Simon Levin Proposal abstracts

Pew Charitable Trust
Pew Program in Biocomplexity Simon A. Levin, Co-director and Daniel I. Rubenstein, Co-director This three-year program will train graduate and postdoctoral researchers through intensely interdisciplinary study across the life and physical sciences. The foremost objective of this initiative is to prepare young scientists to investigate complex biological systems and ultimately to be leaders in what will be a new mode of scientific inquiry with significant applications in medicine. Our program, combines a rigorous education in the biological sciences with training in the physical, computational, and information sciences, all of which are increasingly being used to measure, analyze, and model complex biological dynamics. It builds on the strengths of the biology, physics, and mathematics programs at Princeton, which have a strong research presence in the three cornerstones of the training program we propose: modeling of biological dynamics, instrumentation and methodology for measuring biological dynamics, and mathematics and statistical analysis of biological dynamics. This combination of strengths and diversity, complementing and extending Princeton's advantages of small scale and interdisciplinary culture, offers prospective students a unique opportunity to prepare for and conduct interdisciplinary research at the cutting edge of the life sciences. Note: This program is not accepting new students. (pdf) "Pew Program in Biocomplexity"

Pew Charitable Trust

Pew Program in Biocomplexity
Simon A. Levin, Co-director and Daniel I. Rubenstein, Co-director
This three-year program will train graduate and postdoctoral researchers through intensely interdisciplinary study across the life and physical sciences. The foremost objective of this initiative is to prepare young scientists to investigate complex biological systems and ultimately to be leaders in what will be a new mode of scientific inquiry with significant applications in medicine. Our program, combines a rigorous education in the biological sciences with training in the physical, computational, and information sciences, all of which are increasingly being used to measure, analyze, and model complex biological dynamics. It builds on the strengths of the biology, physics, and mathematics programs at Princeton, which have a strong research presence in the three cornerstones of the training program we propose: modeling of biological dynamics, instrumentation and methodology for measuring biological dynamics, and mathematics and statistical analysis of biological dynamics. This combination of strengths and diversity, complementing and extending Princeton's advantages of small scale and interdisciplinary culture, offers prospective students a unique opportunity to prepare for and conduct interdisciplinary research at the cutting edge of the life sciences. Note: This program is not accepting new students.

(pdf) "Pew Program in Biocomplexity"

Defense Advanced Research Projects Agency (DARPA)
Microstates to Macrodynamics: A New Mathematics of Biology PI: Simon Levin with 15 Co-PIs: Peter Bates, Robert Bryant, Timothy Buchman, Jim Damon, Charlie Epstein, Michael Deem, Herbert Edelsbrunner, Richard Lenski, Jack Morava, Lior Pachter, Olivier Pourquie, Sorin Popescu, Bernd Sturmfels, Joshua Weitz, Ned Wingreen The past decade has witnessed an explosion of interest in what mathematics can contribute to biology, and indeed a growing recognition that the power and promise of mathematical approaches must force a revolution in biological research and training. Mathematics is finally being recognized as providing indispensable tools for any biological scientist. However, mathematics is not new to biology: Mathematical constructs have for a century been at the core of such fields as population genetics, ecology, epidemiology and, more recently, neurobiology. In recent years, its successes have expanded to include cell biology, immunology, physiology and, especially, sequence analysis. Such successes have just scratched the surface; the integration of mathematics into biology is still in its infancy, and the time is right to build upon the successes of the past in order to elucidate the fundamental laws of biology through the power of mathematical analysis. This proposed project will foster collaborations among leading mathematicians and biologists, building a community of researchers who will develop the new mathematics of biology, and discover fundamental unifying principles. This could not have been achieved a decade ago and may not happen for decades without a structure and program to bring these disparate groups together in dialogue and collaboration. We have thus assembled a unique team of experimental biologists eager to contribute to the development of mathematical foundations of their subject, and mathematicians eager to help create the mathematical tools that can shed new insights on these problems. The central biological questions involve scaling from cells to organisms to populations to ecosystems, with attention to robustness, collective phenomena, as well as the structure and dynamics of complex networks. The mathematical tools will be drawn from a wide spectrum, from dynamical systems to algebraic statistics to differential topology, from the deterministic to the stochastic, with full expectation that novel formalisms will be established as the project develops. This project, relying on leaders from mathematics and biology, will initiate a new dialogue unconstrained by past approaches and aim to fundamentally change the landscape of biology. (pdf) Microstates to Macrodynamics

Defense Advanced Research Projects Agency (DARPA)

Microstates to Macrodynamics: A New Mathematics of Biology
PI: Simon Levin with 15 Co-PIs: Peter Bates, Robert Bryant, Timothy Buchman, Jim Damon, Charlie Epstein, Michael Deem, Herbert Edelsbrunner, Richard Lenski, Jack Morava, Lior Pachter, Olivier Pourquie, Sorin Popescu, Bernd Sturmfels, Joshua Weitz, Ned Wingreen
The past decade has witnessed an explosion of interest in what mathematics can contribute to biology, and indeed a growing recognition that the power and promise of mathematical approaches must force a revolution in biological research and training. Mathematics is finally being recognized as providing indispensable tools for any biological scientist. However, mathematics is not new to biology: Mathematical constructs have for a century been at the core of such fields as population genetics, ecology, epidemiology and, more recently, neurobiology. In recent years, its successes have expanded to include cell biology, immunology, physiology and, especially, sequence analysis. Such successes have just scratched the surface; the integration of mathematics into biology is still in its infancy, and the time is right to build upon the successes of the past in order to elucidate the fundamental laws of biology through the power of mathematical analysis.
This proposed project will foster collaborations among leading mathematicians and biologists, building a community of researchers who will develop the new mathematics of biology, and discover fundamental unifying principles. This could not have been achieved a decade ago and may not happen for decades without a structure and program to bring these disparate groups together in dialogue and collaboration. We have thus assembled a unique team of experimental biologists eager to contribute to the development of mathematical foundations of their subject, and mathematicians eager to help create the mathematical tools that can shed new insights on these problems. The central biological questions involve scaling from cells to organisms to populations to ecosystems, with attention to robustness, collective phenomena, as well as the structure and dynamics of complex networks. The mathematical tools will be drawn from a wide spectrum, from dynamical systems to algebraic statistics to differential topology, from the deterministic to the stochastic, with full expectation that novel formalisms will be established as the project develops. This project, relying on leaders from mathematics and biology, will initiate a new dialogue unconstrained by past approaches and aim to fundamentally change the landscape of biology.

(pdf) Microstates to Macrodynamics

National Science Foundation
Center for BioComplexity Biocomplexity: The emergence of ecosystem pattern PI: Simon Levin Co-PIs: Stephen Pacala, Ignacio Rodriguez-Iturbe, François Morel, Lars Hedin Ecosystems are the integrated networks of biotic and abiotic elements through which materials and information flow, and that support our continued existence on the planet. From ecosystems we derive food and fiber, fuel and pharmaceuticals. Ecosystems mediate local and regional climates, stabilize soils, purify water and in general provide a nearly endless list of services essential to life as we know it. The case for the preservation of ecosystems and these services is manifestly clear, but the essential challenge of how to do it depends on our knowledge of how macroscopic properties develop from, and feed back upon, diverse assemblages of biotic and abiotic elements. At the levels of ecosystems, as well as the biosphere as a whole, homeostatic processes regulate climate, and maintain the physical and chemical environment that sustains our life-support systems. This proposal seeks to understand what mechanisms, at the level of the interactions between organisms and their environments, sustain those processes, The existence of macroscopic properties at scales of ocean basins and forested regions is relevant both for basic questions on how biocomplexity emerges above the level of organisms and species, and for applied questions about sustainability and management of ecological systems. The approach will combine empirical and theoretical work to attempt to answer these questions, and to provide the scientific basis to aid in our management of the biosphere. (pdf) "Biocomplexity: The emergence of ecosystem pattern"

Collaborative Research: MSPA-CSE: Equation-Free Modeling of Biological Self Organization: Coarse Computational Computing PI: Jeff Moehlis (UC Santa Barbara) Co-PIs: Simon A. Levin and Yannis Kevrekidis (Princeton University) Co-PI: Daniel Grunbaum (University of Washington) Animal populations, such as fish and zooplankton in the oceans, and terrestrial species from bison to locusts and midges, can self-organize into schools and swarms, through the interactions of individuals with each other and their environment. This project aspires to achieve a new level of understanding of the emergence of such population-level behaviors through the development, implementation, and validation of coarse-grained, systems-level numerical methods for individual-based models of collections of organisms. Systems-level tasks enabled through this computational approach include long-time predictions, stability and bifurcation analysis (which details how observed behavior depends on environmental and organism properties), control, and optimization. Understanding aggregation behavior is of both theoretical and applied importance, for problems as diverse as fisheries management and pest control. The details of animal behavior involve individual-level dynamics that are too complicated to analyze rigorously. What is of interest, however, are the macroscopic dynamics of populations. This project will build a tool for providing this understanding, in a flexible and effective way. The algorithms and ideas that will be developed will also have an impact outside of biology, with potential applications in computational chemistry, materials science, and economics. (pdf) "Equation-Free Modeling ..." project summary

National Science Foundation

Center for BioComplexity
Biocomplexity: The emergence of ecosystem pattern
PI: Simon Levin
Co-PIs: Stephen Pacala, Ignacio Rodriguez-Iturbe, François Morel, Lars Hedin
Ecosystems are the integrated networks of biotic and abiotic elements through which materials and information flow, and that support our continued existence on the planet. From ecosystems we derive food and fiber, fuel and pharmaceuticals. Ecosystems mediate local and regional climates, stabilize soils, purify water and in general provide a nearly endless list of services essential to life as we know it. The case for the preservation of ecosystems and these services is manifestly clear, but the essential challenge of how to do it depends on our knowledge of how macroscopic properties develop from, and feed back upon, diverse assemblages of biotic and abiotic elements.
At the levels of ecosystems, as well as the biosphere as a whole, homeostatic processes regulate climate, and maintain the physical and chemical environment that sustains our life-support systems. This proposal seeks to understand what mechanisms, at the level of the interactions between organisms and their environments, sustain those processes, The existence of macroscopic properties at scales of ocean basins and forested regions is relevant both for basic questions on how biocomplexity emerges above the level of organisms and species, and for applied questions about sustainability and management of ecological systems. The approach will combine empirical and theoretical work to attempt to answer these questions, and to provide the scientific basis to aid in our management of the biosphere.

(pdf) "Biocomplexity: The emergence of ecosystem pattern"

Collaborative Research: MSPA-CSE: Equation-Free Modeling of Biological Self Organization: Coarse Computational Computing
PI: Jeff Moehlis (UC Santa Barbara)
Co-PIs: Simon A. Levin and Yannis Kevrekidis (Princeton University)
Co-PI: Daniel Grunbaum (University of Washington)
Animal populations, such as fish and zooplankton in the oceans, and terrestrial species from bison to locusts and midges, can self-organize into schools and swarms, through the interactions of individuals with each other and their environment. This project aspires to achieve a new level of understanding of the emergence of such population-level behaviors through the development, implementation, and validation of coarse-grained, systems-level numerical methods for individual-based models of collections of organisms. Systems-level tasks enabled through this computational approach include long-time predictions, stability and bifurcation analysis (which details how observed behavior depends on environmental and organism properties), control, and optimization.
Understanding aggregation behavior is of both theoretical and applied importance, for problems as diverse as fisheries management and pest control. The details of animal behavior involve individual-level dynamics that are too complicated to analyze rigorously. What is of interest, however, are the macroscopic dynamics of populations. This project will build a tool for providing this understanding, in a flexible and effective way. The algorithms and ideas that will be developed will also have an impact outside of biology, with potential applications in computational chemistry, materials science, and economics.

(pdf) "Equation-Free Modeling ..." project summary

Andrew W. Mellon Foundation
The Emergence and Evolution of Ecosystem Functioning Principal investigators: Simon A. Levin, Lars O. Hedin, Stephen W. Pacala Other faculty: Henry S. Horn, François Morel, Ignacio Rodriguez-Iturbe, Daniel Sigman, and Bess Ward For decades, the disciplines of population biology and ecosystems science have developed with inadequate contact between them, seemingly addressing distinct problems on different scales. That situation has changed dramatically in the past decade, even as ecosystems science has become more global in scope, and as much of population biology has relied increasingly on molecular techniques. Indeed, the need to deal with phenomena across these distinct levels of organization and complexity has made more obvious, and more urgent, the importance of finding ways to scale, from the small scale to the large, and from the individual to the biosphere. The time is ripe for innovative, integrative approaches to such integration from theoretical as well as empirical perspectives. Princeton certainly is not alone in its attention to these problems, but has unique capabilities to develop novel approaches in understanding and conceptualizing the dynamics of diverse systems. Our group has over the past year and a half developed strong partnerships reaching from autecology and population biology to hydrology and biogeochemical cycling, and involving both theoretical and empirical approaches. We propose to use this foundation to further develop a collaborative training and research program at the interface between population biology and biogeochemical cycling, with central focus on training graduate students and postdoctoral fellows. In this way, we expect to develop a cadre of young scientists well-grounded in both disciplines, and with the interdisciplinary perspectives that are necessary for future intellectual leadership in ecology and biogeochemistry. The general themes of this project will involve an understanding of community and ecosystem structure and functioning, across systems and across scales. We shall particularly be interested in grasslands, temperate and tropical forests, and marine coastal and off-shore systems. In all of this research, the work will be soundly based in empirical work, but also closely linked to the development of theoretical and quantitative models. . In particular, we will build on techniques we have long been developing for modeling spatially distributed populations, and for scaling from microscopic to macroscopic phenomena. Many of these techniques, and many of the empirical patterns that we will address, have been developed under prior Mellon funding. (pdf) "The Emergence and Evolution of Ecosystem Functioning"

Andrew W. Mellon Foundation

The Emergence and Evolution of Ecosystem Functioning
Principal investigators: Simon A. Levin, Lars O. Hedin, Stephen W. Pacala
Other faculty: Henry S. Horn, François Morel, Ignacio Rodriguez-Iturbe, Daniel Sigman, and Bess Ward
For decades, the disciplines of population biology and ecosystems science have developed with inadequate contact between them, seemingly addressing distinct problems on different scales. That situation has changed dramatically in the past decade, even as ecosystems science has become more global in scope, and as much of population biology has relied increasingly on molecular techniques. Indeed, the need to deal with phenomena across these distinct levels of organization and complexity has made more obvious, and more urgent, the importance of finding ways to scale, from the small scale to the large, and from the individual to the biosphere.
The time is ripe for innovative, integrative approaches to such integration from theoretical as well as empirical perspectives. Princeton certainly is not alone in its attention to these problems, but has unique capabilities to develop novel approaches in understanding and conceptualizing the dynamics of diverse systems. Our group has over the past year and a half developed strong partnerships reaching from autecology and population biology to hydrology and biogeochemical cycling, and involving both theoretical and empirical approaches. We propose to use this foundation to further develop a collaborative training and research program at the interface between population biology and biogeochemical cycling, with central focus on training graduate students and postdoctoral fellows. In this way, we expect to develop a cadre of young scientists well-grounded in both disciplines, and with the interdisciplinary perspectives that are necessary for future intellectual leadership in ecology and biogeochemistry.
The general themes of this project will involve an understanding of community and ecosystem structure and functioning, across systems and across scales. We shall particularly be interested in grasslands, temperate and tropical forests, and marine coastal and off-shore systems. In all of this research, the work will be soundly based in empirical work, but also closely linked to the development of theoretical and quantitative models. . In particular, we will build on techniques we have long been developing for modeling spatially distributed populations, and for scaling from microscopic to macroscopic phenomena. Many of these techniques, and many of the empirical patterns that we will address, have been developed under prior Mellon funding.

(pdf) "The Emergence and Evolution of Ecosystem Functioning"

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