Habitat associations of breeding mallards and Canada geese in southern Ontario, Canada
Bibliographic record
Abstract
ABSTRACT Understanding habitat associations of breeding mallards ( Anas platyrhynchos ) and Canada geese ( Branta canadensis maxima ) in the eastern US and Canada is important for conservation planning, yet studies at spatial scales useful to conservation planners have mostly occurred in the midcontinent prairie pothole region (PPR). Our broad objective was to determine whether breeding pairs were associated with similar habitat types in an eastern ecozone, the mixed woodland plain of southern Ontario, Canada, as they are in the PPR, despite substantial differences in relative habitat availability and land use practices. We used helicopter surveys and remote sensing to investigate habitat associations at landscape (25 km 2 ) and local (500 m wetland buffer [79 ha]) scales during the 2008 and 2009 breeding seasons. At both spatial scales, mallard indicated breeding pairs (IBP) were positively associated with the abundance or area of temporary open water and emergent (seasonal or semipermanent) wetland types, similar to the PPR. However, against expectations, we did not detect an effect of grassland area. Canada goose IBP were most strongly associated with total wetland abundance, and not specifically with emergent and permanent open‐water wetlands as expected. At the local scale, goose IBP presence was positively associated with riverine wetland area. Unlike the PPR, our study area contained a high proportion of forested and riverine wetlands; however, with the exception of the riverine wetland–Canada goose association noted above, we did not detect a disproportionate influence of these wetland types on mallards or geese. © 2015 The Wildlife Society.
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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 | 0.000 |
| Scholarly communication | 0.001 | 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".