Assessing length-related bias and the need for data standardization in the development of standard weight equations

The recently developed empirical percentile (EmP) method, a technique for deriving standard weight (W_s) equations, putatively reduces the length-related biases that often plague such equations. To determine whether the EmP method is superior to the regression line-percentile (RLP) method in reducing length-related biases, we developed new W_s equations by applying both methods to two morphologically distinct species, walleye Sander vitreus and black crappie Pomoxis nigromaculatus. We also investigated diagnostic approaches to provide quality control for weight-length data. We evaluated the new W_s equations with filtered independent data to determine which equation reduced length bias the most. We suggest a protocol for evaluating length-related bias using an independent data set. Our results showed that for randomly selected walleye populations, the RLP method did not have any length-related biases when relative weight (W_r) was plotted as a function of length. However, the W_r values calculated from the EmP W_s equations were length biased when the latter were applied to those same populations. Both methods generated W_s equations that were length biased when W_r was plotted as a function of length for black crappies. Further, the absolute difference in W_r between the RLP and EmP methods indicates that there is little difference between the methods as far as their relevance to management is concerned. Based on these results, we believethat revising existing W_s equations using the EmP method is unnecessary and that the RLP technique should remain the standard for developing W_s equations pending the development of an approach that clearly eliminates methodological length bias.