Organic and inorganic whole system metabolism in two acidified coastal systems in Ireland
Bibliographic record
Abstract
Organic and inorganic whole system metabolism for two Irish coastal areas were compared to evaluate carbonate system resilience to acidification. The two systems are characterized by contrasting watershed input types and composition. Kinvara Bay is fed by Submarine Groundwater Discharge (SGD) derived from a karstic catchment while Killary Harbour is fed by river discharge draining a siliciclastic catchment. Freshwater sources to sea have distinct Total Alkalinity (TA) and Dissolved Inorganic Carbon (DIC) concentrations, higher and lower than the open ocean, respectively, but both evidence seasonally variable low pH, ranging from 6.20 to 7.50. Retention of TA and DIC was calculated for the two areas using LOICZ methodology. In Kinvara bay, annually averaged retention of DIC was greater than for TA (5 × 104 and 1.5 × 105 mol d-1), suggesting the system is acidifying further. Conversely, Killary Harbour shows negative TA and DIC retention, with DIC:TA <1, suggesting an internal buffer against ocean acidification is operating. Net Community Production (NCP) was calculated for both systems using Dissolved Oxygen data. Subsequently, we estimated Net Community Calcification (NCC) from the ratio between TA and DIC. NCP was always positive in Killary Harbour with an average of 318 mmol O2 m-2 d-1 (equivalent to 89 mol C m-2 y-1). However, Kinvara Bay shows relatively lower positive NCP in spring and summer (average of 46 mmol O2 m-2 d-1), but negative NCP in autumn and winter. Therefore, Kinvara Bay’s Total Organic Carbon (TOC) production was low, at ~21 g m-2 y-1 and not enough to overcome acidification driven by the SGD source composition. These results emphasize the complexity of interactions between the drivers of coastal acidification rate, affecting our ability to accurately assess the resilience of the carbonate system in these areas to ocean acidification pressure in the future.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".