Conservation biology combines ecological and evolutionary principles with resource management, the social sciences, and ethics to understand, manage and maintain biodiversity. This seminar is designed to familiarize students with the questions conservation biologists ask and the methods they use to conserve life on Earth. Students engage in problem-solving exercises that examine conservation-related questions at the genetic, population, community, landscape or ecosystem levels and employ suitable analytical techniques or strategies to address the questions.

This lab course involves field and laboratory investigations of plant ecology, with an emphasis on Northeastern plant species and plant communities. The labs explore interactions between plants and insects, visit wetland and upland habitats, and investigate plant population dynamics at sites around western Massachusetts. Students gain hands-on experience with descriptive and experimental research approaches used to investigate ecological processes in plant communities. Corequisite: BIO 364. Enrollment limited to 20.

This course surveys the environmental factors, historical processes and ecological interactions that influence the distribution and abundance of plant species in the landscape. The class examines how plant communities are assembled and what processes influence their structure and diversity, including past and present human activities. We focus in particular on plant communities of the Northeast, using examples from the local landscape to illustrate key ecological concepts. Prerequisite: a course in plant biology, ecology or environmental science; statistics is recommended (e.g., MTH 220).

Research design and methodology for field and laboratory studies of animal behavior. Prerequisite, one of the following: BIO 260, 272, 362, a statistics course, or permission of the instructor. Enrollment limited to 15 students.

This seminar focuses on neglected tropical diseases (NTDs), parasitic and viral diseases other rare diseases that are a public health concern, including Ebola, Chikungunya, Dengue Fever, West Nile, SARS, avian influenza, malaria, river blindness, anthrax and smallpox. We look at pandemics of the past (the influenza of 1918, the Black Death of the Middle Ages, the typhus epidemic of 1914–21) and modern biotechnology.

This lab will cover genomic analysis pipelines from nucleic acid isolation to sequence analysis in Linux
and R environments. Students will independently design and execute a high-throughput sequencing
experiment to measure genetic variation in natural populations. Prerequisite: BIO 230 or 232. Corequisite: BIO 336. Enrollment limited to 12.

Ongoing developments in high-throughput sequencing technologies have made genomic analysis a central feature of many scientific disciplines, including forensics, medicine, ecology, and evolution. This course will review the scope and applications of genome sequencing projects. After completing the course, students will be prepared to design a high-throughput sequencing project and interpret the results of genomic analysis. Prerequisite: BIO 230, BIO 232, or permission of the instructor. Enrollment limited to 40.

This lab introduces the computational and quantitative tools underlying contemporary bioinformatics. We explore the various approaches to phylogenetic reconstruction using molecular data, methods of data mining in genome databases, comparative genomics, structure-function modeling, and the use of molecular data to reconstruct population and evolutionary history. Students are encouraged to explore datasets of particular interest to them. Prerequisite: BIO 334 (normally taken concurrently), or permission of the instructor. Enrollment limited to 14.

This course focuses on methods and approaches in the emerging fields of bioinformatics and molecular evolution. Topics include the quantitative examination of genetic variation; selective and stochastic forces shaping proteins and catalytic RNA; data mining; comparative analysis of whole genome data sets; comparative genomics and bioinformatics; and hypothesis testing in computational biology. We explore the role of bioinformatics and comparative methods in the fields of molecular medicine, drug design, and in systematic, conservation and population biology.