AP Biology

Throughout this course, core scientific principles, theories, and processes governing living organisms and biological systems are studied. The curriculum is organized into Science Practices (skills) and Big Ideas (content).

Science Practices and Skills

Students are expected to develop and apply specific skills throughout the course:

• Concept explanation.

• Analyzing visual representations.

• Determining scientific questions and methods.

• Representing and describing data.

• Performing statistical tests and data analysis.

• Developing and justifying scientific arguments using evidence.

The Four Big Ideas

The content of AP Biology is anchored in four foundational concepts:

• Big Idea 1: Evolution: The process of evolution drives the diversity and unity of life.

• Big Idea 2: Energetics: Biological systems use energy and molecular building blocks to grow, reproduce, and maintain dynamic homeostasis.

• Big Idea 3: Information Storage and Transmission: Living systems store, retrieve, transmit, and respond to information essential to life processes.

• Big Idea 4: Systems Interactions: Biological systems interact, and these systems and their interactions exhibit complex properties.

Course Units and Interconnectivity

The curriculum is divided into eight units, each touching upon multiple Big Ideas:

• Unit 1: Chemistry of Life: Covers Big Ideas $2-4$.

• Unit 2: Cells: Covers Big Ideas $1$, $2$, and $4$.

• Unit 3: Cellular Energetics: Covers Big Idea $2$.

• Unit 4: Cell Communication and Cell Cycle: Covers Big Ideas $2$ and $3$.

• Unit 5: Heredity: Covers Big Ideas $1$, $3$, and $4$.

• Unit 6: Gene Expression and Regulation: Covers Big Idea $3$.

• Unit 7: Natural Selection: Covers Big Ideas $1$ and $4$.

• Unit 8: Ecology: Covers Big Ideas $1-4$.

The Big Ideas in each unit overlap and build upon one another; knowledge gained in early units remains critical for understanding subsequent material.

Defined Academic Task Verbs

Specific verbs define what a student must do to satisfy learning objectives:

• Calculate: Perform mathematical steps to arrive at a final answer. This includes algebraic expressions, properly substituted numbers, and correct labeling of units and significant figures.

• Construct/Draw: Create a diagram, graph, representation, or model that illustrates or explains relationships or phenomena. Labels may or may not be required.

• Describe: Provide relevant characteristic(s) of a specified topic.

• Determine: Decide or conclude after reasoning, observation, or applying mathematical routines (calculations).

• Evaluate: Judge or determine the significance or importance of information, or the quality or accuracy of a claim.

• Explain: Provide information about how or why a relationship, process, pattern, position, situation, or outcome occurs, using evidence and/or reasoning to support or qualify a claim.

  • Explain "how": Typically requires analyzing the relationship, process, pattern, position, situation, or outcome.

  • Explain "why": Typically requires analysis of motivations or reasons for the relationship, process, pattern, position, situation, or outcome.

• Identify: Indicate or provide information about a specified topic without elaboration.

• Justify: Provide evidence to support, qualify, or defend a claim, and provide reasoning to explain how that evidence supports or qualifies the claim.

The Scientific Method

The scientific method is a step-by-step process used to investigate questions, gather evidence, and draw conclusions based on experiments and observations. The sequence includes:

1. Observation: Initial exploration of phenomena.

2. Questions: Asking what causes the observed phenomenon; can it be manipulated for a repeatable experiment?

3. Hypothesis: Forming a testable explanation.

4. Experiment: Designing a study to test the hypothesis.

5. Data: Collecting and analyzing results.

6. Conclusion: Drawing a final determination. This involves comparing expected versus actual results to support or reject the hypothesis or form new hypotheses.

Hypothesis Development and Testing

A hypothesis is a testable explanation for an observation that explains the relationship between variables and what a researcher expects to happen if one variable changes.

• Structure: While often structured as "If… then… (because…)", this format is not mandatory.

  • "If" represents the manipulated variable.

  • "Then" represents the responding variable.

  • "Because" represents an optional explanation.

• Outcomes: Results either support or do not support/refute the hypothesis. One must never state, "The hypothesis is correct."

Statistical Hypothesis Testing

Statistical tests help determine if observed differences between groups are statistically significant or due to chance.

• Null Hypothesis ($H_0$): The hypothesis that there is no effect or no difference between the two groups of data. It assumes observations are the result of chance. It provides a baseline for comparison.

• Alternative Hypothesis ($H_a$ or $H_1$, $H_2$, etc.): The hypothesis that there is a relationship, effect, or difference between groups. It assumes observations are due to a non-random cause. This is usually what the researcher is claiming or studying.

Experimental Design Components

Groups

• Experimental Group: Receives the experimental treatment or independent variable (IV) being tested.

• Control Group: Used for comparison; helps validate statistical analysis and increases confidence in conclusions.

• Replication: At least $3$ trials are needed per group to ensure reliability.

Types of Controls

• Negative Control: A group not exposed to any treatment or exposed to a treatment known to have no effect. This ensures there is no effect when there should be none.

• Positive Control: A group not exposed to the experimental IV but exposed to a treatment known to have an expected effect. This ensures the experimental setup can produce a known effect and provides a reference point for what that effect looks like.

Variables

• Independent Variable (IV): The one factor changed between groups; the manipulated factor. Graphed on the $x$-axis.

• Dependent Variable (DV): The factor that is measured and affected by the IV. Graphed on the $y$-axis.

• Constant (Controlled Variables): Factors kept consistent for all groups to ensure only the IV affects the outcome.

Scientific Practice and Case Studies

Case Study: Monarch Butterflies

• Observation: Monarch butterflies sometimes fly at night near artificial light sources (streetlights).

• Literature Review:

  • Monarchs are diurnal (active by day, resting at night).

  • They have a circadian rhythm (internal clock).

  • They are migratory, using sunlight as a compass.

  • Antennae help track the sun during flight.

  • Proteins needed for flight are processed at night during rest.

• Scientific Question: How does exposure to artificial light at night affect the number of monarch butterflies that initiate flight?

• Example Hypotheses:

  • $H_0$: Exposure to artificial light at night has no effect on the number of monarch butterflies that initiate flight.

  • $H_1$: Exposure to artificial light at night increases the number of monarch butterflies that initiate flight.

Case Study: Hyaluronic Acid (HA) and Skin

• Premise: Researcher suggests small doses of HA promote water uptake in human skin and prevent evaporation.

• Experiment: Creams are tested on $100$ people, comparing skin before and after use.

• Hypotheses:

  • $H_0$: Hyaluronic acid has no effect on skin dryness (no significant difference in hydration before/after).

  • $H_1$: Hyaluronic acid will decrease symptoms of dryness and dehydration.

Case Study: Penicillin Replacement

• Premise: Testing a new antibiotic against Streptococcus pyogenes (which causes pharyngitis and tonsillitis).

• Design:

  • Experimental Group: Bacteria exposed to the new antibiotic.

  • Negative Control: Bacteria with no treatment.

  • Positive Control: Bacteria treated with penicillin (a known effective treatment).

Factors Affecting Experiments

• Manipulation: It is critical to change only the IV to ensure observed changes in the DV are directly caused by that specific manipulation.

• Bias: Bias is a prejudice in favor of or against something. Researchers may design experiments or interpret data based on their desire to prove a specific result.

• Mitigation: To eliminate bias, researchers use blind and double-blind studies.

Concept Check Practice

• Car Washing: If you earn $10$ per car washed, the IV is the number of cars washed and the DV is the amount of money made.

• Stress and Heart Rate: In a study on physical stress, the IV is the level of physical stress and the DV is the heart rate.

• Bird Warning Calls: In a study on rare birds, the IV is the warning call and the DV is the reaction of surrounding birds.

• Fish Speed: In a study on water temperature, the IV is the temperature of the water and the DV is the swimming speed of the fish.

• Ivy Growth: Comparing sun vs. shade, the $H_0$ is that sun has no effect on growth; the $H_1$ is that areas with more sun exposure have increased growth.