UC Reserve System Environmental Data

This post was to fulfill two small goals. I wanted to explore the publicly available UC Reserve Data and learn how to host small datasets within the blogdown blog framework that this website is written in. I also wanted to make sure I could save small output analyses and come back to them at a later date.

There is a good discussion of how hugo can handle internal datasets and how to organize the datasets here. I only found this post after playing around with various configurations so this could save some headache.

The UC Reserve System has a many data sources including species lists. For this post I used the Plant Species List Excel File compiled by Brian P. Haggerty and Susan J. Mazer of UC Santa Barbara. I did a little data cleaning on this multi-tabbed spreadsheet. I will do a short post on that process soon.

library(tidyverse)
eco_data <- read.csv("../../../static/data/reserve-eco-data.csv")

Take a quick look at how the data is structured.

glimpse(eco_data)

## Rows: 36
## Columns: 11
## $ UC.Natural.Reserve                        <chr> "Año Nuevo Island Reserve (s…
## $ X..Unique.Species..excluding.ssp....var.. <int> 0, 42, 55, 87, 150, 159, 170…
## $ X..Taxa.including.ssp....var.             <int> 0, 45, 72, 88, 151, 162, 173…
## $ Reserve.Size..ha.                         <int> 10, 18624, 8, 11, 69, 22, 24…
## $ Elevation.Low..m.                         <int> 0, 0, 0, 0, 0, 1250, 21, 0, …
## $ Elevation.High..m.                        <int> 13, 742, 2, 15, 12, 4012, 58…
## $ Elevation.Range..m.                       <int> 13, 742, 2, 15, 12, 2762, 37…
## $ Precipitation..cm.                        <int> 50, 50, 22, 62, 77, 32, 46, …
## $ Temperature.Low...C.                      <chr> "4", "10", "9", "12", "6", "…
## $ Temperature.High...C.                     <chr> "24", "22", "25", "15", "24"…
## $ X                                         <chr> "24", "22", "25", "15", "24"…

Data clean up and header labeling.

eco_data <- eco_data[1:10]
names(eco_data)[1:10] <- paste(c("reserve", "unique", "taxa", "size", "elevation_low", "elevation_high", "elevation_range","precip", "temp_low", "temp_high"))
names(eco_data)

##  [1] "reserve"         "unique"          "taxa"            "size"           
##  [5] "elevation_low"   "elevation_high"  "elevation_range" "precip"         
##  [9] "temp_low"        "temp_high"

eco_data$temp_high <- as.numeric(eco_data$temp_high)

The classic precipitation vs. temperature ecological plot.

classic <- ggplot(eco_data, aes(x=temp_high, y = precip)) +
geom_point() +
scale_x_continuous(name="High Temp (C)") +
scale_y_continuous(name="Precipitation (mm)")
classic

Another quick plot.

elevation_plot1 <- ggplot(eco_data, aes(x=elevation_range, y = unique)) +
geom_point() +
scale_x_continuous(name="Elevation Range (m)") +
scale_y_continuous(name="Number of Unique Species")
elevation_plot1