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1 <br />1 <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br />ii <br />1 <br /> <br /> <br /> <br /> <br />Structure and Components of The Mechanistic Simulation Model <br />The conceptual life-history model illustrates the larger framework within which the <br />mechanistic simulation model was used to evaluate the effects of environmental factors on <br />survival and growth ofage-0 Colorado squawfish during their first summer. Age-0 fish were <br />chosen as the subject of study for the simulation model for several reasons. First, recruitment <br />from eazly life stages has been shown to be an important factor in determining year-class strength <br />in other fishes (Houde 1987). Second, eazly life stages of Colorado squawfish have been the <br />subject of numerous field and laboratory studies. Third, we intended to collect empirical data for <br />construction of the model by conducting pertinent experiments, and hatchery-reazed age-0 <br />Colorado squawfish were readily available. During model construction, results of these <br />experiments were integrated with field observations; thus the model has a foundation grounded <br />in empirical data which increases the likelihood that its predictions aze ecologically relevant. <br />An individual-based model (IBM) structure was selected as the fundamental basis for the <br />simulation model because we suspected that individual differences in size and growth of larvae <br />may affect recruitment patterns as much or more than average differences of populations (Rice <br />et al.1993; DeAngelis and Rose 1992). The IBM that was ixutially proposed had components <br />that (a) linked river dischazge to prey availability for larvae, (b) incorporated starvation effects on <br />larvae, (c) allowed multiple species to prey on larval Colorado squawfish, and (d) simulated the <br />influence of temperature regime on growth of larvae (Figure 2). Every effort was made to <br />identify pre-existing data that could be used to derive quantitative relationships relevant to each <br />component of the IBM. However, during eazly stages of IBM development, it became evident <br />6 <br /> <br />