On tropical mistletoes: tractable models for evolutionary ecology, ecosystem function, and phytochemistry
Bibliographic record
Abstract
In 2001, I synthesised published information on mistletoe–animal interactions, demonstrating the pervasive influence these hemiparasites have on community composition and proposing that mistletoes represent keystone resources. Although the review was global in scope, I noted “Tropical regions, in particular, are underrepresented in the mistletoe literature, and it is unclear if mistletoe is as important in structuring these highly diverse ecosystems as in less diverse temperate areas”. Since then, research on tropical mistletoes has burgeoned, as a growing number of researchers use these forest and woodland hemiparasites to address a wide range of ecological and evolutionary questions. In this commentary, I highlight some recent findings, revisit and refine some emergent inferences, and suggest that tropical mistletoes offer many opportunities for further research, representing tractable models to address many unanswered questions in the life sciences. As well as reinforcing the role of mistletoes as facilitators for plant communities and keystone resources for animal assemblages, research on mistletoe pollination, seed dispersal, and host-range, challenge the established views about the ecological maintenance and evolutionary trajectory of specialization.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".