The relation between global palm distribution and climate
Bibliographic record
Abstract
Fossil palms provide qualitative evidence of (sub-) tropical conditions and frost-free winters in the geological past, including modern cold climate regions (e.g., boreal, or polar climates). The freeze intolerance of palms varies across different organs and life stages, with seedlings in particular less tolerant of sub-zero temperatures than adult plants, limiting successful establishment of populations while permitting adult palms to survive in cultivation outside their natural ranges. Quantitatively, palms indicate minimum cold month mean temperature (CMMT) at 2-8 °C in palaeoclimate reconstructions. These data have accentuated model-proxy mismatches for high latitudes during Paleogene hyperthermals when palms expanded poleward in both hemispheres. We constructed a manually filtered dataset of >20,000 georeferenced Arecaceae records, by eliminating cultivars. Statistically derived mean annual temperature, mean annual temperature range, and CMMT thresholds for the Arecaceae and lower rank subfamilies and tribes reveal large differences in temperature sensitivity depending on lower taxonomic classification. Cold tolerant tribes such as the Trachycarpeae produce thresholds as low as CMMT ≥ 2.2 °C. However, within the palm family, CMMT < 5 °C is anomalous. Moreover, palm expansion into temperate biomes is likely a post-Palaeogene event. We recognize a CMMT ≥ 5.2 °C threshold for the palm family, unless a lower taxonomic rank can be assigned.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".