Responses of ichthyoplankton assemblages to the recent marine heatwave and previous climate fluctuations in several Northeast Pacific marine ecosystems
Bibliographic record
Abstract
The effects of climate warming on ecosystem dynamics are widespread throughout the world's oceans. In the Northeast Pacific, large-scale climate patterns such as the El Niño/Southern Oscillation and Pacific Decadal Oscillation, and recently unprecedented warm ocean conditions from 2014 to 2016, referred to as a marine heatwave (MHW), resulted in large-scale ecosystem changes. Larval fishes quickly respond to environmental variability and are sensitive indicators of ecosystem change. Categorizing ichthyoplankton dynamics across marine ecosystem in the Northeast Pacific can help elucidate the magnitude of assemblage shifts, and whether responses are synchronous or alternatively governed by local responses to regional oceanographic conditions. We analyzed time-series data of ichthyoplankton abundances from four ecoregions in the Northeast Pacific ranging from subarctic to subtropical: the Gulf of Alaska (1981-2017), British Columbia (2001-2017), Oregon (1998-2017), and the southern California Current (1981-2017). We assessed the impact of the recent (2014-2016) MHW and how ichthyoplankton assemblages responded to past major climate perturbations since 1981 in these ecosystems. Our results indicate that the MHW caused widespread changes in the ichthyoplankton fauna along the coast of the Northeast Pacific Ocean, but impacts differed between marine ecosystems. For example, abundances for most dominant taxa were at all-time lows since the beginning of sampling in the Gulf of Alaska and British Columbia, while in Oregon and the southern California Current species richness increased as did abundances of species associated with warmer waters. Lastly, species associated with cold waters also increased in abundances close to shore in southern California during the MHW, a pattern that was distinctly different from previous El Niño events. We also found several large-scale, synchronized ichthyoplankton assemblage composition shifts during past major climate events. Current climate projections suggest that MHWs will become more intense and thus our findings can help project future changes in larval dynamics, allowing for improved ecosystem management decisions.
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 | 0.000 | 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 | 0.001 |
| 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".