Previous research has demonstrated a large movement of hatchery-reared Chinook salmon (Oncorhynchus tshawytscha) from Lake Huron to Lake Michigan, suggesting the potential for wild fish to exhibit similar movement patterns. We assessed the feasibility of using otolith microchemistry to estimate the natal source composition of wild Chinook salmon in Lake Michigan and evaluate interbasin movement. Otolith pairs were extracted from juvenile and adult fish collected in 2015 and 2016 from Great Lakes tributaries. Otoliths were analyzed using laser ablation inductively coupled plasma mass spectrometry to determine trace element concentrations, and four multivariate classification algorithms were evaluated for classification accuracy. Juvenile data reclassified to their natal regions with up to 89% success on a basin level, with a random forest approach performing the best among all models. Assigning adults to their natal origins resulted in more success on a basin-wide scale (74% to 88%) compared with a regional scale (32% to 51%), but success was still below juvenile reclassification accuracy. Our findings suggest that otolith microchemistry can be used to estimate wild Chinook salmon interbasin movement and that classification accuracy can be improved by matching juvenile and adult year classes in our assessment samples. Ultimately, we intend to use these models to assess the effects of wild Chinook salmon interbasin movement on Lake Michigan predatory demand and evaluate the risks of various stocking alternatives.
Effective water quality management depends on enactment of appropriately designed monitoring programs to reveal current and forecasted conditions. Because water quality conditions are influenced by numerous factors, commonly measured attributes such as total phosphorus (TP) can be highly temporally varying. For highly varying processes, monitoring programs should be long-term and periodic quantitative analyses are needed so that temporal trends can be distinguished from stochastic variation, which can yield insights into potential modifications to the program. Using generalized additive mixed modeling, we assessed temporal (yearly and monthly) trends and quantified other sources of variation (daily and subsampling) in TP concentrations from a multidecadal depth-specific monitoring program on Big Platte Lake, Michigan. Yearly TP concentrations decreased from the late 1980s to late 1990s before rebounding through the early 2000s. At depths of 2.29 to 13.72 m, TP concentrations have cycled around stationary points since the early 2000s, while at the surface and depths ≥ 18.29 concentrations have continued declining. Summer and fall peaks in TP concentrations were observed at most depths, with the fall peak at deeper depths occurring 1 month earlier than shallower depths. Daily sampling variation (i.e., variation within a given month and year) was greatest at shallowest and deepest depths. Variation in subsamples collected from depth-specific water samples constituted a small fraction of total variation. Based on model results, cost-saving measures to consider for the monitoring program include reducing subsampling of depth-specific concentrations and reducing the number of sampling depths given observed consistencies across the program period.
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