Density and success of upland duck nests in native‐ and tame‐seeded conservation fields
Bibliographic record
Abstract
ABSTRACT The Conservation Reserve Program (CRP) generates substantial benefits to continental duck populations by providing grassland nesting habitat in rested cropland. Seeding mixes of CRP grasslands vary among numerous conservation practices, but one contrast of interest in the Prairie Pothole Region is the use of introduced, or “tame” versus native grass. Although the benefits of CRP to duck populations are well‐known, relative values of these planting practices to nesting ducks have received little attention. Understanding differences in benefits to ducks due to planting practices would aid in prioritizing and selecting management practices for CRP and other restoration activities. We evaluated nest survival and density of ducks nesting in tame‐ and native‐seeded CRP fields in 36 study areas in the Prairie Pothole Region of North Dakota and South Dakota, USA, during 2002–2003. We searched for duck nests in 209 fields totaling 5,386 ha and found 2,941 nests. We found no support for differences in nest survival for any upland‐nesting duck species between fields seeded to tame versus native grass based on a design and analyses that accounted for spatial and temporal variation. Additionally, nest densities, adjusted for nest survival rates, of all duck species were similar between tame‐seeded and native‐seeded fields. We conclude that benefits to nesting ducks from native‐grass seeding practices of CRP were similar to those of tame‐grass seeding practices. Although there may be other reasons to plant native seed mixes when establishing CRP tracts (e.g., native pollinators or insects, other wildlife species, etc.), our study suggests that duck nesting density and nest survival are not among those reasons. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
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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 | 0.000 |
| 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) | 0.001 | 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".