Time Schedule:
John M. Marzluff
ESRM 450
Seattle Campus
Covers advanced principles of wildlife ecology such as habitat selection, population viability, and landscape ecology, and illustrates how they apply to wildlife conservation problems with terrestrial, aquatic, and marine wildlife. Students must share costs of field trips. Prerequisite: ESRM 350; recommended: introductory statistics. Offered: W.
Class description
This course is designed to give advanced undergraduates and graduate students entry into the current practices of wildlife ecology and conservation with a focus on forest landscape ecology, processes, and conservation. We will draw heavily from the current primary literature in this field to survey what is evolving and emerging as important theoretical, methodological, and conceptual foundations. • Objectives:1) Introduce you to current thought in the field of wildlife and forest conservation; 2) Immerse you in the primary wildlife conservation and forest landscape ecology literature; 3) Increase your comfort with new ecological paradigms including scale, emergence, disturbance, and patch dynamics; 4) Increase your familiarity with analytical methods to quantify and project landscape change; 5) Increase your understanding of local, regional, and global conservation issues; 6) Improve your ability to work in interdisciplinary settings to solve problems, devise conservation strategies, and plan effectively.
Student learning goals
General method of instruction
Podcasts and powerpoint presentations are on the website so that class time can be devoted to discussion of important topics and student questions.
Recommended preparation
This class requires a solid foundation of understanding in Natural Science Disciplines (including Forest Resources, Biology, Zoology, Environmental Studies, and Comparative Psychology), and quantitative approaches to ecology and conservation (especially basic statistical reasoning and GIS).
Class assignments and grading
Discussion questions, lab exercises to learn software and analyze data, culminating project.
Midterm, class discussion, lab assignments and final project.
