Is Eye Allometry the Silver Bullet for Measuring Marine Fishes with a Single Camera?

Abstract

Reliable length frequency distributions are useful tools for the assessment and management of fish populations. However, in situ estimation of fish length with single-camera video systems may be inaccurate. The use of allometric changes of eye diameter (ED) and head height (HH) was proposed as a promising technique to estimate fish length from single-camera footage. However, the method, so far, has proven to be effective for a limited number of species and families, and the replicability among taxa remains uncertain. We described the allometric patterns of eye diameter and head height for a set of Osteichthyes and Chondrichthyes bearing heterogeneous morphological, taxonomical, and habitat-type features from northern Patagonia, Argentina. To assess the usefulness of the method, we regressed fish length on the HH:ED ratio for each of 12 common species by using artificial neural network models and compared the results with those obtained by standard regression models. We found relevant variability in allometry among the species analyzed and described four general cases. Furthermore, artificial neural network models outperformed conventional regression, although both models converged to similar results for several species. Overall, our findings highlighted the utility of the allometry method and suggested an association of both allometric patterns and model performance with fish morphology and habitat type. Whereas osteichthyan reef species were highly suitable for using this technique, models obtained for chondrichthyans and fusiform body-shaped species were less accurate. Our findings have practical implications for the estimation of fish length using single-camera systems and provide a framework to understand the differential suitability of the allometric approach.