Fall 2019 - REM 311 D100

Applied Ecology and Sustainable Environments (3)

Class Number: 1423

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 3 – Dec 2, 2019: Tue, 10:30 a.m.–12:20 p.m.
    Burnaby

  • Exam Times + Location:

    Dec 16, 2019
    Mon, 12:00–3:00 p.m.
    Burnaby

  • Prerequisites:

    REM 100 or EVSC 100; BISC 204 or GEOG 215; STAT 201 or 203 or 205 or GEOG 251 or equivalent.

Description

CALENDAR DESCRIPTION:

Students will learn to apply the ecological concepts introduced in prereq courses to applied ecological problems at the population, community, and ecosystem levels of organization. Emphasis will be placed on processes which drive ecological dynamics, on recognizing those processes and dynamics in applied contexts, and on interpreting ecological data. Quantitative.

COURSE DETAILS:

REM 311 builds on the ecological concepts introduced in prerequisite courses to study the ecological processes that govern the dynamics of populations. Students will use quantitative models to examine the role of data, variability, uncertainty, and assumptions in science and decision making. Students will learn how to improve the sustainable use of natural capital by applying scientific data, ecological theory, ecological models, critical thinking, and Adaptive Management to societal decisions. Before the first class, students should install on their laptops the free, online software programs R (https://www.r-project.org/) and R Studio (https://www.rstudio.com/).

COURSE-LEVEL EDUCATIONAL GOALS:

Upon successful completion of this course, students will achieve the following taxonomy of significant learning (Fink, L.D. 2013. Creating significant learning experiences: An integrated approach to designing college courses. Jossey-Bass, San Francisco, California). Course instruction will reflect all taxa of significant learning listed below (i.e., A - F) and the associated Learning Objectives (i.e., 1 - 26). Student assessment will focus on the 15 Learning Objectives under the taxa A) Foundational Knowledge, B) Application, and C) Integration:

A)    Foundational Knowledge:

1.     Recall ecological theory related to foraging, competition, and predation.
2.     Describe the processes that govern the dynamics of populations.
3.     Explain the role of data, variation, uncertainty, assumptions, and quantitative models in science and decision making.
4.     Describe the process of Adaptive Management.

B)    Application:
5.     Link patterns in data to specific ecological models.
6.     Write computer code in R. 3.     Build ecological models.
7.     Interpret the results of quantitative population models.
8.     Apply quantitative population models to decisions about species recovery, resource management, environmental monitoring, and land-use planning.

C)    Integration:
9.     Exhibit critical thinking in problem-solving skills.
10.     Demonstrate how to use R to enter, manage, analyse, and present data.
11.     Demonstrate the use of models for assessing population dynamics.
12.     Explain the implications of ecological dynamics for the sustainable use of natural capital.
13.     Demonstrate how to integrate quantitative models into Adaptive Management to improve decision making.
14.     Outline how Adaptive Management improves societal decisions about the sustainable use of natural capital.

D)    Human Dimension:
15.     Recognise the value of peer review and collaboration for shared learning.
16.     Evaluate how your work ethic reflects your professionalism and character.
17.     Evaluate how your punctuality and engagement reflect your professionalism and character.
18.     Reflect on the ways that data should contribute to societal decisions.

E)    Caring:
19.     Reflect on the accomplishment of learning new topics and improving your knowledge and skills.
20.     Reflect on how your professionalism demonstrates respect for your colleagues.
21.     Reflect on how you can improve the sustainable use of natural capital by applying Adaptive Management to societal decisions.

F)    Learning How to Learn:
22.     Identify techniques and resources that are available to improve your computer programming skills.
23.     Reflect on how you rise to any challenges of gaining new knowledge and new skills.
24.     Reflect on how you rise to any challenges of learning in new ways.
25.     Reflect on the role of practise for continual improvement.  

Grading

  • Assignments 40%
  • Quizzes 20%
  • Mid-term exam 15%
  • Final exam 25%

REQUIREMENTS:

Students will require a laptop in class. The SFU library has free, 4-hr loans of laptops: https://www.lib.sfu.ca/borrow/borrow-materials/laptops-equipment/borrow-laptop.

Materials

REQUIRED READING:

Readings including reports, journal articles, and media articles will be available on Canvas.

Registrar Notes:

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS