As part of state-wide conservation and educational efforts, California tracks and maintains databases of native species. To show the full richness of this biodiversity, the state is divided into 63,890 2.5 square mile hexagons (based on Hex_ID). This article visualizes the data of native bird, mammal, and reptile species. Part 1 is focused on visualizing species’ frequencies and Part 2 is focused on visualizing the geographic high and low density spots across the state for solely the native bird species data.

Part 1

Graph 1

Resources (for code):

https://stackoverflow.com/questions/1299871/how-to-join-merge-data-frames-inner-outer-left-right

https://www.dataanalytics.org.uk/make-transparent-colors-in-r/

https://www.rapidtables.com/web/color/RGB_Color.html

bird <- read.csv("~/Downloads/bird layer.csv", stringsAsFactors=TRUE)
mammal <- read.csv("~/Downloads/mammal layer.csv", stringsAsFactors=TRUE)
reptile <- read.csv("~/Downloads/reptile layer.csv", stringsAsFactors=TRUE)

InnerJoinTable <- merge(bird,mammal)
dat1 <- InnerJoinTable
InnerJoinTable <- merge(dat1,reptile)
dat <- InnerJoinTable

mycol1 <- rgb(107, 174, 214, max = 255, alpha = 125, names = "#6baed6")
mycol2 <- rgb(189, 58, 189, max = 255, alpha = 125, names = "#BD3AA4")
mycol3 <- rgb(91,180,80, max = 255, alpha = 125, names = "#5bb450")

par(mfrow=c(1,3))

hist(dat$NtvBird, xlim = c(0,250), ylim = c(0,20000), xlab = "Number of Species", ylab = "Frequency (Hexagons)", main = "Native Bird Species in California", col = mycol1)
hist(dat$NtvMamm, xlim = c(0,80), ylim = c(0,20000), xlab = "Number of Species", ylab = "Frequency (Hexagons)", main = "Native Mammal Species in California", col = mycol2)
hist(dat$NtvRept, xlim = c(0,50), ylim = c(0,20000), xlab = "Number of Species", ylab = "Frequency (Hexagons)", main = "Native Reptile Species in California", col = mycol3)

Caption: This 3-panel graph visualizes the distribution of native bird, mammal, and reptile species across the state; the x-axis shows the number of species within each hexagon and the y-axis shows the frequency of that number AKA the number of hexagons that have that number of native species.

Graph 2

Resources (for code):

https://stackoverflow.com/questions/3541713/how-can-i-plot-two-histograms-together-in-r

mam1 <- hist(dat$NtvMamm)
bird1 <- hist(dat$NtvBird)
rept1 <- hist(dat$NtvRept)
par(mfrow=c(1,3))

plot(bird1, main = "Native Mammals and Birds in California", xlab = "Number of Native Species", ylab = "Frequency (Hexagons)", col = mycol1, ylim = c(0,20000))
plot(mam1, add = TRUE, col = mycol2) ##Graph 1##

plot(rept1, main = "Native Mammals and Reptiles in California", xlab = "Number of Native Species", ylab = "Frequency (Hexagons)", col = mycol3, xlim =c(0,90), ylim = c(0,20000))
plot(mam1, add = TRUE, col = mycol2) ##Graph 2##

plot(bird1, main = "Native Birds and Reptiles in California", xlab = "Number of Native Species", ylab = "Frequency (Hexagons)", col = mycol1, ylim = c(0,20000))
plot(rept1, add = TRUE, col = mycol3)
legend("top",title = "Legend", legend = c("Native Mammals", "Native Birds", "Native Reptiles"), col = c(mycol2, mycol1, mycol3), pch = 19, cex=1.5) ##Graph 3##

Caption: This 3-panel graph visualizes the relationship between the native species; the x-axis and y-axis remain the same from the previous graph but the overlapping bargraphs in each panel show the relative variation between the bird, mammal, and reptile species. This perspective visualizes that there are significantly less native mammal and reptile species compared to native bird species, and therefore, they also have higher frequencies (represented as taller bars) as the total number of hexagons is consistent across the data.

Author’s Note: I chose overlapping bargraphs because I felt the scalar difference was the clearest and easiest to interpret compared to other relationship visualizations such as a matrix network.

Part 2

Density of Native Bird Species of California

Caption: This map shows, as a gradient, the highest and lowest densities of native bird species richness in California.
Caption: This map shows, as a gradient, the highest and lowest densities of native bird species richness in California.

Q: In what part(s) of California is the native bird species richness the highest? The lowest?

A: Following the legend, it can be interpreted that areas near the coast with the darkest blue on the gradient scale have the highest species richness. The lowest areas are scattered through the state, but a notably low region is South-Eastern part of the state where the Mojave Desert is located.