Bibliographic record
Abstract
Altering food web structure has been shown to influence mercury (Hg) concentrations in sport fish. Here, we describe a whole-system manipulation designed to assess the effectiveness of stocking relatively high quality, low Hg prey (rainbow trout, Oncorhynchus mykiss), as means of increasing northern pike (Esox lucius) growth to reduce Hg concentrations. A replicated pond experiment served as a reference for the lake experiment, and provided information to parameterize bioenergetics simulations. Results indicate that stocking relatively high quality, low Hg prey is a rapid and effective method to reduce sport fish Hg concentrations by up to 50% through an increase in individual northern pike biomass. Large northern pike, those fish that tend to be the most contaminated, were affected most by the manipulation. The observed declines in northern pike Hg concentrations indicate that stocking might be used to reduce Hg concentrations in sport fish prior to harvest. However, after one year, northern pike Hg concentrations rebounded, suggesting that reductions would be temporary without continuous stocking. Thus, perhaps the most effective method of perpetually reducing sport fish Hg concentrations would be to manage for the development of a naturally reproducing forage fish population with relatively high energy content and low Hg concentrations. For the full manuscript see: Lepak, J.M., Kinzli, K.D., Fetherman, E.R., Pate, W.M., Hansen, A.G., Gardunio, E.I., Cathcart, C.N., Stacy, W.L., Underwood, Z.E., Brandt, M.M., Myrick, C.M., and Johnson, B.M. 2012. Manipulation of growth to reduce sport fish mercury concentrations on a whole-lake scale. Canadian Journal of Fisheries and Aquatic Sciences. 69:122-135. A manuscript related to the collaborative project listed above was also completed and published. ABSTRACT: The American Fisheries Society (AFS) student subunits have the potential to train fisheries biologists and to benefit participating faculty as well. In order for this potential to be realized, subunit student and faculty members must demonstrate strong leadership and enthusiasm to encourage and maintain the participation of those around them. Collaboration between student subunit members and fisheries professionals contributes to the core AFS mission of “advancing fisheries and aquatic science and promoting the development of fisheries professionals.” Here we describe how a recent collaboration between the Colorado State University (CSU) subunit and natural resource management agencies from the state of Colorado is helping meet the AFS mission. With the guidance of CSU faculty and the determination of the subunit officers, the research project The American Fisheries Society (AFS) student subunits have the potential to train fisheries biologists and to benefit participating faculty as well. In order for this potential to be realized, subunit student and faculty members must demonstrate strong leadership and enthusiasm to encourage and maintain the participation of those around them. Collaboration between student subunit members and fisheries professionals contributes to the core AFS mission of “advancing fisheries and aquatic science and promoting the development of fisheries professionals.” Here we describe how a recent collaboration between the Colorado State University (CSU) subunit and natural resource management agencies from the state of Colorado is helping meet the AFS mission. With the guidance of CSU faculty and the determination of the subunit officers, the research project
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 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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".