Animal Behavior Drift Feeding & Habitat Selection Habitat selection is a cornerstone of theoretical ecology and of great importance to understanding how population distribution patterns affect our applied conservation efforts.  For drift feeding species, such as Salmonids,  preferred locations are based on a collage of local physical gradients, resource distributions and niche dynamics (e.g., intra-specific hierarchies, competition and coexistence). Using data gathered from the literature and the field we are currently testing existing sensory-based models of drift feeding behavior.  Our objective is to incorporate local physical data and internal state into the foraging behavior of sensitive species in an effort to improve habitat selection forecasts.   Animal Group Behavior While social environments can provide individuals with added security from predators, or assist in finding food patches, individuals must often contend with competitive interactions and balance their vigilance levels accordingly.  In collaboration with colleagues at the University of Washington we are modeling collective behavior to determine how individuals manage to extract pertinent information from the cacophony of signals and cues that surround them. Understanding how social animals identify influential neighbors from the crowd remains an important, and as of yet, unresolved question. Hudsonian godwits foraging along a tide line on the island of Chiloe, Chile. Photograph by Bob Christensen. Journal Publications Lemasson, B. H., Anderson, J. J., and Goodwin, R. A. (2009). “Collective motion in animal groups from a neurobiological perspective: The adaptive benefits of dynamic sensory loads and selective attention.” Journal of Theoretical Biology, 261(4), 501–510. Refereed Conference Proceedings Anderson, J. J., Lemasson, B. H., and Goodwin, R. A. (2009). “Advantages of a retinal-based model for studying swarm cognition.” Proceedings of the Swarm Cognition Workshop, Annual Meeting of the Cognitive Science Society (CogSci 2009), 29 July – 1 August 2009, Amsterdam, The Netherlands. Goodwin, R. A., Lemasson, B. H., Anderson, J. J., and Bridges, T. S. (2008). “Discerning properties of a self-organizing network (swarm) shaping its structure, function, and resilience.” Proceedings of the 26th Army Science Conference, 1–4 December 2008, Orlando, Florida. Lemasson, B. H., Anderson, J. J., and Goodwin, R. A. (2008). “Communication properties of self-organizing networks (swarms) as inferred from optical mechanics.” Proceedings of the 26th Army Science Conference, 1–4 December 2008, Orlando, Florida.   Fish Swimming Behavior in Artificial Environments Migratory fish species frequently encounter barriers in the form of dams, power stations and pumping plants.  Such artificial barriers can significantly impact fish populations by reducing the ability of individuals to move between adjacent habitats.  Working with collaborators from Utah State University and the Bureau of Reclamation I used a combination of video analysis and individual-based modeling to predict the energetic costs of barrier avoidance behaviors demonstrated by rainbow trout using virtual agents. Example of several simulated fish responding to their local environment  according to different prescribed behaviors observed in the laboratory.  In this image, fish drift with the current in a virtual channel and must avoid the diagonal barrier to safely pass through the system (Lemasson et al., 2008). Journal Publications Lemasson, B. H., Haefner, J. W., and Bowen, M. D. (2008). “The effect of avoidance behavior on predicting fish passage rates through water diversion structures.” Ecological Modelling, 219(1–2), 178–188.