Broad-scale mercury bioaccumulation patterns in two freshwater sport fishes: testing the role of growth dilution in a warming climate
Bibliographic record
Abstract
Abstract Sport fishes at the apex of aquatic food webs are indicators of mercury in the environment. However bioaccumulation of mercury in fish is a complex process that varies in space and time. Both large-scale climatic and environmental, as well as biological factors are drivers of these space-time variations. In this study, we avail a long-running monitoring program from Ontario, Canada to better understand spatiotemporal variations in fish mercury bioaccumulation. Focussing on two common large-bodied fishes (Walleye and Northern Pike), the data were first stratified by latitudinal zone (north, mid, and south) and eight temporal periods (between 1975 & 2015). A series of linear mixed-effects models (LMEMs) with latitudinal zone, time period, and their interactions as random effects were used to capture the spatial, temporal, and spatiotemporal variations in mercury bioaccumulation. The random slopes from the best-fitting LMEM were used to define bioaccumulation index and capture trends in space and time. Given the generally warming climate trend over the past 45 years, the role of growth dilution in modulating the bioaccumulation trends was also evaluated. The full model comprising of space, time and space-time interactions was the best-fit with interaction effects explaining most of the variation. Spatiotemporal trends showed overall similar patterns for both species. Growth dilution in conjunction with estimated rates of warming for different latitudinal zones failed to explain the spatiotemporal trends. Temporal trends showed contrasting bioaccumulation patterns-increasing in Northern Pike and decreasing in Walleye, suggesting temperature-driven growth dilution is more likely in latter. However, a space-for-time substitution revealed only a weak presence of growth dilution in Walleye, and it was not attributable to temperature differences. Overall, our study summarizes broad-scale variations in fish mercury and explores the role of growth dilution in shaping the observed patterns.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".