HW1: The Coastal Kelp Forest Crisis

A Statistical Investigation

Author

Dr. Marcela Alfaro Córdoba

🔍 The Case

Welcome, Statistical Detective!

You’ve been hired as a data consultant by the California Coastal Conservation Agency, which monitors 5 marine protected areas (MPAs) along the central coast. The lead marine biologist, Dr. Chen, has noticed something alarming:

“Our northern MPA is showing signs of ecosystem decline. Kelp coverage is decreasing, sea urchin populations are exploding, and biodiversity metrics are dropping. But I don’t know the root cause! Is it water temperature? Pollution? Sea otter populations? I need your help to figure this out using data and proper statistical methods.”

Dr. Chen has some hypotheses but needs scientific evidence before recommending expensive conservation interventions.

Your mission: Use your statistical knowledge to help Dr. Chen investigate this mystery and make data-driven recommendations!

Part 1: Why Statistics Matters in Marine Biology

Question 1: The Role of Statistics (4-5 sentences)

a. Explain how statistics helps scientists like Dr. Chen make better decisions about ecosystem management. Why can’t Dr. Chen just rely on personal observations or hunches?

b. Give ONE example of how you’ve encountered statistics in your everyday life recently (news, social media, health app, etc.). Was the statistical claim trustworthy? Why or why not?

Part 2: Understanding Variables in Marine Research

Dr. Chen’s research team will collect data on multiple aspects of kelp forest ecosystems.

Question 2: Classify the Variables

For each variable, identify it as numerical (continuous or discrete) or categorical (nominal or ordinal):

Variable Type Specific Classification
Water temperature (°C)
Number of sea urchins counted in a 1m² quadrat
Dominant kelp species (bull kelp, giant kelp, feather boa)
Ecosystem health rating (critical, poor, fair, good, excellent)
Kelp canopy coverage (% of surveyed area)
MPA location name (North Bay, Seal Cove, etc.)
Presence of sea otters (yes/no)
pH level of seawater

Question 3: Variables in Context

a. Dr. Chen wants to investigate whether water temperature affects sea urchin population size. Identify the explanatory variable and the response variable.

b. Name TWO other variables that might affect sea urchin populations (besides temperature) that Dr. Chen should measure or control for.

Part 3: Avoiding Bias in Data Collection

Dr. Chen needs to design a study to compare kelp forest health across the 5 MPAs.

Question 4: Sampling Strategy

a. Dr. Chen’s assistant suggests: “Let’s just survey the kelp forests closest to our research station since they’re easiest to access.”

  • What type of bias does this introduce?
  • How would this bias affect Dr. Chen’s conclusions about MPA health?
  • Suggest a better sampling approach.

b. Another assistant suggests: “Let’s post on social media asking divers to report kelp coverage whenever they visit an MPA.”

  • What type of bias does this introduce?
  • Why might this data be unreliable?
  • Suggest a better data collection approach.

Question 5: Confounding Variables

Dr. Chen compares two MPAs and finds that Northern MPA has less kelp coverage and fewer sea otters than Southern MPA. She concludes: “Sea otters must be causing increased kelp coverage!”

a. What’s wrong with this conclusion?

b. The Northern MPA is located near agricultural runoff, while the Southern MPA is in a pristine area. The Northern MPA also has warmer water temperatures. Explain how these are confounding variables.

c. How could Dr. Chen design a better study to isolate the effect of sea otters on kelp coverage?

Part 4: Statistics in Scientific Discovery

Question 6: Real-World Application

a. Read this claim: “A recent study found that areas with more sea otters have 40% more kelp coverage on average.”

Based on what you’ve learned, list THREE questions you would ask before accepting this claim:

b. Dr. Chen measures kelp coverage at 50 random locations in the Northern MPA. She calculates that the average coverage is 28%.

  • Is 28% a parameter or a statistic? Explain.
  • What is the population in this scenario?
  • What is the sample?

💭 Question 7: Reflection (4-5 sentences)

Think about a health or environmental issue you care about (e.g., air quality, disease prevention, climate change, nutrition, mental health).

  • How could data and statistical reasoning help scientists or policymakers better understand this issue?
  • What types of variables would be important to measure?
  • What biases might researchers need to watch out for when collecting data on this issue?

🎉 Good luck, Statistical Detective! Evidence-based conservation is counting on you!