Peanut Butter Club and ECOL 8030

  1. What is Peanut Butter Club? 

Peanut Butter Club takes on two flavors throughout the year. In the fall the club is more informal, covering a wide range of topics. The spring semester is organized around a specific topic and taught as ECOL8030, led by OSE graduate students.

Spring 2024 Edition : Deep Dive into R

This course will be complementary to Rico Holdo’s 8990 course. Rico’s course is an introductory R course covering things like intro to R, data management, data wrangling, data visualization, and other topics. This course will be diving in a bit more and focusing on things like screening abstracts in an R-based GUI for meta-analyses or general reading, a module on mapping in R, dealing with messy data structures, loading multiple (or many) files, etc. One week a month will be an open class time to bring in issues you’re working on in R and work through them with the group.

It will take place on Mondays from 10:20a – 11:10a, on the weeks that Rico’s 8990 does not meet. Rico’s course will meet from 10:20a – 12:50p, five Mondays during the semester. While the two courses are complementary to one another, they do not have to be taken in tandem. Please feel free reach out to Katie Schroeder with any questions.

Spring 2022 Edition: Machine Learning for Ecologists

This course is as a low-stakes seminar course where students survey topics related to machine learning. Topics discussed will include statistical machine learning algorithms, data mining, image processing, and genomic data analysis. Students will develop a familiarity with machine learning and leave with the ability to talk intelligently about the topic and its applications to a wide variety of fields, as well as provide a foundation to anyone who might want to apply machine learning in their own research.

Spring 2021 Edition : Global Geo-Socio Ecologies 

In this course, students will engage with interdisciplinary ecologies and environmental sciences to intentionally explore themes from underrepresented sociobiogeographical and cultural perspectives following continental themes covering Asia, Africa, South & Central America and Oceania.

Spring 2020 Edition : Exploring Representation and Identity within the Sciences

This course is organized around several topics: representation and inclusivity within STEM, institutional/structural inclusivity, and applied inclusivity. Classes consist of in-class lectures and discussion-based inquiry coupled with out-of-class reading material.

Spring 2019 Edition : Meta-analyses in Ecology

This course will provide an introduction to meta-analysis, focusing on biological or ecological questions.  Students will learn the conceptual basis of meta-analysis and gain practical experience in each step in the meta-analysis process.

The course will be divided into two sections.  The first section will be a theoretical overview of meta-analysis, which will take approximately a third of the semester.  This section of the class will take the form of lectures and discussions based on reading material provided before class.  The second two-thirds of the course will focus on the practical aspects of how to conduct a meta-analysis.  In this section, students will learn to use open-source software for meta-analysis (e.g., the metagear and metafor packages in R), and will conduct a meta-analysis group project on a topic of their choosing.  Students will perform all the steps of a meta-analysis by the end of the semester, but will only be required to assemble a preliminary dataset (i.e. extract data from a subset of their primary studies) to analyze and interpret.

The course website will be available once complete.

Spring 2018 Edition

This semester Ecology 8030 is a professional development seminar designed to provide exposure to non-academic career paths and help graduate students position ourselves for jobs (both academic and not). Topics include: CVs, teaching and research statements, interviews, negotiation, work-life balance and more. The course will involve visits from guests from academic and non-academic careers.

Spring 2017 Edition : Data Carpentry for Ecologists

This semester the Odum graduate students will be tackling Data Carpentry for Ecologist. The course will cover introductory material for teaching ecologists how to interact with data including: data structure, database management systems, and programming for data manipulation, analysis, and visualization. It is designed to be used as a flipped university course and also to be useful for self-guided students.

See the course website for more information.

Fall 2016 Edition

It essentially boils down to academics eating lunch together. This is an informal group where we will discuss scientific issues over whatever you brought in for lunch that day.

When? : Fridays, noon in the seminar room 117 (check out the calendar for events)

The lunch will be very adaptable to the needs of folks who come to it. Below, we outline some potential categories for lunchtime fun.

  • Informal discussion of research ideas or ecological issues (including non-research ideas that are of general interest to the Odum community). e.g., Is neutral theory still relevant to ecology, or should we treat it solely as a “null”?
  • “Papers everyone should read” : lead a discussion about a paper you think should be of general interest to ecologists – be sure to include a couple of sentences about why the paper is something everyone should read when you sign up! This will be fairly rare, as these papers need to be big conceptual or methodological advancements. e.g., Anderson, R.M. & May, R.M. (1978) Regulation and stability of host-parasite population interactions (JANE) would qualify if it was before 1980
  • Skills workshops : Do you know something that would be helpful to your fellow graduate students or postdocs? Teach us. e.g., R markdown, Version control with GitHub, SQL, LaTex/BibTex, Slidify, etc.
  • Experimental design/analysis : struggling with a general problem concerning how to design or analyze experimental data? Talk it out over lunch.

If you have any questions, email  Reni Kaul