Long‐Term Dynamics of the Northern Humboldt Current System Pelagic Fish Community: A Look Into Community Shifts
Bibliographic record
Abstract
ABSTRACT The northern Humboldt Current System (nHCS) has high environmental variability that impacts key demographic and community‐scale processes. Understanding the role and ecological implications of these interannual or long‐term events is crucial in describing the dynamics of the nHCS community. Using catch data from pelagic assessment surveys from 1983 to 2019 and the community trajectory analysis framework, we tested and characterised the patterns and compositional dynamics of the nHCS pelagic fish community over space and time. Spatially, changes were evaluated for ecological regions with similar community composition. We found that the community has experienced constant interannual variability consistent with the long‐term warm and cold periods previously identified in the system. Two shifts in 1990 and 2001 were identified and associated with a change in the average oceanographic conditions in the system. Coastal fish species dominated the community after 2001, while oceanic and tropical species were more abundant before 1990. We found lower and higher interannual variability for the coastal and oceanic areas, respectively. Moreover, the coastal area reported a higher change in the community structure from 1983 to 2019. Temperature and oxygen were two oceanographic variables significantly associated with the main changes in the community, finding that warmer and less oxygenated years lead to higher diversity. This study helps to understand the magnitude, direction, and mechanisms involved in the long‐term changes of the nHCS pelagic fish community.
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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 | 0.000 | 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".