Development of a robust classifier of freshwater residence in barramundi (Lates calcarifer) life histories using elemental ratios in scales and boosted regression trees

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Abstract
Field and experimental studies showed that solution-based analysis of scales could be used to discriminate the long-term freshwater residents in the coastal fishery for catadromous barramundi. A new, robust classification technique was developed using boosted regression trees (MART) and its performance was compared with traditional linear discriminant analysis (LDA). The non-parametric MART had errors 33–81% less than LDA, and could account for non-linear relationships and interactions among elemental ratios. The best model used Sr : Ca, Ba : Ca, Fe : Ca and Mn : Ca in scales as predictors of salinity regime. Analysis of scales collected repeatedly from sub-adult fish of known environmental history showed the MART classifier could identify fish of freshwater origin until at least 10 months residence in seawater, and possibly several years, but scale growth rate could affect the temporal stability of the classifier after that time. The experiment indicated an approximate fourfold rise in Sr : Ba ratios in new scale margins, which were strongly classified by the MART as coming from saltwater fish, but inner scale sections of the same scales were still correctly classified as coming from freshwater fish. We conclude that solution-based elemental analyses of whole scales, and also annuli within scales, could offer a cost-effective, non-destructive technique to help understand the mechanisms causing enhanced year-class strength following high freshwater outflows.