Nature calls: Is there an ecological basis for abnormal behaviour and breeding problems in captive psittacines?
Bibliographic record
Abstract
Psittaciformes are popular as pets, and as aviculture species. However, in captivity they show variation among species in susceptibility to problems such as stereotypic behaviours and poor breeding. For example, self-inflicted feather-damaging behaviour (e.g., self-plucking) is prevalent in African grey parrots, Psittacus erithacus, but rare in Senegal parrots, Poicephalus senegalus; while monk parakeets, Myiopsitta monachus, breed readily, yet blue-throated macaws, Ara glaucogularis, do not. Comparing species using phylogenetic comparative methods could help provide insights into the fundamental bases of such problems; thereby identifying species pre-disposed to be good pets and inform species’ ex situ conservation management. This study therefore investigated relationships between various species-typical biological traits proposed to affect parrot welfare and three welfare-sensitive captive outcomes: feather damaging behaviour (FDB), other stereotypic behaviours (SB), and hatch rate (HR). Prevalences of FDB and other SBs were gleaned via a survey of pet parrot owners, yielding information on 53 species (~1,380 birds). Captive HRs (chicks hatched/breeding pair/p.a.) for 122 species were taken from Allen and Johnson (1990 Psittacine Captive Breeding Survey). Next, phylogenetic generalised least squares regressions were used to examine the predictive power of the following aspects of species-typical biology: sociality (maximum group size, communal roosting); foraging effort; ecological flexibility (diet and habitat breadth); intelligence (innovation rate, relative brain volume); and IUCN conservation status. Communal roosting (T4, 33=1.87, P=0.04, λ = 0.54 [one-tailed]) predicted FDB, while higher foraging effort (T3, 34=-0.10, P=0.06, λ=0.65 [one-tailed]) tended to predict FDB. Relatively large brain size predicted other SBs (whole body: T3, 36=2.90, P=0.01, λ=0.27; oral: T2, 38=2.36, P=0.02, λ=0). More threatened species had lower captive HR (T5, 75=-2.12, P=0.02, λ=0.34 [one-tailed]). These traits can thus be considered species-level risk factors for poor parrot welfare, and provide an evidence-based platform to inspire ways of tackling these specific problems.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".