The conservation of Black-crowned Night-herons at Tommy Thompson Park
Bibliographic record
Abstract
Environmental planning involves making decisions about the natural environment, working landscapes, and public health to create an improved environment. This paper explores how planning can be used to create different options for a healthier environment for wildlife. Black-crowned night-herons (Nycticorax nycticorax; night-herons) will be used as an example, to discuss the relation between environmental planning and wildlife conservation. Night-herons are the most abundant and widespread heron in the world, and one of the largest North American colonies nest at Tommy Thompson Park, in Toronto, Canada. The aim of this paper was to analyze the night-heron population in Ontario and assess whether the trend in colony size at Tommy Thompson Park is doing better or worse than others in the eastern North America (east of Lake Michigan). An analysis of a ten-year night-heron nest success at Tommy Thompson Park, showed repeated and wide-spread nest failures, likely and primarily due to raccoon predation; and a substantial decline in nest numbers over time. Nest counts from one other area in New York also showed declines; and the species has been listed in many jurisdictions. The colony at Tommy Thompson Park was one of the largest, yet now is relatively small. I recommend that the park managers need to consider predator control to ensure the night-heron population at Tommy Thompson Park is maintained.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".