Population trends of colonial waterbirds nesting in Hamilton Harbour in relation to changes in habitat and management
Bibliographic record
Abstract
Since 1975, the diversity and abundance of colonial waterbirds breeding in Hamilton Harbour have increased, making it an important nesting site on the Great Lakes. An adaptive management approach has been employed to control hyper-abundant species and guide conservation efforts for vulnerable species, with the goal of maintaining a diverse waterbird community. Four species exhibited increasing or stable population trends (1975–2013): Double-crested Cormorants (Phalacrocorax auritus; from 0 to 4747 nests); Black-crowned Night-Herons (Nycticorax nycticorax; ranged from 6 to 259 nests); Herring Gulls (Larus argentatus; from 0 to 244 nests); and Caspian Terns (Hydroprogne caspia; from 0 to 496 nests). Cormorants are currently above (2,500 nests), while Caspian Terns (400–600 nests), Night-Herons (100–200 nests) and Herring Gulls (200–300 nests) are within population targets set out in the Hamilton Harbour Remedial Action Plan. Despite conservation efforts, Common Terns (Sterna hirundo) declined from a peak of 1,028 nests (1990) to 333 nests (2013), although currently within the population target (300–600 nests). Ring-billed Gulls (L. delawarensis), through long-term management and habitat restrictions, were reduced from a peak of 39,621 nests (1990) to 11,133 nests (2013), but still exceed the target (<10,000 nests). Changes in the amount of available habitat have affected waterbird distributions: the loss of 42 ha (peak in 1999) of former nesting areas to development has been partially offset by the creation or securement of 1.9 ha of dedicated breeding habitat. Continued management, assessed and refined annually, is required to maintain species diversity in the area. Current management techniques focus on preventing Ring-billed Gulls from nesting on private lands and dedicated Tern nesting habitat, excluding Cormorants from nesting at specific sites, and reducing inter-specific competition with Night-Herons and Herring Gulls. Recommendations and considerations regarding future management and conservation efforts to reach Remedial Action Plan targets in the harbor are outlined.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".