Env. Science Course Descriptions

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The following courses required for all environmental science majors.

ENSCI 2XX. Fundamentals of Environmental Science. 

Environmental science is a multifaceted study, covering a huge range of topics and issues, including water, air, and soil quality, plastics and pollution, invasive species, and so much more. In this course, we will focus on asking environmental questions and learning to design the experiments that will answer those questions. This course will use feature sample collection in the field, laboratory experiments, and statistical analysis to tie together the many interdisciplinary aspects of environmental science.

ENVS 101. Our Shared Environment.

This course introduces students to the basic concepts and interrelationships needed to understand the complexities of environmental problems.  The course surveys the characteristics of natural environments coupled with diverse human populations, explores how those systems function and interact, discusses causes and consequences of environmental degradation, and assesses multifaceted solutions to environmental problems.  Students examine these socio-environmental systems through the lens of many disciplines (including natural sciences, social sciences, and the humanities) and frameworks (justice, sustainability, resilience, and limits) to understand the environment and to discover solutions to environmental problems.  The course also highlights the impact of economic over-production, governmental policy, and personal lifestyles, including affluence, as well as the environmental, social, and racial injustices associated with environmental degradation.  The course emphasizes interdisciplinary thinking.

STAT 113. Applied Statistics.

An introduction to statistics with emphasis on applications. Topics include the description of data with numerical summaries and graphs, the production of data through sampling and experimental design, techniques of making inferences from data such as confidence intervals, and hypothesis tests for both categorical and quantitative data. The course includes an introduction to computer analysis of data with a statistical computing package.

GEOL 233. Geographic Info Systems w/Lab.

Geographic Information Systems (GIS) is the use of computers to manage, display and analyze spatial or geographical information. This course introduces students to the basic concepts, functions, and applications of GIS. We discuss maps, data sources and management, and geographic techniques, including global positioning systems, aerial photography and satellite imagery. Through a series of lab exercises students explore the analytical functions of GIS, such as proximity, overlay and three dimensional modeling. To further understand GIS practices and applications, each student develops a GIS project with data appropriate to his or her area of interest. Counts toward the public health minor.

The following courses are examples of recommended labs and electives for the environmental science major.

  • BIO 221 General Ecology, BIO 303 Biostatistics, any Ecosystem related course, and any course with an organismal lab. See Biology Course Descriptions.
  • CHEM 205 Quantitative Analysis, CHEM 223 Organic I, CHEM 306 Environmental Chemistry and Toxicology, and CHEM 356 Environmental Chemistry Lab. See Chemistry Course Descriptions.
  • ENVS 236 Health Effects of Pollution,  ENVS 271 Landscape Ecology, ENVS 309 Taming Trash, ENVS 326 Once and Future Forest, ENVS 329 Adapting to Climate Change, ENVS 336 Living Lab, ENVS 338 Ecology of Agroecosystems, ENVS 360 Sustainable Agricultural Systems, ENVS 369 Ecological Restoration, ENVS 370 Global Amphibian Decline, ENVS 372 Transboundary Wildlife Conservation, ENVS 379 Renewable Energy Systems, ENVS 383 Energy Life Cycle Analysis. See Environmental Studies and Sciences Course Descriptions.
  • GEOL 211 Geomorphology and GEOL 216 Sedimentology. See Geology Course Descriptions.
  • PHYS 242 Climate Systems, PHYS 317 Instrumentation Lab (0.5 units), PHYS 318 Electronics Lab (0.5 units), and PHYS 333 Math Methods of Physics. See Physics Course Descriptions.
  • STAT 213 Applied Regression, DATA/STAT 234 Foundations of Data Science, STAT 313 Advanced Modeling, DATA/STAT 334 Data Visualization, and STAT 343 Time Series Analysis. See Statistics Course Descriptions.