Course Description

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Ecological modeling will provide a comprehensive overview of the modeling of ecological systems to include biological and environmental systems. The class will provide an in-depth exploration of the methods used for modeling ecological and environmental systems with an emphasis on system dynamics and agent-based modeling. We will examine concepts of complex systems, including emergent properties, nonlinearities and feedbacks between system components. We will utilize the system dynamics software Stella and the agent-based programming language Netlogo.

This course is an online hybrid class. We will meet one time a week virtually to review that weeks' material, address questions, review assigments and solutions. This will be a reading intensive class where students will learn by doing. There will be weekly reading assignments and modeling exercises through which students will learn the modeling process and associated computer languages and software.

Course Requisites or Co-requisites

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This is course is crosslisted as PBIO 3990 for undergraduates and PBIO 5940 for graduate students with different assignments and expectations. Pre-requisites include a general ecology class for PBIO 3990 and graduate level standing for PBIO 5940.

Course Goals & Structure

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Learning Objectives. After completing this course, the student will be able to

1. Describe system feedbacks, emergence, and other properties of complex ecological and environmental systems.
2. Describe the fundamental properties of systems and system dynamics modeling.
3. Describe the structure and characteristics of agent-based models.
4. Apply system dynamic and agent-based modeling approaches to model ecological systems and their relationship to the climate and human components of the Earth system.
5. Construct models of ecological and environmental systems, analyze the model, and produce a description of the model and its behavior.

Class Structure. Students will achieve course objectives through readings and assigned media, online discussions and model-building exercises. Completing readings and assigned exercises, participating in online discussions, and reviewing weekly solutions to assigned exercises will be critical to achieving class learning objectives.

1. Readings. This class will be reading intensive with weekly assigned readings from course texts and other sources. The readings will provide fundamental information on the modeling process.

2. Online discussions. Students will examine and analyze the concepts presented in the readings and other assigned media through online discussions. Here is more information on the online discussions.

3. Exercises. Weekly exercises will be assigned based on readings. These exercises will be a primary means to learn modeling concepts and to become proficient in the programming platforms Stella and Netlogo. Reviewing weekly solutions to assigned exercises is a critical component of the learning process.

4. Learning Assessments. Weekly quizzes will assess student understanding of assigned readings and a cumulative final exam will assess student understanding of course content. Here is a more detailed description of the quizzes.

5. Media. Videos and other media that reinforce and supplement the readings may be assigned as appropriate. These may include full length documentaries, shorter video presentations, and podcasts. The online discussions and learning assessments will integrate material from these media.

6. Undergraduate Student Modeling Project . Research paper. Undergraduate students will construct, parameterize, and analyze both an SD and ABM model of an ecological, environmental, or natural system, and produce a video presentation of their model. These will be team projects, with teams consisting of ~3 students, with a single video presentation for each team.

7. Graduate Student Modeling Project. Graduate students will construct, parameterize, and analyze both an SD and ABM model of an ecological, environmental, or natural system, and produce a video presentation of their model. These will be team projects, with teams consisting of ~3 students, with a single video presentation and report for each team.

Grading

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Student grades will be based on the following components:

Grading scale:

Grades less than 70 are considered failing for graduate students.

Text Books

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Students will be assigned readings from the following set of books (below). These books will be required for this class and are available in the university bookstore or from the publisher or other online sources as hardcopies or ebooks.

1. Steven F. Railsback and Volker Grimm. 2019. Agent-Based and Individual-Based Modeling: A Practical Introduction, Second Edition. ISBN 9780691190839. Link to book.
2. Ford, Andrew. 2009. Modeling the Environment, Second Edition. Island Press. ISBN: 9781597264730. Link to book
3. Meadows, D.H., 2008. Thinking in systems: A primer. Chelsea Green Publishing. ISBN: 9781603580557. Link to book.

Grades less than 70 are considered failing for graduate students.

Software

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We will use two software packages: Stella and Netlogo.

1. Stella. We will build system dynamics models in the graphical programming language Stella created by ISEE Systems. This will require a semester student license for the Stella software at a cost of $59. You should receive an email from ISEE with instructions for purchasing and accessing Stella at the beginning of the semester. Below are some resources for working with Stella.

2. Netlogo. We will build agent-based models in the programming language Netlogo. Netlogo is a free, open source language. Below are some resources for working with Netlogo.

Policies

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• Academic Honesty and Plagiarism
• Student Learning Accomodations
• Academic Integrity
• Religious Holidays