Diets and Trophic Linkages of Epipelagic Fish Predators in Coastal Southeast Alaska during a Period of Warm and Cold Climate Years, 1997–2011
Bibliographic record
Abstract
Abstract This study identifies important trophic links for epipelagic marine fish predators in Southeast Alaska to improve understanding of marine ecosystem dynamics in response to climate change. Fish predators can be viewed as autonomous samplers whose diets should integrate the available prey taxa commensurate with environmental conditions. We examined fish predators from annual (1997–2011) surveys conducted in May to September by the Southeast Coastal Monitoring (SECM) project of Auke Bay Laboratories in the marine waters of Southeast Alaska. This project has emphasized long-term monitoring of strait and coastal marine habitats used by juvenile Pacific salmon Oncorhynchus spp. and associated epipelagic fishes to understand how environmental variation affects the sustainability of salmon resources. From 1,295 surface trawl hauls, trophic links were identified for 2,473 fish representing 19 predator species, principally adult and immature salmon, immature walleye pollock Theragra chalcogramma, and spiny dogfish Squalus acanthias. The most common fish prey consumed were fish larvae, juvenile salmon, Pacific herring Clupea pallasii, capelin Mallotus villosus, walleye pollock, lanternfishes (Myctophidae), and Pacific sand lance Ammodytes hexapterus, whereas the most common invertebrate prey consumed were euphausiids, decapod larvae, pteropods, and amphipods. This study describes the degree of piscivory, incidence of juvenile salmon prey, and frequency and weight composition of prey in the diets of epipelagic fish predators, but it did not clearly detect an effect of warm-versus-cold climate years on the diets of key planktivorous or piscivorous predators over the 15-year time series. Identifying the persistence of trophic links in epipelagic waters over time is important because climate-related changes in the upper water column have the potential to impact Southeast Alaska marine ecosystem dynamics and the productivity of important regional fisheries by altering key prey resources and trophic interactions. Received December 2, 2011; accepted May 9, 2012
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.002 |
| 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 teacher head, 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".