Simon Asher Levin, Ph.D. - US grants

9707610 Levin An important process shaping the ecology of any organisms in nature is coevolution, the evolutionary interplay among distinct species. Understanding coevolution requires mathematical and computer models to describe how interactions among species change over long time intervals; yet the construction and analysis of such models is rarely possible because of inadequate understanding of the biological processes, and the complexity of the mathematical description. Empirical work by the investigators, however, has produced useful short-term models of interactions between insects and their pathogens, and mathematical breakthroughs in the PI's lab have greatly simplified long term coevolutionary models. In this research, the investigators will apply these advances to understanding how host-pathogen interactions, especially in insects, are affected by the coevolution of host and pathogen. Because insects are important agricultural pests, and because pathogens are important natural means of pest control, the research will have direct and important environmental applications.

9725937 Levin Support for this project will enable American researchers to collaborate with and benefit from researchers and facilities at the Center for Ecological Research at Kyoto University in Japan and the Center for Population Biology at the Imperial College in the United Kingdom. The impact of environmental variability and competitive exclusion on the number of species required to maintain a certain level of function in communities will be determined mathematically. Those relationships will then be tested in a series of experiments in which species numbers and environments are manipulated. The U.S. team will be primarily responsible for the derivation of the theoretical diversity-function relationships, and will, in cooperation with the U.K. team, conduct field experiments in which species number, precipitation, and herbivory are manipulated. The Japanese team will perform growth-chamber experiments on communities subjected to different levels of predation or parasitism. Many current analyses of ecological diversity-function relationships ignore variations in the performance of individual species with varying environmental conditions, and ignore the impacts of competitive exclusion on multi- year measures of community function. This project will combine the expertise and facilities of American, Japanese and British research groups to investigate the level of biodiversity preservation required to maintain essential ecosystem services and functions. ***

Pacala
9807755
The primary goal of this project is to interpret
analytically the effects of spatial environmental heterogeneity
on the community dynamics and biodiversity of ecological systems.
Simulation models and experimental studies have convincingly
demonstrated the importance of endogenous and exogenous spatial
heterogeneity, such as variation in resource supply rate or
topography, to the coexistence and the maintenance of diversity
in ecological communities. However, both mathematicians and
ecologists still lack analytic understanding of the mechanisms
operating, particularly in fully spatial, stochastic
environments. The investigators extend existing analyses of the
effects of heterogeneity by using a wide range of models (from
metapopulation models to interacting particle systems and point
processes); they develop moment approximations, which express
spatial population dynamics in terms of mean densities and
covariances, to simplify the analysis while preserving both
exogenous and endogenous heterogeneity. The study uses moment
approximations, and more standard techniques, to analyze the
effects of environmental heterogeneity, endogenous heterogeneity,
and their interaction on population dynamics and competitive
outcomes in ecological models of plant and marine intertidal
communities.
Field ecologists have long known that small-scale
variability in environmental factors such as soils or temperature
can affect the structure and diversity of ecological communities
--- which and how many species can live together in a region.
Ecological modellers, however, have often found simple
explanations for small-scale spatial patterns of biodiversity,
caused by interactions between plants or animals (such as
competition or predation), that ignore environmental variability.
Computer simulation models have recently gone a long way toward
reconciling these two camps, but (1) simulations show that
patterns occur, but do not always explain why; and (2) even
powerful computers have limits (it could be foolhardy, for
example, to attempt to simulate every tree on a continent in
order to predict the effects of global climate change). This
study develops simple mathematical models that combine spatial
variability caused by interactions between organisms with spatial
variability caused by the environment to explore how these two
kinds of variability affect the structure and diversity of
communities. The results from these simple models will eventually
show how to build more complex and realistic models that can
predict patterns of biodiversity and ecosystem productivity, and
will provide a much more general understanding of how variability
in the environment leads to diversity in ecological communities.

0083566
Levin
Biological systems, from ecosystems to the biosphere, support our continued existence on the planet. From them 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; the essential challenges are in the details of how to do it. The key is in understanding biocomplexity - how it arises, how it is maintained, and how it sustains the services we derive from it.

This project will examine the mechanisms sustaining crucial regional and global processes that underlie our life-support systems. The research approach will combine empirical and theoretical work, documenting emergent laws of organization, and examining through sophisticated modeling the mechanisms that generate and maintain biocomplexity and predictable

The goals of this proposal are to improve our understanding of both the evolution and management of influenza by developing a unified modeling framework. In particular, the questions we will address are (1) How do given strain and subtype structures, and the associated patterns of cross-reactivity, affect disease dynamics? (2) How does cross-reactivity affect pathogen evolution? (3) How do strain structure and patterns of cross-reactivity self-organize over evolutionary time, for example into quasi-species, and how does this organization feed back to affect dynamics? (4) What are the implications of these issues for vaccination strategies, and what are the reciprocal effects of vaccination programs upon the organization of the viral population?

Forests in our landscape are increasingly becoming isolated "islands" in a "sea" of urban, suburban, or agricultural land. For their populations to persist in such a landscape, trees must disperse their seeds from one island to the next. Many trees use the wind to disperse their seeds. In strong winds, especially over a rugged forest canopy or near the edge of a forest, three-dimensional "whirlpools" form with winds that sometimes blow upwards. If the upward velocity of the wind is greater than the rate of fall of the seed, the seed can go up rather than down. It may even get caught in a large updraft, such as happens where warm air rises, or where winds are deflected by a hill, a forest edge, or a large building. Such updrafts can take a seed high into the atmosphere, where it encounters faster winds. Or the updraft itself can move for miles, as it does in a thunderstorm, before letting the seed settle to ground.

This project is a collaboration between biologists and atmospheric scientists to determine how often seeds go into these long-distance modes of dispersal. This will require measuring how strong the wind must be before seeds break loose from the tree, how slowly seeds fall in still air, and how the upward velocity of wind changes in different settings. Finally it will test experimentally whether winds can carry seeds as far as the distance between forest islands. The importance of updrafts for seed dispersal and the frequency of long-distance dispersal will be compared for 18 wind-dispersed tree species of the northeastern United States. Such information is vital for understanding the dynamics of forest species, and for maintaining them as humans increasingly fragment the landscape.

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 systematic, 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.

Nitrogen availability limits plant growth and carbon storage in many temperate and boreal forests. Biological nitrogen fixation, the conversion of atmospheric nitrogen gas into a biologically useful form, has the capacity to alleviate nitrogen limitation in these ecosystems, yet nitrogen fixing trees are only present in young forests, while nitrogen limitation persists in old forests. Why are nitrogen fixing trees excluded early in temperate and boreal forest development? Recent theory, including a mathematical model developed by the investigators, has revealed a number of possible explanations for this seeming paradox. There is empirical support for some of these explanations, yet few have been tested experimentally. This proposal describes a highly controlled experiment to evaluate four of the key issues highlighted by theory. This experiment will focus the development of new theory and field-based studies, and this combination of approaches will unravel the seeming paradox of sustained nitrogen limitation.

The challenges of achieving a sustainable future for humanity are among the most crucial facing society today. To understand the complex and dynamic interconnections among human and environmental systems, and to mobilize that knowledge to inform effective management and policy making, will require increasingly powerful quantitative tools, building upon but expanding dramatically the approaches available for modeling, prediction and analysis of climate systems, ecosystems and socio-economic systems. To address these challenges, the organizers will hold a workshop in Winter 2009 to bring together scientists and practitioners from across a broad spectrum of disciplines, to identify crucial open research questions whose solution would advance the field by quantum levels. Our hope is that the products of this workshop will help guide priorities for funding of research on sustainability.

Intellectual merit. One of the fundamental patterns of ocean biogeochemistry is the Redfield ratio, linking the stoichiometry of surface plankton with the chemistry of the deep ocean. There is no obvious mechanism for the globally consistent C:N:P ratio of 106:16:1 (Redfield ratio), especially as there is substantial elemental variation among plankton communities in different ocean regions. Thus, knowing how biodiversity regulates the elemental composition of the ocean is important for understanding the ocean and climate as a whole -- now and in the future.

The conceptual hypotheses for this study are as follows:
1. The C:N:P ratio of a cell is constrained by its broad taxonomic group, which determines, for example, whether it has an outer shell, its size, functional metabolism, membrane lipid composition.
2. Within a taxon, there is high genetic diversity. Some of this genetic diversity is potentially laterally transferred, or can be lost within taxa, and confers various functional abilities (organic phosphate assimilation, nitrate assimilation, photoheterotrophy, etc.). Functional diversity provides the cell with further flexibility, such as the ability to respond to varying nutrient supply rates/ratios, and affects a cell's C:N:P ratio within the range specified by the taxon.
3. Given these taxonomic and genetic constraints, a cell is physiologically plastic and modifies how it allocates cellular resources in response to nutrient supply rates/ratios in the environment.
4. The microbial diversity (taxonomic, genetic, and functional) of the surface ocean varies over time and space, driven by many factors in addition to nutrients. The sum of this mixture composes the ecosystem C:N:P, the ratio that Redfield described.

Based on this framework, the CoPIs will make field observations of taxon-specific stoichiometry and growth rates, genomic analyses, and conduct laboratory chemostat experiments to improve understanding of how ocean taxonomic, genetic, and functional biodiversity control the stoichiometry of the surface ocean plankton. Their analyses of these data would lead to a mechanistic understanding of variations in the Redfield ratio, both spatially and temporally.

Broader impacts. This study will greatly expand knowledge of the genomic diversity among ocean microbes and how this diversity affects biogeochemistry. The stoichiometry of the ocean's microbes is a parameter that nearly every chemical or biological oceanographer uses, from converting measurements made in one element to another, to estimating regional and global nitrogen budgets. The research also has important implications for the global carbon budget and any changes that might result from climate change. Beyond training three postdoctoral scholars and two graduate students, a Gateway Mentoring Program will be established to recruit undergraduates (total of 12) transferring from community colleges in the Southern California area, training and preparing them for careers in research-oriented science. The program will consist of extensive mentoring, research experiences at UCI, internships at BIOS, Princeton, or UCSD, and presentations at national conferences. This intensive mentoring and research experience prepares students well for a career in science, and enhances acceptance to post-graduate schools. The Program will have a very high proportion of underrepresented groups as reflected in the targeted colleges.

Integration. To understand mechanistically temporal and spatial variability of the plankton C:N:P ratio, biodiversity must be studied not only at the traditional taxonomic level, but at the genetic and functional levels which dictate organism response to their environment. Data will be integrated into a combined ocean ecological, evolutionary, and biogeochemical model, with flexible stoichiometry, including cellular biochemical allocations. Seeding a coupled physical-biological model of the oceans with multiple competing genotypes enables the exploration of ecological and evolutionary patterns of resource acquisition and C:N:P ratios. Developing a more mechanistic examination of the course of ecology and evolution, in which laboratory and field data define tradeoffs between different growth and nutrient acquisition strategies, would estabblish the framework of adaptive dynamics for determining "evolutionarily convergence". Finally, model outcomes will be evaluated against field data.

Despite the common conception of nature as "red in tooth and claw," almost all organisms, from soil bacteria to primates -including humans-, must cooperate with others to survive and reproduce. How such cooperation persists evolutionarily despite conflicts of interests is a central question in biology. The problem is exacerbated when individuals face uncertainty about factors affecting their payoffs, because this creates incentives for deception that would undermine cooperation. This project will study how incentives for cooperation and the related social structure evolve when individuals face uncertainty and have private information.

The PI and his colleagues will use a suite of mathematical tools originally developed in economics, called mechanism design theory. Mechanism design studies how appropriate incentive structures can be set up to prevent self-interested individuals from deceiving each other and undermining the desired outcome. However, classic applications of mechanism design theory, such as the design of auctions and trading schemes, usually presuppose an agent (such as a government) with the power of setting the "rules of the game". In contrast, natural selection acts on individuals that can alter the game only in limited ways by themselves. Hence, the evolved "rules of the game" represent the outcome of natural selection working in a decentralized way through individuals. The aim of this project is to understand how natural selection thus organizes interactions between individuals to achieve mutually beneficial outcomes.

The project's interdisciplinary approach will not only further our understanding of fundamental evolutionary processes, but also help in understanding how we in human societies can cooperate without relying on a central authority to tackle problems such as global climate change. It will also produce new results in social evolution theory that are sure to capture the public's attention, and will therefore aid in furthering science education and public understanding of science.

The oceans are one of the most dynamic environments on Earth, presenting a profound challenge for understanding the complex social, ecological, and physical interactions that occur within them. Fishers are naturally tuned to this complexity and meet their individual goals by targeting their efforts towards particular locations and types of catch, and by adapting their social interactions. Yet we - the scientific community - lack an understanding of how social behavior and ecological dynamics are coupled. Further, these feedbacks are largely ignored in present management approaches. We aim to fill this knowledge gap by answering three questions: (1) How does fisher social behavior (defined as the level to which individual fishers share information) change in response to ecological, technological and management factors? (2) What effect does social behavior have on fisher spatial dynamics and on the social structure of the fishing community? (3) How can management strategies be designed to account for the social behavior of fishers? To answer these questions we will conduct a comprehensive research project involving data gathering and analysis, theoretical modeling and the development of novel mathematical theory. This project will have direct implications for agencies responsible for managing marine resources along the west coast of the U.S. and in Hawaii, some of whom are collaborating in the research. By increasing our understanding of how humans using a natural resource interact with one another and how this in turn affects that resource, the results of this study will be relevant to fields as diverse as finance and global food security.

We propose to gather data on the spatial and behavioral dynamics of fishers along the U.S. west coast, in Brazil and in Fiji - three marine systems with contrasting social, ecological, technological and management characteristics. U.S. data will come from collaborations with the NOAA National Marine Fisheries Service, and data from Brazil and Fiji will be obtained using economic field experiments. All three data sources will be used to develop agent-based models that simulate both the dynamics of fish and individual fishers. We will distinguish ourselves from traditional modeling approaches by adopting a Complex Adaptive Systems (CAS) perspective. With a CAS perspective the spatial dynamics of fish and fishers and the social structure of fisher communities, along with other macroscopic properties, emerge from processes operating at low levels of organization, namely the actions of individual fishers and their target species. Our agent-based models will have the CAS perspective at heart, with fisher agents able to adapt and learn different behavioral strategies (e.g. sharing or not sharing information). A combination of variation, fitness and reproduction will create a selective mechanism whereby fisher behaviors converge to evolutionary stable types. We will complement our agent-based modeling with evolutionary game theory and investigate why certain social behaviors are evolutionarily stable in some marine systems and not in others. Last, we will use mechanism design theory to develop management strategies that account for changes in fisher social behavior.

Climate change presents a profound challenge to the sustainability of coastal systems. Most research has overlooked the important coupling between human responses to climate effects and the cumulative impacts of these responses on ecosystems. Fisheries are a prime example of this feedback: climate changes cause shifts in species distributions and abundances, and fisheries adapt to these shifts. However, changes in the location and intensity of fishing also have major ecosystem impacts. This project's goal is to understand how climate and fishing interact to affect the long-term sustainability of marine populations and the ecosystem services they support. In addition, the project will explore how to design fisheries management and other institutions that are robust to climate-driven shifts in species distributions. The project focuses on fisheries for summer flounder and hake on the northeast U.S. continental shelf, which target some of the most rapidly shifting species in North America. By focusing on factors affecting the adaptation of fish, fisheries, fishing communities, and management institutions to the impacts of climate change, this project will have direct application to coastal sustainability. The project involves close collaboration with the National Oceanic and Atmospheric Administration, and researchers will conduct regular presentations for and maintain frequent dialogue with the Mid-Atlantic and New England Fisheries Management Councils in charge of the summer flounder and hake fisheries. To enhance undergraduate education, project participants will design a new online laboratory investigation to explore the impacts of climate change on fisheries, complete with visualization tools that allow students to explore inquiry-driven problems and that highlight the benefits of teaching with authentic data. This project is supported as part of the National Science Foundation's Coastal Science, Engineering, and Education for Sustainability program - Coastal SEES.

The project will address three questions: 1) How do the interacting impacts of fishing and climate change affect the persistence, abundance, and distribution of marine fishes? 2) How do fishers and fishing communities adapt to species range shifts and related changes in abundance? and 3) Which institutions create incentives that sustain or maximize the value of natural capital and comprehensive social wealth in the face of rapid climate change? An interdisciplinary team of scientists will use dynamic range and statistical models with four decades of geo-referenced data on fisheries catch and fish biogeography to determine how fish populations are affected by the cumulative impacts of fishing, climate, and changing species interactions. The group will then use comprehensive information on changes in fisher behavior to understand how fishers respond to changes in species distribution and abundance. Interviews will explore the social, regulatory, and economic factors that shape these strategies. Finally, a bioeconomic model for summer flounder and hake fisheries will examine how spatial distribution of regulatory authority, social feedbacks within human communities, and uncertainty affect society's ability to maintain natural and social capital.

This project provides graduate students with tools needed to recognize opportunities for development of mathematical approaches to challenges related to global environmental change, from physics to biology to society, using as the common denominator the subject of water. These environmental and societal challenges involve many complex factors, and students will be trained to apply and implement mathematical strategies that effectively address these complexities. Essential to the training will be opportunities afforded by visits to important European policy centers, such as the International Institute for Applied Systems Analysis (Austria) and the Stockholm Resilience Center, where policy issues are articulated and integrated with scientific analyses. The overarching goal of this project is to offer an avenue to train talented mathematical scientists to contribute substantively to the understanding of the interactions between society and nature and to formulate well-founded strategies to manage these interactions to assure a sustainable future. This project has received co-funding from the Global Venture Fund of the Office of International Science and Engineering.

The mathematical modeling of the problems addressed in this project involves a variety of tools, from game theory and network theory to deterministic and stochastic partial differential equations. The application of powerful analytical and numerical methods to the challenges of modeling water as a societal resource promises significant advances in policy and planning. On the other hand, the questions raised by societal challenges related to water will require new directions of research in game theory and stochastic and deterministic partial differential equations, contributing to advances in mathematics. The interactions among mathematicians and scientists in this project will bring to bear powerful new mathematical perspective and techniques to societal problems surrounding the crucial resource that is water.

Tropical forests contain most of the world's bird and mammal species, many of which are heavily threatened by overhunting. This project seeks to understand how habitat loss and hunting synergistically affect vertebrate communities. Doctoral Dissertation Improvement funds will complement ongoing research by supporting the collection of detailed information on hunter decision-making behavior, including hunter motivations, their prey preferences, and their searching strategies. The motivation for hunting - whether for subsistence livelihood, commercial markets, or recreation - can determine whether or not excessive hunting is likely to occur. Improved understanding of hunting behavior, in combination with spatial distribution patterns of different species, will improve management of hunting throughout the tropics, as well as in other low-governance areas. Such areas are often committed to the conflicting goals of biodiversity preservation and access by low-income rural populations to natural resources. The project will focus on capacity building and knowledge exchange with local partner institutions, ranging from protected area administration to research stations with local Chinese and Laotian graduate students and faculty. It will contribute significantly to training a graduate student by supporting the integration of social science surveys with existing field research to address an increasing problem.

A field study focusing on hunters and a suite of tropical bird species, ranging from species that are widely distributed and rarely hunted to those that have been heavily hunted and occur only in isolated fragments, will be conducted in Tropical East Asia. The investigators posit that the failure of current models to manage exploited populations results from the fact that hunting occurs in a multi-prey context. Common, unprotected prey species can subsidize the exploitation of rare species, a phenomenon called opportunistic exploitation. The researchers will adapt multi-species competition and predation models to include anthropogenic hunting, thereby offering novel predictors for vulnerability to over-exploitation. Point count transects will describe the abundance and distribution patterns of avian species within and around protected areas in Southwest China and Northern Laos. Household interviews of villagers living within 5km of protected areas will be conducted to assess hunter behavioral motivations, and hunting techniques and intensity. The field survey data will inform a mathematical model of multi-species hunting to better understand how to conserve tropical diversity.

Ecologists have long emphasized climate as primary factor determining ecosystem dynamics at large scales, but the relationship between climate and vegetation is not always deterministic. Where vegetation-environment feedbacks are significant (e.g., in savannas), predicting responses to climate can be especially difficult. Recent work suggests that feedbacks with fire may make savannas much more common than they would be were their distributions solely determined by climate; as a result, savanna and forest responses to global change may thus be drastic, sudden, and difficult to foresee. However, existing work does not explain why savanna is spatially aggregated with savanna and forest with forest -- a pattern that indicates that spatial processes may also play a role in determining ecosystem responses to climate. Here the investigators will consider the impacts of those spatial interactions between savanna and forest on their distributions and on their potential responses to climate and land-use change, both in the past and into the future.

The investigators have identified three hypotheses to explain the spatial aggregation of savanna and forest: H1) that savanna and forest are bistable, and that spatial structure in initial conditions (as a result of past climate) determines their distributions, H2) that savanna and forest are bistable, but that spatial processes within savanna (e.g., fire spread) result in spatially structured distributions, and/or H3) that nearest neighbor interactions between savanna and forest change their distributions on long time scales, impacting their long-term stability. These hypotheses are variously supported in the empirical literature, and existing work has not attempted to disentangle these processes. Results will allow the research team to generate informed theoretical and empirical predictions about the past and future distribution of savanna and forest globally. The proposed work will also generate novel mathematical results. Possible outcomes of theoretical, spatial-stochastic models include a) savanna and forest coexistence in landscapes, b) forest exclusion by savanna, c) savanna exclusion by forest, or d) alternative stable states in biome savanna/forest dominance. The last outcome would be unlikely in a homogeneous spatial stochastic model, where the winning biome is decided by the direction of movement of the biome boundary (i.e., the front), but most closely resembles real biome distributions. Spatial stochastic model results will be reconciled with observations using theoretical and simulation modeling.

This project will use available data sets for COVID-19 in other countries, and in NYC, Virginia, and Maryland to build compartmental and metapopulation models to quantify the events that transpired there, and what interventions at various stages may have achieved. This will permit gaining control of future situations earlier. The epidemic models developed during this project will lead to innovations in computational epidemiology and enable approaches that mitigate the negative effects of COVID-19 on public health, society, and the economy.

Based on publicly available data sets for COVID-19 in other countries, and in NYC, Virginia, and Maryland, the researchers propose to build compartmental and metapopulation models to quantify the events that transpired there, understand the impacts of interventions at various stages, and develop optimal strategies for containing the pandemic. The basic model will subdivide the population into classes according to age, gender, and infectious status; examine the impact of the quarantine that was imposed; and then consider additional strategies that could have been imposed, in particular to reduce contact rates. The project will apply and extend the approach of "transfer learning" to this problem. The research team is well positioned to conduct this research; they have a long history of experience tracking and modeling infectious disease spread (e.g., Ebola, SARS) and are already participating in the CDC forecasting challenge for COVID-19.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.