This project explores global deforestation over time and some factors that may be related. The data comes from Our World in Data.

The relevant data sets is downloaded with the following code:

forest <- read_csv('http://web.stcloudstate.edu/mdernst/325/forest.csv') forest_area <- read_csv('http://web.stcloudstate.edu/mdernst/325/forest_area.csv') soybean_use <- read_csv('http://web.stcloudstate.edu/mdernst/325/soybean_use.csv') vegetable_oil <- read_csv('http://web.stcloudstate.edu/mdernst/325/vegetable_oil.csv')

Create an R Markdown file that provides complete, easy-to-read code for each of the following exercises. For each exercise, you should have a single block of code that does all of the steps requested. Your code should rely heavily on the concepts covered in the textbook.

1.Find the five top countries that contained the highest percentage of the world's forests in 2020.

2.Thenet_forest_conversionvariable in the forest.csv data measures each country's gain in hectares of forest (negative values indicate a loss). Find the five countries with the highest total deforestation (forest loss) over the time period covered in the data.

3.When a country produces more crops, like soybeans, it is often achieved by converting forests to cropland. To investigate this relationship, do the following:

a.Calculate the total soybean production for each country in each year, regardless of how it's used.

b.Merge this data with the forest_area.csv data.

c.Create a scatterplot of the forest_area (as a % of global forests) versus total soybean production for each of the five countries in Exercise 1. Use different colors to differentiate the countries.

d.Is there evidence that increased soybean production leads to decreased forest_area?