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NSF Q&A: Statistics and the Division of Environmental Biology

1 March 2024 242 views No Comment
To strengthen the connection between the statistical community and National Science Foundation, we continue the series introduced in the May 2023 issue that poses questions to NSF program officers and awardees. If you have questions or comments for the program officers, send them to ASA Director of Science Policy Steve Pierson.

Program Director

Glasses, big smileSamuel Scheiner has worked at the National Science Foundation since 1998 in the Division of Environmental Biology and helps manage three programs: Evolutionary Processes; Ecology and Evolution of Infectious Diseases; and Biology Integration Institutes. Previously, he was an associate professor at Arizona State University West, assistant and associate professor at Northern Illinois University, and adjunct faculty at the University of Arizona. He earned his BA, MS, and PhD from The University of Chicago and is a fellow of the American Association for the Advancement of Science.

    What is the Division of Environmental Biology?

    DEB supports research and training on evolutionary and ecological processes acting at the level of populations, species, communities, ecosystems, macrosystems, and biogeographic extents. It encourages research that elucidates fundamental principles identifying and explaining the unity and diversity of life and its interactions with the environment over space and time. Research may incorporate field, laboratory, or collection-based approaches; observational or manipulative studies; synthesis activities; phylogenetic discovery projects; or theoretical approaches involving analytical, statistical, or computational modeling.

    The division consists of four core programs: Ecosystem Science; Evolutionary Processes; Population and Community Ecology; and Systematics and Biodiversity Science. It also encourages interdisciplinary proposals that cross conceptual boundaries and integrate over levels of biological organization or across multiple spatial and temporal scales.

    Does a statistician need to collaborate with a DEB scientist to be considered by the program?

    No, a collaboration is not required as long as the project advances a question in ecology and evolutionary biology or develops methods for use by those communities. That said, DEB welcomes proposals that involve collaborations between statisticians and DEB researchers.

    Does a proposal to the program need to include applications?

    Technically no, a proposal does not need to include specific applications. At a minimum, however, a proposal should demonstrate the value of the proposed methods for the DEB community. And proposals that include applications with real-world data in areas supported by DEB are most welcome.

    What are the differences between the programs in DEB and the statistics program in the Division of Mathematical Sciences?

    If we think of statistical research on a continuum from basic to applied, one could characterize the statistics program as more on the basic end and the programs in DEB as more on the applied end. DEB-supported projects would be considered basic from the perspective of ecology and evolutionary biology, but not perhaps from the perspective of the statistics program. That said, there is some overlap in the missions of the programs. Because of that, the programs in DEB and the statistics program have a long history of co-review.

    Is there anything else we should know about the DEB program?

    Besides the core programs listed above, DEB has several special solicitations that focus on specific topics.


    Ali Rahnavard is an assistant professor of biostatistics and bioinformatics at The George Washington University. He is interested in the intersection of the microbiome and metabolome for understanding their interactions in health and disease. His lab uses systems biology–based approaches, applying computational methods to multi-omic data with the goal of generating hypotheses of the underlying processes involved in disease activity.
    Keith Crandall, founding director of The George Washington University Computational Biology Institute, is a highly cited researcher and Fulbright Scholar with extensive publications, including The Evolution of HIV. His work spans infectious diseases to biogeography, earning him recognition as an American Association for the Advancement of Science fellow.

      The NSF funded an initiative led by Rahnavard and Crandall to study SARS-CoV-2’s evolution. Awarded $1.8 million, they aim to create a computational platform to examine virus-host interactions over five years, affecting humans, animals, and plants. The focus is on understanding treatment-driven viral changes and identifying -omic markers linked to health outcomes and viral traits.

      What will the proposal accomplish?

      The proposal sponsored by the NSF Ecology and Evolution of Infectious Disease program aims to gain a deeper understanding of the SARS-CoV-2 virus mutations across different regions and time and characterize the human body’s immediate and sustained responses to infection and treatments, including vaccination.

      An essential aspect of the proposal is to equip researchers and students in the public health domain with the skills to use new technologies and methodologies, enhancing their ability to address pandemics and infectious diseases effectively.

      The broader effects include creating mentorship and educational initiatives, hosting workshops to share research methods, and training students and researchers in new technologies to combat pandemics.

      Additionally, the project integrates missing components in bioinformatics into existing courses, especially in the biological and statistical curricula. Sustainability is enhanced through open-source tools and educational materials, with a focus on including undergraduate and minority students in research and validation of methods.

      What advice do you have for others applying for NSF funding?

      When applying for NSF funding, it is essential to craft a proposal that aligns with the NSF’s goals, directly addressing the priorities outlined in the request for funding announcement. Your proposal must be responsive and clearly articulate how it fulfills specific requirements and aligns with the NSF’s mission.

      Assemble a multidisciplinary team whose expertise complements the project. Underscore each member’s unique contributions and demonstrate how their collaboration will ensure success.

      Innovation should be at the forefront of your proposal. Introduce novel research approaches that promise significant advances in your field and support these with evidence of feasibility through preliminary data or proof-of-concept results.

      Additionally, your proposal should detail how the research outcomes will affect society and demonstrate a clear plan for applying results to community and societal needs, such as promoting diversity in the workforce and considering minority groups. This focus on broader impacts can greatly enhance the relevance and appeal of your research proposal to the NSF.

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