About Short Courses
Short courses offer participants an opportunity to learn new skills through interactive instruction and hands-on training in a live video session. Short courses require advance signup and an additional fee. Short courses may include some uploaded materials available in advance, such as slides, prerecorded videos, and handouts. These materials will only be available to attendees who have signed up for the short course. Most short courses are 3 hours long. Two short courses (SC 1 and SC 5) include 6 hours of instruction time with an additional 30 minutes for break time included.
Short Course 1
Introduction to Bayesian and Hierarchical Bayesian Modeling Applications in Ecology
7:00 AM – 1:30 PM Pacific Time
This 6 hour short course includes a 30 minute break in the middle.
Ecologists increasingly rely spatially, temporally, or hierarchically variable data. Contemporary ecological problems require synthesis of multiple, often incomplete data sources, arising from mixtures of nonlinear and/or non-Gaussian processes. Hierarchical Bayesian statistical methods are powerful tools for analyzing disparate, large, and/or complex data sets.
While “canned” R packages are becoming available for performing traditional analyses within a Bayesian framework, a key advantage of Bayesian methods is custom model building. User-designed models enable flexible incorporation of experimental design, theory, and/or prior system knowledge. Creative, iterative model building is a key way to learn about the structure and functioning of your ecological system.
This short course covers introductory level Bayesian modeling. We will demonstrate the use of JAGS (freely available Bayesian software package), and discuss alternative model fitting software (e.g. Stan). Thus, participants should have some familiarity with R (e.g., for loops, list structuring, indexing).
Participants will develop and implement a Bayesian model based on a selection of data-motivated example problems. These examples will familiarize participants with different data structures or analysis techniques relevant for addressing ecological problems.
By the end of the short course, participants will understand the fundamentals of Bayesian modeling and implement basic hierarchical models. We will provide reference materials so participants can explore these topics in greater depth on their own. These materials should serve as a starting point for those interested in employing or further developing their skill in Bayesian methods.
A half day short course to introduce attendees to Bayesian statistical inference and model-building in ecology, covering the motivation, some of the underlying theory, and hands on examples to gain exposure to some of the key software. Reference materials to further explore Bayesian topics after the short course will be provided.
Drew Peltier – Northern Arizona University, Department of Biological Sciences
Jessica Guo – University of Arizona, College of Agriculture and Life Sciences
Robert Shriver – University of Nevada-Reno
Short Course 2
Science Policy 101: Survival in and Dynamics of the Congressional Ecosystem
7:00 AM – 10:00 AM Pacific Time
Congress is an ecosystem unto itself with different communities on each side of the Hill (Senate and House of Representatives), different populations within those communities, odd mutualistic relationships, and competition (for votes) to avoid extinction (losing reelection). This short course will provide an overview of how Congress works and how to frame a message for different members of Congress. Short course participants will use their own research and the tips learned during the morning to compose a 1-minute pitch for a member of Congress. As we craft talking points and pitches together, we will also walk through resources for uncovering what your member of Congress cares about, how to connect with her/him/them, start a conversation to share a message as a constituent, and build a relationship. Afterward, you will be invited to submit your 1-minute pitch to our ESA Policy Pitch Contest on YouTube for a chance to win a prize!
Ever wanted to meet with your member of Congress but weren’t sure how? This short course will guide you through the Congressional ecosystem to provide you the context, tools and words to prepare you for any interaction, with a focus on creating a 1-minute pitch for a member of Congress.
Charlotte Levy – University of Massachusetts, School of the Environment
Emily Graves – University of California, Davis, Environmental Science & Policy
Caroline E. Ridley – US EPA, Center for Public Health and Environmental Assessment
Sarah M Anderson – USDA Forest Service
Theresa Burnham – San Diego State University
Skylar Bayer – Maine Sea Grant
Short Course 3
NEON Biodiversity: Explore and Work with NEON Organismal Data
7:00 AM – 10:00 AM Pacific Time
The National Ecological Observatory Network (NEON) provides open ecological data from 81 locations across the United States. NEON data cover a wide range of subject areas within ecology, including organismal observations, biogeochemistry, remote sensing, and micrometeorology. This short course will focus on NEON biodiversity data. Instruction will include an overview of the breadth of NEON organismal data before providing code-along instruction on how to convert NEON organismal data into standardized formats for use with a variety of R packages commonly used to calculate standard biodiversity metrics. Examples will include Jost (2007)-style alpha, beta, and gamma diversity using the vegetarian and/or iNEXT packages; alpha, beta, and gamma variability using the ltmc package; and ordinations using the vegan package. Additionally, participants will learn about interoperability with the ecocomDP data format developed by the Environmental Data Initiative (EDI) and data discovery and visualization tools available in the ecocomDP package (https://github.com/EDIorg/ecocomDP). At the end of the short course, time will be reserved for participants to work with the NEON data of their choice with instructors present to address any questions that arise while working with the individual data sets. Basic familiarity with R is required for participation in the short course.
This short course does not provide a general overview of NEON data, nor the details of different ways of accessing NEON data. If you are interested in these topics, we recommend attending the “NEON Data Skills: Access and Work with NEON data” short course instead of, or in addition to, this one.
This short course will provide participants with an overview of NEON biodiversity data products, instruction on how to import the data into an R session, and guidance on how to convert imported data to formats that can be used in standard community ecology data visualizations and analyses.
Eric R. Sokol – Batelle, National Ecological Observatory Network (NEON)
Donal S. O’Leary – National Ecological Observatory Network, Education
Short Course 4
Strategies for Incorporating Diversity, Equity, Inclusion, and Social Justice into Ecology Curricula
7:00 AM – 10:00 AM Pacific Time
Incorporating and addressing the human dimension of ecology in undergraduate and graduate courses better prepares students to tackle the complex ecological problems we face in the Anthropocene. Research in ecology demonstrates that highlighting the contributions of individuals from all backgrounds in our courses tells students that their diverse perspectives, cultures, languages, and identities bring valuable assets to ecology. But how can we thoughtfully integrate the social justice components of ecology in our courses? Considering the recent calls to discuss the intersectionality of social justice and science, this is a charge all educators are currently facing.
In this short course, participants will meaningfully integrate inclusive and social justice pedagogy in their curricula, workshop a syllabus to incorporate inclusive curricula, and leave with tangible lesson plans that explore the intersection of social justice and ecology. This interactive virtual short course will integrate active participation using breakout rooms, polls, surveys, individual activities, and the exploration of resources that will be provided. Instructors will model a short example lesson in ecology that also addresses social issues, then participants will have the opportunity to work in small groups to share ideas and approaches for incorporating the human dimension of ecology into lessons and syllabi. Participants will have an option to join a listserv of people working on inclusive pedagogy practices.
After this short course, participants will be able to:
- Describe elements of inclusive pedagogy
- Explain why inclusive pedagogy is important in ecology
- Integrate inclusive pedagogy practices into their courses
In this short course, participants will gain experience describing elements of inclusive pedagogy and its importance, and practice incorporating social justice elements into their lessons and syllabi.
A.M. Aramati Casper – Colorado State University
Mallory M. Rice – San Francisco State University
Allyson Salisbury – The Morton Arboretum
Laura Nunes – UW-Madison
Short Course 5
Quantitative Analysis in Plant Community Ecology using R
10:30 AM – 5:00 PM Pacific Time
This 6 hour short course includes a 30 minute break in the middle.
This session will introduce participants to fundamental and selected advanced analytical approaches commonly used in plant community ecology. Topics include both univariate and multivariate approaches, specifically: calculating community diversity metrics, distance and dissimilarity measures, transformations, and the applications of direct and/or indirect ordinations, cluster analysis, indicator species analysis, non-parametric multivariate statistical tests for differences between groups, and data visualization. Short course participants will use one core dataset in an interactive format to practice analytical methods using R (https://www.r-project.org/), an open-source statistical software widely and increasingly used by ecologists. Participants will be exposed to a variety of R packages and functions, and all data, code, and supporting documents will be made available prior to the short course to enhance learning. All participants who have not used R previously will complete a short tutorial beforehand. The short course is co-organized by the executive committee of the Vegetation Section, and the organizing committee represents ecologists from different genders, backgrounds, career stages (student to Associate Professor), and career pathways (academic to government). One goal is to provide opportunities for students and early-career vegetation ecologists from diverse backgrounds to gain important quantitative skills that will accelerate their professional development. As such, the Vegetation Section will cover the costs of the short course for 5 to 10 student and early career participants (depending on final short course costs) and will prioritize funds for applicants from groups currently underrepresented in ecology.
This course explores cutting-edge techniques in R that will let participants answer important questions in plant community ecology. We will investigate species, traits, phylogenies, spatial patterns, and environmental responses of communities using univariate and multivariate approaches. This includes diversity metrics, ordination, clustering, phylogenetic and trait analyses, and data visualization.
Kyle Palmquist – Marshall University, Department of Biological Sciences
Martin Dovciak – State University of New York College of Environmental Science and Forestry, Department of Environmental Biology
Samuel Jordan – Arizona State University, School of Life Sciences
Lisa Kluesner – US Forest Service, Wayne National Forest
Robert J Smith – US Forest Service, Pacific Northwest Research Station
Short Course 6
Managing Ecological Data for Effective Use and Re-Use
10:30 AM – 1:30 PM Pacific Time
While graduate students in ecology learn about methods for collecting and analyzing ecological data, there is less emphasis on managing and using the resulting data effectively. This is an increasingly important skill set as the research landscape changes. Researchers are increasingly engaging in collaboration across networks, many funding agencies require data management plans, journals are requiring that data and code be accessible, and society is increasingly expecting that research be reproducible. Ecologists can maximize the productivity of their research program with good data skills, in that they can effectively and efficiently share their data and other research products with the scientific community, and potentially benefit from the re-use of their data by others.
The purpose of this short course is to give attendees an introduction to a set of practical tools for organizing and sharing their data through all parts of the research cycle. The target audience is early-career scientists but is open to any researcher who would benefit from developing better data management skills. Topics will include data organization, data documentation, and the importance of good data management practices for data sharing, collaboration, and data re-use. The short course will be an interactive combination of presentation, discussion and activities. Participants must bring their own laptop to work on exercises.
Learn to organize and share your data through all parts of the research cycle. Topics include data organization, data documentation, and the importance of good data management practices for data sharing, collaboration, and data re-use.
Jeanette Clark – University of California, Santa Barbara, NCEAS, Arctic Data Center
Amber Budden – University of California, Santa Barbara, NCEAS
Matthew B. Jones – University of California, Santa Barbara, NCEAS
Erin McLean – Arctic Data Center
Short Course 7
Bringing Computational Data Sciences to Your Undergraduate Ecology Classroom
2:00 PM – 5:00 PM Pacific Time
The biological and environmental sciences have been rapidly and fundamentally reshaped by recent technological advances, including increased computational power, sensor technologies, publicly available software and data, and Internet connectivity. These advances, together with the demands that we provide our students with technical skills to navigate data and technology in the 21st century, necessitate the integration of computational data sciences into our undergraduate and graduate classrooms. However, many instructors do not feel qualified or prepared to teach such materials, either for lack of technical skills or pedagogical training, limiting the usefulness of already developed computational course or lab modules. This “train the teachers” short course will include both technical training for fundamental data science skills, including R and Markdown, and pedagogical training for communicating those skills in the classroom and lab. Working through data science examples in-real time, participants will experience the material as a learner and gain strategies toward including and being able to teach these skills in their own courses. Participants will also learn and practice the use of pedagogy techniques, such as backwards design, to envision how data science can be integrated within their courses. The goal is to equip instructors with technical tools and instructional strategies that they can then confidently customize to their own curricular goals and institutional needs.
This “train the teachers” short course will include technical training for fundamental data science skills and pedagogical training for teaching and communicating those skills in your own classroom and lab.
Matthew E. Aiello-Lammens – Pace University, Environmental Studies and Science
Sarah Supp – Denison University, Data Analytics
Naupaka Zimmerman – University of San Francisco, Biology
Andrew J. Kerkhoff – Kenyon College, Biology Department
Short Course 8
Connecting Ecology and Natural History Specimen Data: Using Tools in Public, Symbiota Data Portals
2:00 PM – 5:00 PM Pacific Time
To best understand biodiversity in a rapidly changing world, forming connections between scientific disciplines are vital. One such key connection is between ecologists and natural history specimen collections (Alba et al. 2021). In this short course, we seek to bridge this gap by teaching participants how to access, use, and organize natural history specimen data (e.g., herbarium specimens, mounted insects, preserved mammals and fish, fungal and algal specimens) that are housed in publicly accessible online portals that use the Symbiota software platform. In this hands-on short course, participants will learn (1) where to access natural history specimen data, (2) how to search and download specimen data, including phenological and other trait data, when available, (3) how to read and interpret downloaded data, which are stored according to the Darwin Core standard, (4) how to create and edit research checklists in a data portal, and (5) how to manage and submit data about your own voucher collections to appropriate collections portals for archiving.
We expect to cover topics 1-4 in the first 90 minutes of the short course. The last 90 minutes of the short course is optional and will cover topic 5 and additional questions or topics as desired.
Learn to access, organize, and utilize natural history specimen data from online portals that use the Symbiota content management system (e.g., SEINet, NEON Biorepository, SCAN, CCH2). Participants will learn to find and download data, create and edit research checklists, and submit data to collections.
Katelin Pearson – California Polytechnic State University, Biology
Jenn M. Yost – California Polytechnic State University, Biology
Edward E. Gilbert – Arizona State University, School of Life Sciences
Nico M. Franz – Arizona State University, School of Life Sciences