Trophodynamic indicators for an ecosystem approach to fisheries
Why this work is in the frame
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Bibliographic record
Abstract
Acknowledging ecological interactions, such as predation, is key to an ecosystem approach to fisheries. Trophodynamic indicators are needed to measure the strength of the interactions between the different living components, and of structural ecosystem changes resulting from exploitation. We review trophodynamic indicators derived from models, as well as from emergent patterns such as trophic cascades and regime shifts. From 46 indicators identified in the literature, six (catch or biomass ratios, primary production required to support catch, production or consumption ratios and predation mortality, trophic level of the catch, fishing-in-balance, and mixed trophic impact) were selected because of their ability to reveal ecosystem-level patterns, and because they match published criteria. This suite of indicators is applied to the northern and southern Benguela ecosystems, and their performance is evaluated to depict drastic and contrasted ecosystem changes. A few complementary indicators are suggested as needed to detect the trophodynamic impacts of fisheries and ecosystem changes. Trends in indicators are sensitive to the choice of trophic level made for certain species. Trophodynamic indicators appear to be conservative, because they respond slowly to large structural changes in an ecosystem. Application of the selected indicators to other marine ecosystems is encouraged so as to evaluate fully their usefulness to an ecosystem approach to fisheries, and to establish international comparability.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it