4. Lesson 4: Competition Between Populations

Sugat Dabholkar, Kevin Hall, Philip Woods, Connor Bain
Biology, Environmental Science
45-60 minutes
Introductory High School Biology
v3

Overview

Students are introduced to a new participatory computer simulation where each student takes of a critter designer. They design the movement behavior, reproductive behavior, and if their critter is a consumer or predator, and they release a critter into an ecosystem in an attempt to outcompete other populations of critters that other students release into the ecosystem. As a class they investigate whether they can create at least one species of critter, which outcompetes all other species all the time, even as the environmental conditions are changing. They discover that this is impossible. Through discussion, the teacher helps build consensus about how changes in the environmental conditions and interactions affected the success of their population, why different trait combinations have different competitive advantages (different fitness) for survival, and why no single “design” is optimal all the time in a changing environment. This discovery partially motivates the investigation of the evolution WISE project as a future unit of study. In their homework students learn about other major environmental changes that have occurred over the history of life on Earth. They describe why environmental changes would change the competitive advantage for a set of traits in an ecosystem. They predict whether variation in individual attributes would increase the likelihood or decrease the likelihood of some individuals form their population surviving for various populations.

Underlying Pages

Standards

Next Generation Science Standards
  •   Life Science
    • [HS-LS2] Ecosystems: Interactions, Energy, and Dynamics
    • [HS-LS4] Biological Evolution: Unity and Diversity
  •   NGSS Crosscutting Concept
    • Patterns
    • Systems
    • Stability and Change
  •   NGSS Practice
    • Analyzing Data
    • Using Models
    • Conducting Investigations
Computational Thinking in STEM
  •   Data Practices
    • Analyzing Data
    • Manipulating Data
    • Visualizing Data
  •   Modeling and Simulation Practices
    • Using Computational Models to Find and Test Solutions
    • Using Computational Models to Understand a Concept
  •   Computational Problem Solving Practices
    • Troubleshooting and Debugging
  •   Systems Thinking Practices
    • Investigating a Complex System as a Whole
    • Thinking in Levels
    • Understanding the Relationships within a System