Qualitative and quantitative reconstructions of surface water characteristics and recent hydrographical changes in the Trondheimsfjord, central Norway
Bibliographic record
Abstract
Abstract. In the present study we investigated dinocyst assemblages in the Trondheimsfjord over the last 25 to 50 yr from three well-dated multi-cores (210Pb and 137Cs) retrieved along the fjord axis. The downcore distribution of the dinocysts is discussed in view of changes in key hydrographic parameters of the surface waters (sea-surface temperatures (SSTs), sea-surface salinities (SSSs), and river discharges) monitored in the fjord. We examine the impact of the North Atlantic Oscillation pattern and of waste water supply from the local industry and agriculture on the fjord ecological state and thus dinocyst species diversity. Our results show that dinocyst production and diversity in the fjord is not evidently affected by human-induced eutrophication. Instead the assemblages appear to be mainly controlled by the NAO-related changes in nutrient availability and the physico-chemical characteristics of the surface mixed layer. Still, discharges of major rivers have been modulated since 1985 by the implementation of hydropower plants, which certainly influences the amounts of nutrients supplied to the fjord. The impact, however, is variable according to the local geographical setting, and barely differentiated from natural changes in river run off. We ultimately test the use of the modern analogue technique (MAT) for the reconstruction of winter and summer SSTs and SSSs and annual primary productivity (PP) in this particular fjord setting. The reconstructed data are compared with time series of summer and winter SSTs and SSSs measured at 10 m water depth, as well as with mean annual PPs along the Norwegian coast and in Scandinavian fjords. The reconstructions are generally in good agreement with the instrumental measurements and observations from other fjords. Major deviations can be attributed to peculiarities in the assemblages linked to the particular fjord setting and the related hydrological structure.
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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 | 0.000 |
| 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".