Fire and dwarf mistletoe (Viscaceae: <i>Arceuthobium</i> species) in western North America: contrasting <i>Arceuthobium tsugense</i> and <i>Arceuthobium americanum</i>
Bibliographic record
Abstract
Dwarf mistletoes (Viscaceae: Arceuthobium spp.) and fire interact in important ways in the coniferous forests of western North America. Fire directly affects dwarf mistletoes by killing the host, host branch, or heating/smoking the aerial shoots and fruits. Fire is a primary determinant of dwarf mistletoe distribution on the landscape, and time since fire controls many aspects of dwarf mistletoe epidemiology. Conversely, dwarf mistletoes can influence fire by causing changes in forest composition, structure, and fuels. Prescribed fire is important for management of dwarf mistletoes, while fire suppression is thought to have increased dwarf mistletoe abundance in western forests. Two dwarf mistletoes are compared in order to illustrate fire interactions in Oregon and Washington, USA: Arceuthobium americanum Nutt. ex Engelm. (lodgepole pine dwarf mistletoe) and Arceuthobium tsugense (Rosendahl)(western hemlock dwarf mistletoe). Arceuthobium persists on the landscape where the host is not killed by fire. Arceuthobium americanum spreads directly into the regenerating Pinus contorta Dougl. ex Loud., while A. tsugense persists in refugia for 200 years or more following fire. Host successional status is a driver of fire – dwarf mistletoe interactions, but forest disturbance agents also play a role. Given the importance of these interactions to the ecology of fire-prone forests, dwarf mistletoes warrant inclusion in disturbance ecology research.
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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 | 0.000 | 0.000 |
| 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".