Forecasting for climate change, land-use, invasive species
During the 21st century, citizens around the world will continue to face grand environmental challenges, including climate change, land-use, and invasive species.
How we deal and adapt to these ecological challenges will have global implications.
A group of researchers, led by Quinn Thomas, associate professor in the Department of Forest Resources and Environmental Conservation in the College of Natural Resources and Environment at Virginia Tech, received a $500,000 grant from the National Science Foundation (NSF) to tackle some of these grand environmental challenges with the creation of a new Ecological Forecasting Initiative Research Coordination Network (EFI-RCN).
“The EFI-RCN will build a community of practice dedicated to improving our capacity to forecast continental-scale environmental changes using data from the National Ecological Observatory Network, or NEON, which is a research effort that standardizes data collection across 81 sites that span the diverse ecosystems of the entire U.S.,” said Thomas, who is an affiliated faculty member of the Global Change Center, an arm of the Fralin Life Sciences Institute at Virginia Tech.
Funded by the NSF, NEON helps researchers understand the rapid and complex ecological changes we are facing on the North American continent.
The EFI-RCN is composed of a network of collaborators throughout Virginia Tech and across the United States. Joining Thomas on the EFI-RCN steering committee from Virginia Tech are Associate Professor Cayelan Carey from the Department of Biological Sciences and Assistant Professor Leah Johnson from the Department of Statistics, both from the College of Science and affiliated faculty members of the Global Change Center.
The recently awarded grant helps galvanize the ecological forecasting research by bringing together scientists, government officials, and stakeholders in meetings and other activities. The diversity of perspectives brought by all involved helps to create a robust network.
“All partner institutions have their strengths,” Thomas said. “Notre Dame is leading education; Minnesota is leading decision support and partner engagement; Boston University is leading tools and methods development; and a NEON scientist is helping with standards and environmental informatics.”
The Virginia Tech researchers bring a strong foundation in ecological forecasting and mathematical modeling to this collaboration.
The EFI-RCN researchers are using NEON data to create ecological forecasting models that help predict the changes in forest composition, water quality, and vector-borne disease, among other issues. Anticipating and responding to these changes requires development of novel approaches that integrate data and observation across multiple sites.
“There is a real need for ecology to become a more predictive science. With the EFI-RCN, we can ramp up iterative forecasting with shorter time scales and learn quickly about how to make better predictions,” said Michael Dietze, a co-principal investigator on the grant and associate professor at Boston University who specializes in forecasting theory and has run previous near-term ecological forecasts with NEON data.
Some of the activities that will bring these partners together include a forecasting challenge to compare and refine how models predict NEON data, a hackathon to help partners develop shared resources, and efforts to develop best practices and community standards.
The EFI-RCN builds on a successful first meeting of the Ecological Forecasting Initiative in 2019 where Dietze and Heather Lynch, associate professor of ecology and evolution at Stony Brook University, brought together an interdisciplinary group of more than 100 natural and social scientists, public health professionals, engineers, and industry and federal agency representatives, with the goal of advancing research and collaboration around the use of near-term (subdaily to decadal) forecasts to understand, manage, and conserve ecosystems. These 100 collaborators will become part of the EFI-RCN.
“The end goal is to think about ecological forecasting like weather forecasting. It’s a tool used in decision-making and we want people to be able to rely on it,” Thomas said.
The broader impacts of ecological forecasting are that it helps us anticipate changes to ecological systems so that we can then take action. Unlike a long-range climate change model, ecological forecasting models are deliberately built on shorter time scales — daily to decadal, for instance — to help people understand changes and act now.
The predictive models improve in real-time. As forecasters learn more about how the models are working, they can fine-tune them based on which predictions came true.
But, before those predictions can take place, collaborators must coordinate with one another to lay the groundwork. The EFI-RCN is a big part of that groundwork. With the field of ecological forecasting still very much in development, a strong coordination network is essential to making sure that the best models are built. Now that NEON’s data sets are complete and fully available, researchers can get to the task of building their predictive models to answer both theoretical and applied questions.
“We’re trying to discover what is predictable in nature, to test and understand how nature works, but also to anticipate changes and help support management and conservation,” said Thomas. “In the end, if there’s a community of ecological forecasters that identify this as one of the main things they do, and they have a common language and a set of overarching objectives they’re working towards, then we’ve been successful.”
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