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From Ecosystems To Speciation - Preview

From Ecosystems To Speciation

Subject: Biology
Time: 8-10 classes, 45-50 min each
Level:

Introductory High School Biology


Unit Overview

Students will develop an understanding of how populations interact with each  other within a community, discussing ideas concerning carrying capacity, competition, and interdependence. From there students will use models to explain the connection between genetic drift, natural selection, and speciation.

Lesson 1: Students will gather information from real-world case study (the Isle Royale wolf & moose ecosystem) and develop questions about factors that might be influencing population size changes. 

Lesson 1 Teacher Guide


Lesson 2: Students will look at single population of organisms and investigate how population growth is influenced by limiting factors such as resources. Using this NetLogo model they will be able to visualize some of the factors that lead to the formation of a carrying capacity for organism within a defined area. Students will then simulate how carrying capacity is affected by the introduction of a predator to the system and will also be able to see the dynamic interaction between these two organisms over the course of a large time scale.

Lesson 2 Teacher Guide


Lesson 3: Students will describe how consumer/producer interactions for limited resources necessary for survival leads to the emergence of a competition for those resources, even when there is no intentional effort being made by individuals to outcompete each other.

Lesson 3 Teacher Guide


Lesson 4: Students will explain how populations indirectly compete against each other, by applying the concepts of stability and change in population sizes over time, direct and indirect interactions between individuals, and immediate and delayed outcomes in two different ecosystems, each more complex than those modeled previously computer.

Lesson 4 Teacher Guide


Lesson 5: Students experiment with a population of bacteria growing in an environment with sugar as an energy source. The population of bacteria consist of different types represented with different colors. Different types of bacteria have different number of flagella; however, in this model there is no selective advantage of having more number of flagella. Students explore this model to investigate the phenomenon of genetic drift. They discover that even though there is no selective advantage of having more or less flagella, eventually only one type survives in the population. This happens because of statistical selection, also referred to as genetic drift.

Lesson 5 Teacher Guide


Lesson 6: In this activity students engage in simulated natural selection to discover how natural selection emerges from mechanisms: a) variation in heritable traits in a population and b) interactions in the environment give individuals with some variations a competitive advantage over other individuals. Another purpose  of this lesson is to describe the outcome of natural selection as an increase in the proportion of individuals with advantageous heritable trait variations in a population over multiple generations.

Lesson 6 Teacher Guide


Lesson 7 and Lesson 8: The purpose of the activities in these lessons is to understand how new species can form from old species through the mechanisms of evolution covered so far in the unit (mutation, genetic drift, changes in environmental conditions, and natural selection).

Lesson 7 Teacher Guide         Lesson 8 Teacher Guide

Lessons Overview

1. Lesson 1: Introduction to Ecosystems and Models Overview

Lesson 1 Teacher Guide

Purpose

To teach students to understand biological systems using individual- or agent-level behaviors and interactions.

Prerequisite Knowledge

  • Food is a source of energy and building blocks for organisms
  • Food is necessary for animals to survive
  • Plants make their own food while animals and decomposers must consume other organisms
  • Familiarity with food webs and trophic levels

Lesson Description

Students will use their prior knowledge of food webs to examine the specific ecosystem of Isle Royale.  They will make predictions about how the populations of wolves and moose change over time, and attempt to construct a simple agent-based model based on the ecosystem.

Lesson Outline

  1. Introduction
  2. Think about differences between ecosystems broadly
  3. Think about interaction between populations broadly
  4. Think about Isle Royale broadly
  5. Predictions about wolf and moose populations
  6. Brainstorm rules for the model
  7. Revisiting predictions about wolf and moose populations
  8. Think about how and why models are useful
  9. Wrap-up
2. Lesson 2: Population Dynamics Overview

The Wolf-Moose Predation NetLogo model simulates the interactions between predator and prey within an ecosystem. These systems are looked at as being stable if these populations are able to maintain a relatively steady population over time, whereas an unstable system will result in the extinction in one or more of the populations.

 

3. Lesson 3: Competition Between Individuals Overview

In this lesson, students are introduced to a participatory computer simulation where each student takes the role of an individual consumer (a bug) in an ecosystem. Students make predictions about various model runs and compare their predictions to the outcomes they observe. In one exploration they control the direction of movement of a bug, trying to gather as much food (grass) as possible in a variety of conditions. In another exploration they observe the outcome when many bugs move randomly and blindly around an ecosystem consuming food without any intentional control. Students recreate a physical representation of a histogram graph (of energy levels of bugs) from NetLogo and analyze characteristics of the population in the graph to draw comparisons between populations and individuals. Through discussion, the teacher helps build consensus about what they discovered: Competition is an emergent outcome that results from 1) limited resources necessary for survival, 2) and unequal distribution of those resources throughout the ecosystem, 3) and from interactions (intentional or unintentional) that always are occurring between each individual and their environment. In their homework students address the difference between intentional and unintentional competition further. They critique the modeling assumptions used in the computer simulation. They describe the variation in local resource availability for individuals in the computer model. They calculate how changes in the amount of grass or amount of bugs in would change the average amount of grass per bug in the ecosystem and they identify that ecosystems with lower average grass per bug would have higher levels of competition than those with higher average amounts of grass per bug.

4. Lesson 4: Competition Between Populations 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.

5. Lesson 5: Genetic Drift Overview

Students experiment with a population of bacteria growing in an environment with sugar as an energy source. The population of bacteria consist of different types represented with different colors. Different types of bacteria have different number of flagella; however, in this model there is no selective advantage of having more number of flagella. Students explore this model to investigate the phenomenon of genetic drift. They discover that even though there is no selective advantage of having more or less flagella, eventually only one type survives in the population. This happens because of statistical selection, also referred to as genetic drift.  

6. Lesson 6: Natural Selection Overview

The teacher first introduces the new model. Students then design and perform computational experiments to explore how selective advantage because of different behaviors (due to a physical trait – flagella number) affect the outcomes of natural selection in population of virtual bacteria. Students present their initial results to the class and the class discusses possible explanations for why these different conditions yield different shifts in the distribution of trait variations from natural selection. Groups return to their experimentation and develop their explanations further, and report these out at the end of their experimentation. At the end of class, the teacher develops class consensus on the big ideas regarding the conditions necessary for natural selection and revises the scientific principle from the last lesson.

This lesson uses the same model as the previous lesson of a population of bacteria with different types. However, there are some important differences. In this model, there is an advantage of having higher number of flagella and there is cost associated to having flagella. 

[Note: Computational scientists use variations of a model to study different but related phenomena. Though the model in this lesson looks similar to the one in previous lesson, it has important differences.] 

7. Lesson 7: Adaptive Radiation in the Galapagos Overview
  • A new trait might grant individual(s) a competitive advantage for survival and/or reproduction in an environment (an adaptation), or a competitive disadvantage, or neither.
  • Advantageous traits tend to accumulate in populations over many generations yielding a population progressively better adapted to survive and reproduce in that environment over time.
8. Lesson 8: Mechanisms of Speciation Overview

Purpose: The purpose of this activity is to understand how new species can form from old species through the mechanisms of evolution covered so far in the unit (mutation, genetic drift, changes in environmental conditions, and natural selection).


Connection to previous activities: Students refer to the mechanisms of mutation (introduced in the last activity), genetic drift (from the activity before that), changes in environmental conditions and natural selection (from two previous activities), to develop the explanations for the outcomes in this activity.


Learning Performances

• Analyze data from a computer investigation applying concepts of statistics and probability to explain why adaptations for reproductive isolation can help reinforce specialized adaptations for survival for different niches within different gene pools in a population. [Emphasis is on analyzing shifts in numerical distribution of traits in a histogram and using these shifts as evidence to support explanations.]


Scientific Principles Discovered in This Activity:

• New species emerge from old species (a group of organisms that is capable of interbreeding only between each other to produce fertile offspring).

• Speciation can occur when specialization for survival in different niches is available to a population; this specialization opportunity can tend to reinforce adaptations that lead to greater reproductive isolation between those populations.

• Speciation can occur when geographic isolation leads to separate populations that through mutation and genetic drift, develop genes and corresponding traits that make descendent from each population less reproductively compatible with each other over time.


Description of the Lesson

The class revisits their definition of a species and discusses whether genetic drift alone could account for why new species emerge.

They then use a computer model of plants in an ecosystem to explore how speciation always could also emerge from a single population over time under certain conditions.

Through discussion, the teacher helps build consensus about why speciation might occur when mutation initiates the pathway to speciation, but natural selection and adaptation are the driving mechanisms that continue to reinforce the emergence of this outcome.

In the homework, they study examples of how speciation has been created in laboratory conditions with human intervention and contrast the mechanisms at work in real world ecosystems when new species emerge. And they read Darwin’s finches on the Galapagos Islands as a real-world example of adaptive radiation.

Compatible With


mac

windows

laptops

chrome books

phones

tablets

Standards

Next Generation Science Standards
  • Life Science
    • [HS-LS4] Biological Evolution: Unity and Diversity
    • [HS-LS2] Ecosystems: Interactions, Energy, and Dynamics
  • NGSS Crosscutting Concept
    • Patterns
    • Systems
    • Stability and Change
  • NGSS Practice
    • Using Models
    • Conducting Investigations
    • Analyzing Data

Computational Thinking in STEM
  • 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
  • Data Practices
    • Analyzing Data
    • Manipulating Data
    • Visualizing Data
  • Systems Thinking Practices
    • Investigating a Complex System as a Whole
    • Thinking in Levels
    • Understanding the Relationships within a System

Acknowledgement

CODAP is developed and built by The Concord Consortium at https://codap.concord.org/  

Lesson 7 is based on the lesson Evolution in Action: The Galápagos Finches Authored by Paul Strode for Howard Hughes Medical Institute based on data collected by Peter and Rosemary Grant, Princeton University.

This work is supported by the National Science Foundation (grants CNS-1138461, CNS-1441041 and DRL-1020101) and the Spencer Foundation (grant 201600069). Any opinions, findings, conclusions, and/or recommendations are those of the investigators and do not necessarily reflect the views of the funding organizations.

Comments, Feedback, and Questions

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Lesson 7: Adaptive Radiation in the Galapagos


The purpose of this activity is to discover how the combination of mutations, natural selection, and environmental change generate progressively better-suited adaptations.