Back to top

SFS Annual Meeting


The list below are all of the workshops that are currently offered. All workshops are subject to a minimum number of attendees signing up for each. Final offerings will be announced after Early Registration closes. If your selection is canceled, you will be refunded the amount paid.

Sunday, June 2, 2024

Getting Published: A Science Writing Workshop

8:00 AM - 12:00 PM

Organizer: Chuck Hawkins

Registration Cost: $35.00

Most scientists are expected to publish their research, and career advancement often depends on how frequently and well we publish. However, completing a technically sound research project does not guarantee it will be published. Manuscripts need to (1) target an appropriate audience and (2) tell an interesting story that is easily understood by readers. In this workshop, I will cover how to select the most appropriate journal for your paper and ways to improve the likelihood that your manuscript will be accepted. The specific topics we will cover include:

  • Selecting a journal – it may not be Science or Nature
  • The life history of a submitted manuscript including dealing with reviewers and editors
  • The elements of effective scientific writing: clarity and economy
    • Writing for the reader
    • Beyond IMRD – organizing your paper to tell a compelling and easily understood story
    • Effective and responsible use of citations – less is often more
    • Paragraphs – topic sentences and a central, unified focus
    • Syntax and grammar – the stuff you learned in high school (maybe) and then forgot (apparently almost everybody)
  • Where to get additional help (self-help resources)

Ecological Applications of Bayesian Statistics – with R and Stan

9:00 AM - 4:00 PM

Organizers: Song Qian and Mark DuFour

Registration Cost: $100.00

This workshop focuses on the practical applications of Bayesian statistics within the environmental and ecological sciences, drawing from the examples provided in "Bayesian Applications in Environmental and Ecological Studies with R and Stan" by Qian, DuFour, and Alameddine (2023, CRC Press). We envision a day-long workshop that begins with an overview of fundamental statistical inference logic. This is followed by an exploration of the modern numerical techniques that have made Bayesian statistics more accessible, liberating practitioners from the complexities of mathematics that previously limited its application to simple cases. The morning session will wrap up with several straightforward examples that illustrate the use of a relatively simple computer program for Bayesian modeling. In the afternoon session, we delve into real-world data examples to illustrate the iterative process of statistical modeling. This process includes model formulation, model-fitting, and model evaluation. These examples highlight Bayesian hierarchical modeling as a versatile framework for almost all environmental and ecological data analysis and modeling problems. This short course offers practical guidance on modern Bayesian computation using R and Stan. Participants will have hands-on experience with annotated computer code and datasets available through a designated GitHub repository. This workshop initially debuted at the SFS2023 Conference in Brisbane, Australia, where it drew an audience of more than 30 colleagues. The upcoming workshop represents an enhanced iteration, incorporating valuable insights from the 2023 experience. It includes improved handout materials and an upgraded computer program.

Spatial Analysis and Statistical Modeling with R and spmodel

9:00 AM - 4:00 PM

Organizers: Michael Dumelle and Ryan Hill

Registration Cost: $60.00

Statistical models often assume that the data are independent. Incorrectly assuming data independence can harm models, resulting in incorrect slope estimates, misleading p-values, and poor predictions. The independence assumption is often inappropriate for spatial data, as spatial observations close together tend to be more similar than spatial observations far apart (Tobler’s Law). Statistical models for spatial data that incorporate spatial dependence tend to notably outperform similar models that rely on independence. Unfortunately, building spatial dependence directly into statistical models is challenging, both from theoretical and computational perspectives, limiting the use of these models in ecological settings. However, recent advances in R software, which we will discuss throughout the workshop, make acquiring spatial data and building spatial models much more accessible.

In this workshop, we will first focus on R tools for accessing and handling the spatial data required to build models, highlighting R data libraries like EPA’s StreamCatTools, FedData, prism, and other data web services. Then we will focus on using these data to build spatial statistical models using the R package spmodel ( With spmodel, ecologists can seamlessly incorporate spatial dependence into their statistical models. spmodel implements user-friendly syntax that builds from the lm() and glm() functions familiar to base-R users, which significantly eases the transition from fitting independence models to fitting spatial models. We will practice using spmodel to fit these spatial statistical models, interpret the model fit and inspect model diagnostics, perform model selection, and make predictions at unobserved locations. We also discuss some advanced spmodel tools and extensions to modeling binary, count, and skewed data, implementing random forests, and incorporating dependence via non-Euclidean distance measures like neighborhood distance or stream distance.

NEON Aquatic Biodiversity Workshop

12:00 PM - 4:00 PM

Organizers: Stephanie Parker and Eric Sokol

Registration Cost: $35.00

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 collected from our 34 aquatic sites, including 24 wadeable streams, 3 rivers, and 7 lakes for taxonomic groups such as fishes, benthic macroinvertebrates, and algae. Instructors will first provide an overview of the breadth of NEON aquatic biodiversity data before leading a code-along exercise on how to find, access, and work with the datasets. Instruction will include how to search for taxa, locations, and dates of interest and then download and format NEON biodiversity datasets for standard ecological analyses in R. Specifically, we will provide an overview of how to use the data discovery and visualization tools available in the neonUtilities and ecocomDP R packages ( for this task. We will then demonstrate how properly formatted NEON data can be used as inputs for some common ecological analyses available in widely used R packages (e.g., vegan). Examples include: Jost (2007)-style alpha, beta, and gamma diversity; alpha, beta, and gamma variability; and multivariate analyses and data visualizations using common ordination techniques (e.g., NMDS). At the end of the workshop, 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 workshop.

Introduction to DIY Water Monitoring Technology

12:30 PM - 4:00 PM

Organizers: Shannon Hicks and Scott Ensign

Registration Cost: $35.00

It is easier than ever for researchers to assemble their own water monitoring technologies instead of buying pre-assembled commercial products. Researchers pursue this Do-It-Yourself path for a variety of reasons: to customize monitoring technology not available commercially; to save money; to explore new techniques; to take advantage of real-time data capabilities. Stroud Water Research Center has developed an ecosystem of open-source DIY hardware and software ( intended to make it easier and less expensive for researchers to get started with DIY environmental monitoring. This workshop will provide a hands-on introduction (a DIY "ice-breaker") to the core component of any DIY device: a programmable microcontroller and data logger. Participants will 1) learn basic terminology and functionality of the Mayfly Data Logger, 2) learn how to program the Mayfly to interrogate environmental sensors and record measurements, 3) gain confidence in pursuing the next steps for connecting commercially-available environmental sensors to the Mayfly to make field-ready monitoring equipment. This workshop is for beginners with little (or no) electronics experience, but who are eager to learn DIY techniques for conducting their research or incorporating it in their classrooms. The workshop will briefly introduce the Monitor My Watershed Data Sharing Portal as a tool for relaying real-time sensor data from a Mayfly Data Logger to the web and sharing that data publicly. The workshop will not cover how to make environmental sensors (we rely on commercially available sensors for our instruction and application).