A Selected Review of Impacts of Ocean Deoxygenation on Fish and Fisheries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Oxygen is crucial for the survival of marine species. Yet, the ocean has experienced a loss of approximately 2% of its oxygen inventory since the last century, resulting in adverse impacts on marine life and ecosystems. In particular, changes in the gap between the supply and demand for dissolved oxygen lead to physiological and ecological variations, which cause alterations in habitats and food webs for fish and ecosystem services. These changes vary over time and by region, and the heterogeneous characteristics of marine species bring about non-linear consequences to human society. Despite this, identifying the potential ripple effects of deoxygenation on human society is challenging due to the integrated impacts of other stressors, such as global warming and ocean acidification, and their varying changes depending on environmental conditions and regions, such as upwelling and eutrophication. Therefore, we conducted a literature review on ocean deoxygenation and its effects on fish dynamics and the ecosystem, with a focus on the environmental and societal impact, to present crucial considerations and pathways for future research on ocean deoxygenation. We found that quantitative approaches are necessary to assess the dynamic changes under deoxygenation, and the consequent effects on marine ecosystems should be verified to exploit the natural resources from the ocean. One of the most reliable approaches to quantifying the ripple impacts of deoxygenation is to model spatial and temporal changes with other climate stressors, forming a global network encompassing socio-economic and regional effects of this global change to facilitate and improve capabilities to address the impacts of ocean deoxygenation.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it