Ten years of resident Canada goose damage management in a New Jersey tidal freshwater wetland
Bibliographic record
Abstract
ABSTRACT Intensive grazing by Atlantic Flyway Resident Population Canada geese ( Branta canadensis ) has been shown to dramatically reduce wild rice ( Zizania aquatica ) abundance in tidal freshwater marshes in the Mid‐Atlantic Region of the United States. From 2001 to 2010, I implemented an integrated damage management program (IDMP) during spring to abate Canada goose herbivory to wild rice in tidal freshwater marshes of the Maurice River, New Jersey, USA. The IDMP consisted of shooting, rendering goose nests unhatchable, and euthanizing molting geese. With implementation of an IDMP, the number of nests on the study area declined 70% over 10 years and the number of geese declined over time. Consequently, the amount of IDMP effort needed to sustain rice was reduced. Because the study area was a key nesting site for ospreys ( Pandion haliaetus ), which are state‐threatened species, there was concern that disturbance from IDMP activities could have a negative impact on osprey nesting or recruitment. The mean annual number of nesting ospreys doubled and the mean number of young fledged/nest was similar between years prior to and during implementation of the IDMP, suggesting that the IDMP did not have a negative impact on ospreys. Wetland managers should consider damage from excessive herbivory caused by non‐native, breeding waterfowl, such as resident Canada geese or mute swans ( Cygnus olor ), in their suite of wetland mitigation strategies. © 2013 The Wildlife Society.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".