Affiliated Departments & Programs

Drew Kerkhoff joined Kenyon's faculty in 2005 after earning a Ph.D. at the University of New Mexico and completing a postdoc at the University of Arizona. He is a quantitative ecologist whose research is motivated by two key environmental challenges: global change (including climate and land use) and biodiversity conservation. He leads the Kenyon Macroecology Lab, where students use computational and field-based approaches to analyze the distribution and evolution of plant biodiversity and the functional role of Earth's vegetation in the global carbon cycle.

Along with his research, Professor Kerkhoff also works to improve the quantitative, computational and data-intensive components of the biology curriculum, to better integrate writing instruction into science education, and to increase public understanding of evolution, biodiversity and global change.

Areas of Expertise

Scaling and macroecology, plant and insect herbivore communities

Education

2002 — Doctor of Philosophy from Univ New Mexico Albuquerque

1997 — Master of Science from Univ New Mexico Albuquerque

1990 — Bachelor of Arts from Rutgers University

Courses Recently Taught

This course continues the honors research project and gives attention to scientific writing and the mechanics of producing a thesis. A thesis is required and is defended orally to an outside examiner. The letter grade is determined by the instructor and project advisor in consultation with the department. Permission of instructor and department chair required. Prerequisite: BIOL 385 and 497.

This is a basic course in statistics. The topics covered are the nature of statistical reasoning, graphical and descriptive statistical methods, design of experiments, sampling methods, probability, probability distributions, sampling distributions, estimation and statistical inference. Confidence intervals and hypothesis tests for means and proportions are studied in the one- and two-sample settings. The course concludes with inference-regarding correlation, linear regression, chi-square tests for two-way tables and one-way ANOVA. Statistical software is used throughout the course, and students engage in a wide variety of hands-on projects. This counts toward the core course requirement for the major. Students with credit for STAT 116 cannot take STAT 106 for credit. No prerequisite. Offered every semester.