Understanding the Rules of Life: Emergent Networks | 21 560

Opportunity Information: Apply for 21 560

Understanding the Rules of Life: Emergent Networks (URoLEN) is a National Science Foundation (NSF) research grant opportunity created under NSF's broader set of "Big Ideas," long-term priorities meant to push the frontiers of science and engineering through convergence research. Although proposals are submitted through NSF's Directorate for Biological Sciences, Division of Emerging Frontiers (BIO/EF), the program is intentionally cross-disciplinary in how it is reviewed and managed, with a team of NSF program directors spanning multiple fields. The central motivation is to move beyond studying biological components in isolation and instead build a predictive science of how living systems behave when they are embedded in complex webs of interaction with other organisms, environments, and human systems.

URoLEN extends NSF's "Understanding the Rules of Life: Predicting Phenotype" Big Idea, which focuses on how properties of living systems arise from the interplay of genomes, phenotypes, and changing environments. Earlier NSF efforts under this umbrella have targeted things like "minimal rules" (for example, principles needed to build a synthetic cell), "rules of complexity" (such as epigenetic regulation), and "rules of interaction" (including microbiome dynamics). URoLEN adds another layer by aiming at the "rules of emergence" that govern networks, meaning the system-level behaviors that arise when many interacting parts create outcomes that are nonlinear, surprising, and not straightforwardly inferable from studying the parts alone.

The program emphasizes "emergent networks" as networks of living systems that are tightly coupled with natural environments, built infrastructure, and social systems, including human-engineered components. In these networks, outcomes are shaped not only by chemistry, physics, and biology at the level of molecules, cells, organisms, and populations, but also by communication and information flow across the network. A key point is that these coupled networks can produce wide-ranging and high-impact consequences, and that prediction is increasingly difficult as environments shift faster and extreme or rare events become more frequent. URoLEN is framed around a major unsolved problem: identifying and explaining the emergent properties of these networks, especially those that appear only when multiple systems interact and that do not exist when each system is considered separately.

The solicitation illustrates the idea with the example of chestnut blight (Cryphonectria parasitica), a nonnative pathogen introduced through nursery stock that essentially removed the American chestnut from North American forests. That single introduction triggered cascading effects across ecological networks (species interactions, forest structure), abiotic conditions, and social and economic systems, ranging from local community impacts to broader consequences for timber markets. This kind of case captures what URoLEN is after: understanding, modeling, and ultimately anticipating the ripple effects and feedback loops that occur when biological change intersects with environmental and human systems across scales.

Competitive URoLEN projects are expected to use convergent approaches, bringing together multiple disciplines, methods, and levels of organization to uncover generalizable principles and to improve predictive capability. The intended outcomes include new theory and more reliable predictions about how specific environmental changes will alter the behavior of complex living systems. In addition to prediction, the program also welcomes work aimed at "engineerable" interventions and technologies, meaning actionable strategies or tools grounded in discovered rules of life that can help address real-world consequences and deliver societal benefits.

URoLEN also places noticeable value on education, training, and outreach as integrated parts of a research plan. Because the work requires teams that can operate across disciplinary boundaries, the program encourages projects that create convergent training opportunities for researchers and students, develop new teaching modules, and broaden participation for groups historically underrepresented in science. The expectation is that the same cross-cutting nature that makes this research hard also creates an opportunity to prepare a workforce fluent in integrating biology with computation, engineering, environmental science, and social dimensions where relevant.

From an administrative and funding standpoint, this is a discretionary NSF grant program (Funding Opportunity Number 21-560) in the science and technology research and development category, with CFDA listings spanning multiple NSF accounts (including 47.041, 47.049, 47.050, 47.070, 47.074, 47.075, 47.076, 47.079, 47.083). The opportunity anticipated around 10 awards. Projects could be supported for up to five years, with budgets described as up to $3,000,000. The solicitation was originally posted February 9, 2021, with an original closing date of May 10, 2021. Eligibility is listed broadly as "others," with applicants directed to consult the solicitation's eligibility section for specifics.

• The National Science Foundation in the science and technology and other research and development sector is offering a public funding opportunity titled "Understanding the Rules of Life: Emergent Networks" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 47.041, 47.049, 47.050, 47.070, 47.074, 47.075, 47.076, 47.079, 47.083.
• This funding opportunity was created on Feb 09, 2021.
• Applicants must submit their applications by May 10, 2021. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• The number of recipients for this funding is limited to 10 candidate(s).
• Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).

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