Effects of Water Depth, Cover and Food Resources on Habitat use of Marsh Birds and Waterfowl in Boreal Wetlands of Manitoba, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To evaluate water-level manipulations as a management tool in boreal wetlands, marsh bird and waterfowl habitat use were studied in the Saskatchewan River Delta, Manitoba, Canada, during 2008 and 2009. Call-response and aerial surveys were used to estimate densities of marsh birds and waterfowl, respectively, within six wetland basins undergoing two different water-level treatments. Generalized linear models were used to determine relationships between presence and densities of birds to water depth, vegetation characteristics, and relative forage fish and invertebrate abundances at two spatial scales. American Bittern (Botaurus lentiginosus) and Piedbilled Grebe (Podilymbus podiceps) densities were positively influenced by water depth and relative fish abundance. American Coots (Fulica americana) and diver waterfowl (Aythya, Bucephala) also responded positively to increased water depth, whereas dabbler waterfowl (Anas, Aix) were negatively influenced by increasing water depth. Densities of Sora (Porzana Carolina) and Virginia Rail (Rallus limicola) were positively correlated with the relative abundances of invertebrates, but negatively correlated with relative fish abundance. Due to the high avian biodiversity in the region, managers should focus on providing a variety of wetland habitats. Using a combination of partial water-level drawdowns and high water, habitat for numerous avian species can be created simultaneously within wetland complexes.
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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 | 0.000 | 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) | 0.000 | 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 it