Will life find a way? Evolution of marine species under global change
Bibliographic record
Abstract
Projections of marine biodiversity and implementation of effective actions for its maintenance in the face of current rapid global environmental change are constrained by our limited understanding of species' adaptive responses, including transgenerational plasticity, epigenetics and natural selection. This special issue presents 13 novel studies, which employ experimental and modelling approaches to (i) investigate plastic and evolutionary responses of marine species to major global change drivers; (ii) ask relevant broad eco-evolutionary questions, implementing multiple species and populations studies; (iii) show the advantages of using advanced experimental designs and tools; (iv) construct novel model organisms for marine evolution; (v) help identifying future challenges for the field; and (vi) highlight the importance of incorporating existing evolutionary theory into management solutions for the marine realm. What emerges is that at least some populations of marine species have the ability to adapt to future global change conditions. However, marine organisms' capacity for adaptation appears finite, due to evolutionary trade-offs and possible rapid losses in genetic diversity. This further corroborates the idea that acquiring an evolutionary perspective on how marine life will respond to the selective pressure of future global changes will guide us in better identifying which conservation efforts will be most needed and most effective.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".