TOPICS: NUMERICAL APPROACHES TO PROBLEM SOLVING IN ENVI SCI in Spring 2020 (SC2091)

Environmental Science is a highly interdisciplinary field, which means scientists must draw from a number of resources to solve environmental problems that arise. A conservation biologist may need to decide what is a critically low population size that puts an endangered species at risk of extinction. A parks manager may need to decide how much fertilizer in the land surrounding a recreational lake puts that lake at risk of developing toxic algae blooms that can decimate fish stocks. A forest warden may need to decide how many nesting sites are needed to maintain a breeding population of owls that inhabit that forest.

This course will help students learn quantitative skills to aid decision making in Environmental Science. The course will make use of (i) reading scientific literature, (ii) learning to input, manage, and analyze data in the statistical programming language R, and (iii) creating visualizations of data to aid communication with decision makers. The course will focus on a series of case studies where students can read about the problem, learn models or numerical techniques that were used by decision-makers, work with real data sets to implement models and analysis methods, and produce reports describing the results of the analysis and providing visual aids to communicate those results. Working with datasets is an important focus of the class, and students will work on statistical programming during and outside of class.