An Evaluation of Relative Weight as an Indicator of Body Composition and Nutritional Status in Wild Fish
Condition indices are widely used to generate biological insight. However, purported relationships to indices are imprecise or inconsistent in the wild. I investigated factors influencing relative weight (Wr), a condition index commonly applied to fish.
I first examined the relationship of Wr to physiology in two bluegill Lepomis macrochirus populations over a year. I regressed tissue composition (percentages of lipid, protein and water) and organ indices (liver-, gonad-, and viscerosomatic indices) on Wr. The regression model had little explanatory power (adjusted R2 = 0.14). Lipid was most influential (partial R2 = 0.11), but correlation strength fluctuated by season and population.
To test the generality of these results, I performed a similar regression on a bluegill population with higher average Wr. Again, variables were not well correlated to Wr (adjusted R2 = 0.13). Combining comparable data sets increased Wr range 64% but explanatory power was low (adjusted R2 = 0.41) Both studies showed that expected correlations of physiological variables to Wr can be confounded in natural environments.
To examine differences between natural and laboratory environments, I manipulated initial Wr and ration of juvenile bluegills. Although organ indices and tissue composition of all groups changed in time ((Wilks' Δ > 0.387, P > 0.03), no temporal pattern matched to Wr. At termination, all variables showed high correlations to Wr (r2 > 0.64). Correlation strength increased with time in the laboratory. Both ration and environment influenced correlations.
Lastly, I examined differences in interpretation of Wr for chain pickerels Esox niger, largemouth bass Micropterus salmoides, and black crappies Pomoxis nigromaculatus. Regression models were compared to concurrent bluegill models. Piscivore models fit well (adjusted R2 > 0.50), whereas bluegill models had the lowest explanatory power (adjusted R2 = 0.13 and 0.14). Ecological specialization affected correlations to Wr.
Theoretically, condition index values are determined by resource acquisition versus expenditure. Exact physiological expression is determined by life history and performance. Condition indices are imprecise predictors but track net somatic investment with great generality. Ancillary data, such as growth or length-at-maturity, may clarify interpretation. Condition indices should be used as qualitative monitoring tools, not omnibus physiological predictors.