Data and code from: Farm management and landscape context shape plant diversity at wetland edges in the prairie pothole region of Canada.
Bibliographic record
Abstract
<b>Abstract from associated paper (</b><b>Farm management and landscape context shape plant diversity at wetland edges in the prairie pothole region of Canada, Ecological Applications in press).</b>Evaluating the impacts of farming systems on biodiversity is increasingly important given the need to stem biodiversity loss, decrease fossil fuel dependency, and maintain ecosystem services benefiting farmers. We recorded woody and herbaceous plant species diversity, composition, and abundance in 43 wetland‐adjacent prairie remnants beside crop fields managed using conventional, minimum tillage, organic, or perennial cover (wildlife-friendly) land management in the Prairie Pothole Region. We used a hierarchical framework to estimate diversity at regional and local scales (gamma, alpha), and how these are related through species turnover (beta diversity). We tested the expectation that gamma richness/evenness and beta diversity of all plants would be higher in remnants adjacent to perennial cover and organic fields than in conventional and minimum tillage fields. We expected the same findings for plants providing ecosystem services (bee‐pollinated species) and disservices (introduced species). We predicted similar relative effects of land management on alpha diversity, but with the expectation that the benefits of organic farming would decrease with increasing grassland in surrounding landscapes. Gamma richness and evenness of all plants were highest for perennial cover, followed by minimum tillage, organic, and conventional sites. Bee‐pollinated species followed a similar pattern for richness, but for evenness organic farming came second, after perennial cover sites, followed by minimum tillage and conventional. For introduced species, organic sites had the highest gamma richness and evenness. Grassland amount moderated the effect of land management type on all plants and bee‐pollinated plant richness, but not as expected. The richness of organic sites increased with the amount of grassland in the surrounding landscape. Conversely, for conventional sites, richness increased as the amount of grassland in the landscape declined. Our results are consistent with the expectation that adopting wildlife‐friendly land management practices can benefit biodiversity at regional and local scales, in particular the use of perennial cover to benefit plant diversity at regional scales. At more local extents, organic farming increased plant richness, but only when sufficient grassland was available in the surrounding landscape; organic farms also had the highest beta diversity for all plants and bee‐pollinated plants. Maintaining native cover in agroecosystems, in addition to low‐intensity farming practices, could sustain plant biodiversity and facilitate important ecosystem services.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".