Differentiating Between Direct (Physiological) and Food-Chain Mediated (Bioenergetic) Effects on Fish in Metal-Impacted Lakes
Bibliographic record
Abstract
The objectives of this field project were to test relationships between the physiological and population status of indigenous fish and (a) ecological factors (habitat quality, food resources), (b) toxicological factors (ambient and tissue metal concentrations), and (c) metal detoxification factors (metallothionein induction and subcellular metal partitioning). The sentinel species, yellow perch (YP: Perca flavescens), was collected from lakes with contrasting metal levels located on the Canadian Precambrian Shield, downwind and downstream from metal smelters. In lakes at the high end of our exposure gradient, metals (Cu, Ni, and especially Cd) accumulate in YP to concentrations well above background tissue values; increases in tissue Zn concentrations were much more modest, despite the existence of a very marked gradient in ambient [Zn]. Metal accumulation in YP is accompanied by metallothionein induction, but all evidence to date suggests that metal detoxification by metallothionein is incomplete. Indeed, direct effects of metal toxicity are detected at multiple levels of biological organization, from effects at the cellular level, to effects in organs and tissues, to individuals and populations, in a pattern linked to accumulated metal concentrations (i.e., along the contamination gradient). In addition to direct or physiological effects, we also documented indirect, food-web-mediated effects of metals on YP in the most contaminated lakes. The most common indication of such indirect effects on YP is severely stunted growth coupled with a high degree of zooplankton dependence throughout their life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".