Up to 80% of threatened and commercial species across European marine protected areas face novel climates under high emission scenario
Bibliographic record
Abstract
Abstract Marine protected areas (MPAs) are a critical tool for safeguarding marine species and habitats for the future, though the effects of projected climate change raise concerns about their long-term success. Assessing the degree to which MPAs may be exposed to future novel climatic conditions is, therefore, crucial for informing conservation and management actions aimed at ensuring a resilient and thriving ocean in the years to come. Here, we evaluate the future exposure of 398 threatened and commercially important species to novel and extremely novel climatic conditions within European MPAs. We estimated climate novelty through multivariate analyses considering biologically meaningful distribution drivers of temperature, oxygen, pH, and primary productivity from present-day to the end of the 21st-century conditions under contrasting shared socioeconomic pathways (SSP) scenarios—low emission scenario (SSP1–1.9) and high emission scenario (SSP5–8.5). Our findings suggest that, under SSP1–1.9, ~6.5% of species and 0.5% of European MPAs will be at risk due to future novel conditions. In contrast, under SSP5–8.5, 87% of MPAs and 80% of species are projected to be at risk. Notably, up to 100% of species currently located in the MPAs of enclosed and semi-enclosed seas like the Baltic Sea and the Black Sea are projected to be exposed to novel or even extremely novel conditions. Virtually all species in most of those regions will be at risk, suggesting that even new MPAs might not be able to adequately protect them. Comparatively, the Norwegian Sea, North-East Atlantic, and western parts of the Mediterranean and North Seas are expected to be less impacted even under the high emission scenario. Overall, our study advances the understanding of the potential impacts of future climate change scenarios on threatened and commercially important marine species in European MPAs and reinforces the urgent need to meet the Paris Agreement. Our results suggest that existing approaches to marine governance in Europe may be insufficient for ensuring the success of MPAs in light of future impacts and that novel anticipatory forms of governance are needed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".