Ecosystem Model of the Entire Beaufort Sea Marine Ecosystem: A Temporal Tool for Assessing Food-Web Structure and Marine Animal Populations from 1970 to 2014
Bibliographic record
Abstract
The Beaufort Sea coastal-marine ecosystem is a 476,000 km2 area in the Arctic Ocean, which extends from -112.5 to -158.0° longitude to 67.5 to 75.0° latitude. Within this polar area the United States indigenous communities of Barrow, Kaktovik, and Nuiqsut, and the Canadian indigenous communities of Aklavik, Inuvik, Tuktoyaktuk, Paulatuk, Ulukhaktok, and Sachs Harbour, subsist by harvesting marine mammals, fish, and invertebrates to provide the majority of their community foods. The Beaufort Sea coastal-marine ecosystem includes many specialized marine animals whose life history is tied to the sea ice, such as polar bears that rely on sea-ice for foraging activities and denning, or ice algae that attach to the seasonal cryosphere. Changes in sea-ice extent and sea surface temperature affect the ecosystem through losses of animal habitat, alterations to trophodynamics, and/or impacts to indigenous community harvesting. The present study focuses on developing a dynamic whole-ecosystem model that can be used for natural resource management. The resulting Ecopath with Ecosim (EwE) temporal model (1970 to 2014) utilizes forcing and mediation functions that describe food web and relationships between sea-ice extent, SST, and Inuit community harvesting efforts. Following model calibrations, vulnerability estimates, trophic level validation, and sensitivity analyses, the Beaufort Sea model produces population and dietary changes over time that are analogous to observations. Changes in temporal whole-ecosystem trophodynamics highlight a potential climatological tipping point in 1993, followed by a biological tipping point in 1998.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 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".