One fly to rule them all—muscid flies are the key pollinators in the Arctic
Bibliographic record
Abstract
Global change is causing drastic changes in the pollinator communities of the Arctic. While arctic flowers are visited by a wide range of insects, flies in family Muscidae have been proposed as a pollinator group of particular importance. To understand the functional outcome of current changes in pollinator community composition, we examined the role of muscids in the pollination of a key plant species, the mountain avens (Dryas). We monitored the seed set of Dryas across 15 sites at Zackenberg, northeast Greenland, and used sticky flower mimics and DNA barcoding to describe the flower-visiting community at each site. To evaluate the consequences of shifts in pollinator phenology under climate change, we compared the flower visitors between the early and the late season. Our approach revealed a diverse community of insects visiting Dryas, including two-thirds of all insect species known from the area. Even against this diverse background, the abundance of muscid flies emerged as a key predictor for seed set in Dryas, whereas overall insect abundance and species richness had little or no effect. With muscid flies as the main drivers of the pollinating function in the High Arctic, a recently observed decline in their abundances offers cause for concern.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".