Threatened skates exhibit abiotic niche stability despite climate change in the southwestern Atlantic Ocean
Bibliographic record
Abstract
Climatic changes are disrupting distribution patterns of populations through shifts in species abiotic niches and habitat loss. The abiotic niche of marine benthic taxa such as skates, however, may be more climatically stable compared with the upper layers of the water column, which are more exposed to immediate impacts of warming. Here, we estimate climate change impacts in Riorajini, a tribe of four skates, as a proxy to evaluate the vulnerability of a temperate coastal zone in the Southwest Atlantic, and study niche dynamics in a scenario of environmental changes on this group of threatened species. We modelled the abiotic niche of each species under present climatic conditions (2000–2014), projected them to the future (2100), then measured distributional stability, expansion, and unfilling. Our results revealed abiotic stability between the scenarios modelled despite the advancement of climate change, suggesting that the benthic layers where these skates occur may be a refuge from the increasing thermal stress. However, the exposure of shallow waters to climate change may be detrimental to nursery habitats. Thus, although their abiotic niche may remain stable in the future, the loss of extension of occurrence might be a peril for them with climate change.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".