Module 1.2 Notes: Science Literacy and the Process of Science

Module 1.2: Science Literacy and the Process of Science

  • Fungal Attacker Threatens Bats: Unraveling the Mystery behind Bat Deaths (Edward Kinsman/Getty Images)
  • Focus: Science literacy and the process of science illustrated through a fungal epidemic in bats (White-Nose Syndrome, WNS).

The Nature of Science

  • Science is essential for:
    • Sorting fact from fiction
    • Developing solutions to problems we face
  • Limitations of science:
    • It must quantify observations and test predictions
    • Some questions lie outside the scope of science (e.g., questions about the soul, God, or beauty)

Types of Science

  • Discovery science / Natural History Science
    • Describes and catalogs phenomena without a priori testing of a specific hypothesis
  • Hypothesis-driven science (testing a hypothesis)
    • Starts with a hypothesis and then tests predictions derived from it
  • Example of hypothesis in life science:
    • Example: Cells will divide more rapidly under warmer temperatures

Discovery Science and Cell Theory

  • Discovery Science example focus: observational descriptions that lead to generalizations
  • Historical anchor: Cell Theory (conceptual framework arising from observations by scientists such as Leeuwenhoek)

Types of Science (Summary)

  • Discovery science / Natural History Science: descriptive, observational
  • Hypothesis-driven science: testable predictions and controlled testing
  • Relationship: Discovery science often generates hypotheses that hypothesis-driven science then tests

The Scientific Method: Order and Flow

  • Common simplified sequence (as presented in the material):
    • Observations → ask question → hypothesis → testing → results
  • Alternative phrasing highlighted in class:
    • Observations generate questions, which lead to hypotheses and testable predictions
  • Infographic 1.2-1 (Karr et al.):
    • Observations generate questions
    • Choose a question to investigate
    • Consult literature
    • Develop a hypothesis (H#1) and a testable prediction (P#1)
    • Design and carry out an experimental or observational study to collect data
    • Test new predictions
    • Publish results in a peer-reviewed journal
    • Analyze data
    • Draw conclusions that support (or refute) the hypothesis
    • Society benefits from science and influences which questions are pursued

Peer Review and Publication

  • Importance of Peer Review
  • Process (Taylor & Francis Group):
    • Author submits article to journal
    • Journal Editor screens the paper
    • Reviewer 1 and Reviewer 2 evaluate
    • Editor makes final assessment
    • Possible outcomes: REJECTED, revisions requested, or ACCEPTED
  • Revisions may be required before acceptance

White-Nose Syndrome (WNS): A Case Study in the Scientific Method

  • Had you heard of white-nose syndrome before now? (Poll: Yes / No)
  • The Search for the Cause of White-Nose Syndrome (Case Study):
    • In 2007, thousands of dead bats discovered in New York State
    • Bats were emaciated with white fuzz observed on them
    • Rapid regional and national spread
    • By 2016, ~6 million bats dead
  • The image and description emphasize the case as an illustration of applying the scientific method to a real-world problem

The Culprit: Pseudogymnoascus destructans (Pd)

  • Pd identified as the fungus associated with WNS
  • Quotation from David Blehert: "It was an obscure little fungus, that hardly anyone even knew existed … And it was part of a family that was not known to be pathogenic at all."
  • Questions generated after the discovery:
    1) Where did the fungus come from?
    2) Was the fungus causing the deaths of the bats, or merely correlated with them?
    3) If the fungus was always present and was the cause, why was it only now becoming harmful?

Testing Hypotheses: Variables and Hypotheses

  • Variables (as introduced on the slide):
    • Independent variable: ??? (text partially missing on the slide)
    • Dependent variable: ??? (text partially missing on the slide)
  • Hypothesis (example): The Pd fungus alone can lead to bat mortality
  • What is the dependent variable in this study? (per slide):
    • The presence/absence of the Pd fungus
    • Mortality and presence/absence of white-nose syndrome lesions
  • Prediction (under the hypothesis):
    • Otherwise healthy bats infected with the Pd fungus would experience the same symptoms and mortality as seen in wild populations

Types of Hypothesis Testing: Observational vs. Experimental Studies

  • Observational study

    • Example: Reeder et al. on WNS and torpor in six caves
    • Hypothesis: WNS causes starvation in bats due to increased activity during hibernation
    • Prediction: Bats with WNS will have abnormally shortened torpor bouts due to more frequent arousals
    • Procedure: Track bats in six caves; determine awake vs. asleep via body temperature; compare torpor between uninfected bats and those with WNS (survivors and nonsurvivors)
    • Results (illustrative): Shorter torpor bouts associated with WNS; increased mortality/disease state linked to shortened torpor due to frequent arousals
    • Independent variable: WNS status (infected vs not infected)
    • Dependent variable: Torpor bout length
    • Conclusion: Association between WNS and shortened torpor bouts; higher mortality with WNS
    • Visuals referenced: Infographic 1.2-4

  • Experimental study

    • Example: Warnecke et al. on WNS and torpor in bats
    • Hypothesis: WNS causes starvation in bats due to increased activity during hibernation
    • Prediction: Bats inoculated with WNS fungus will awaken from torpor more frequently than sham-inoculated bats
    • Procedure: Randomly assign bats to Pd inoculation or sham inoculation; monitor torpor length at different hibernation stages; use video to monitor arousals
    • Treatments: CONTROL (sham inoculation) vs TEST (inoculated with Pd)
    • Results (illustrative): Increased arousal frequencies in Pd-inoculated bats, particularly later in hibernation; association with death by starvation
    • Independent variable: Infection status (Pd vs no Pd)
    • Dependent variable: Arousal frequency during hibernation
    • Conclusion: Pd infection leads to more frequent arousals and contributes to mortality through starvation

Experimental Design Terminology

  • Experiment: a controlled test of a hypothesis
  • Variables:
    • Independent variable (the factor deliberately changed or varied)
    • Dependent variable (the measured outcome)
    • Controlled variables (factors kept constant)
  • Experimental treatment: the level of the independent variable applied to treatment group
  • Control treatment: the baseline or placebo condition
  • Sample Size / Replicates: number of subjects and repeats used to ensure reliability
  • Data: recorded observations and measurements

Experimental Design Practice: Frogs with Deformities (Observational and Experimental Design)

  • Observations: Frogs in a pond with deformities; pond near agricultural field; ozone depletion noted in early spring; presence of tiny parasites
  • Experimental Design 1 (practice exercise):
    • a) Identify a hypothesis: Exposure to __ will result in increased incidence of leg deformities in frogs
    • b) Test design: propose test group, control group, life stage (eggs, tadpoles, adults), number of subjects per group, independent variable, dependent variables
    • Note: students are asked to present as a schematic or flow-chart and specify life stages and subjects
  • Observational study design (exercise 2): describe how to determine correlation between a factor and deformities in a few sentences

Experimental vs. Observational Examples: Sunlight and Trematodes

  • Example 1 (Experiment or Observation?):
    • Independent variable: sunlight exposure
    • Dependent variable: % frogs with deformities
    • Example reference: Ankely et al. 2002
    • Methods mentioned: neutral density filters to reduce natural sunlight, Glass to remove UVB, Acrylamide to remove UVB and UVA
  • Example 2 (Experiment or Observation?):
    • Independent variable: trematode density
    • Dependent variable: frequency of frogs with limb abnormalities
    • Example reference: Johnson et al. 1999
    • Graph note: solid line = tadpole survivorship; dashed line = frequency of adults with limb abnormality
  • Example 3 (Scale study):
    • 101 lakes/ponds surveyed
    • Independent variable: trematode levels measured
    • Dependent variable: frequency of deformities
    • Example reference: Johnson et al. 2002
  • Key takeaway: Trematode exposure is associated with limb deformities in amphibians; designs span both observational and experimental approaches

Limb Deformities Induced by Trematodes (Johnson et al. 1999/2002)

  • Visuals and captions indicate a link between trematode infection density and deformity frequency in amphibians
  • The study design involved field measurements across multiple habitats and analysis of deformity incidence

Importance of Statistics in Science

  • Statistics quantify how likely observed differences are due to the tested variable versus chance
  • Certainty is expressed via P-values:
    • If the P-value is below a threshold, commonly P < 0.05, the hypothesis is considered supported
  • The line of reasoning: more evidence across different lines of inquiry increases certainty; absolute proof is not expected in science

Statistics-Based Question (WNS and Torpor Length)

  • Clicker-style question: Based on statistics, how did WNS affect torpor length?
    • 1) WNS significantly reduced torpor length in infected bats that died and those that didn’t die
    • 2) WNS caused no significant reduction in torpor length
    • 3) WNS significantly reduced torpor length only in the infected bats that died (P < 0.05)
  • Answer cue provided in the slide: option 3, with a reported P-value of P < 0.05, indicating a statistically significant reduction in torpor length in the specified subset
  • Note: This reflects how statistics are used to interpret experimental results and determine when effects are meaningful

Theories in Science

  • Definition 1 (scientific use): A set of statements or principles that explain a broad group of facts or phenomena, repeatedly tested, widely accepted, and capable of making predictions
  • Definition 2: Abstract reasoning or speculation (non-scientific use)
  • Definition 3: An assumption based on limited information (conjecture)
  • Question: How is a theory different from a hypothesis?
    • A theory is a well-substantiated explanation that integrates a wide range of observations and hypotheses; a hypothesis is a testable statement that can be tested and possibly refined or rejected

Certainty in Science: Degrees of Confidence

  • Infographic: CERTAINTY IN SCIENCE
  • There are degrees of certainty; more evidence from different lines of inquiry increases certainty
  • Science does not rely on absolute proof; all ideas are open to reevaluation
  • Progression: NO CLUE → HYPOTHESES → SCIENCE → THEORY → ABSOLUTE PROOF (with caveats about the last term in practice)

Other Introduced Fungal Pathogens in Herpetology and Amphibian declines

  • Chytrid fungus (Bd): Batrachochytrium dendrobatidis
    • Associated with widespread amphibian declines (declines in >90% of species/countries in some cases)
  • Bd lineages and global distribution: GPL, ASIA-3, ASIA-1, ASIA-2/BRAZIL, etc. (diverse lineages and geographic origins)
  • Bsal (Batrachochytrium salamandrivorans): notable amphibian pathogen with geographic considerations (e.g., CAPE, CH, etc.)

Chestnut Blight and the American Chestnut

  • Chestnut blight is another introduced fungal pathogen affecting the American chestnut
  • Geographic range of the American chestnut illustrated on a map (Natural Range depicted with latitude/longitude markers)

Map and Geographic Contexts

  • The final slide provides a natural-range map for the American chestnut, including latitudinal and longitudinal markers
  • Interpretive note: range maps help frame how introduced pathogens can affect native species across landscapes

Connections and Takeaways

  • The process of science combines discovery (descriptive observations) with hypothesis testing (predictive, controlled experiments)
  • Important skills emphasized: forming testable hypotheses, distinguishing correlation from causation, designing observational versus experimental studies, and interpreting results with statistics
  • The WNS case study demonstrates how a novel pathogen is identified, tested for causation, and evaluated through both observational and experimental evidence
  • Ethical and practical implications include wildlife conservation decisions, disease management strategies, and policy implications based on scientific findings

P < 0.05