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<br />1 coefficient of vaziation (14.1 %). During a simulation, daily growth rate was calculated using a <br />' temperature-dependent growth equation: <br />' -0.279 + 0.0387 • tem - 0.000637 • tem 2 <br />( P P) <br />' Daily growth rate =baseline growth rate • (1) <br />0.283 <br />' where temp is daily water temperature, baseline growth rate is the growth rate assigned to the <br />larva at the beginning of the simulation, and 0.283 is the solution to Bestgen's (1996) <br />temperature- and ration-dependent growth equation at 24°C and high ration. <br />' Simulations were conducted using two different temperature regimes based on data from <br />the U.S. Geological Survey hydrologic gauge on the Green River neaz Jensen, Utah: a relatively <br />' warm thermal re ime observed durin summer 1994 and a substantiall cooler re ime observed <br />g g Y g <br />' in 1983, when temperatures were 6-10°C cooler for much of the season (Figure 5). <br />Because water temperatures change substantially throughout the season, temperatures and <br />predator size distributions experienced by Colorado squawfish larvae will be affected by the <br />1 timing of spawning and subsequent larval arrival in backwater nursery azeas. The arrival of <br />' larvae in backwaters varies among years from as early as 1 June to as late as 1 August. To <br />examine the effect of time of arrival on squawfish growth and survival we conducted simulations <br />' usin arrival times of 1 June 1 Jul and 1 Au t. <br />g ~ Y~ ~ <br /> <br />' Probability of Capture <br />The likelihood of a larva being eaten is the product of at least three probabilities: the <br />' probability of being encountered by a predator, the probability of being attacked if encountered, <br />' 10 <br /> <br />