Local and remote physical processes driving variability of the planktonic system in the Juan Fernández Archipelago: A multidisciplinary framework providing conservation insights
Bibliographic record
Abstract
Abstract The Juan Fernandez Ridge, a vulnerable marine ecosystem located far off the coast of central Chile and formed by several seamounts, guyots and three islands (Robinson Crusoe, Santa Clara and Alejandro Selkirk), has recently been declared a Coastal Marine Protected Area of Multiple Uses with several National Parks embedded in it. Recent studies have highlighted the influence of remote and local oceanographic structures on the hydrographic dynamics of this ridge. However, there is still a gap in understanding how they affect the structure and dynamics of the surrounding insular planktonic communities. A hydroacoustic and oceanographic survey was conducted during the austral spring (October 2016), including hydrographic and zooplankton sampling around Robinson Crusoe Island. Oceanographic features were identified and tracked using satellite data (chlorophyll‐a (Chl‐a) and sea surface temperature) and modelling results. Two events of Chl‐a increase relative to a threshold (>0.45 mg m−3) were forced by different physical processes, both affecting the western side of Robinson Crusoe Island. In event A during the cruise period, Chl‐a subsurface maxima were associated with the arrival of a coastal meander originating on the continental shelf off Chile (remote process); the zooplankton was dominated by copepods and salps, with an evident coastal–oceanic gradient. In event B, Chl‐a maxima were linked to a local upwelling forced by the intensification of a localized SSW wind. No influence of remote eddies or local Von Kármán vortices on Chl‐a distribution was observed. These findings highlight the influence of remote and local physical processes on the structure of planktonic communities around Robinson Crusoe Island. Understanding the variability of these mechanisms and their effects at the base of the pelagic food web is critical in adopting an ecosystem‐level approach.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".