Datasets for Macrosystems Research
Thanks to everyone who joined us for this event live on April 4, 2023!
If you weren’t able to join us, then we hope you’ll view the recording (below).
In this event recording, you’ll hear four macrosystems ecologists share their projects and details about useful datasets in macrosystems research. You’ll be encouraged to think about what types of datasets may be useful for your own research topics of interest.
MEFA ‘Datasets for Macrosystems Research’ Event Transcript (recording below)
AGENDA
- Introduction to the Macrosystems Ecology for All Research Coordination Network
- Guest Speaker Presentations
- Breakout Discussions on Datasets needed for Macrosystems Research
- Information on Upcoming MEFA Events & Conclude
GUEST SPEAKERS
Dr. Claire Lunch, NEON Headquarters
Dr. Lunch is a trained plant ecophysiologist. At NEON, Dr. Lunch oversees the science needs of the data pipeline for observational data and develops open-source code and instructional materials to assist the user community in working with NEON data.
Dr. John Zobitz, Augsburg University
Dr. Zobitz is a mathematician who is focused on mathematical modeling in biology and research in environmental science. He is collaboratively studying soil respiration in partnership with NEON. Concurrently, he is leading a new Faculty Mentoring Cohort through BioQUEST/QUBES with Dr. Zimmerman from our first MEFA event.
Dr. Sparkle Malone, Yale University
Dr. Malone’s research centers on the impacts of climate, hydrology and land management on ecosystem structure and function. She uses big data systems to study ecosystems across space and time to build data-driven strategies that improve ecosystem condition, sustainability, and resilience to climate extremes.
Dr. Ranjan Muthukrishnan, Boston University
Dr. Muthukrishnan integrates empirical and theoretical models to understand the interconnected processes that control ecosystems and evaluate systems as a whole. As a broadly trained ecologist, his work is mainly focused on the dynamics of major shifts in ecological communities influenced by anthropogenic impacts. He incorporates the use of large, publicly available datasets to evaluate these ecological relationships and processes.
