During the last few decades concern about environmental decline and our understanding of its drivers and consequences have expanded at a phenomenal pace. A concurrent trend in science and society is an increasing awareness of the degree and mechanisms by which the Earth system functions as an interactive whole. Thus, we are increasingly aware that what were once perceived as local environmental problems have significant implications for the entire Earth system and its biota, including humanity. Meanwhile, despite notable and encouraging conservation successes, our most severe and systemic environmental problems continue to worsen at an ever-increasing pace. As participants in the global community, all Earth citizens are well served by an understanding of the scientific principles and anthropogenic forces that underlie our environment and its ever-changing condition. This course is intended to provide this basic understanding from a realistic and objective perspective, and to survey options that may help insure a healthy, habitable environment for the future. Link to class website.

This course provides a foundation for understanding the geographic distributions and temporal dynamics characteristic of Earth's biosphere. We will begin with a section on the development of biogeographic thinking, and consider the placement of the major themes of this course within the guiding principles of the field. We will then turn our attention to abiotic and biotic phenomena that interact to structure the spatial and temporal patterns of life across geographic scales. Abiotic factors include climate, hydrology, energy, geology, geography, and disturbance, which together produce the physical settings within which organisms are able to survive. Biotic factors include physiology, physiognomy, reproduction, dispersal, life-history, and and species interactions, which provide species the means to arrive, occupy and persist in suitable environments.Throughout the course we will cover and apply analytical tools that are used to understand and predict biogeographic phenomena. Link to class website

This course introduces the fundamental elements of the remote sensing process, the properties of remotely sensed data, and digital image processing methodologies. These topics will be covered in the context of a variety of natural resource applications, which involve the inference of Earth surface properties using remotely sensed data. An important goal of the course is to expose students to the range of technical approaches available for extracting surface information from digital satellite data. Students will also be introduced to the statistical and quantitative aspects of remote sensing and image processing methods. An emphasis is placed on remote sensing of vegetation, although those interested in atmospheric, aquatic, or geologic applications will benefit equally and are encouraged to enroll. Link to class website.

This course will focus on a set of common, advanced methods for analyzing a variety of data types and their combinations. Most procedures that are discussed will be put into practice through lab exercises. We will begin with a review of basic concepts, methods, and theory. This section will quickly cover distributions, parameters and estimates, significance tests, point-pattern-analysis, and the background and theory behind these methods. The review section will lead us into common advanced statistical procedures, with an emphasis on estimation, hypothesis testing, model construction, interpretation, and residual analysis. This section will include simple- and multiple regression, one-way- and two-way ANOVA, dummy-variable regression, logistic regression, weighted (spatial) regression, and spatial interpolation. We will then turn to two methods that are powerful exploratory tools, but that do not explicitly allow significance tests of parameter estimates or hypotheses. Data transformations will begin with Principle Components Analysis and progress through a set of Ordination methods frequently used for community classification and gradient analysis in community ecology. Classification and Regression Trees (CART) will be the last scheduled topic for the course. Link to class website.