Otolith‐Chemistry‐Based Discrimination of Wild‐ and Hatchery‐Origin Steelhead across the Lake Michigan Basin. (14th June 2018)

• Record Type: Journal Article
• Authors: Watson, Nicole M.; Prichard, Carson G.; Jonas, Jory L.; Student, James J.; Pangle, Kevin L.
• Is Part Of: North American journal of fisheries management. Volume 38:Number 4(2018)
• Page Start: 820
• Page End: 832
• Publication Date: 2018-06-14
• Subjects: Fishery management -- United States -- Periodicals; 333.956097305
• DOI: 10.1002/nafm.10178
• Languages: English
• ISSNs: 0275-5947

Abstract

Abstract: Effective conservation and management of mixed‐stock fisheries depends upon accurate stock identification of individual fish. We evaluated the utility of otolith chemical analysis as an approach to classify juvenile, premigratory steelhead Oncorhynchus mykiss collected in tributaries of Lake Michigan as either wild or hatchery origin. Two primary hypotheses proposed were that otolith chemistry can be used (1) to classify juvenile, hatchery‐origin steelhead to the correct hatchery of origin and (2) to correctly classify stream‐collected juvenile steelhead as wild or hatchery origin. Using laser‐ablation inductively coupled plasma mass spectrometry, we analyzed the concentrations of seven elements (using 25 Mg, 55 Mn, 65 Cu, 66 Zn, 88 Sr, 137 Ba, 208 Pb) in the otoliths of juvenile steelhead collected from five hatcheries and 25 streams in the Lake Michigan basin. When discriminating among hatcheries, only 4.41% of fish misclassified to an alternate hatchery when subjected to the best random forest classification algorithm that included all elements as predictor variables. Distinct chemical signatures between fish of wild and hatchery origin supported 100% classification accuracies of known‐wild, age‐0 steelhead as wild origin for 19 of the 25 streams sampled. Misclassification of wild, age‐0, and hatchery‐origin fish, which tended to occur for streams that were located in close proximity to the hatchery, never exceeded 3.4% for a given stream. Our findings demonstrate highly successful discrimination of hatchery‐origin and wild juvenile steelhead across a broad geographic range. Applying the classification algorithms developed herein to unknown‐origin steelhead provides the ability to infer survival of year‐classes from specific hatcheries. Further, the ability to differentiate hatchery‐ and wild‐origin fish will assist in stock assessment efforts allowing for increased effectiveness of conservation and management of the species.