Bibliographic record
Abstract
Long-term population and harvest data have shown that the continental population of lesser scaup (Aythya affinis) has been steadily declining, about 150,000 per year, over the past 20 years. Due to the temporal length of their population decline, scaup have received widespread attention by resource management agencies and private conservation groups throughout the U.S. and Canada. My objectives were to determine lesser scaup occupancy (use) on wetlands of various size and classification during the spring migration period in eastern South Dakota. I determined lesser scaup occupancy of wetlands of various size and classification with multiple surveys conducted during 30 March – 16 May, 2003 on 26 wetlands along a 28-mile-long (45 km) road transect in Brookings County, South Dakota, and from the analysis of long-term scaup and wetland data collected during 1987-2002 by the US Fish and Wildlife Service/HAPET staff in Bismarck, North Dakota. The total number of scaup counted during 11 roadside wetland surveys did not differ between morning (n = 16,800), midday (n = 16,150), and evening (n = 16,525) surveys (p = 0.99). The highest number of lesser scaup counted on road transect wetlands occurred during the week of 10 April. A total of 11,698 lesser scaup were counted on the 4-square mile (10.36-km2) plot surveys from 1987 to 2002. Highest counts of scaup occurred during 1995, 1996, and 1997. A total of 10,358 (89%) lesser scaup were counted during 1 May to 15 May surveys, of which 6,427 were males and 3,931 were females. A total of 1,340 (11%) lesser scaup were counted between 20 May to 5 June of which 899 were males and 441 were females. Over 7,000 scaup were counted in the Prairie Coteau while only 139 were counted within the Minnesota Red- River Lowland. Throughout the entire survey 827 ponds were surveyed, in which lesser scaup occurred on 221 (27%) of them. The sample of survey wetlands used by lesser scaup consisted of 8 (4%) temporary, 50 (23%) seasonal, 146 (66%) semipermanent and 17 (7%) permanent. Most lesser scaup (63%) were observed on semipermanent wetlands with an open water cover type. Forty-nine percent of the wetlands surveyed where scaup occurred were less than 2.02 hectares in size. However, 85% of the scaup were observed on wetlands ≥ 2.02 hectares. Of the 5,382 scaup observed in flocks, 75% occurred in flock sizes of ≤ 50. Seventy-one percent of the flocks observed had ≤ 10 birds within them. The information attained from the distribution of lesser scaup during migration in South Dakota will be used with data from other studies to determine what factors are contributing to the scaup population decline in North America.
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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 | 0.001 | 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".