Contrasting pelagic ecosystem functioning in eastern and western Baffin Bay revealed by trophic network modeling
Bibliographic record
Abstract
Baffin Bay, located at the Arctic Ocean’s ‘doorstep’, is a heterogeneous environment where a warm and salty eastern current flows northwards in the opposite direction of a cold and relatively fresh Arctic current flowing along the west coast of the bay. This circulation affects the physical and biogeochemical environment on both sides of the bay. The phytoplanktonic species composition is driven by its environment and, in turn, shapes carbon transfer through the planktonic food web. This study aims at determining the effects of such contrasting environments on ecosystem structure and functioning and the consequences for the carbon cycle. Ecological indices calculated from food web flow values provide ecosystem properties that are not accessible by direct in situ measurement. From new biological data gathered during the Green Edge project, we built a planktonic food web model for each side of Baffin Bay, considering several biological processes involved in the carbon cycle, notably in the gravitational, lipid, and microbial carbon pumps. Missing flow values were estimated by linear inverse modeling. Calculated ecological network analysis indices revealed significant differences in the functioning of each ecosystem. The eastern Baffin Bay food web presents a more specialized food web that constrains carbon through specific and efficient pathways, leading to segregation of the microbial loop from the classical grazing chain. In contrast, the western food web showed redundant and shorter pathways that caused a higher carbon export, especially via lipid and microbial pumps, and thus promoted carbon sequestration. Moreover, indirect effects resulting from bottom-up and top-down control impacted pairwise relations between species differently and led to the dominance of mutualism in the eastern food web. These differences in pairwise relations affect the dynamics and evolution of each food web and thus might lead to contrasting responses to ongoing climate change.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".