the different species and climates
var.multiply	multiplier for the values to be plotted; 0.1 should be used if the bioclimatic variable was multiplied by 10 in the raster layers as in WorldClim and AFRICLIM
ref.lines	If TRUE, then horizontal reference lines will be added for the minimum and maximum values of the species or climate plotted on the extreme left in the graph
x	RasterStack object (stack) containing all environmental layers for which statistics should be calculated; see also ensemble.bioclim.
p	presence points used for calibrating the suitability models, typically available in 2-column (lon, lat) dataframe; see also ensemble.bioclim.
fraction	Fraction of range representing the optimal limits, default value of 0.9 as in the original BIOCLIM software; see also ensemble.bioclim.
species.climate.name	Name for the species or climate that will be used as label in the graph.
factors	vector that indicates which variables are factors; these variables will be ignored by the BIOCLIM algorithm; see also ensemble.bioclim.

Details

The function creates a graph that shows mean, median, minimum, maximum and upper and lower limits for a range of species and climates. The graph can be useful in interpreting results of ensemble.bioclim or ensemble.novel.

In the graphs, means are indicated by an asterisk (pch=8 and medians as larger circles (pch=1)).

Value

function ensemble.bioclim.graph.data creates a data frame, function ensemble.bioclim.graph allows for plotting.

Author(s)

Roeland Kindt (World Agroforestry Centre)

See Also

ensemble.bioclim

Examples

## Not run: 

# get predictor variables
library(dismo)
predictor.files <- list.files(path=paste(system.file(package="dismo"), '/ex', sep=''),
    pattern='grd', full.names=TRUE)
predictors <- stack(predictor.files)
# subset based on Variance Inflation Factors
predictors <- subset(predictors, subset=c("bio5", "bio6", 
    "bio16", "bio17", "biome"))
predictors
predictors@title <- "base"

# presence points
presence_file <- paste(system.file(package="dismo"), '/ex/bradypus.csv', sep='')
pres <- read.table(presence_file, header=TRUE, sep=',')[,-1]

# climates for north and south (use same process for future climates)
ext2 <- extent(-90, -32, 0, 23)
predictors2 <- crop(predictors, y=ext2)
predictors2 <- stack(predictors2)
predictors2@title <- "north"

ext3 <- extent(-90, -32, -33, 0)
predictors3 <- crop(predictors, y=ext3)
predictors3 <- stack(predictors3)
predictors3@title <- "south"

graph.data1 <- ensemble.bioclim.graph.data(predictors, p=pres, 
    factors="biome", species.climate.name="Bradypus")
graph.data2 <- ensemble.bioclim.graph.data(predictors, p=NULL, 
    factors="biome", species.climate.name="baseline")
graph.data3 <- ensemble.bioclim.graph.data(predictors2, p=NULL, 
    factors="biome", species.climate.name="north")
graph.data4 <- ensemble.bioclim.graph.data(predictors3, p=NULL, 
    factors="biome", species.climate.name="south")
graph.data.all <- rbind(graph.data1, graph.data2, graph.data3, graph.data4)

par.old <- graphics::par(no.readonly=T)
graphics::par(mfrow=c(2, 2))

ensemble.bioclim.graph(graph.data.all, focal.var="bio5", 
    var.multiply=0.1, cols=c("black", rep("blue", 3)))
ensemble.bioclim.graph(graph.data.all, focal.var="bio6", 
    var.multiply=0.1, cols=c("black", rep("blue", 3)))
ensemble.bioclim.graph(graph.data.all, focal.var="bio16", 
    var.multiply=1.0, cols=c("black", rep("blue", 3)))
ensemble.bioclim.graph(graph.data.all, focal.var="bio17", 
    var.multiply=1.0, cols=c("black", rep("blue", 3)))

graphics::par(par.old)


## End(Not run)

BiodiversityR documentation built on Oct. 22, 2023, 5:06 p.m.