Role of hydrodynamics in shaping chemical habitats and modulating the responses of coastal benthic systems to ocean global change
Bibliographic record
Abstract
Marine coastal zones are highly productive, and dominated by engineer species (e.g. macrophytes, molluscs, corals) that modify the chemistry of their surrounding seawater via their metabolism, causing substantial fluctuations in oxygen, dissolved inorganic carbon, pH, and nutrients. The magnitude of these biologically driven chemical fluctuations is regulated by hydrodynamics, can exceed values predicted for the future open ocean, and creates chemical patchiness in subtidal areas at various spatial (µm to meters) and temporal (minutes to months) scales. Although the role of hydrodynamics is well explored for planktonic communities, its influence as a crucial driver of benthic organism and community functioning is poorly addressed, particularly in the context of ocean global change. Hydrodynamics can directly modulate organismal physiological activity or indirectly influence an organism's performance by modifying its habitat. This review addresses recent developments in (i) the influence of hydrodynamics on the biological activity of engineer species, (ii) the description of chemical habitats resulting from the interaction between hydrodynamics and biological activity, (iii) the role of these chemical habitat as refugia against ocean acidification and deoxygenation, and (iv) how species living in such chemical habitats may respond to ocean global change. Recommendations are provided to integrate the effect of hydrodynamics and environmental fluctuations in future research, to better predict the responses of coastal benthic ecosystems to ongoing ocean global 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".