Different factors govern the performance of three closely related and ecologically similar<i>Dryopteris</i>species with contrastingly different abundance in a transplant experiment
Bibliographic record
Abstract
We conducted a transplant experiment to address aspects of the contrasting ecological performance of three forest ferns with similar habitat preferences: Dryopteris carthusiana (Vill.) H.P. Fuchs (common in Estonia), Dryopteris expansa (C. Presl) Fraser-Jenkins & Jermy (less common in Estonia), and Dryopteris dilatata (Hoffm.) A. Gray (rare in Estonia). Sporophytes of the three species were reciprocally planted in pots of soil in three neighbouring sites, where only (i) the most common, (ii) two more common, or (iii) all three grow naturally. The experimental design allowed the grouping of the possible limiting factors: light-related, soil-related, and effect of locale (factors associated with a particular locality but not directly related to light or soil). D. expansa (less common) was vulnerable to edaphic conditions: its performance was significantly poorer in soil from the site where it was naturally absent. D. dilatata (rare) was unaffected by soil conditions, indicating that either limited dispersal or effect of locale is responsible for its rarity. Our results indicate that even for taxonomically close and ecologically similar species, the forces that shape plants’ distribution and abundance can be markedly different.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".