Fonctionnement des écosystèmes benthiques peu profonds Arctiques et sub-Arctiques en système côtier hautement stratifié
Bibliographic record
Abstract
Under climate change, Arctic and sub-Arctic Coastal Systems expérience one of the largest increases in stratification at the global scale due to warming and/or freshening of their surface waters. However, the subséquent impacts of these environmental changes on the functioning of Coastal benthic ecosystems is still poorly understood. This thesis aims to study how future increases in stratification in these ecosystems could affect the organic matter quality, pelagic-benthic coupling intensity and benthic food web structures. Two Coastal Systems subject to strong seasonal variations in sea surface température and salinity were studied: a high- arctic fjord (Young Sound, NE Greenland) characterized by strong haline stratification and a sub-Arctic archipelago (Saint-Pierre-et-Miquelon, Newfoundland continental shelf) exposed to strong thermal stratification. In the first part of this PhD we show that strong stratification reduces the quality of pelagic organic matter sources and intensity of organic matter transfers from surface waters toward the benthic compartiment. On the other hand, no impact was observed on the quality of benthic organic matter sources. In the second part we show that stratification does not alter benthic food web structures thanks to the high trophic plasticity of primary consumers and high levels of omnivory in the community. In addition, benthic primary production in Coastal environment could potentially provide an alternative source of organic matter to pelagic primary production for primary consumers during high stratification conditions. Through these results, we propose several conceptual models describing the potential évolutions of these ecosystems under climate change and we show the importance of considering the singularity of coastal ecosystems as well as their small-scale spatial variations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".