Climate‐driven trends and ecological implications of event‐scale upwelling in the <scp>C</scp>alifornia <scp>C</scp>urrent <scp>S</scp>ystem
Bibliographic record
Abstract
Abstract Eastern boundary current systems are among the most productive and lucrative ecosystems on Earth because they benefit from upwelling currents. Upwelling currents subsidize the base of the coastal food web by bringing deep, cold and nutrient‐rich water to the surface. As upwelling is driven by large‐scale atmospheric patterns, global climate change has the potential to affect a wide range of significant ecological processes through changes in water chemistry, water temperature, and the transport processes that influence species dispersal and recruitment. We examined long‐term trends in the frequency, duration, and strength of continuous upwelling events for the Oregon and California regions of the California Current System in the eastern Pacific Ocean. We then associated event‐scale upwelling with up to 21 years of barnacle and mussel recruitment, and water temperature data measured at rocky intertidal field sites along the Oregon coast. Our analyses suggest that upwelling events are changing in ways that are consistent with climate change predictions: upwelling events are becoming less frequent, stronger, and longer in duration. In addition, upwelling events have a quasi‐instantaneous and cumulative effect on rocky intertidal water temperatures, with longer events leading to colder temperatures. Longer, more persistent upwelling events were negatively associated with barnacle recruitment but positively associated with mussel recruitment. However, since barnacles facilitate mussel recruitment by providing attachment sites, increased upwelling persistence could have indirect negative impacts on mussel populations. Overall, our results indicate that changes in coastal upwelling that are consistent with climate change predictions are altering the tempo and the mode of environmental forcing in near‐shore ecosystems, with potentially severe and discontinuous ramifications for ecosystem structure and functioning.
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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 | 0.001 | 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".