Evolutionary constraints on physiology confound range shift predictions of two nacellid limpets
Bibliographic record
Abstract
Physiological comparisons are fundamental to quantitative assessments of the capacity of species to persist within their current distribution and to predict their rates of redistribution in response to climate change. Yet, the degree to which physiological traits are conserved through evolutionary history may fundamentally constrain the capacity for species to adapt and shift their geographic range. Taxa that straddle major climate transitions provide the opportunity to test the mechanisms underlying evolutionary constraints and how such constraints may influence range shift predictions. Here we focus on two abundant and shallow water nacellid limpets which have representative species on either side of the Polar front. We test the thermal thresholds of the Southern Patagonian limpet, Nacella deaurata and show that its optimal temperatures for growth (4 °C), activity (-1.2 to -0.2 °C) and survival (1 to 8 °C) are mismatched to its currently experienced annual sea surface temperature range (5.9 to 10 °C). Comparisons with the congeneric Antarctic limpet, N. concinna, reveal an evolutionary constraint on N. deaurata physiology, with overlapping thermal capacities, suggesting that a cold climate legacy has been maintained through the evolution of these species. These physiological assessments predict that the South American range of N. deaurata will likely decline with continued warming. It is, however, one of the first species with demonstrated physiological capacity to successfully colonize the cold Southern Ocean. With the expected increase in opportunities for transport within high southern latitudes, N. deaurata has the potential to establish and drive ecological change within the shallow Southern Ocean.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".