Teaching

Marine Biology (BSC 3312)

Spring semester (except 2017)

Marine Biology focuses on the organisms that inhabit the 71% of the Earth’s surface that is covered by salt water. The course begins with a look at the geology of ocean basins, the physics of tides and currents, and the chemistry of seawater. Building on that background, we then consider the amazing diversity of organisms that inhabit the sea and their special modifications for living in various underwater environments and interacting with each other. Habitats covered in detail include the deep sea, open ocean, continental shelf, inter-tidal rocky and soft sediment shores, coastal wetlands, and coral reefs. All of the information and ideas covered are integrated as we conclude with discussions of marine fisheries and other human uses and abuses of the sea, as well as creative ways of serving as responsible stewards.

 


Quantitative Methods (BSC 5936)

Fall semester

This is a graduate level course that covers the fundamental concepts and methods of statistical analyses as they are employed in ecology and evolutionary biology. This includes a review of probability theory and distributions, particularly those distributions most commonly encountered in the discipline. The course treats parameter estimation and hypothesis testing in detail, with applications to their most common uses in empirical work. Frequentist, Likelihood, and Bayesian approaches will be compared and contrasted, with an emphasis on their practical and philosophical underpinnings. The course will emphasize the methods students are most likely to encounter in the current literature, with special emphasis on the practical aspects of sampling and experimental design. The course will also examine how biological ideas translate into the collection of data through field exercises in which the class will gather original data (as part of section 0003 – Field QM) and through readings and discussions of current journal articles. I also provide an introduction to R, a free software program for statistics and graphics, and we will be using R to analyze data.