HR: 09:45h
AN: B41A-06    [Abstracts]
TI: Spatially Explicit, Individual-Based Models Can Predict Fish Population Responses to Spatio-Temporal Variation in Physical Processes
AU: * Harvey, B C
EM: bch3@humboldt.edu
AF: USFS Redwood Sciences Lab, 1700 Bayview Drive, Arcata, CA 95521 United States
AU: Railsback, S F
EM: LRA@northcoast.com
AF: Lang, Railsback and Associates, 250 California Avenue, Arcata, CA 95521 United States
AB: Spatially explicit, individual-based models of fish populations can provide insights into the interactions of physical and biological processes in rivers. These models can include virtual environments with many of the complexities of real river habitat, including spatial and temporal variation in hydraulic conditions, cover, predation risk, and competition for resources. Model fish can use realistic behaviors to adapt to their physical environment, especially by moving to habitats that offer relatively high fitness potential. We used an individual-based model of stream trout with a daily time step to estimate responses to variation in physical conditions and processes at various spatial scales. Within simulated reaches, greater physical heterogeneity at the habitat-cell scale produced populations with greater variation in size and age distributions and less variable overall abundance. Realistic variation in reach-scale physical factors such as turbidity and redd scour probability had strong consequences for fish abundance and biomass. However, time lags in some biological responses reached several years. Sensitivity analyses of the model highlight the need for greater understanding of abiotically driven spatial and temporal variation in key biological processes.
DE: 9810 New fields (not classifiable under other headings)
SC: Biogeosciences [B]
MN: 2005 Joint Assembly