Glacial Refugia and Future Habitat Coverage of Selected Dactylorhiza Representatives (Orchidaceae)
Bibliographic record
Abstract
The intensively discussed taxonomic complexity of the Dactylorhiza genus is probably correlated with its migration history during glaciations and interglacial periods. Previous studies on past processes affecting the current distribution of Dactylorhiza species as well as the history of the polyploid complex formation were based only on molecular data. In the present study the ecological niche modeling (ENM) technique was applied in order to describe the distribution of potential refugia for the selected Dactylorhiza representatives during the Last Glacial Maximum. Additionally, future changes in their potential habitat coverage were measured with regard to three various climatic change scenarios. The maximum entropy method was used to create models of suitable niche distribution. A database of Dactylorhiza localities was prepared on the grounds of information collected from literature and data gathered during field works. Our research indicated that the habitats of majority of the studied taxa will decrease by 2080, except for D. incarnata var. incarnata, for which suitable habitats will increase almost two-fold in the global scale. Moreover, the potential habitats of some taxa are located outside their currently known geographical ranges, e.g. the Aleutian Islands, the western slopes of the Rocky Mountains, Newfoundland, southern Greenland and Iceland. ENM analysis did not confirm that the Balkans, central Europe or central Russia served as the most important refugia for individual representatives of the Dactylorhiza incarnata/maculata complex. Our study rather indicated that the Black Sea coast, southern Apennines and Corsica were the main areas characterized by habitats suitable for most of the taxa.
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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 | 0.000 | 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".