Courses taught

Fundamentals of Ecology (EVSC 3200)
Next taught in Spring 2021

Ecology is the scientific study of the relationships among organisms and their environments. Among the primary goals of ecology are to understand the distribution and dynamics of life in all its complexity, how living organisms relate to one another, and how they interact with the non-living world (atmosphere, geosphere, hydrosphere). In this course, we cover all of the foundational aspects of ecology, including evolution (e.g., adaptation, life history, ecological genetics), biogeography, population dynamics, community ecology (e.g., species interactions, succession, biodiversity, infectious disease), ecosystem ecology (e.g., energy flow, nutrient cycling, biogeochemistry), and interactions between humans and the biosphere (e.g., anthropogenic impacts, sustainability, conservation, climate change).

Spatial Ecology (EVSC 4170 / EVEC 7170)
Next taught in Spring 2022

Our world is fundamentally structured by the interactions of organisms across space. Understanding how spatial processes influence species abundances, distributions, and interactions is a fundamental and enduring challenge in ecology. Knowledge of spatial dynamics is also key to solving ecological problems such as conserving biodiversity in fragmented landscapes, designing effective reserve networks, minimizing the spread of biological invasions, and stopping infectious disease outbreaks.

In this course, we explore how spatial patterns and processes influence ecological systems across a broad range of biological organization that includes genes, populations, communities, and ecosystems. Our discussions take us across a variety of habitats, from mountaintops to the open ocean. We also learn about the central role of humans in altering the spatial ecology of the biosphere and the consequences of spatial ecological processes for human wellbeing. 

Advanced Ecological Data Analysis (EVSC 5040)
Next taught in Fall 2022

Ecological and environmental data are often messy, failing the assumptions of classical statistical models and challenging our ability to glean clear interpretations. This course explores the many types of complex data structures that are common in observational and experimental environmental science, such as non-linear effects, heterogeneity of variance, nested data, non-independence (e.g., spatial and temporal correlation, autocorrelation due to repeated measurements), missing data, truncated data, data with non-normal distributions (e.g., count, binary, proportional, Poisson), zero-inflation, and mediating covariates. Students will be provided with an introduction to implementing several types of advanced statistical models using R, such as generalized least squares models (GLS), linear mixed-effects models (LMM), generalized linear models (GLM), generalized linear mixed-effects models (GLMM), generalized additive models (GAM), and generalized additive mixed-effects models (GAMM).

Coastal Ecology Seminar (EVSC 7122)
Next taught in Spring 2022

An exploration of contemporary topics in coastal ecology through readings, discussions, and critiques of primary literature.