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<br />ISMP backwater sampling evaluation <br />where green sunfish density was number offish per 10 m2. Re-ordering the logistic equation to <br />yield probability of detection given an investigator-chosen green sunfish density value is of the <br />form: <br />pY = <br />1 <br />1 + exp(1.5935 - 2.7317(green sunfish density) <br />where green sunfish density was number of fish per 10 m2. <br />(4) <br />This relationship again assumes the average backwater condition (e.g., surface area, <br />depth) in the Colorado River in the Grand Valley. Solutions to the logistic regression equation <br />over a range of green sunfish density values suggested that the probability that the ISMP <br />technique would detect sunfish in a backwater was relatively low even when green sunfish were <br />abundant (Fig. 11). For example, a 50 % probability of detection in backwaters was achieved <br />only after green sunfish abundance exceeded 0.58 per 10 m2 backwater surface area, the same <br />value as for bass. Again assuming that the average backwater surface area in the Grand Valley in <br />1997 and 1998 was 718 m2, this translates into an abundance level of 42 green sunfish in the <br />backwater in order to achieve a 50 % probability of detection. The positive intercept in this <br />relationship suggested that there was a small probability of detecting green sunfish with ISMP <br />sampling when estimated abundance was low. A more reliable 90 % probability of detection <br />level for largemouth bass and green sunfish was achieved only after their density in backwaters <br />exceeded 1.4 per 10 m2 , or 101 fish in a 718 m2 backwater. <br />1 -14-