The Potential Global Distribution of Tall Buttercup (<i>Ranunculus acris</i> ssp. <i>acris</i>): Opposing Effects of Irrigation and Climate Change
Bibliographic record
Abstract
Tall buttercup, a native of central and northern Europe, has become naturalized in the United States and Canada, and in South Africa, Tasmania and New Zealand. In Canada and New Zealand it has become an economically significant weed in cattle-grazed pastures. In this study we develop a CLIMEX model for tall buttercup and use it to project the weed's potential distribution under current and future climates and in the presence and absence of irrigation. There was close concordance between the model's projection of suitable climate and recorded observations of the species. The projection was highly sensitive to irrigation; the area of potentially suitable land globally increasing by 30% (from 34 to 45 million km 2 ) under current climate when a “top-up” irrigation regime (rainfall topped up 4 mm d −1 on irrigable land), was included in the model. Most of the area that becomes suitable under irrigation is located in central Asia and central North America. By contrast, climate change is projected to have the opposite effect; the potential global distribution diminishing by 18% (from 34 to 28 million km 2 ). This range contraction was the net result of a northward expansion in the northern limit for the species in Canada and the Russian Federation, and a relatively larger increase in the land area becoming unsuitable mainly in central Asia and south eastern United States.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".