datb <- read.csv("~/Desktop/ANT109 FINAL ASSIGNMENT/species richness csv files/bird layer.csv", stringsAsFactors=TRUE)
datm <- read.csv("~/Desktop/ANT109 FINAL ASSIGNMENT/species richness csv files/mammal layer.csv", stringsAsFactors=TRUE)
datr <- read.csv("~/Desktop/ANT109 FINAL ASSIGNMENT/species richness csv files/reptile layer.csv", stringsAsFactors=TRUE)
nrow(datb)
nrow(datm)
nrow(datr)
The bird, mammal, and reptile datasets each have 63890 hexagons.
dat <- merge(datb, datm)
dat <- merge(dat, datr)
par(mfrow=c(1,3))
hist(dat$NtvBird, main = "Distribution of Native Birds", xlab = "Native Bird Species", col = "lightgreen", ylim=c(0,20000))
hist(dat$NtvMamm, main = "Distribution of Native Mammals", xlab = "Native Mammal Species", col = "skyblue", ylim=c(0,20000))
hist(dat$NtvRept, main = "Distribution of Native Reptiles", xlab = "Native Reptile Species", col = "lightcoral", ylim=c(0,20000))
The graphs display the distributions of native bird, mammal, and reptile species richness across hexagonal regions in California.
par(mfrow = c(1, 3))
# Scatter plot: NtvMamm vs. NtvBird
plot(dat$NtvMamm, dat$NtvBird, main = "Native Mammals vs Native Birds", xlab = "Native Mammal Species", ylab = "Native Bird Species", col = "lightgreen", pch=22)
# Scatter plot: NtvMamm vs. NtvRept
plot(dat$NtvMamm, dat$NtvRept, main = "Native Mammals vs Native Reptiles", xlab = "Native Mammal Species", ylab = "Native Reptile Species", col = "skyblue", pch=22)
# Scatter plot: NtvBird vs. NtvRept
plot(dat$NtvBird, dat$NtvRept, main = "Native Birds vs Native Reptiles", xlab = "Native Bird Species", ylab = "Native Reptile Species", col = "lightcoral", pch=22)
The graphs show the relationships between native mammal, bird, and reptile species richness across hexagonal regions in California. Each graph displays a scatter plot depicting the relationship between two variables: Native Mammals and Native Birds, Native Mammals and Native Reptiles, and Native Birds and Native Reptiles.