Great lakes double‐crested cormorant management affects co‐nester colony growth
Bibliographic record
Abstract
ABSTRACT The population of double‐crested cormorants (Phalacorocorax auritus; cormorants) in the North American Great Lakes has increased substantially since the 1970s, sparking economic, social, and biological concerns that have led to widespread management of the species within United States waters. Previous studies have quantified behavioral impacts of cormorants on other waterbird species that share breeding colony sites with cormorants. However, no study has yet examined how these impacts might scale to entire colonies, nor have potential effects of cormorant management on co‐nesters been examined. Our objective was to estimate effects of cormorant abundance and management on colony growth indices of 4 species that commonly co‐nest with cormorants in the North American Great Lakes; 3 of these species are conservation or stewardship priorities for the region. We estimated colony growth using the Great Lakes Colonial Waterbird Survey and comparable Canadian surveys, conducted between 1976 and 2010. We then applied linear mixed models to determine association of co‐nester colony growth indices with cormorant abundance and management presence and intensity while controlling for other factors that likely influenced growth rates. According to the fitted models, black‐crowned night‐heron (Nycticorax nycticorax) colony growth was negatively related to cormorant abundance and management, whereas great blue herons (Ardea herodias) had little response to cormorant abundance, and herring gulls (Larus argentatus) and ring‐billed gulls (Larus delawarensis) responded positively to cormorant abundance and management. These results suggest that cormorant management may not be as neutral to co‐nesters as is often assumed. Responsible management plans for cormorants should take into account the likely effects on co‐nesters present so that conservation and management goals for co‐nesters can also be met. © 2017 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 | 0.000 | 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".