A Spatially and Temporally Explicit, Individual-Based, Life-History and Productivity Modeling Approach: HexSim for Aquatic Populations

Realized life history expression and productivity in aquatic species, and salmonid fishes in particular, is the result of multiple interacting factors including genetics, habitat, growth potential and condition, and the thermal regime individuals experience, both at critical stages and throughout development.  Individual fishes, each with their inherited propensities and characteristics, experience spatially and temporally specific conditions throughout their lives that influence growth, movement, and life history “decisions”.  Modeling the interaction of these factors at the (potentially) broad spatial and temporal scales at which individuals carry out their life histories is a challenge.  There are individual-based modeling approaches which are not spatially-explicit (or limited to restricted and specific spatial domains), spatially-explicit models that are not individual-based, and “spatially-explicit”, individual-based models that neglect or simplify the temporal specificity of spatially-explicit conditions.  HexSim is a spatially-explicit, individual-based, multi-species computer simulation designed to model terrestrial wildlife population dynamics and interactions.  HexSim treats space as a series of continuous hexagonal grids that individuals experience and interact with over discrete time steps.  The individual-based modeling modules in HexSim are robust and allow for detailed parameterization of individuals, populations, and events.  We are presenting a modification of HexSim for aquatic populations.  The unique spatial constraints of stream system modeling, and modifications to the simulation model necessary for inclusion of relevant aspects of fish biology and behavior, will be discussed.  Our initial goal is to predict life history expression and production of steelhead (Oncorhynchus mykiss) in the John Day River basin, Oregon.  Development of spatially and temporally continuous parameter datasets (e.g. water temperature and food availability) for the John Day will also be presented.