Herbarium specimens reveal a constrained seasonal climate niche despite diverged annual climates across a wildflower clade
Bibliographic record
Abstract
) clade (Brassicaceae), which originated in deserts and diversified into cooler, moister areas. To understand how climate niches evolved, we used historical climate records to estimate each species' 1) classic annual climate niche, averaged over specimen collection sites; 2) growing season niche, from estimated specimen germination date to collection date, averaged across specimens (specimen-specific niche); and 3) standardized seasonal niche based on average growing seasons of all species (clade-seasonal niche). In addition to estimating how phenological variation maps onto climate niche evolution, we explored how spatial refugia shape the climate experienced by species by 1) analyzing how field soil texture changes relative to the climate space that species occupy and 2) comparing soil water holding capacity from each specimen locality to that of surrounding areas. Specimen-specific niches exhibited less clade-wide variation in climatic water deficit (CWD) than did annual or clade-seasonal niches, and specimen-specific temperature niches showed no phylogenetic signal, in contrast to annual and clade-seasonal temperature niches. Species occupying cooler regions tracked hotter and drier climates by growing later into the summer, and by inhabiting refugia on drought-prone soils. These results underscore how phenological shifts, spatial refugia, and germination timing shape "lived" climate. Despite occupying a large range of annual climates, we found these species are constrained in the conditions under which they thrive.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".