Bibliographic record
Abstract
Temperate grasslands are the least protected ecosystem in the world. In North America, only < 4% of tallgrass prairie, 64% of mixed-grass prairie, and 66% of shortgrass prairie are intact. Historically, grazing played an important role in maintaining prairie landscapes through nutrient cycling and the diversification of vegetation structure and composition. Within grasslands, the plains bison (Bos bison) was the most numerous and influential grazer. However, by 1900 bison were reduced to ¡Ü 1,000 animals throughout North America. Today, bison are scattered throughout their historical range, numbering > 500,000 individuals. Recent questions have surfaced regarding the success of this effort, however, because < 21,000 plains bison are managed as conservation herds (n = 62) and 8% of those herds are managed on areas of > 2,000 km2. In addition, >100,000,000 cattle now graze rangelands in the U.S. and Canada leading to questions regarding the ecological significance of replacing bison with livestock. Our objectives were to increase knowledge regarding the ecological similarities between bison and cattle, and to determine how both species can be managed to mimic ecological patterns that approximate historical bison populations. We used behavioral observations, movement analyses, and Resource Selection Function (RSF) analyses too quantify similarities and differences between the bison and cattle in the Northern Great Plains. We observed a higher proportion of time spent grazing by cattle (45-49%) than bison (26-28%) and a greater amount of time spent at water. We used First-Passage-Time (FPT) analyses to compare the spatial scale of bison and cattle within pastures. We report selection of spatial scales by bison of 1.8 ¨C 9.0 x greater than currently provided. Lastly, RSF analysis identified important resources including selection of water resources by bison. These results have implications when bison are used to meet grazing restoration objectives because water resources may alter grazing regimes important for prairie obligate species (i.e. grassland birds). For livestock, the time spent at water and grazing encourages grazing practices that increase grazing rotation and movement across the landscape. These may include changes in timing and intensity of grazing, and adjustable mineral and water resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".