Spatial and temporal variability of zooplankton off <scp>N</scp>ew <scp>C</scp>aledonia (<scp>S</scp>outhwestern <scp>P</scp>acific) from acoustics and net measurements
Bibliographic record
Abstract
Abstract Spatial and temporal distribution of zooplankton off New Caledonia in the eastern Coral Sea was studied during two multidisciplinary cruises in 2011, during the cool and the hot seasons. Acoustic measurements of zooplankton were made using a shipborne acoustic Doppler current profiler (S‐ADCP), a scientific echosounder and a Tracor acoustic profiling system (TAPS). Relative backscatter from ADCP was converted to biomass estimates using zooplankton weights from net‐samples collected during the cruises. Zooplankton biomass was estimated using four methods: weighing, digital imaging (ZooScan), ADCP and TAPS. Significant correlations were found between the different biomass estimators and between the backscatters of the ADCP and the echosounder. There was a consistent diel pattern in ADCP derived biomass and echosounder backscatter resulting from the diel vertical migration (DVM) of zooplankton. Higher DVM amplitudes were associated with higher abundance of small zooplankton and cold waters to the south of the study area, while lower DVM amplitudes in the north were associated with warmer waters and higher abundance of large organisms. Zooplankton was largely dominated by copepods (71–73%) among which calanoids prevailed (40–42%), with Paracalanus spp. as the dominant species (16–17%). Overall, zooplankton exhibited low abundance and biomass (mean night dry biomass of 4.7 ± 2.2 mg m 3 during the cool season and 2.4 ± 0.4 mg m 3 during the hot season) but high richness and diversity (Shannon index ∼4). Substantially enhanced biomass and abundance appeared to be episodically associated with mesoscale features contributing to shape a rather patchy zooplankton distribution.
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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".