Effects of predator activity on the nesting of American Black Ducks and other birds on barrier islands in the mid-Atlantic coast
Bibliographic record
Abstract
Landscape change throughout North America has resulted in heightened nest predator population and declining avian productivity. Essential to establishing effective management design is an understanding of differential predation pressure among avian groups as group specific responses to predation impact may exist. The objective of this study was to examine the efficacy of predator trapping on the nest success and density of ground nesting avifauna in 2004-2005 in the Virginia Coast Reserve, specifically dabbling ducks, Canada Goose and Willet. Second, we determine the impact of predation on ground nesting birds by relating indices of predator abundance to nest density and nest success for island plots. Overall Mayfield nest success for dabbling ducks was 54.4% (n = 12) in 2004 and 17.7% (n = 30) in 2005. Green Transformed nest success for dabbling ducks was 34.5% (n = 25) in 2004 and 23.0% (n = 42). For Canada goose, overall Mayfield nest success was 53.1 (n = 37) in 2004 and 47.7% (n = 39) in 2005. Overall Green Transformed nest success for Canada Goose was 59.5% (n = 57) in 2004 and 50.6% (n = 51) in 2005. Finally, overall Green Transformed nest success for Willet was 53.7% (n = 110) in 2004 and 46.0% (n = 118) in 2005. Nest success estimates on island plots varied greatly. There was no difference in nest success between trapped and non-trapped islands for dabbling ducks (P = 0.1990), Canada Goose (P = 0.4860), Willet (P = 0.4920) and artificial nest success (P = 0.4200). Likewise, there was no difference in nest density between trapped and non-trapped islands for dabbling ducks (P = 0.2408), Canada Goose (P = 0.2950), and Willet (P = 0.1381). Several factors may explain this result including a lack of trapping efficacy, design flaws, low intensity of trapping, and differences in island habitat affecting avian nest site selection and sample size. Nest success for both dabbling ducks (P = 0.0225) and Willets (P < 0.0001) was inversely related to predator activity, as measured by artificial nest success. In contrast, Canada Goose (P = 0.6686) showed no relationship between nest success and predator activity. For Canada Goose (P = 0.0064) and Willet (P = 0.0029), nest density decreased with increasing predator activity on island plots. Biased nest detection, philopatry to islands with reduced predation risk, and active selection for reduced predator environments may explain the higher nest density on islands with
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 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".