Ecotourism Tutorial

Joining occurrence, tourism, and weather data

🎯 Objectives

Practice joining wildlife occurrence records with tourism and weather data from the ecotourism package, and explore how visitor numbers relate to wildlife sightings across different regions, organisms, and months.

🔧 Preparation

• Install the ecotourism package by running remotes::install_github("vahdatjavad/ecotourism") in the Console.
• Complete the weekly quiz, before the deadline!
• Open your RStudio Project for this unit, (the one you created in week 1). Create a .qmd document for this week’s activities.

📥 Exercises

The ecotourism package contains wildlife occurrence records and quarterly tourism trip counts for Australia, linked by ws_id. In the setup chunk, tourism_total has been created by summing trips across purposes per ws_id, year, and quarter.

Object	Description
gouldian_finch	Gouldian Finch occurrence records (2014–2024)
manta_rays	Manta Ray occurrence records (2014–2024)
glowworms	Glowworm occurrence records (2014–2024)
tourism_quarterly	Quarterly tourism trips by region and purpose
weather	Daily weather by station: temp, max, min, prcp linked by ws_id and date

Question 1 (one region). Join gouldian_finch with tourism_total and ecotourism::weather, keeping only sightings from Western Australia (obs_state == "Western Australia"). How many sightings are in the joined table? How many have a non-NA value for max (daily maximum temperature)? What does this tell you about the completeness of the weather data in the current package?

Question 2 (one organism). Join manta_rays with tourism_total and ecotourism::weather across all regions and months. For each month, calculate the mean total tourism trips and the proportion of sighting days that have a non-NA max value. In which months is weather data available, and what does the pattern of missing weather tell you?

Question 3 (one month). Join glowworms with tourism_total and ecotourism::weather, keeping only sightings from April (month == 4). Make a scatter plot of total_trips against year, colouring by obs_state. Add a note to the plot title indicating how many sighting days have weather data available. What would this plot look like once the weather data is complete?

👌 Finishing up

Make sure you say thanks and good-bye to your tutor. This is a time to also report what you enjoyed and what you found difficult.