Renesting by Dusky Canada Geese on the Copper River Delta, Alaska
Bibliographic record
Abstract
The population of dusky Canada geese (Branta canadensis occidentalis; hereafter duskies) breeding on the Copper River Delta (CRD), Alaska, USA, has been in long-term decline, largely as a result of reduced productivity. Estimates of renesting rates by duskies may be useful for adjusting estimates of the size of the breeding population derived from aerial surveys and for understanding population dynamics. We used a marked population of dusky females to obtain estimates of renesting propensity and renesting interval on the CRD, 1999–2000. Continuation nests, replacement nests initiated without a break in the laying sequence, resulted only after first nests were destroyed in the laying stage with ≤4 eggs laid. Renesting propensity declined with nest age from 72% in mid-laying to 30% in early incubation. Between first nests and renests, mean interval was 11.9 ± 0.6 days, mean distance was 74.5 m (range 0–214 m), and clutch size declined 0.9 ± 0.4 eggs. We incorporated our renesting estimates and available estimates of other nesting parameters into an individual-based model to predict the proportion of first nests, continuation nests, and renests, and to examine female success on the CRD, 1997–2000. Our model predicted that 19–36% of nests each year were continuation nests and renests. Also, through 15 May (the approx. date of breeding ground surveys), 1.1–1.3 nests were initiated per female. Thus, the number of nests per female would have a significant, though relatively consistent, effect on adjusting the relation between numbers of nests found on ground surveys versus numbers of birds seen during aerial surveys. We also suggest a method that managers could use to predict nests per female using nest success of early nests. Our model predicted that relative to observed estimates of nest success, female success was 32–100% greater, due to replacement nests. Thus, although nest success remains low, production for duskies was higher than previously thought. For dusky Canada geese, managers need to consider both continuation nests and renests in designing surveys and in calculating adjustment factors for the expansion of aerial survey data using nest densities.
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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".