Wildlife conservation decisions are spatial decisions. Where is habitat, where are animals, where can they move, and where should limited protection dollars go? Answering those questions well requires more than a GIS — it requires models that take seriously how organisms use landscapes and how badly we observe them.

This course teaches the modeling toolkit that connects wildlife ecology to conservation planning: species distribution models, occupancy and detection models, resource selection and movement analysis, landscape connectivity, and spatial prioritization. Throughout, the emphasis is on what each model actually estimates, what assumptions it smuggles in, and how to communicate its limits to someone who has to make a decision.

The course is built for students who have ecology and statistics but not necessarily a spatial background. We begin with a three-week on-ramp in spatial data handling in R, and all subsequent analysis is done in R using provided, working code that you modify, extend, and critique. You are not expected to write models from scratch. You are expected to understand what you have run and defend the choices behind it.

The term is organized as a single cumulative project. In week two you choose a species and a landscape, and every module afterward adds a component to a Spatial Conservation Assessment for that species — culminating in a decision brief written for a named agency and reviewed by a panel of your classmates.