Relationships of Different Covers

Load Libraries

library(googlesheets4) #handles data
library(dplyr) #for data manipulation
library(ggplot2) # for plotting

theme_set(theme_classic(base_size = 18))

Load Data

# Load in the data and turn degree/minute/second into latlong
kelp_labels <- read_sheet("https://docs.google.com/spreadsheets/d/1rpz1wXdVTWC8lSkdoh4vjBuHYXUA7L86Qg1rVo_sOU4/",
                          col_types = "cccccddd")

kelp_labels_filtered <- 
  kelp_labels |>
  filter(!is.na(`Kelp % Cover`),
         !is.na(`Non-Kelp Vegetation % Cover`),
         !is.na(`Substrate % Cover`))

Kelp v. Understory Vegetation

ggplot(kelp_labels_filtered,
       mapping = aes(x = `Kelp % Cover`,
                     y = `Non-Kelp Vegetation % Cover`)) +
  geom_point(size = 2) +
  stat_smooth()

Pearson Correlation: -0.65

Kelp v. Substrate

ggplot(kelp_labels_filtered,
       mapping = aes(x = `Kelp % Cover`,
                     y = `Substrate % Cover`)) +
  geom_point(size = 2) +
  stat_smooth()

Pearson Correlation: -0.32

Understory Vegetation v. Substrate

ggplot(kelp_labels_filtered,
       mapping = aes(x = `Substrate % Cover`,
                     y = `Non-Kelp Vegetation % Cover`)) +
  geom_point(size = 2) +
  stat_smooth()

Pearson Correlation: -0.51