Climate change undermines seafood micronutrient supply from wild-capture fisheries in Southeast Asia and Pacific Island countries
Bibliographic record
Abstract
Marine ecosystem functions are affected by climate change impacts such as ocean warming, deoxygenation and acidification. These impacts drive changes in distributions and body size of fish species and directly affect fisheries. Wild-capture fisheries are crucial for providing nutrients, livelihoods, and employment in tropical Southeast Asia and Pacific Island countries, where coastal communities are highly vulnerable to climate change. We examined the impacts of climate change on fish stocks and nutrient availability of seven key micronutrients (calcium, Omega-3 fatty acids, iodine, iron, vitamin A, vitamin B12 and zinc) in Southeast Asia, Pacific Islands, and Oceania (Australia and New Zealand). We combined micronutrient demands by local human populations with Sea Around Us reconstructed catch time series and catch projections from a dynamic bioclimate envelope model for the 21st century. The model predicted a decline in the Maximum Catch Potential (MCP) within Exclusive Economic Zones for Oceania, Pacific Islands, and Southeast Asian countries. Under the 'strong mitigation' scenario, catch potential reductions ranged from a decline of 54-66 % in Oceania, 58-92 % in Pacific Islands, and 65-86 % in Southeast Asia by the mid to the end of the 21st century relative to the historical period, respectively. Under the 'no-mitigation' climate scenario, reductions were more severe, with a decline of 55-70 % in Oceania, 66-92 % in Pacific Islands, and 70-86 % in Southeast Asia for the same time periods. Our findings indicate that Australia and New Zealand are unlikely to meet the recommended nutrient intake demand for most micronutrients through their fisheries (not considering trade or aquaculture production), except for iodine and vitamin B12. Pacific Island countries will likely follow the same pattern while Southeast Asia is expected to face worsening deficits, except for iodine and vitamin B12. This study highlights the importance of incorporating nutritional considerations of seafood into national food, trade and economic policies.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".