Seasonal dynamics of coastal ecosystems and export production at high latitudes: A modeling study
Bibliographic record
Abstract
Export of organic matter from the surface to deeper waters often shows much smaller seasonal variations than primary production or nitrate‐based new production in mid‐ to high‐latitude marine systems. The mechanisms underlying this pattern remain poorly understood, but seasonal shifts in food web structure and dynamics have been implicated. We report here on an ecosystem modeling analysis of a high‐resolution (biweekly) time series of biomass, production, and export flux (sediment trap) measurements conducted in 1991 in Bonne Bay (Newfoundland). This time series shows the classical pattern of a spring bloom followed by a summer low biomass period, yet export is bimodal, with maxima during spring and late summer. The ecosystem model was forced by diagnostic vertical mixing calculations based on temperature and salinity records taken every 3 d and hourly wind data. The physical analysis indicated that the nitrate flux into the euphotic zone during summer was equivalent to that during the spring and fall seasons and accounted for half of the summer export. Statistical adjustments of the parameters of the ecosystem model indicated that strong production of dissolved organic carbon during the spring bloom, high temperature dependence of microbial activity, and physico‐chemical particle aggregation played key roles in explaining the remainder of the summer export. Seasonal changes in trophic pathways between spring and summer, such as a shift from a herbivorous to a microbial food web, played a comparatively smaller role. Our modeling analysis suggests that physical mixing processes and physico‐chemical aggregation processes are at least as important as shifts in food web trophic pathways in explaining the postbloom export flux in mid‐ to high‐latitude marine systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".