Nesting ecology of waterbirds at Grays Lake, Idaho
Bibliographic record
Abstract
Montane wetlands provide valuable habitat for nesting waterfowl and other waterbirds in the western United States, but relatively little information is available about the nesting ecology of their waterbird communities. We describe the general nesting ecology of breeding waterbirds at a large, shallow, montane wetland in southeastern Idaho during 1997–2000. Habitats include upland grasslands and intermittently to semipermanently flooded wetland habitats. We located a total of 1207 nests of 23 bird species: Eared Grebe (Podiceps nigricollis), Canada Goose (Branta canadensis), Mallard (Anas platyrhynchos), Gadwall (A. strepera), American Wigeon (A. americana), Green-winged Teal (A. crecca), Blue-winged Teal (A. discors), Cinnamon Teal (A. cyanoptera), Northern Shoveler (A. clypeata), Northern Pintail (A. acuta), Redhead (Aythya americana), Canvasback (A. valisineria), Lesser Scaup (A. affinis), Ruddy Duck (Oxyura jamaicensis), Northern Harrier (Circus cyaneus), American Coot (Fulica americana), Virginia Rail (Rallus limicola), Greater Sandhill Crane (Grus canadensis tabida), American Avocet (Recurvirostra americana), Long-billed Curlew (Numenius americanus), Wilson's Snipe (Gallinago delicata), Wilson's Phalarope (Phalaropus tricolor), and Short-eared Owl (Asio flammeus). Most nests were initiated in May–early June and were terminated (hatched or destroyed) by the 3rd week of June. Mean daily survival rate (DSR) for Canada Goose nests was 0.954 ± 0.005 (sx̄; n = 127 nests), equivalent to Mayfield nest success of 21%. Mean DSR for dabbling duck nests over all 4 years was 0.938 ± 0.006 (n = 41), equivalent to Mayfield nest success of 11%. For all other species where we found >10 nests each year (Eared Grebe, Redhead, Canvasback, Coot, Sandhill Crane, American Avocet, and Wilson's Snipe), >50% of nests found hatched at least 1 young. Success rates for geese, cranes, and ducks were lower than reported for Grays Lake during 1949–1951 and lower than most other wetlands in the region.
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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 | 0.001 | 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".