Relationships between grazing and waterfowl production in the Canadian prairies
Bibliographic record
Abstract
Abstract The survival of waterfowl nests is positively correlated with the amount of grassland on the landscape, and population growth rates of some waterfowl species (e.g., mallards [ Anas platyrhynchos ]) are sensitive to nest survival rates. Thus, the effect of actions that alter grassland vegetation physiognomy, such as grazing, on waterfowl production is of interest to waterfowl habitat managers. Additionally, grasslands contribute other ecological goods (e.g., forage for livestock and wildlife) and services (e.g., photosynthesis, carbon sequestration), which can be influenced by grazing practices. We address key uncertainties about the linkages between grazing, vegetation physiognomy, and the survival and density of duck nests at study‐site, field, and nest‐site spatial scales. Using data from 2,554 duck nests found in 434 grazed or idled fields (median field size = 48.0 ha) in the Canadian Prairie Pothole Region between 2002 and 2009, we found that vegetation physiognomy affected nest survival at both the field and nest‐site scales, such that nest survival increased with nest‐site vegetation density and late‐season field vegetation density. Nest survival also responded to early‐season within‐field variation in vegetation height in a quadratic manner, such that survival was greatest in fields with moderate variation in vegetation height. Nest survival was negatively related to the intensity of grazing and to the amount of cropland in the surrounding landscape. Both the abundance of wetlands and the average vegetation height in the field had a positive influence on nest density. Fields idled during the breeding season had greater densities of nests than fields grazed either early or late in the breeding season. Leaving lands idled may be the most effective way to increase both waterfowl nest survival and nest density. When management of upland vegetation is required, we recommend grazing at moderate stocking rates (between 2 and 2.5 animal unit months [AUM]/ha) after the waterfowl breeding season is complete and monitoring vegetative characteristics to ensure they remain suitable to attract nesting waterfowl (e.g., leaving vegetation height >28 cm). Where grazing must be carried out during the breeding season, low to moderate stocking rates should be encouraged as these rates appear to have the least negative impact on both waterfowl nest survival and nest density. These stocking rates also will maintain rangeland in good condition to the long‐term benefit of producers. © 2013 The Wildlife Society.
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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 | 0.000 |
| 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 | 0.000 |
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".