EFB 390: Wildlife Ecology and Management

Syllabus — Fall 2026

Instructor: Dr. Elie Gurarie

  • Office: Illick 206
  • Office hours: Thursday 3:30–4:30 and by appointment
  • Email: egurarie@esf.edu

Teaching Assistants:

Office hours and locations TBA.

Lecture: Tues & Thurs 2:00–3:20, Illick 5

Recitations: - Tues 3:30–4:25 (Baker 310) - Tues 5:00–5:55 (Baker 314) - Wed 3:45–4:40 (Baker 314) - Thurs 8:00–8:55 (Baker 314)

Course Description

This is a broad, foundational course. The overarching goal is to make students familiar with fundamental topics in wildlife ecology and management.

Wildlife ecology is an extremely complex science, that explores themes like population dynamics, behaviors, space use, disease, habitat, trophic interactions, that is studied with a suite of rapidly evolving tools — field observations, advancing technology, statistics and modeling.

Wildlife management places all the complexity of wildlife ecology into a sloppy social, political, historical, ethical and legal realm. Most professional “wildlife” managers will openly admit that they spend much more time trying to manage people.

In this course, we will introduce methods, theories, concepts, and contemporary research topics in wildlife ecology, placing these into the very human inflected context of management.

We will hopefully also get you even more interested in wildlife ecology than you maybe already are! It is my opinion that there is no better or more interesting job than being a wildlife ecologist.

Course Learning Objectives / Outcomes

  • Understand fundamental concepts in wildlife ecology and ecological theory, such as population dynamics, wildlife-habitat relationships, limiting factors, surveying and estimation, wildlife statistics.
  • Develop and hone research skills — especially building a bibliography, understanding and synthesizing peer reviewed literature and grey literature on wildlife ecology and management.
  • Develop some rudimentary skills in R programming and statistical tools for fitting and interpreting commonly used models in wildlife ecology.
  • Learn to establish and maintain a camera trap study.
  • Become familiar with the historical context and current (conflicting) philosophies of wildlife management, how these apply to past, present, and future approaches to wildlife research and management.
  • Become familiar with the human dimensions of wildlife ecology and management including the role of social, economic, and political dimensions through analysis and synthesis of research articles, popular press articles, reports, and other media, and discussions.
  • Synthesize concepts in wildlife ecology, wildlife and habitat management, policy, and human dimensions components to describe, understand, and consider solutions to contemporary wildlife conservation and management challenges, using evidence-based approaches.

College Learning Outcomes

Scientific Reasoning | Quantitative Reasoning | Communication Skills

Technological and Information Literacy (Zotero!) | Basic programming and statistics (R!)

Values, Ethics and Diverse Perspectives | Critical Thinking | Collaborative work

Textbooks and Supplies

There is no required textbook in this class, though a few texts can be recommended. There will, however, be many readings assigned — book chapters, scientific articles, population articles, “grey literature,” some seminal readings. All materials will be made available on the course Blackboard page. All lectures (and other important materials) will be on the course website: https://eligurarie.github.io/EFB390/. Bookmark this page!

Attendance Policy

This course will primarily cover material that does not appear in your assigned readings or other out-of-class materials. Thus, you should make an effort to attend all classes. If you must be absent for a class, consult with me beforehand and make sure to obtain class notes from a classmate.

We strongly encourage you to make sure to come to class prepared. If you come to class consistently, come prepared having completed any assigned reading or viewing, and pay attention, you are highly likely to succeed in learning the concepts and knowledge I am hoping for you to learn and earning a grade you are satisfied with.

In view of the AI policy (see below), there will be occasional assessments or quizzes in recitation, for which attendance will be obligatory.

Also — visit us, all of us, at office hours (or at other times)! We love to talk about this stuff.

Grading Structure

Your grade will be based on 1 (or 2) quizzes, weekly assignments (including several group projects during the semester), and a final major project + final group presentation.

Assignment Grade Percentage
Weekly Assignments 30%
Exams (2) 25%
Final project + presentation 25%
Participation + engagement + quizzes 20%
Total 100%

Academic dishonesty, non-discrimination and inclusive excellence, and others, can be found in the ESF student handbook (https://www.esf.edu/students/handbook/).

Policy on AI Tools

Large Language Models (LLMs) and other generative AI programs (ChatGPT, Claude, Gemini, etc.) are becoming increasingly powerful and accessible. As a practicing wildlife ecologist I do use them occasionally in my work – almost exclusively to speed up routine or tedious tasks, never to write, and never to think. There are real risks to relying on these tools too much. Remember: AI is a tool – like a fussy and often inaccurate calculator – and most definitely NOT a substitute for thought. As an analogy, we are, mainly, no longer hunters and gatherers and could theoretically live a lifetime without exercising any muscles at all. And yet — we chose to move. In a similar way, choose to use your brain! Yes — you can get a result with a single prompt. If you ask it to think for you, there is a large risk that it will simply be wrong, and the result will almost definitely be unsatisfying. Compare to the act of internalizing information and processing ideas, working through them, discussing and sitting on and sleeping on them before — finally, going through the act of articulating and communicating those ideas through writing. With that in mind, the policy in this course will be to:

  1. Be transparent: If you use a generative AI in completing assignments, you must clearly disclose (a) which you used, and (b) what for.
  2. Have higher expectations: Because these tools can accelerate some tasks, the standards for depth, accuracy, and originality in your work will be higher than in past versions of this course.
  3. More in-class assessments: To ensure each student is developing their own skills, a slightly greater portion of your grade will come from in-class assessments (e.g., short quizzes during recitation).

This is a dynamic and rapidly evolving aspect of teaching and learning — we can work together to make the most of these new opportunities.

Tentative Class Schedule

Classes begin Tuesday, August 25. See the academic calendar below for holidays and exam dates.

GL = Guest Lecture, filled out as speakers are confirmed. Recitation topics listed in italics.

Module Date Day Topic
I. Background Aug 25 Tues. Basics and Definitions
Aug 25 Recitation Wildlife in the News
Aug 27 Thurs. Library Science and Research (GL: Moon Library)
Sep 1 Tues. Human-Wildlife History – Part I
Sep 1 Recitation Referencing and Bibliographies
Sep 3 Thurs. Human-Wildlife History – Part II
II. Estimation and Sampling Sep 8 Tues. Counting Animals – Part I
Sep 8 Recitation Survey Methods + Camera Trap Deployment
Sep 10 Thurs. Counting Animals – Part II
Sep 15 Tues. Counting Animals – Sampling Uncertainty
Sep 15 Recitation Strategizing Flag Abundance Estimation
Sep 17 Thurs. Flag Abundance – Field Simulation + Data Entry
Sep 22 Tues. Mark-Recapture + Index Counts
Sep 22 Recitation (no EG) Count data analysis (R lab I)
Sep 24 Thurs. (no EG) Walrus Studies in Alaska (GL: Irina Trukhanova)
III. Ranges and Habitats Sep 29 Tues. Distributions and Ranges | Niches and Habitats
Sep 29 Recitation Wildlife Statistics (R lab II)
Oct 1 Thurs. Modeling just about anything I
Oct 6 Tues. Modeling just about anything II
Oct 6 Recitation AIC Symposium Prep
Oct 8 Thurs. Mega symposium of mini-talks on delta AIC in Wildlife Ecology
Oct 15 Thurs. Forest Management for Wildlife (GL: Andrew Vander Yacht?)
Oct 20 Tues. Exam 1 Review
Oct 20 Recitation (no EG, no SJ) ID’ing, Storing and Managing Camera Trap Data
IV. Populations Oct 22 Thurs. (no EG, no SJ) Exam I**
Oct 27 Tues. Population Growth
Oct 27 Recitation Estimating Population Growth (R Lab 3)
Oct 29 Thurs. Limits to Growth
Nov 3 Tues. Population Structure II (GL: Chloe Beaupré?)
Nov 3 Recitation Structured Populations (R Lab 4)
Nov 5 Thurs. Species Interactions | Wildlife Diseases
V. Models of Management Nov 10 Tues. North American Model of Wildlife Conservation
Nov 12 Thurs. Beyond NAM (GL: Kyle Artelle or Neil Patterson?)
Nov 17 Tues. Mechanisms and Alternatives of NAM (GL: Josh Millspaugh)
VI. Wildlife Management in Practice Nov 19 Thurs. Guest Lecture TBD (Birds | Physiology | Feds | Collections)
Nov 24–26 Tues./Thurs. NO CLASS | NO RECITATION (Thanksgiving Recess)
Dec 1 Tues. Urban Ecology
Dec 3 Thurs. Exam Review
Dec 8 Tues. Exam 2 (last day of classes)
Finals Dec 10–11, 14–15 (TBD) Final Project Presentations

* Date of Exam Review and Exam may change depending on guest speaker availability.

** For the final portion of class, recitations will be devoted to guided progress on final projects.

Important

I retain the right to change anything at any time! In practice this is nearly always to the benefit of the students.

Academic Calendar

Event Date(s)
Classes begin August 24
Labor Day (no classes) September 7
Fall Break (no classes) October 12–13
Mid-term grading October 12–16
Thanksgiving Recess (no classes) November 22–29
Last day of classes December 8
Final Exams December 10–11
Final Exams December 14–15
Grades due December 22

Additional Important Information

Religious holy days: Students who miss coursework due to the observance of a religious holy day will be given the opportunity to complete the work missed within a reasonable time after the absence, provided that the instructor is notified in advance (notify the course instructor at least 2 weeks prior to the class or an exam that will be missed).

Scholastic dishonesty: Students must act with integrity in accordance to ESF’s Code of Academic Integrity.

Common courtesy: Turn cell phones off, put on silent mode, or whatever it takes to keep them quiet. No texting, emailing, etc. during lecture. Please be on time.

Disability Services: SUNY-ESF works with the Office of Disability Services (ODS) at Syracuse University, who is responsible for coordinating disability-related accommodations. Students can contact ODS at 804 University Avenue-Room 309, 315-443-4498 to schedule an appointment and discuss their needs and the process for requesting accommodations. Students may also contact the ESF Office of Student Affairs, 110 Bray Hall, 315-470-6660 for assistance with the process. To learn more about ODS, visit http://disabilityservices.syr.edu. Authorized accommodation forms must be in the instructor’s possession one week prior to any anticipated accommodation. Since accommodations may require early planning and generally are not provided retroactively, please contact ODS as soon as possible.

Diversity and Inclusion: SUNY-ESF values diversity and inclusion; we are committed to a climate of mutual respect and full participation. Our goal is to create learning environments that are usable, equitable, inclusive and welcoming. If there are aspects of the instruction or design of this course that result in barriers to your inclusion or accurate assessment or achievement, we invite any student to meet with us to discuss additional strategies beyond accommodations that may be helpful to your success.