Bird declines over 22 years in forest remnants in southeastern Australia: Evidence of faunal relaxation?
Bibliographic record
Abstract
Declines in Australia's forest avifauna are largely attributed to loss of native vegetation. Many studies have examined patches of remnant vegetation, but few have considered changes over many years. In our study, bird data were collected 22 years apart (survey period A (SPA), 1980–1983; survey period B (SPB), 2002–2005) in 20 forest remnants in a rural landscape in southeastern Australia. Initial modelling (SPA) predicted a decline of nine species per patch in the 100 years following fragmentation. Our data showed that average species richness declined by nine species per patch in just 22 years between SPA and SPB, perhaps representing an example of faunal relaxation. Observer variation, changes in climate, changes in land use, and interspecific competition from an aggressive edge-adapted native bird (the noisy miner, Manorina melanocephala (Latham, 1802)) did not appear to be the main drivers of this decline. However, noisy miners were strongly associated with high turnover of forest species where they occurred above a threshold of six birds per count. Revisiting sites after an interval of many years has shed new light on the dynamics of a fragmented ecosystem, and indicates that further bird declines are likely as a result of past habitat loss.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".