Courses/presentations

New for Spring 2023: Ecological Diversity and Climate Change (Environ 623/323, spring 2023)

Evaluate the science of biodiversity and climate change, including changes happening now, in the past, and what we can expect in the future. The issues are focused by three contrasting case studies, including the field trip to Kruger National Park, South Africa, during spring break. Topics include woodland diebacks, intensifying drought, increased wildfire, insect and pathogen outbreaks, and poleward migrations of populations. We take a food-web approach, considering how species interactions respond dynamically to global change. Class activities include lectures, working group collaborations, class discussions, and the field trip. Analytical tools used to quantify change include data manipulation in R, including data sets collected during the course. Examples include population size and growth, regression, GLMs, and species distribution modeling. Prerequisites: statistics.

Bayesian Inference for Environmental Models (BIO/ENV 665, 2023)

Application of environmental models and applications to data using Bayesian analysis. Provides the basic distribution theory needed for model building and algorithm development. Computation is done with the language R. Applications include physiology, population growth, species interactions, disturbance, and ecosystem dynamics. Discussions focus on classical and current primary literature. Prerequisite: one semester each of stats, calculus

Schedule and links for 2022:scheduleENV665

biodiversity sampling demos on youtube

previous years:

data files from lab manual

Environmental Change in the Big Data Era (ENV 89S, spring 2023)

What are the changes happening now and where are they leading us? This course combines key topics in climate change, biodiversity, and big data, examining scientific issues, their importance for the public at large, and how well we understand them. 89S courses focus on student discussions. In this case, discussions consider a combination of scientific literature, contemporary media, and analysis of data.