Regional distribution patterns of wetland monocots with different root turnover strategies are associated with local variation in soil temperature
Bibliographic record
Abstract
Herbaceous perennial wetland monocots in Northern Ontario, Canada, show dichotomous root overwintering patterns, either with full senescence in autumn or survival over the winter, comparable to deciduous and evergreen leaf habits in trees. To test if these root strategies differ in their associations with growing season length, soil temperatures were recorded in autumn, winter and spring on 38 wetland sites with their dominant species being either of these two root overwintering strategies, altogether 19 monocot species. Traits associated with these strategies were assessed in garden experiments for a subset of these species. Sites with species with autumn-senescing roots were, on average, warmer than sites with species with overwintering roots. The 13 coldest sites were all sites of species with overwintering roots. Spring shoot growth in the field was delayed in species with autumn-senescing roots, despite their higher shoot relative growth rates in the garden, possibly due to the necessity to produce roots first. We conclude that species with autumn-senescing roots are more constrained by temperature than species with overwintering roots, limiting their occurrence in cool climates to locally warm soils and constraining their distribution towards the north. This is comparable to constraints on distribution of deciduous and evergreen trees.
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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".