Waterfowl Nesting in Fall‐Seeded and Spring‐Seeded Cropland in Saskatchewan
Bibliographic record
Abstract
Abstract: Waterfowl nesting in annual croplands has remained a little‐known aspect of waterfowl nesting ecology because of the inability of many studies to systematically search this habitat through the nesting season. Where searches have been conducted, they are generally restricted to the period prior to seeding, and many nests found are destroyed by the seeding operation. Consequently, fall‐seeded crops have been promoted as an alternative cropping practice that could increase nest survival of waterfowl nesting in croplands. During 1996–1999, we conducted 3–4 complete nest searches on 4,274 ha of cropland, including spring‐seeded wheat and barley, winter wheat, and fall rye in southern Saskatchewan, Canada. Using suites of predictive models, we tested hypotheses regarding relative nest abundance and nest survival among crop types and tested the influence of several landscape‐scale covariates on these metrics. Apparent nest densities were higher in fall‐seeded crops (winter wheat: 0.39 nests/ha, fall rye: 0.25 nests/ha) than in spring‐seeded crops (0.03 nests/ha), and nest density in spring‐seeded croplands increased with percent cropland and percent wetland habitat in the surrounding landscape. Nest survival was higher in winter wheat (38%) than in either fall rye (18%) or spring‐seeded crops (12%), and nest survival in spring‐seeded crops increased with relative nest initiation date. Nest survival was unaffected by surrounding landscape characteristics but tended to be higher in years of average wetness. Based on our findings, winter wheat and fall rye have the potential to provide productive nesting habitat for ≥7 species of upland nesting ducks and fall‐seeded crops are a conservation tool well suited to highly cropped landscapes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".