Assessing Avian Predation on Juvenile Salmonids using Passive Integrated Transponder Tag Recoveries and Mark–Recapture Methods
Bibliographic record
Abstract
Abstract Many populations of coho salmon Oncorhynchus kisutch and steelhead O. mykiss are listed under the U.S. Endangered Species Act. Until recently, the role of avian predation in limiting recovery of coho salmon and steelhead in central California coastal watersheds has been overlooked. We used recoveries of passive integrated transponder (PIT) tags from Año Nuevo Island (ANI), a breeding site for several species of piscivorous seabirds, to estimate predation rates on juvenile salmonids and identify susceptible life stages and species responsible for predation. A total of 34,485 PIT tags were deployed in coho salmon and steelhead in six watersheds in San Mateo and Santa Cruz counties. Tags were deposited on ANI by predators after ingestion of tagged fish. Because tags were not removed from the island and were detected on multiple sampling occasions, we were able to use mark–recapture models to generate a corrected minimum predation estimate. We used POPAN, a variation of the Jolly–Seber model, to generate an estimate of gross population abundance, which accounted for tags deposited on the island but not detected during surveys. Detections of 196 tags from surveys conducted between autumn 2006 and spring 2009 were incorporated into the model, producing a gross population estimate of 242 tags (SE = 9.8). Addition of tags detected between autumn 2009 and 2010 to the abundance estimate from POPAN produced a new minimum estimate of 362 tags on ANI. Western gulls Larus occidentalis probably were the primary predator depositing tags on ANI. Minimum predation estimates ranged from 0.1% (Soquel Creek) to 4.6% (Waddell Creek) of outmigrating coho salmon and steelhead smolts. Predation was potentially greater given still unquantified deposition of tags off-colony and destruction of tags during digestive processes of predators. Finally, avian predators targeted estuary-reared fish, which contributed disproportionately to adult populations, further impacting imperiled salmon populations. Received August 4, 2011; accepted August 27, 2012
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".