Insect Herbivory on the Plant Rhinanthus minor over its Elevational Range in the Canadian Rockies
Bibliographic record
Abstract
All species of plants and animals occur over a finite area of the Earth’s surface. This is referred to as the species range, and many species ranges have shifted or are predicted to shift with climate change. Scientific models have predicted how these shifts are expected to change and what proportion of the implicated species will go extinct in the process. Most models assume that climatic variables such as temperature and rainfall are solely responsible for these range shifts. However, we know that the success of a species is strongly influenced by both their positive and negative interactions with other species, such as competition, mutualism, predation and herbivory. But how these biotic factors affect species ranges is poorly understood. I am using a field experiment on a species in its native habitat to better understand these interactions. My study took place in the Canadian Rocky Mountains on populations of the plant Yellow Rattle (Rhinanthus minor). I studied two transects, each with plant populations at low, mid and high elevations. Insect herbivory on plant populations was observed, as well as manipulated, via a pesticide treatment to reduce insect herbivory, and a clipping treatment to simulate natural insect herbivory. Understanding herbivory and herbivore-plant interactions over an elevational gradient may help give us a clearer idea of the complex relationship between the climatic and biotic factors that affect plant species ranges.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".