A Bioenergetics Approach to Assessing Potential Impacts of Avian Predation on Juvenile Steelhead during Freshwater Rearing
Bibliographic record
Abstract
Abstract Avian predation on juvenile salmonids is an important source of mortality in freshwater and estuarine habitats when birds and salmonids overlap spatially and temporally. We assessed the potential impact of avian predation upon juvenile steelhead Oncorhynchus mykiss in a coastal watershed in central California. We conducted stream surveys between 2008 and 2010 to determine the composition, distribution, and density of piscivorous birds in areas that provide rearing habitat for juvenile steelhead. The most commonly sighted bird species were common mergansers Mergus merganser and belted kingfishers Megacyrle alcyon. The density of avian predators varied spatially and temporally but was greatest in the estuary regardless of season and decreased with increasing distance from the estuary. In the absence of local predator diet data, we applied a bioenergetics model to estimate the potential predation on juvenile steelhead by mergansers and kingfishers in the Scott Creek estuary. Model parameters included (1) published values of bird energetic requirements and steelhead energy density, (2) the number of birds present in the estuary during the closure period (from stream surveys), and (3) the size frequency and abundance of steelhead present in the estuary during closure. We predicted the extent of predation for different values of steelhead in bird diets, accounting for uncertainty in the estimates using a Monte Carlo simulation approach. With the assumed contribution of steelhead to the diet ranging from 20% to 100%, the population of kingfishers foraging in the Scott Creek estuary had the potential to remove 3–17% of annual production, whereas mergansers had the potential to remove 5–54% of annual steelhead production. Our results suggest that predation by avian species, particularly mergansers, is an important source of mortality for threatened steelhead populations in central California and should be addressed in future salmonid research and recovery planning. Received February 13, 2013; accepted June 4, 2013
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".