Environmental Complexity Lab

Civil and Environmental Engineering
Stanford University

Contact:

Nicholas T. Ouellette
Department of Civil and Environmental Engineering
Stanford University

Jerry Yang and Akiko Yamazaki Environment and Energy Building
Room 153
473 Via Ortega
Stanford, CA 94305

Tel: (650) 723-4860
Fax: (650) 725-9720
nto -at- stanford.edu

Research

Collective Animal Behavior

From sheets of crawling cells to pods of whales, every size scale in biology shows remarkable self-organized collective behavior. Bird flocks, fish schools, and ungulate herds have fascinated scientists from a wide range of disciplines for many reasons. Biologists, for example, may be interested in understanding the pressures that drive aggregation, while engineers may hope to exploit self-organized collective behavior as a biomimetic design principle.

Swarm Trajectories

But even though there is broad interest in collective animal behavior, surprisingly little empirical data exists for real animals. We have therefore begun working with insect swarms in the laboroty in order to fill this gap. We maintain a breeding colony of the non-biting midge Chironomus riparius in our lab. Every evening at dusk, the males of the colony form a mating swarm, or lek, that may contain anywhere from a few individuals to over a hundred. Using the same stereoimaging hardware and software we use to study turbulent flow, we measure the trajectories and kinematics of each individual midge in the swarm. We are currently studying both the large-scale emergent behavior of the swarms and trying to extract the low-level inter-individual behavior. We aim to test current models of collective animal behavior, and to propose new models based on our measurements.

In parallel with our experiments, we are also studying collective behavior numerically using canonical models. We are interested in the influence of spatiotemporally correlated flow fields (such as turbulent flow) on the model behavior, since real flocking animals in nature live in strongly fluctuating but non-random environments. We are also studying the ways in which flocks interact with obstacles, including solid objects or other flocks, in an effort to understand potential analogies with granular systems.

Representative Publications

D. H. Kelley and N. T. Ouellette, "Emergent dynamics of laboratory insect swarms," Sci. Rep. 3, 1073 (2013).

R. M. Lee, D. H. Kelley, K. N. Nordstrom, N. T. Ouellette, and W. Losert, "Quantifying stretching and rearrangement in epithelial sheet migration," New J. Phys. 15, 025036 (2013).

N. Khurana and N. T. Ouellette, "Stability of model flocks in turbulent-like flow," New J. Phys. 15, 095015 (2013).

P. W. Miller and N. T. Ouellette, "Impact fragmentation of model flocks," Phys. Rev. E 89, 042806 (2014).

J. G. Puckett, D. H. Kelley, and N. T. Ouellette, "Searching for effective forces in laboratory insect swarms," Sci. Rep. 4, 4766 (2014).

J. G. Puckett and N. T. Ouellette, "Determining asymptotically large population sizes in insect swarms," J. R. Soc. Interface 11, 20140710 (2014).

N. T. Ouellette, "Empirical questions for collective-behaviour modelling," Pramana - J. Phys. 84, 353-363 (2015).

J. G. Puckett, R. Ni, and N. T. Ouellette, "Time-frequency analysis reveals pairwise interactions in insect swarms," Phys. Rev. Lett. 114, 258103 (2015).

R. Ni, J. G. Puckett, E. R. Dufresne, and N. T. Ouellette, "Intrinsic fluctuations and driven response of insect swarms," Phys. Rev. Lett. 115, 118104 (2015).

R. Ni and N. T. Ouellette, "Velocity correlations in laboratory insect swarms," Eur. Phys. J. Special Topics 224, 3271-3277 (2015).

D. Gorbonos, R. Ianconescu, J. G. Puckett, R. Ni, N. T. Ouellette, and N. S. Gov, "Long-range acoustic interactions in insect swarms: An adaptive gravity model," New J. Phys. 18, 073042 (2016).