Agricultural mosaics offer nesting habitat to dabbling ducks in the arid Intermountain West of the United States
Bibliographic record
Abstract
Abstract The debate over the best agricultural practices for biological conservation often focuses on the degree to which agricultural lands should be interspersed with desirable habitat versus protecting lands entirely from production. It is important to understand the benefits agriculture provides for wildlife because it is consuming an increasing proportion of the landscape. We evaluated the nesting ecology of breeding ducks within a mosaic of flood‐irrigated conservation areas and agricultural lands in hay production. We assessed how habitat features at two spatial scales across these lands were related to nest site selection, nest density, and nest survival of multiple duck species. Birds selected nest sites with higher visual obstruction, a higher proportion of shrubs around the nest, and less bare ground, but we did not detect evidence of selection per se at larger spatial scales. Nest density was marginally higher along linear features, including irrigation ditches and riparian stretches, but nest survival remained similar across land‐use types and habitats features. This system is representative of many agricultural landscapes around the globe and highlights the ways agroecosystems can be managed to maintain habitat suitability for wildlife on working lands.
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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 | 0.000 |
| 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) | 0.001 | 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".