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> Department of Ecology
F&WL
502 - Analysis
of Population & Habitat Data
Fall 2011
Lecture:
1:10-2:00 T, Th (407 Lewis Hall)
Lab: 9:00-11:00 M (407 Lewis Hall)
Course
Description
This course
is designed to provide students with philosophy, theory, and methods of
making valid inferences about animal populations using empirical data
collected from studies of animals and their habitats. The course
focuses on theory and methods of sampling and analysis that can be used
to
- provide
reliable estimates of population parameters,
- provide
valid measures of precision for estimates, and
- relate
parameter estimates to covariates of interest.
Analyses
and inferences will be based on development and evaluation of competing
models that represent hypotheses concerning patterns in the observed
data and, when possible, processes that yielded the observed
data. Thus, the course will seek to give students a better
understanding of:
- model
development and selection,
- how
to make valid inferences,
- the
importance of underlying assumptions of various methods, and
- current
methods, computer-software packages, and literature related to various
types of analyses of population and habitat data.
After
completing the course students should be better prepared to judge the
quality of results and conclusions of population and habitat studies.
Grading
Grades will
be based upon 2 exams (1 given during the term (100 pts) and a
cumulative final exam (150 pts) and 12 lab assignments (10 pts each).
If a student’s score is
close to one of the deciles used for grade cut-offs, then their
performance in class will be considered. If participation was
excellent, the higher letter grade will be awarded.
Syllabus
See the calendar of
topics for lectures and labs. I will adjust the schedule as is
appropriate for the class. I am more interested in having you learn the
key concepts associated with each topic than in slavishly obeying the
syllabus to ensure that we get through everything!
Textbook and Readings
The book by
Williams et al. provides the underlying philosophy of the course and
will be relied upon throughout the course.
Williams,
B. K., J. D. Nichols, & M. J. Conroy.
2002. Analysis
and management of animal populations: modeling, estimation, and
decision making. Academic Press, New York.
Various
additional readings will be assigned to supplement the book and
software documentation. For example in lab, we’ll rely
heavily on Cooch and White (2007), which will serve as an excellent lab
manual for many exercises. The reference for this excellent
electronic book is: Cooch, E., and
G. C. White, editors. 2009. Program MARK: A gentle introduction.
For those of you interested in printing the book, you can save quite a
bit of paper by working with a rotated, double-columned version
of the book that is available here
with a smaller but still legible font size.
Course
Background
This course
is modeled after a similar course taught at Colorado State University
- FW663 -
(originally
by David Anderson and Gary White and most recently by Gary White and
Paul Doherty). I took the first offering of their course in the
late 1980s and have found what I learned in the course to be very
useful. As you will see throughout the course, F&WL 502 takes
advantage of excellent on-line materials used today at CSU in
FW663. F&WL 502 is, however, different in several respects:
(1) our course will spend a bit more time reviewing some basic
statistics; and (2) our course is for 2 fewer credits and thus, will
not cover all the topics that you’ll see on the web site for the
CSU course. By thoroughly learning the material presented in this
course, you will be prepared to learn on your own the additional
materials presented on line for the CSU course.
Today,
several fairly similar courses exist at other universities. These
provide excellent materials that you may find useful. Three excellent
examples are courses by Michael Conroy at
University of Georgia, Barry Grand
at Auburn University, and Mark Lindberg at
University of Alaska-Fairbanks.
An Important Fact
This is an
intensive course and much of the material will require careful thought
if you are to understand it. Students should plan their schedules
for the semester accordingly. Students that are statistically
challenged or computer impaired should expect to spend a large amount
of extra time outside of class on this course.
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