Long-Term Productivity of Canvasbacks (Aythya Valisineria) in a Snowpack-Driven Desert Marsh
Bibliographic record
Abstract
Abstract Ruby Lake, Nevada, is a large palustrine wetland that hosts the southern-most major breeding population of Canvasbacks (Aythya valisineria). That arid marsh, fed by springs derived from mountain snowpack, differs in climate and hydrology from glaciated potholes of the northern prairies where most Canvasbacks breed. Fourteen years of nesting data on Canvasbacks over a 31 year period (1970–2000) were analyzed to determine factors affecting breeding performance at Ruby Lake and whether they differed from those in the prairies. Long-term Mayfield nest success at Ruby Lake (50% of all nests) was in the range of that in the northern prairies (21–65%). Of all Canvasback nests, 73% were parasitized (mostly by Redheads [Aythya americana]) as compared to 83–97% in a large Manitoba marsh and 57–65% in Manitoba potholes. However, as in the northern prairies, nest parasitism generally had little or no effect on either nest success or percentage of host eggs that hatched. In Manitoba potholes, nest success was unrelated to habitat variables measured; but successful nests at Ruby Lake were over shallower water, farther from shore, in wider bands of emergent vegetation, and surrounded by lower stem densities than unsuccessful nests. Water level is the key factor in breeding performance of Canvasbacks at both Ruby Lake and the northern prairies; however, the source of water differs (mountain snowpack at Ruby Lake, direct precipitation in the prairies) and effects of water-level variations are reversed. In small prairie potholes (mostly <0.4 ha) with many mammalian predators, productivity of Canvasbacks (which build floating nests) is increased by high water that floods the emergent fringe. At Ruby Lake, a very large marsh (2,830 ha) with mostly avian predators, Canvasback productivity is decreased by high water that floods interior emergent stands too deeply. Water level at Ruby Lake was highly correlated (multiple R2 = 0.91) with mountain snowpack up to three years earlier, emphasizing the strong effect of climatic variations on wetland birds in that arid region.
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How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".