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WILLIS, MURPHY, AND GUY REVIEWS IN FISHERIES SCIENCE TABLE 4 Summary of Correlation Coefficients (r) between Stock Density Indices of Predator or Prey Species and Other Parameters Predator Prey Species Parameter Species Parameter r Ref. Largemouth CPUE Bluegill PSD 0.71 Guy and Willis (1990)8 bass PSD PSD -0.83 Guy and Willis (1990) RSD-P Growth -0.64 Guy and Willis (1990) Largemouth PSD Crappie PSD -0.85 Gabelhouse (1984b)b bass RSD-P PSD -0.84 Gabelhouse (1984b)b Largemouth PSD Crappie CPUE 0.73 Boxrucker (1987)° bass RSD-P CPUE 0.88 Boxrucker (1987)° CPUE PSD 0.56 Boxrucker (1987) PSD PSD -0.56 Boxrucker (1987)° Largemouth CPUE Yellow perch PSD 0.81 Guy and Willis (1991a)d bass PSD PSD -0.82 Guy and Willis (1991 a)° PSD Growth -0.95 Guy and Willis (1991a)d Largemouth PSD Black Mean -0.81 Saffel et al. (1990)8 bass bullhead length Note: PSD =proportional stock density, RSD-P =relative stock density ofpreferred-length fish; CPUE _ catch per unit effort ° Impoundment size 1.2-5.1 ha. n Impoundment size O.~r10.5 ha. Impoundment size 3-106 ha. ° Impoundment size 0.9-27.9 ha. e Impoundment size 1.6.1 ha. In one of their assessments, they used 15 ha as the breakpoint at which expected inverse relationships between size structure of largemouth bass and bluegills could be expected. Gabelhouse <1984c) documented a case history in 34-ha Cowley State Fishing Lake (an impoundment), Kansas, where the fish community was dominated by ahigh-density largemouth bass population with low PSD and a Bluegill popu- lation with high PSD. Willis and Guy (1991) reported similar case histories for a largemouth bass/Bluegill community in 55-ha Lake Louise, South Dakota, and for a largemouth bass/yellow perch community in 28-ha Perch Lake (both waters are impoundments). The bottom line on most of the correlations we have presented is that most have quite a bit of unexplained variability. We contend that these correlations indicate that stock density indices are useful tools not only to reflect size structure, but also to reflect density and the rate functions. However, because of the inherent variability and possible confounding factors, stock density indices should be used in combi- nation with other assessment tools to properly evaluate a fish population or community. Such tools might include simple indices such as catch per unit effort (CPUE; Hubert, 1983) and fish condition (e.g., relative weight; Murphy et al., 1991), or more time-consuming analyses such as growth assessment and population or biomass estimates. 214