rm(list=ls())
# Load necessary libraries
# install.packages("ggplot2")
library(ggplot2)

# Number of mammals
n <- 500 

# Simulate mass of species (assuming a log-normal distribution)
mass <- rlnorm(n, meanlog=5, sdlog=2)

# Simulate diet breadth rate of change 
# (assuming larger mammals have a slightly slower rate)
diet_breadth_change <- rnorm(n, mean=0.5 - 0.2 * log(mass), sd=0.3)

# Simulate climate niche adaptability
climate_niche_change <- rnorm(n, mean=0.5 - 0.2 * log(mass), sd=0.3)

# Simulate range size adaptability
range_size_change <- rnorm(n, mean=0.5 - 0.2 * log(mass), sd=0.3)

# Combine into a dataframe
mammals_data <- data.frame(
  Mass = mass,
  DietBreadthChange = diet_breadth_change,
  ClimateNicheChange = climate_niche_change,
  RangeSizeChange = range_size_change
)

# Example Plot: Mass vs. Diet Breadth Change
ggplot(mammals_data, aes(x=Mass, y=DietBreadthChange)) +
  geom_point(alpha=0.6) +
  labs(title="Mass vs. Diet Breadth Change", 
       x="Mass of Mammal", 
       y="Rate of Change in Diet Breadth") +
  theme_minimal()