Potential impacts of climate change on marine wild capture fisheries: an update
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
SUMMARY This paper provides a brief update on the potential impacts of climate change on marine ecosystems and marine wild capture fisheries based on the scientific literature published since 2007. Current models predict shifts in fish distributions of 45–60 km per decade, with 0·80 of species moving poleward. With a high CO 2 emissions scenario, little overall change in the global maximum potential fisheries catch is projected (±1%), although with high spatial variability: decreases of 40% are projected for the tropics, with increases of 30–70% for higher latitudes. Tropical nations appear to be most vulnerable to the impacts of climate change on fisheries production. Coupled atmosphere–ocean–fish production–human society models are beginning to be developed for specific market systems. Results suggest that how society responds can have as large or larger an effect as the strength of the climate impact. Good observations of the impacts of climate change exist for high latitude, coral reef and North Atlantic systems. Management strategies are being developed to address climate change and fisheries, including risk and vulnerability assessment frameworks, pro-active planning with stakeholders regarding potential impacts and responses and examining existing regulations to identify gaps created by altered species distributions (e.g. unregulated fishing in newly ice-free areas). Overall, fisheries governance systems are needed which are flexible and can quickly adapt to changing ecological and human societal conditions. Significant knowledge gaps include a comprehensive and co-ordinated global network of observations to help distinguish climate change from variability, and increased detail in the structure and processes of models. Necessary next steps include reducing the uncertainties of climate impacts models at present, understanding the synergistic effects of multiple stressors and the inclusion of humans into coupled models and socio-economic analyses, in particular at regional and local scales. In the intermediate term, developing nations in tropical regions are likely to be most negatively impacted, whereas developed nations at higher latitudes are most likely to benefit. In the longer term, overall marine food security will depend on the impacts of climate change on marine primary production, for which the present projections are highly uncertain. Adoption of an integrated social–ecological approach that improves the adaptive capacities of ecological and human social systems will help to sustain food security from marine wild capture fisheries.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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