Fish stocking occurs in aquatic systems around the world for conservation purposes, to create or enhance recreational fisheries, and to enhance wild-catch commercial fisheries. Identifying and quantifying the contribution of stocking efforts to the wild population is crucial to informing these management objectives. Existing provenance determination methods trade off accuracy, replicability, and cost-effectiveness at fishery-relevant scales.
Extensive stocking of unmarked barramundi (Lates calcarifer) fingerlings into Queensland waterways has been a challenge for accurate stock assessment. We present results of an extensive, multidisciplinary approach to provenance determination using a case study of >800 barramundi in the Dry Tropics region of northern Australia. The performance of a novel application of Near Infra-Red Spectroscopy (NIRS) is compared to two established methods for fish provenance: otolith microchemistry and genetic parentage analysis using microsatellites.
As a result of distinct differences in the trace element composition of wild and hatchery environments, the otolith microchemistry method was able to provide extremely high provenance resolution (>99% accuracy) using just four trace elements (manganese, magnesium, barium, and strontium). The microsatellite parentage analysis method had a lower overall accuracy (95%), likely as a result of genetic introgression in this system. Provenance determination using otolith NIRS was not successful in this instance. We propose that the provenance-related differences in otolith microchemical composition, or their proxies, fell below the detectability limit of the NIRS hyperspectral sensor used in this study, or that the sample size was insufficient to resolve provenance related spectral differences from spectral “noise”. We identify directions for future research to improve the accuracy of NIRS of otoliths for provenance determination, in particular regarding sensor specifications and spectral noise. Once these limitations are addressed, otolith NIRS has exciting potential for cost-effective, scalable application to provenance determination.