simple_plot: Plot diversity

In mysteryduck/ggrdiversity: Provides plotting functions for the package rdiversity

Description

Simple function to plot diversity profiles.

Usage

simple_plot(res)

Arguments

res	object of class diversity; output of functions subdiv(), metadiv(), or any of the specific subcommunity- or metacommunity-level diversity functions.

Examples

## Not run: 
# Define metacommunity
pop1 <- data.frame(a = c(1,3), b = c(1,1))
row.names(pop1) <- paste0("sp", 1:2)
pop1 <- pop1/sum(pop1)
meta1 <- metacommunity(pop1)
qs <- 0:2

# Plot subcommunity beta diversity
b <- raw_beta(meta1)
sc <- subdiv(b, qs)
plot(sc)

# Plot metacommunity beta diversity
mc <- metadiv(b, qs)
plot(mc)

# Plot subcommunity and metacommunity beta diversity
res <- diversity(list(sc, mc))
plot(res)

# Plot all subcommunity diversity measures
all_sc <- subdiv(meta1, qs)
plot(all_sc)

# Plot all metacommunity diversity measures
all_mc <- metadiv(meta1, qs)
plot(all_mc)

# Plot all diversity measures
all_res <- diversity(list(all_sc, all_mc))
plot(all_res)

# Try a single population
pop2 <- c(1,3,4)
pop2 <- pop2/sum(pop2)
meta2 <- metacommunity(pop2)
sc <- sub_gamma(meta2, qs)
plot(sc)
mc <- meta_gamma(meta2, qs)
plot(mc)

# Try large number of subcommunities
pop3 <- matrix(sample(1000), ncol = 100)
row.names(pop3) <- paste0("sp", 1:10)
pop3 <- pop3/sum(pop3)
meta3 <- metacommunity(pop3)
sc <- sub_gamma(meta3, qs)
plot(sc)

# Plot naive with similarity
# Create Lookup table
Species <- c("tenuifolium", "asterolepis", "simplex var.grandiflora", "simplex var.ochnacea")
Genus <- c("Protium", "Quararibea", "Swartzia", "Swartzia")
Family <- c("Burseraceae", "Bombacaceae", "Fabaceae", "Fabaceae")
Subclass <- c("Sapindales", "Malvales", "Fabales", "Fabales")
lookup <- cbind.data.frame(Species, Genus, Family, Subclass)

# Assign values for each level (Shimatani's taxonomic distance)
taxDistance <- c(Species = 0, Genus = 1, Family = 2, Subclass = 3, Other = 4)

distance <- tax2dist(lookup, taxDistance)
similarity <- dist2sim(distance, "linear")

pop <- data.frame(a = c(1,3,6,3), b = c(1,1,2,8))
row.names(pop) <- lookup$Species
pop <- pop/sum(pop)

alpha <- norm_meta_alpha(metacommunity(pop), 0:2)
alphaZ <- norm_meta_alpha(metacommunity(pop, similarity), 0:2)
alphaZ$partition_level <- paste0(alphaZ$measure, "_Z")
plot_this <- diversity(list(alpha, alphaZ))
plot(plot_this)


## End(Not run)

mysteryduck/ggrdiversity documentation built on May 9, 2019, 2:59 p.m.