Flower‐visitor communities of an arcto‐alpine plant—Global patterns in species richness, phylogenetic diversity and ecological functioning
Bibliographic record
Abstract
Pollination is an ecosystem function of global importance. Yet, who visits the flower of specific plants, how the composition of these visitors varies in space and time and how such variation translates into pollination services are hard to establish. The use of DNA barcodes allows us to address ecological patterns involving thousands of taxa that are difficult to identify. To clarify the regional variation in the visitor community of a widespread flower resource, we compared the composition of the arthropod community visiting species in the genus Dryas (mountain avens, family Rosaceae), throughout Arctic and high-alpine areas. At each of 15 sites, we sampled Dryas visitors with 100 sticky flower mimics and identified specimens to Barcode Index Numbers (BINs) using a partial sequence of the mitochondrial COI gene. As a measure of ecosystem functioning, we quantified variation in the seed set of Dryas. To test for an association between phylogenetic and functional diversity, we characterized the structure of local visitor communities with both taxonomic and phylogenetic descriptors. In total, we detected 1,360 different BINs, dominated by Diptera and Hymenoptera. The richness of visitors at each site appeared to be driven by local temperature and precipitation. Phylogeographic structure seemed reflective of geological history and mirrored trans-Arctic patterns detected in plants. Seed set success varied widely among sites, with little variation attributable to pollinator species richness. This pattern suggests idiosyncratic associations, with function dominated by few and potentially different taxa at each site. Taken together, our findings illustrate the role of post-glacial history in the assembly of flower-visitor communities in the Arctic and offer insights for understanding how diversity translates into ecosystem functioning.
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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".