Agronomy and Horticulture Department
Date of this Version
Plant and Soil Sciences eLibrary (PASSeL) Lesson
This module covers the adaptive cycle, which is a conceptual model designed to help humans understand and manage how and why change occurs within common complex systems, such as ecosystems, societies, or economies. The adaptive cycle has four phases characterized by growth, stabilization, collapse, or reorganization. In this module we use the example of the Roman Empire and how its different periods can illustrate the phases of the adaptive cycle. Other examples of the adaptive cycle can be found in aquatic algal blooms, commodity crop markets, and other cultures and societies. The concept of the adaptive cycle is useful for management and decision making as an expansion on traditional ecological theory. Traditional ecological theory assumes that systems organize linearly into a single stable state that can be maintained in perpetuity despite unprecedented human change on local, regional, and global scales, which we now know is not the case in our dynamic world.
Overview - What Will You Learn in This Lesson?
This lesson discusses was the adaptive cycle is and how it relates to understanding and interpreting natural phenomena.
This lesson covers the concept of the adaptive cycle. At the completion of the lesson, you should be able to:
- Outline the general definition and purpose of the adaptive cycle.
- Define the four phases of the adaptive cycle.
- Summarize how the phases of the adaptive cycle interact with each other.
- Give an example of how the phases might appear in a system.
- Illustrate how the adaptive cycle expands on the traditional model of ecological succession.
- Lesson home
- Overview and Objectives
- Introduction - What Is the Adaptive Cycle?
- Description - What Are the Details?
- Concept Use in Management - How Is the Adaptive Cycle Relevant in the Real World?
- Example - Ancient Roman Empire
- Summary - What Did We Learn?
- Quiz Questions
- References and Further Reading
Copyright © 2020 Katharine F. E. Hogan, Conor D. Barnes, Dillon Fogarty, Julie A. Fowler, Jessica E. Johnson, Alison K. Ludwig, and Dirac Twidwell. Used by permission.
This material is based upon work supported by the National Science Foundation under Grants No. DGE-1735362 and 1920938. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.