Trends in bird counts 1978–2020 in a New Zealand Nothofagus forest with variable control of mammalian predators
Bibliographic record
Abstract
Many New Zealand native bird species are threatened by introduced mammalian predators, and pest management programs are common in the country. Despite that, measuring the efficacy of such programs is often limited by resources, and thus the long-term population status of many native birds is not well documented. Here, we examined long-term population trends of forest bird species and changes in the bird community structure at Craigieburn Forest Park, where there was intermittent control of stoats (Mustela erminea). We analyzed 10,938 5-min bird point counts covering the periods 1978–1982, 1999–2004, and 2019–2020 in an old-growth Nothofagus (southern beech) forest. We assessed trends over time in the counts of each bird species with season, elevation, and site as co-variables. We also tested for a relationship with variable seed crops of the mast-seeding canopy tree, N. solandri var. cliffortioides. Bellbird (Anthornis melanura) was the only native species showing a continuous increase over time. In the first 25 years of the study, stoat control was intermittent, and more native birds decreased than increased. In later years, stoat control was continuous, and more native species increased than decreased. Large Nothofagus seed crops were associated with significant increases in all six exotic bird species tested, but only one of nine native bird species. These findings suggest that long-term trends of bird populations are influenced by the interactions of species vulnerability to stoat predation and the consistency of pest control efforts. Unfortunately, ship rats (Rattus rattus), which were absent at Craigieburn before 2010, are now common and may pose a new threat to native birds. Our results show that systematic long-term bird and seedfall monitoring, including careful archiving of sampling information, is helpful to guide conservation of the remaining native birds of New Zealand.
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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 | 0.001 |
| 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) | 0.001 | 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".