Final Publication: Goodwin, R.A., J.M. Nestler, J.J. Anderson, L.J. Weber, and D.P. Loucks. 2006. Forecasting 3-D fish movement behavior using a Eulerian-Lagrangian-agent method (ELAM). Ecological Modelling 192: 197-223
Abstract
We describe a Eulerian-Lagrangian-agent method (ELAM) for mechanistically decoding and forecasting 3-D movement patterns of individual fish responding to abiotic stimuli. A ELAM model is an individual-based model (IBM) coupling a (1) Eulerian framework to govern the physical, hydrodynamic, and water quality domains, (2) Lagrangian framework to govern the sensory perception and movement trajectories of individual fish, and (3) agent framework to govern the behavior decisions of individuals. The resulting ELAM framework is well suited for describing large-scale patterns in hydrodynamics and water quality as well as the much smaller scales at which individual fish make movement decisions. This ability of ELAM models to simultaneously handle dynamics at multiple scales allows them to realistically represent fish movements within aquatic systems. We introduce ELAMs with an application to aid in the design and operation of fish passage systems in the Pacific Northwest, USA.