Guano Rain and Growing Pain: Co-Nesting Dynamics of Double-Crested Cormorants and Black-Crowned Night-Herons at Tommy Thompson Park
Bibliographic record
Abstract
This study investigates the co-nesting dynamics between double-crested cormorants (Nannopterum auritum) and black-crowned night-herons (Nycticorax nycticorax) in Tommy Thompson Park, Toronto, Canada, from 1992 to 2023. Linear mixed models with Bayesian inference were used to examine the impacts of cormorant abundance, nest density, management practices, and environmental factors on night-heron population growth. The strongest and only statistically significant relationship was a positive association between cormorant and night-heron growth indices. Results showed substantial uncertainty in the effects of most variables on night-heron growth indices, with wide credible intervals for nest densities, night-heron road proximity, and management activities. Nest densities of both species and proximity to roads had minimal effects on night-heron colony growth, with posterior means near zero. Management activities showed a slight positive but non-significant effect on night-herons. The study revealed that while cormorant population growth generally benefited night-herons, there was high uncertainty in parameter estimates, potentially due to small sample sizes and ecosystem complexity.
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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 | 0.000 |
| 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) | 0.001 | 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".