Answer the following questions and/or complete the exercises in
RMarkdown. Please embed all of your code and push the final work to your
repository. Your report should be organized, clean, and run free from
errors. Remember, you must remove the # for any included
code chunks to run. Any plots must have appropriate titles and
aesthetics.
library("tidyverse")
options(scipen=999) #turn off scientific notationDatabase of vertebrate home range sizes. Reference:
Tamburello N, Cote IM, Dulvy NK (2015) Energy and the scaling of animal
space use. The American Naturalist 186(2):196-211. http://dx.doi.org/10.1086/682070.
Data: http://datadryad.org/resource/doi:10.5061/dryad.q5j65/1
1. Load the data into a new object called
homerange.
2. What is the structure of the homerange data?
Does it have any NA’s? Do a quick exploratory analysis of your choice
below.
3. Which animal groups are represented in the data? Make a plot that shows the number in each class.
4. Are there more carnivores or herbivores represented in the data? Make a plot that shows the number in each trophic guild.
5. Which herbivorous mammals have homeranges greater than 1,000,000 m²? Show only the common name, order, mean homerange size, and mean body mass. Arrange the data in descending order by homerange size and show only the top 10 species.
6. Which two species have the largest and smallest homerange sizes?
7. Which carnivorous mammals have the largest homeranges?
8. Is there a relationship between body mass and homerange size? Make a scatterplot to show this relationship. Be sure to include appropriate labels and a title.
9. Use filter to extract the data for only birds and mammals. Then make a plot that compares the homerange sizes of these two groups. Be sure to include appropriate labels and a title.
10. Do one additional exploratory analysis of your choice.
Before writing the code, write the question you are trying to answer.
The question should be biologically meaningful and appropriate for the
data. It must include at least one filter(),
select(), and arrange().
Please knit your work as an .html file and upload to Canvas. Homework is due before the start of the next lab. No late work is accepted. Make sure to use the formatting conventions of RMarkdown to make your report neat and clean!