Energy content of Pacific salmon as prey of northern and southern resident killer whales
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recovery of depleted species is difficult, but it can be especially complex when the target species interacts strongly with other depleted species. Such is the case for northern and southern resident killer whales Orcinus orca which are listed as 'endangered' under the US Endangered Species Act (ESA) and Canada's Species at Risk Act. These resident killer whales prey heavily on Pacific salmon Oncorhynchus spp., including several 'evolutionarily significant units' also listed under the ESA. In response to concerns that a depleted prey base may affect killer whale recovery, we analyzed proximate composition and calculated caloric content of Pacific salmon to evaluate the importance of salmon species, population, body size, and lipid levels in determining their energy content as prey for killer whales. We sampled all 5 species of Pacific salmon, but emphasized Chinook salmon, a predominant prey of killer whales. Energy density (kcal kg -1 ) was highly correlated with lipid content, whereas total energy value (kcal fish -1 ) was determined primarily by fish mass and secondarily by lipid content. These salmon energetics data can be used to provide better precision and estimates on the caloric value of prey to killer whales. To facilitate application of these results to the co-management of salmon and killer whales, we produced a simple relationship that uses fish length to predict total energy of Chinook salmon as prey where population-specific energy densities and fish masses are lacking. Benefits to killer whales from possible salmon fishery closures, or other activities that affect prey availability, will depend on the salmon species and populations involved.
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.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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