Workshops

The GLEON Student Association is planning workshops for Sunday, 30 October 2022:

Morning

  • Three simple guidelines for science communication (Ben Kraemer)
    2.5 hours
    Our careers and our science depend on our ability to communicate effectively. Communicating effectively helps others to learn from our science, recognize its message, and integrate that message into our collective scientific understanding. However, many scientists are under-trained in how to communicate their science effectively. This workshop will present three simple guidelines that can help us get funding, write well-structured manuscripts, and design effective posters and oral presentations. The workshop will also include “hands-on” activities using examples of your own writing and examples from published literature.
  • Introduction to real-time lake forecasting: learn, teach, and generate forecasts with Macrosystems EDDIE modules and the NEON Forecasting Challenge (Mary Lofton, Freya Olsson, Cayelan Carey)
    2.5 hours
    The use of near-term, iterative forecasting - i.e., making forecasts of future ecosystem conditions with uncertainty that are constantly being updated as new data become available - is rapidly increasing within the lake research community. However, many scientists may not be familiar with forecasting methods, educational materials, or know how to develop their own forecasts. This workshop will tackle this gap! First, we will provide participants with all materials needed to learn and teach the basics of ecological forecasting with four stand-alone, modular activities that use National Ecological Observatory Network (NEON) lake data and are delivered through R Shiny apps. Our educational modules are part of the Macrosystems EDDIE (Environmental Data-Driven Inquiry & Education) program, and each module comprises three ~1 hr activities which may be completed all at once or individually. We will provide an overview of the modules and helpful tips for teaching them in your classroom. Second, we will introduce you to the NEON Forecasting Challenge for lakes, a national-scale effort of generating real-time forecasts for lakes across the U.S. We will provide you with all of the information and materials so that you can start submitting to the Challenge when it opens in Winter 2023. Come join our effort!
Afternoon
  • How to build a model in R (Robert Ladwig, Hilary Dugan and Paul Hanson)

    2.5 hours
    Want to be a modeler but don't know where to start? Do you find the word "model" scary? Wish you knew more about how to get started building models in R? If yes to any of the above, this workshop is for you. If you already have some R basics under your belt, we aim to add modeling to your R skillset. Learn what models are and how models are built, calibrated, and used for simplifing data and prediction.

  • Working with data from the US National Ecological Observatory Network (Kevin Rose)
    Afternoon, ~3 hours
    This workshop will serve as an introduction to the US National Ecological Observatory Network (NEON) and the data it generates and serves to the scientific community. The session will provide a background on the US NEON program, the types of data that are collected in terrestrial, stream, and lake sites, and tools available to access the data. Workshop participants will get a chance to work with GLEON and NEON scientists to dive into the data, make discoveries to understand complex limnological phenomena, and report back to others on what they found. Within this workshop, participants will have the opportunity to further sub-divide into groups according to research interests. During registrration, we will ask you to prioritize a selection, so we can make sure we have the appropriate NEON scientific support during the workshop:
    1. Aquatic water quality sensor data (for example, dissolved oxygen, chlorophyll, turbidity, nitrate, and temperature data)
    2. Aquatic biogeochemical observational data (for example, bathymetry, Secchi depth, water chemistry grab samples, and dissolved gas concentrations)
    3. Aquatic biological data (for example, macroinvertebrate and algal taxonomy, DNA metabarcoding) 
Updated: 8 August 2022

 

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