Assessing the Relationship between Gulls <i>Larus</i> spp. and Pacific Salmon in Central California Using Radiotelemetry
Bibliographic record
Abstract
Abstract Predation by marine birds has resulted in substantial losses to runs of Pacific salmon Oncorhynchus spp., in some cases necessitating management action. Recovery of PIT tags on a seabird breeding colony (Año Nuevo Island) indicated that western gulls Larus occidentalis prey upon federally listed Coho Salmon Oncorhynchus kisutch and steelhead O. mykiss in central California. Whereas salmonid populations in central California have decreased in recent decades, the western gull population on Año Nuevo Island has increased. We observed gulls Larus spp. within estuaries to document predation and used radiotelemetry to examine gull movement in relation to the availability of salmonids. During 2008 and 2009, observed predation events of out-migrating salmonids by gulls were rare; 21 events occurred during 338 h of observations at two estuaries. During the prehatch and chick-rearing phases of breeding, which coincided with migration of salmonids from fresh to salt water, 74% of the detections of radio-tagged western gulls occurred within 25 km of Año Nuevo Island, suggesting that the relative susceptibility of predation by western gulls using Año Nuevo Island decreased with distance from the island. Western gull presence at creek mouths was greatest during daylight hours (91% of detections), while juvenile salmonids were present predominantly at night (65% of detections). The greatest overlap between western gulls and salmonids occurred at dusk, and predation of out-migrating salmonids was likely opportunistic. Deterring gulls from creek mouths when overlap between predator and prey might otherwise occur may buffer out-migrating salmonids from predation. Our results will inform management strategies to most effectively reduce the impacts of gull predation on central California salmonids. Received May 8, 2014; accepted March 11, 2015
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".