Community composition and pollination network structure in a fire managed Canadian tall grass prairie.
Bibliographic record
Abstract
Pollination networks summarize interactions between plants and pollinators, providing insight into ecosystem stability. An unplanned fire provided the opportunity to assess network structure following disturbance in the Tall Grass Prairie Preserve in southern Manitoba. I established transects in sites burned <1 year, 5-6 years, or 10+ years ago. I assessed species richness, diversity, abundance, and phenology of insects and flowering plants. I created interaction matrices by recording plant-insect interactions, and sampled pollen loads from insects. Network structure was assessed by connectance, nestedness, and interaction strength. Flowers were more abundant and bloomed two weeks earlier in newly burned sites in 2010. Bees showed responses to fire based on nesting habitat, however visits by syrphids were related to precipitation. Network structure showed that tall grass prairie pollination networks were resilient to disturbance and variable environmental conditions, and management of prairie by fire did not negatively impact plant-pollinator interactions within the community overall.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".