Data from: More milkweed in farmlands containing small, annual crop fields and many hedgerows
Bibliographic record
Abstract
See Martin et al. (2021, Agriculture, Ecosystems and Environment 319: 107567, https://doi.org/10.1016/j.agee.2021.107567) for full description of methods. Abstract: Milkweed has declined substantially, with over 80% declines in some agricultural regions. This threatens monarch butterfly (Danaus plexippus) persistence, because monarch larvae feed solely on milkweed. Thus conservation actions are needed to enhance the availability of milkweed, particularly in agricultural landscapes. Conservation actions to date have largely focused on reducing intensive agricultural practices, mainly use of herbicides. However, research suggests that landscape-scale alteration of the cropped portion of an agricultural landscape (the "farmland"), for example, to reduce crop field sizes, can benefit herbaceous plants such as milkweed. Here we collected data on milkweed occurrence and cover in agricultural landscapes in Ontario, Canada, capturing variability in milkweed from field edge to interior by sampling in the interior and along the edges of 68 crop fields. We used these data to evaluate the relative effects of farming practices within the sampled field (e.g. herbicide, fertilizer use) on milkweed versus the effects of mean field size, crop diversity, hedgerow cover, and the proportion of farmland in annual crops in the surrounding landscape. Additionally, we evaluated the effects of these variables on the cover of other herbaceous plants, to identify which—if any—could benefit milkweed without increasing overall weed cover. We found more milkweed at sites surrounded by landscapes with smaller crop fields, lower crop diversity, and higher cover of annual crops. Milkweed was more likely to occur at sites surrounded by landscapes with more hedgerows. These landscape-scale effects on milkweed were often larger than those of within-field farming practices. Importantly, we found that most variables had opposite effects on milkweed relative to other plants. Thus, altering the landscape to benefit milkweed does not imply an increase in weed cover.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.037 | 0.009 |
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".