Course Syllabus -- WL 720/720L

3 Credit Hours

QUANTITATIVE FISHERIES SCIENCE

South Dakota State University

Fall 2007

Instructor:                 Michael L. Brown                                  

Phone/email:             688-5599/ michael.brown@sdstate.edu

Office hours:             SNP 141B, no formal hours; mornings preferable or by appointment

Lecture:                     SNP 183 (or Crothers Engineering Hall 217), 9:00-10:50 Tuesday

Lab:                           SAG (AgHall) 113, 9:00-11:50 Wednesday

Course Description:  An advanced analytical fisheries course that focuses on quantitative techniques. Emphasis is placed on populations (e.g., recruitment, growth, mortality), and quantitative assessments of communities (e.g., predator-prey interactions) and ecosystems (e.g., biostressors). Suggested background courses include population dynamics, experimental design, and graduate statistics and/or biometry.

This is an analytical, problem-solving course that builds upon the basic principles of fish population dynamics and fisheries management through the application of quantitative analytical techniques and modeling. Emphasis will be placed on population-level parameter estimation and scientific hypothesis testing using a variety of statistical techniques.

Prerequisite Courses:  There are no prerequisites for this course; however, the student should have an adequate working knowledge of fisheries management, population dynamics, research design, and graduate statistics (e.g., regression).

Technology Skills:  A working knowledge of data management, word processing, statistical and scientific graphics software is important.  Additionally, logic skills are more important than math skills in solving statistical problems.

Course Goals:  Upon completion of this course, the student should be:

• Familiar with the contemporary analytical literature.
• Able to apply current quantitative methods used in fisheries data analysis.
• More confident in analytical problem solving and critical thinking.
• Able to more effectively communicate statistical ideas.

Required Text:  Guy, C.S., and M.L. Brown (editors). 2007. Analysis and interpretation of freshwater fisheries data. American Fisheries Society (AFS), Bethesda, Maryland. ($68, AFS member price [8/2007], hardcover only.)

Supplemental Text:  Haddon, M. 2001. Modeling and quantitative methods in fisheries. Chapman and Hall/CRC, Boca Raton, Florida. ($70-79, Amazon.com; CRCpress.com, $71.96 [8/2007].)

Course Format and Instructional Method:  This course will include lectures and discussions of readings composing one, two-hour period each week. Lectures will summarize the high points; ensuing discussions will target relevant topics in greater detail. (A sign-sheet for leading paper discussions will be available during the first class meeting.) This format should provide an interactive environment whereby you gain greater insight as we explore analytical approaches to fisheries data.

The focus of the lab is to advance your analytical and interpretive skills in statistical modeling through practical application. Thus, the lab portion of this course will cover topic-related computer applications and group projects. Statistical Analysis Systems (SAS) and MicroSoft Excel (e.g., add-ins) will be the primary software tools used for lab work.

Expectations and Evaluation:  The primary expectation for this course is that students are fully prepared to interact, communicate openly, and contribute to class discussions and group activities. Even though attendance will not be taken, students are fully responsible for all course content. 

Evaluations will be based on individual discussion/participation (20%), individual lab projects (20%), a mid-term exam (20%), and a group semester project (manuscript 20%, presentation 20%). Grading will be based on the traditional format (i.e., A = 90-100%; B = 80-89%; C = 70-79%; D = 60-69%; and, F <60%.  Point allocation and activity details are as follows:

Activity                                     Points

Discussion (3 @ 30pts)                            90

Discussion participation  (8 @ 5 pts)         40

Lab projects (8 @ 10 pts ea.)                   80

Mid-term exam                                     100

Semester group project:

Presentation (Dec. 4)                100

Manuscript (Dec. 14)                100

Total points                                           510

Discussion: Chapters from Analysis and Interpretation of Freshwater Fisheries Data (AIFFD) and topic papers are scheduled on a weekly basis. I will cover information from AIFFD and lead those discussions. 

Paper discussions (~15 minute) will be student-led.  The primary objectives of these sessions are to stimulate critical thinking, to help you explore and solve problems, and to develop interest in further learning.  Each student will be responsible for providing an oral overview and leading a discussion on three papers during the semester. (I could randomly select a discussion leader at the beginning of a class, but I prefer that leaders be well-prepared.)  Even though you may not be the discussion leader for a given paper, you must have read the material and be prepared to participate.  Discussion leaders may bring an electronic file on a flash drive to facilitate their discussion.

Discussion leaders are expected to be well-prepared and to communicate points thoroughly – synthesis and communication are crucial aspects of graduate education!  You will be rated on preparedness, communication, and time (30 pts). Participation will be individually monitored and scored on a daily basis (i.e., +5 pts  = participant, 0 pts = nonparticipant).

Lab projects:  Primarily, lab work will consist of programming, manipulating data, and interpreting program code and analysis output. Most assignments will result in a concise summary (e.g., methods and/or results and discussion) of the activity, but specific details will be provided for each assignment. I encourage collaboration in problem solving; however, written submissions are to be your own work and must exhibit good writing skills.

Lab assignments will be due by 5:00 p.m. on the Friday following the Wednesday lab.  Late submissions are penalized 1 point per day, unless you receive prior permission for the late assignment.

Mid-term exam:  The exam will include short, essay-like questions that focus on such topics as the scientific process, logic, data analysis and interpretation. Format of make-up exams will be at my discretion. Other details TBA.

Semester group project:  The culmination of your group efforts will be a presentation (40 minutes, including questions) and a manuscript that targets an analytical subject that has not been resolved in the literature.  Presentations will be judged (current AFS judging rubric) by your peers, myself, and other fisheries faculty.  Similarly, I will review (grade) your co-authored manuscript using AFS guidelines.

Tentative Lecture/Discussion Schedule, Topics, and Supporting Documents:

*Discussion Papers (listed in discussion order):

Sept 18:

      Johnson, D.H. 2002. The role of hypothesis testing in wildlife science. Journal of Wildlife Management 66:272-276.

      Anderson, D.R., K.P. Burnham, and W.L. Thompson. 2000. Null hypothesis testing: Problems, prevalence, and an alternative. Journal of Wildlife Management 64:912-923.

      Burnham, K.P., and D.R. Anderson. 2002. Avoiding pitfalls when using information-theoretic methods. Journal of Wildlife Management 66:912-918.

Sept 25 & Oct 2:

      Murphy, B.R., M.L. Brown, and T.A. Springer. 1990. Evaluation of the relative weight (W_r) index, with new applications to walleye. North American Journal of Fisheries Management 10:85-97.

      Blackwell B.G., M.L. Brown, and D.W. Willis. 2000. Relative weight (W_r) status and current use in fisheries assessment and management. Reviews in Fisheries Science. 81:1–44.

      Gerow, K.G., W.A. Hubert, and R.C. Anderson-Sprecher. 2004. An alternative approach to detection of length-related biases in standard weight equations. North American Journal of Fisheries Management 24:903-910.

      Gerow, K.G., R.C. Anderson-Sprecher, and W.A. Hubert. 2005. New method to compute standard-weight equations that reduces length-related bias. North American Journal of Fisheries Management 25:1288-1300.

      Brendan, T.O., B.R. Murphy, and J.B. Birch. 2003. Statistical properties of the relative weight (W_r) index and an alternative procedure for testing W_r differences between groups. North American Journal of Fisheries Management 23:1136-1151.

      Hansen, M.J., and N.A. Nate. 2005. A method for correcting the relative weight (W_r) index for seasonal patterns in relative condition (K_n) with length as applied to walleye in Wisconsin. North American Journal of Fisheries Management 25:1256-1262.

Oct 9:

      Tomcko, C.M., and R.B. Pierce. 2005. Bluegill recruitment, growth, population size structure, and associated factors in Minnesota lakes. North American Journal of Fisheries Management 25: 171-179.

      Vokoun, J.C., C.F. Rabeni, and J.S. Stanovick. 2001. Sample-size requirements for evaluating population size structure. North American Journal of Fisheries Management 21:660-665.

      Maceina, M.J., P.W. Bettoli, and D.R. DeVries. 1994. Use of a split-plot analysis of variance design for repeated-measures fishery data. Fisheries 19:14-20.

Oct 16:

      Mooij, W.M., J.M. Van Rooij, and S. Winhoven. 1999. Analysis and comparison of small samples of length-at-age data: detection of sexual dimorphism in Eurasian perch as an example. Transactions of the American Fisheries Society 128:483-490.

      Alvarez, P., and U. Cotano. 2005. Growth, mortality and hatch-date distributions of European hake larvae, Merluccius merluccius (L.), in the Bay of Biscay. Fisheries Research 76:379-391.

      Katsanevakis, S. 2007. Modelling fish growth: Model selection, multi-model inference and model selection uncertainty. Fisheries Research 81:229-235.

Nov 6:

      Allen, M.S., K.I. Tugend, M.J. Mann. 2003. Largemouth bass abundance and angler catch rates following a habitat enhancement project at Lake Kissimmee, Florida. North American Journal of Fisheries Management 23:845-855.

      Hoenig, J.M., and T. Gedamke. 2007. A simple method for estimating survival rate from catch rates from multiple years. Transactions of the American Fisheries Society 136:1245-1251.

      Maceina, M.J. 2007. Use of piecewise nonlinear models to estimate variable size-related mortality rates. North American Journal of Fisheries Management 27:971-977.

Nov 13:

      Quist, M.C. 2007. An evaluation of techniques used to index recruitment variation and year-class strength. North American Journal of Fisheries Management 27:30-42.

      Bunnell, D.B., R.S. Hale, M.B. Vanni, and R.A. Stein. 2006. Predicting crappie recruitment in Ohio reservoirs with spawning stock size, larval density, and chlorophyll concentrations. North American Journal of Fisheries Management 26:1-12.

      Hansen, M.J., M.A. Bozek, J.R. Newby, S.P. Newman, and M.D. Staggs. 1998. Factors affecting recruitment of walleyes in Escanaba Lake, Wisconsin, 1958-1996. North American Journal of Fisheries Management 18:764-774.

Nov 20:

      Rogers, M.W., M.J. Hansen, and T.D. Beard, Jr. 2003. Catchability of walleyes to fyke netting and electrofishing in northern Wisconsin lakes. North American Journal of Fisheries Management 23:1193-1206.

      Fabrizio, M.C., J. Raz, and R.R. Bandekar. 2000. Using linear models with correlated errors to analyze changes in abundance of Lake Michigan fishes: 1973-1992. Canadian Journal of Fisheries and Aquatic Sciences 57:775-788.

      Isermann, D.A., D.W. Willis, B.G. Blackwell, and D.O. Lucchesi. 2007. Yellow perch in South Dakota: Population variability and predicted effects of creel limit reductions and minimum length limits. North American Journal of Fisheries Management 27: 918-931.

Lab Schedule and Activities:

Academic Freedom and Responsibility Policy:

Freedom in learning. Students are responsible for learning the content of any course of study in which they are enrolled. Under Board of Regents and University policy, student academic performance shall be evaluated solely on an academic basis and students should be free to take reasoned exception to the data or views offered in any course of study. Students who believe that an academic evaluation is unrelated to academic standards but is related instead to judgment of their personal opinion or conduct should first contact the instructor of the course. If the student remains unsatisfied, the student may contact the department head and/or dean of the college which offers the class to initiate a review of the evaluation.

ADA and Academic Dishonesty Policies:

Students are entitled to ‘reasonable accommodations’ under the provisions of the Americans with Disabilities Act (ADA). Information concerning the provisions of the ADA of 1990 and Section 504 of the Rehabilitation Act are available from the Office of Disability Services located in 145 Binnewies Hall. The telephone number is (605) 688-4504, (605) 688-4394 TTD.

Any form of academic dishonesty will not be tolerated.  You are subject to the academic dishonesty policy in the following section.

Department of Wildlife and Fisheries Sciences

Academic Dishonesty Policy

The Department and the University have taken a strong and clear stand regarding academic dishonesty. We believe that it is unethical and unprofessional to present work done by others in a manner indicating that the student/s is/are presenting material as his/her original ideas or work; such activity is academic dishonesty. Plagiarizing or knowingly assisting others in plagiarizing on tests, quizzes, problems, assignments, research papers, theses, dissertations, or other academic activities is unacceptable behavior. All academic work completed by students is expected to be the original work of that individual student, unless permission is specifically granted beforehand by the faculty member for some form of team effort or other format. If students are unsure if a particular activity may be regarded as a form of academic dishonesty they should consult the faculty member before undertaking such an activity.

The University has a policy on academic honesty, procedures for academic grade and dishonesty appeals, and sanctions for such activities. The Student Code has different procedures for undergraduate and graduate students. http://www3.sdstate.edu/StudentLife/JudicialAffairs/StudentCode/Index.cfm

The Department policy described in this handout is intended to attempt to address perceived academic dishonesty violations between the faculty member/s and student/s before Student Code procedures are implemented. This is done because under Student Code procedures the minimum penalty for academic dishonesty is Disciplinary Probation. These added Department steps (Steps 1, 2, and 3 of the Undergraduate Student and Graduate Student Procedures) should not be construed as an attempt to circumvent the Student Code system; both students and/or the faculty member have the option to go directly into that system. The Department procedures portion of this policy is only available to a student one time; any second perceived offense will immediately follow the Student Code procedures.

Graduate Student Procedures

a.     When a student/s is/are determined to have broken the Academic Dishonesty Policy, he/she will be notified verbally by the faculty member involved as to the problem and sanction selected. This is similar to procedures 02:02:01:03 and 02:02:01:04 in the Student Code. The faculty member will do this immediately after the perceived violation occurs. Sanction options available to the faculty member are as follows:

(1)      provide the student/s a grade of zero or some other score on the test, quiz, problem, assignment, or other academic endeavor involved;

(2)      provide the student/s a grade of “F” in the course;

(3)      request that the student/s withdraw from the course;

(4)      request that the student/s change the grading for the course to an “audit;” or

(5)      immediately refer the case to the Student Code procedures.

The sanction selected is at the discretion of the faculty member, based on the seriousness of the situation. The student’s advisor and/or Advisory Committee may be involved (see Student Code 02:05:01:02, 02:05:01:03, and 02:05:01:04).¹

¹The student’s advisor and/or Advisory Committee may be included because items other than class work could be involved.

b.         If the student/s agrees to the sanction proposed by the faculty member the process is completed. The student’s advisor and /or Advisory Committee may be involved (see Student Code 02:05:01:02, 02:05:01:03, and 02:05:01:04).

c.         If the student/s does not agree to the sanction proposed by the faculty member, he/she has the right to appeal the faculty member’s decision. This Informal Phase Appeal should be made directly (both verbally and in writing) to the faculty member involved within five class days of notification or within seven calendar days of notification, if the incident is at the end of the semester.

The faculty member may then modify or leave unchanged the sanction proposed in step 1. A copy of the student’s written appeal and the faculty member’s written response will be sent to the Department Head so that a confidential record to protect the student/s and the faculty member is established. The student’s written appeal and faculty member written response will be secured in the student’s file until graduation or he/she leaves the program; if no further perceived violations have occurred these materials will be purged from the student’s file. The student’s advisor and/or Advisory Committee may be involved (see Student Code 02:05:01:02, 02:05:01:03, and 02:05:01:04).

d.         If the student/s is/are still dissatisfied with the decision he/she can verbally appeal to the Graduate Dean. (These are steps 02:05:01:05, 02:05:01:06, and 02:05:01:07 in the Informal Phase Appeal process described in the Student Code.)

e.         If all agree on the proposed sanction at this point, the process is completed. Up to this point, no one other than the student/s, faculty member, Graduate Dean, and possibly the student’s advisor and Advisory Committee has been made aware of the situation.

f.          If the student/s, faculty member, advisor, or Advisory Committee are dissatisfied with the Graduate Dean’s decision they can enter the Formal Phase (Student Code 02:05:02) of the Student Code process. It is the responsibility of the student/s, faculty member, and student’s advisor and Advisory Committee to be aware of the procedures and penalties involved.