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(Elevation) - 5.36 (Gradient) - 30.43. This model was significantly <br />correlated to trout standing stock (F = 14.93; P < .000; r = .77) and <br />accounted for 56% of the variation in trout standing stock. The nonforest <br />stream model, based upon 44 stream reaches with complete data for the model <br />variables was: Y = 1.56 (% Bedrock and Boulders) - 5.10 (Gradient) - 16.39 <br />(Order) +65.73. This model was significantly correlated to trout standing <br />stock (F = 24.40; P < .000; r = 0.80) and accounted for 62% of the variation <br />in trout standing stock. The SRICSI was not included in either model due <br />to the effect of colinearity with the variables in the equation and its <br />resultant low contribution to model performance. <br />DISCUSSION <br />The primary objective of this study was to develop a model to predict <br />trout standing stock based upon easily measured components of habitat. The <br />model variables gradient, order and reach elevation can be determined from <br />topographic maps. Percent bedrock and boulder can be estimated visually or <br />by a transect method (Duff and Cooper 1978). <br />Eifert and Wesche (1982) and Wesche (1980) found that instream <br />rubble-boulder area displayed significant positive relationships to trout <br />standing stock. Highest standing stocks were associated with highest <br />rubble-boulder cover areas (Eifert and Wesche 1982). Our study has no direct <br />measure of rubble-boulder areas, but estimates were available of the percent <br />of the reach comprised of bedrock-boulder. Percent bedrock-boulder was <br />significantly correlated, (F = 26.72; P < 0.000; r = 0.61), with trout <br />standing stock in nonforest streams, but not significantly correlated in <br />forested streams. However, both of our models use percent bedrock-boulder. <br />As order increased, Platts (1979) found fish standing stock increased <br />in Idaho. In our study, order was negatively correlated with trout standing <br />crop in nonforest streams. The higher order streams (4th) in the nonforest <br />areas were located in the Bighorn Basin of north central Wyoming. In the <br />Bighorn Basin, streams often approach or exceed the critical maximum <br />temperature limits for trout production.- <br />- In forest area streams, elevation was positively correlated with trout <br />standing crop. As elevation increases in these streams the amount of open, <br />unshaded area tends to increase and the substrate diversity tends to increase, <br />which may result in greater trout production. <br />Platts (1979) observed that as gradient decreased, trout standing stock <br />increased. Similar results were found in this study. Trout require resting <br />habitat and hiding areas, both in low supply in steep rapidly flowing streams., <br />Binns' (1979) model with nine habitat variables was highly correlated to <br />trout standing crop (r = 0.98). None of the variables used by Binns (1979) <br />were used in the modeling effort due to ~he lack of information or the degree <br />of difficulty in data collection. His r value (0.96) was much higher than <br />the best for models presented here. For predicting trout standing stock in <br />24 <br />