Factors Influencing Mottled Duck Nest Success on the Atchafalaya River Delta
Bibliographic record
Abstract
The Atchafalaya River Delta system along with the Wax Lake Outlet Delta and the Mississippi River Delta are the only three areas in Louisiana where land is being gained. Beneficial use of dredge spoil from shipping channel maintenance is used on the Atchafalaya River Delta to supplement natural accretion. These dredge spoil islands have the ability to provide valuable nesting habitat for a variety of waterbirds, including Mottled Ducks. Previous studies on these islands reported mammalian predation to be a significant cause of nest failure for Mottled Ducks. I tested the hypothesis that predator reduction through trapping would increase Mottled Duck nesting success. I selected six islands based on vegetative conditions optimal for nesting vegetation and separated them into three trapped and three control islands. I found mammalian depredation of Mottled Duck nests to be rare and was not successful in detecting or trapping any predators. Instead, I found that flooding, which had been a minor issue in a previous study, to be the major cause of nest failure during the 2012 and 2013 nesting seasons. I found that Mottled Ducks strongly preferred nesting on islands that were isolated from the main delta complex. I used LIDAR elevation data as well as NOAA and pressure transducer data logger water level data to evaluate the relationship between nest elevation and nest success. I found no apparent relationship between nest elevation and nest success. Mayfield nest success for Mottled Duck nests was 20.5% in 2012 and 11.5% in 2013 with 34.5% of nests destroyed by flooding. Further research into the effects of flood duration, frequency, and incubation stage at flooding as well as considering partial loss of clutches may show a clearer relationship between nest success and the effects of flooding
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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) | 0.007 | 0.004 |
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; both teacher heads agree on what is shown here.
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".