Evaluation of muscle lipid extraction and non-lethal fin tissue use for carbon, nitrogen, and sulfur isotope analyses in adult salmonids.

RATIONALE: Chemical lipid extraction or using alternative tissues such as fish fin as opposed to muscle may alter isotopic ratios and influence interpretations of δ13 C, δ15 N, and previously unassessed δ34 S values in stable isotope analyses (SIA). Our objectives were to determine if lipid extraction alters these isotope ratios in muscle, if lipid normalization models can be used for lipid-rich salmonids, and if fin isotope ratios are comparable with those of muscle in adult salmonids. METHODS: In six adult salmonid species (n = 106) collected from Lake Ontario, we compared three isotope ratios in lipid-extracted (LE) muscle with bulk muscle, and LE muscle with fin tissue, with paired t-tests and linear regressions. We compared differences between δ13 C values in LE and bulk muscle with predicted values from lipid normalization models and the log-linear model of best fit and determined model efficiency. RESULTS: The δ15 N values in LE muscle increased (<1‰) relative to bulk muscle for most salmonids, with relationships nearing 1:1. There were either no differences or strong 1:1 relationships in δ34 S values between species-specific bulk and LE muscle. One lipid normalization model had greater model efficiency (97%) than the model of best fit (94%). Fin had higher δ13 C values than LE muscle while δ15 N trends varied (<1‰); however, both isotope ratios had either no or weak linear relationships with fin and LE muscle within species. The δ34 S values in fin were similar to those in LE muscle and had strong 1:1 relationships across species. CONCLUSIONS: We recommend using the lipid normalization model to adjust for δ13 C values in lipid-rich muscle (C:N >3.4). LE muscle could be used without δ15 N or δ34 S adjustments, but the minimal increase in δ15 N values may affect SIA interpretation. With high unexplained variability among adult species in fin-muscle δ13 C and δ15 N relationships, species-specific fin-muscle adjustments are warranted. No fin-muscle tissue adjustment would be required for δ34 S values.

Application of machine learning to identify predators of stocked fish in Lake Ontario: using acoustic telemetry predation tags to inform management.

Understanding predator-prey interactions and food web dynamics is important for ecosystem-based management in aquatic environments, as they experience increasing rates of human-induced changes, such as the addition and removal of fishes. To quantify the post-stocking survival and predation of a prey fish in Lake Ontario, 48 bloater Coregonus hoyi were tagged with acoustic telemetry predation tags and were tracked on an array of 105 acoustic receivers from November 2018 to June 2019. Putative predators of tagged bloater were identified by comparing movement patterns of six species of salmonids (i.e., predators) in Lake Ontario with the post-predated movements of bloater (i.e., prey) using a random forests algorithm, a type of supervised machine learning. A total of 25 bloater (53% of all detected) were consumed by predators on average (± S.D.) 3.1 ± 2.1 days after release. Post-predation detections of predators occurred for an average (± S.D.) of 78.9 ± 76.9 days, providing sufficient detection data to classify movement patterns. Tagged lake trout Salvelinus namaycush provided the most reliable classification from behavioural predictor variables (89% success rate) and was identified as the main consumer of bloater (consumed 50%). Movement networks between predicted and tagged lake trout were significantly correlated over a 6 month period, supporting the classification of lake trout as a common bloater predator. This study demonstrated the ability of supervised learning techniques to provide greater insight into the fate of stocked fishes and predator-prey dynamics, and this technique is widely applicable to inform future stocking and other management efforts.

Accidental bait: do deceased fish increase freshwater turtle bycatch in commercial fyke nets?

Bycatch of turtles in passive inland fyke net fisheries has been poorly studied, yet bycatch is an important conservation issue given the decline in many freshwater turtle populations. Delayed maturity and low natural adult mortality make turtles particularly susceptible to population declines when faced with additional anthropogenic adult mortality such as bycatch. When turtles are captured in fyke nets, the prolonged submergence can lead to stress and subsequent drowning. Fish die within infrequently checked passive fishing nets and dead fish are a potential food source for many freshwater turtles. Dead fish could thus act as attractants and increase turtle captures in fishing nets. We investigated the attraction of turtles to decomposing fish within fyke nets in eastern Ontario. We set fyke nets with either 1 kg of one-day or five-day decomposed fish, or no decomposed fish in the cod-end of the net. Decomposing fish did not alter the capture rate of turtles or fish, nor did it alter the species composition of the catch. Thus, reducing fish mortality in nets using shorter soak times is unlikely to alter turtle bycatch rates since turtles were not attracted by the dead fish. Interestingly, turtle bycatch rates increased as water temperatures did. Water temperature also influences turtle mortality by affecting the duration turtles can remain submerged. We thus suggest that submerged nets to either not be set or have reduced soak times in warm water conditions (e.g., >20 °C) as turtles tend to be captured more frequently and cannot withstand prolonged submergence.