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Jul 01, 2022
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BI 213Z - Principles of Zoology4 Credit(s)
Survey of comparative vertebrate anatomy, vertebrate evolution, cladistics, and ecology. Skills: dissection, digital documentation, cladogram construction, and mathematical models in biology. Designed for Life Science Majors. College-level writing and math skills strongly encouraged.
Prerequisite: BI 212 and BI 212 with a grade of C- or better or instructor consent. Learning Outcomes Upon successful completion of this course, the student will be able to:
- Use the concept of evolution to describe current populations with potential natural selection pressures
- Define the term species using at least two different definitions. Compare and contrast these definitions for a given real-world situation
- Compare and contrast dissections for internal anatomy similarities and differences across vertebrate examples. Propose evolutionary pressures that caused differences to arise
- Construct a cladogram for the evolution of vertebrates, filling in the key character changes. Hypothesize alternative cladograms and critically analyze these alternatives
- Design and complete a population survey. Identify weaknesses in design and describe limits to sampling. Describe population data using mean and standard deviation statistics
- Build a mathematical model of population growth curves. Analyze the mathematical differences between exponential and logistical growth curves
- Use the Hardy-Weinberg Theorem to predict and analyze population genetics between generations. Describe the limits to the theorem and how the theorem is useful despite these strict limits
- Compare and contrast climate change and ozone depletion. Predict effects of both on populations. Use primary literature to argue for effects
- Analyze and draw conclusions from primary literature
- Analyze and draw conclusions from data in table or graph form
- Locate, evaluate, and utilize appropriate scientific research when predicting outcomes of experiments
- Collect, manage, and share data across multiple sections for a multi-week experiment
- Analyze data from large data sets to support individual hypotheses. Critique limits of data
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