The Evolution of Dynamic Response Strategies: Optimal Control and Evolutionary Dynamics

University Of California-Santa Barbara, Santa Barbara CA

Investigators

Abstract

Intellectual Merit: This project will develop theoretical approaches based on optimal control theory and population genetics to understand how living organisms, ranging in size from single cells to large animals, sense changes in their environments and respond to them dynamically. To survive, living organisms must constantly respond to changes in their surroundings, including changes in food supplies and the numbers and types of predators. For example, animals compete with other members of their species for food; thus the foraging strategies of other individuals cause random fluctuations in food availability. The dynamic changes in conditions over time contain information that individual organisms must sense, process, remember, and act on to their advantage. However, these internal processes are subject to noise due to incomplete or inaccurate sensing and processing. This is just as true at the cellular level as it is at the level of whole organisms, for example when humans plan for the future by observing the changing conditions around them. Because organisms have evolved sensory processing strategies in response to the historical fluctuations that the species has experienced, systematic changes in the way that the environment fluctuates can cause the organism to misinterpret change and behave maladaptively. This project considers the genetically encoded dynamic response strategies that enable living organisms to produce a response given a time series of sensed inputs. These dynamic response strategies can take into account the limited reliability of sensory input and changes in the frequency and size of environmental fluctuations. The project focuses on cellular dynamic response systems including simple gene regulation, regulation of interacting genes in a network, cellular sensory mechanisms, and competitive foraging. The mechanistic details of the dynamic response will be modeled using engineering methods and evolutionary outcomes will be determined using population genetic techniques. This project will combine powerful computational techniques from the engineering sciences with detailed knowledge of the constraints on evolving populations from the biological sciences. The engineering solutions will provide upper bounds on the range of improvement in dynamic response strategies that evolution can achieve. These limits will be used to evaluate whether non-optimal mechanisms are adequate for organisms to extract most of the resources available in the environment. This project is potentially transformative because the methods to be developed are expected to be broadly applicable across biological scales and to developmental, physiological, as well as behavioral responses. Broader Impact: One broader impact of this project involves training high school students in the scientific method and engineering principles. Four high school students enrolled in the Dos Peublos High School Engineering Academy will be recruited each year to participate in a summer internship program in co-PI Hespanha's lab. These students are already involved in an intensive engineering program where they learn calculus and computer programming. The student interns will learn to program robots to carry out cooperative and competitive tasks using use the iRobot Create platform. Students will learn to apply the scientific method to refine the performance of their algorithms. Students will apply the skills they learn in the summer as members of their scholastic robotics team. A second aspect of this project involves training undergraduate biology students from UCSB in theoretical biology. PI Proulx has already developed an undergraduate course on modeling behavioral dynamics using the Mathematica programming environment. Funding will support visits by world-class faculty to enrich this course with workshops in mathematical modeling of biological systems based on their own current research and provide participating students with immediate feedback on their modeling studies from visiting experts. The final broader impact of this project involves a Summer Internship Program for undergraduate students. This program provides opportunities for UCSB undergraduates and minority students from local community colleges, including Santa Barbara City College, to work together during the summer on research projects under the supervision of co-PI Hespanha and his graduate students. Participating graduate students will gain valuable mentoring experience.