#3 Scientific Method and Climate Change
Scientific Method & Climate Action Notes
Page 1: Introduction
Course Code: NST1070
Page 2: Outline of Topics
Reading: "The Imperative for Climate Action to Protect Health"
The Scientific Method
Scientific Bias
In-Class Activity
Page 3: Review Reading
Page 4: The Imperative for Climate Action to Protect Health
Central Question: How will climate change contribute to human morbidity and mortality, both directly and indirectly?
Objective: Identify types of policies needed to mitigate risks to human health associated with climate change.
Page 5: Temperature Trends
Figure 1: Changes in Surface Temperatures, 1850–2017. (Reference: Haines A, Ebi K. N Engl J Med 2019;380:263-273)
1850-1900 Temperature Trend:
Displayed minimal change with peaks and valleys.
1970-2017 Temperature Trend:
Trending upward with significant peaks and valleys.
Question: Compare the temperature trends observed in the two timeframes.
Page 6: Health Risks Due to Climate Change
Figure 3: Major Health Risks Associated with Climate Change. (Reference: Haines A, Ebi K. N Engl J Med 2019;380:263-273)
Key Points:
Benefits of climate action generally outweigh drawbacks, especially concerning lives saved.
Statistics: Potential to prevent 120,000 premature deaths annually through clean transportation initiatives.
Authors' Conclusion from IPCC Report:
The implementation costs of mitigation policies can be outweighed by health benefits.
Page 7: Article Insights
Authors: Andy Haines, M.D., and Kristie Ebi, M.P.H., Ph.D.
Publication Date: January 16, 2019, in N Engl J Med 2019;380:263-273.
Reflection: Questions prompted by the reading.
Page 8: Balancing Climate Education
Discussion Prompt:
How can higher education integrate climate literacy across all disciplines while providing specialized knowledge?
Request for examples of successful integrations.
Page 9: Introduction to the Scientific Method
Page 10: The Scientific Method Steps
Hypothesis
Observation
Experiment
Analysis
Conclusion
Communicate Results
Page 11: Understanding the Hypothesis
Definition: A hypothesis is a tentative statement proposing a potential relationship between variables, subject to testing and verification.
Components:
Testable prediction explaining a phenomenon.
Formulated based on prior knowledge, observations, or theories.
Serves as a starting point for scientific investigation and is validated by empirical evidence.
Page 12: Types of Hypotheses
Null Hypothesis: Proposes no significant relationship or effect between variables.
Alternative Hypothesis: Proposes a specific relationship or effect between variables, challenging the null hypothesis.
Page 13: The Scientific Method Cycle
Characteristics of a Good Experiment:
Control for variables in question.
Replication of experiments.
Only change one variable at a time.
Communication of Results: Conduct background research, produce manuscripts, posters, presentations, interviews.
Nature of Science: Science evolves, constantly gaining knowledge to refine our understanding.
Page 14: Example of Scientific Method Application
Page 15: Observation Example
"Fish in the tank near the window are more active and display brighter colors than fish in the tank located in a shaded area."
Page 16: Research Question
Question: Does the amount of light exposure affect the activity level and color intensity of fish?
Page 17: Formulating a Hypothesis
Hypothesis: If fish are exposed to more light, then they will be more active and display brighter colors.
Page 18: Null Hypothesis Example
Null Hypothesis: If fish are exposed to more light, there will be no difference in activity and color displays compared to fish in low light.
Page 19: Experimental Methodology
Setup: Place two identical fish tanks in different lighting conditions—one near a window, one in a shaded area.
Data Collection: Observe and record fish activity levels and color intensity over two weeks.
Controls: Keep water temperature, food, and tank size constant.
Page 20: Methods Design
Methodology Requirements: Include specific directions, measurements, with minimal jargon for clarity.
Page 21: Data Collection Approach
Daily Measurements:
Activity levels (e.g., number of movements in a specific time frame).
Color intensity (using a color scale or photography).
Page 22: Ethogram Data Sheet for Observation
Behavior Categories for Meerkats:
Play: Engaging in social interactions or chasing.
Look Out: Standing upright, looking for surroundings.
Locomotion: Walking, running, climbing.
Feeding: Digging and consuming food.
Resting: Inactive, lying down or sitting.
Not Visible: Meerkats off exhibit or unseen.
Other: Any behavior not categorized.
Page 23: Analysis Phase
Comparative Analysis:
Assess the activity levels and color intensity differences between the two fish groups.
Determine if there is a statistically significant difference.
Page 24: Conclusive Inferences
Conclusion: Determine whether increased light exposure correlates with heightened activity levels and brighter fish colors, based on data gathered.
Page 25: Related Study Insights
Study Focus: Examined environmental factors like photoperiod and melatonin that influence fish pigmentation and health.
Findings: Varying light conditions impact color intensity due to melatonin level changes linked to light exposure.
Page 26: Hypothetical Results Scenario
Question: What if data showed no significant difference in activity or color between fish in varying light conditions?
Page 27: Recap of the Scientific Method
Visualization of the Scientific Cycle: Reiterates components of scientific investigation.
Page 28: Understanding Scientific Bias
Page 29: Definition of Scientific Bias
Bias Defined: In science, bias refers to systematic deviations between study results and the truth. It indicates a preference that compromises objectivity or influences study outcomes.
Page 30: Scientific Bias in Climate Change Recognition
Cognitive Biases Related to Climate Change:
Causes of Bias:
Motivated cognition, cognitive rigidity, lack of awareness, etc.
Debiasing Tools:
Framing, visualization, inoculation, etc.
Page 31: Bias Summary and Tools
Cognitive Biases:
Attentional, perceptual, recall, confirmation, present, status quo, pseudoinefficacy, single action bias.
Debiasing Tools:
Strategies aimed at reducing bias in climate change communication.
Page 32: Evaluating Sources of Bias
Questions to Consider: Assess author's expertise, data timeliness, funding sources, and presence of confirmation bias.
Page 33: Climate Biases and Policies Overview
Source Evaluation: Consider biases in climate policies such as denial, lukewarm responses, risk management, and proposals for revolutionizing systems.
Page 34: Benefits of Peer Review
Open Peer Review Advantages:
Enhances discussion, reduces bias, improves quality, accelerates discoveries.
Page 35: Peer Review Process Steps
Idea / Theory Formation
Write Manuscript
Submission to Journal Editor
Review by Experts (3-5 reviewers)
Decision: Accept / Revise / Reject
Page 36: Source Skepticism Spectrum
Source Quality Comparison: Peer-reviewed publications considered highly credible compared to biased blogs or general audience articles.
Page 37: Case Study: Theranos
Page 38: Finding Credible Sources
Utilize Google Scholar for accessing articles and case law.
Page 39: Addressing Bias in Writing
Reflection Points: Explore methods to avoid bias, and recognize unavoidable biases when communicating responses to climate change.
Page 40: In-Class Group Activity
Page 41: Lab Requirements
Next Steps: Attend lab day prepared and read the experiment details in advance.
Page 42: Safety Rules in the Laboratory
Arrive on time and prepared.
Conduct assigned experiments only, with permission for changes.
Avoid horseplay.
Know safety equipment locations and usage.
Wear appropriate laboratory attire and safety gear.
Prohibit eating or drinking in the lab.
Handle chemicals with care and follow labeling instructions.
Page 43: Pre-Lab Reminder
Assignment Due: Pre-Lab 1 by September 8.
Page 44: In-Class Data Activity
Data Analysis: Students will collaborate on data from Mauna Loa Observatory.
Page 45: Location Specification
Mauna Loa, Hawaii
Page 46: Temperature Data Overview
Monthly Average Temperature (Degrees C) from 1981-2010: Graphical representation of temperature trends over the months.
Page 47: Hypothesis Development Task
Questions for Further Exploration:
Formulate hypotheses regarding photosynthesis based on collected temperature data.
Design an experiment to test these hypotheses, outlining methods for assessment, particularly in rejecting the null hypothesis.