A field test of the use of pop-off data storage tags in freshwater fishes

Realized thermal niche approach eliminates temperature bias in bioenergetic model estimates

Bioenergetics models estimate ectotherm growth, production, and prey consumption - all key for effective ecosystem management during changing global temperatures. Based on species-specific allometric and thermodynamic relationships, these models typically use the species' lab-derived optimum temperatures (physiological optimum) as opposed to empirical field data (realized thermal niche) that reflect actual thermal experience. Yet, dynamic behavioral thermoregulation mediated by biotic and abiotic interactions may provide substantial divergence between physiological optimum and realized thermal niche temperatures to significantly bias model outcomes. Here, using the Wisconsin bioenergetics model and in-situ year-round temperature data, we tested the two approaches and compared the maximum attainable lifetime weight and lifetime prey consumption estimates for two salmonid species with differing life histories. We demonstrate that using the realized thermal niche is the better approach because it eliminates significant biases in estimates produced by the physiological optimum. Specifically, using the physiological optimum, slower-growing Salvelinus namaycush maximum attainable lifetime weight was underestimated, and consumption overestimated, while fast-growing Oncorhynchus tshawytscha maximum attainable weight was overestimated. While the physiological optimum approach is useful for theoretical studies, our results demonstrate the critical importance that models used by management utilize up-to-date system- and species-specific field data representing actual in-situ behaviors (i.e., realized thermal niche).

Non-Lethal Sampling Supports Integrative Movement Research in Freshwater Fish

Freshwater ecosystems and fishes are enormous resources for human uses and biodiversity worldwide. However, anthropogenic climate change and factors such as dams and environmental contaminants threaten these freshwater systems. One way that researchers can address conservation issues in freshwater fishes is via integrative non-lethal movement research. We review different methods for studying movement, such as with acoustic telemetry. Methods for connecting movement and physiology are then reviewed, by using non-lethal tissue biopsies to assay environmental contaminants, isotope composition, protein metabolism, and gene expression. Methods for connecting movement and genetics are reviewed as well, such as by using population genetics or quantitative genetics and genome-wide association studies. We present further considerations for collecting molecular data, the ethical foundations of non-lethal sampling, integrative approaches to research, and management decisions. Ultimately, we argue that non-lethal sampling is effective for conducting integrative, movement-oriented research in freshwater fishes. This research has the potential for addressing critical issues in freshwater systems in the future.

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.