Red-legged Honeycreepers Breeding success with this beautiful South American species can be achieved!
Bibliographic record
Abstract
I am sure many foreign softbill enthusiasts have dreamed of breeding Red-legged Honeycreepers (Cyanerpes cyaneus). I certainly did, as they were the first pair of softbills I owned way back in 1962! The male has a nuptial (breeding) and an eclipse (non-breeding) plumage, where virtually all the turquoise cap, blue, and black plumage changes to resemble the female. In order to breed them, the male must be in full color, and they are more likely to achieve breeding success in a planted aviary or flight, either indoors or outdoors during the summer months. They must also have access to a dry, heated indoor shelter during inclement winter months, especially in some European countries and states in the USA and Canada. In 1934, Mrs. K. Drake achieved the first UK breeding of Red-legged Honeycreepers. A breeding account was published in the Avicultural Society magazine in that year. While breeding success is not often recorded, they have been bred in Europe as well as the USA and South Africa. REMARKABLE BREEDING SUCCESS IN SOUTH AFRICA Fred Barnicoat, one of South Africa's most prominent aviculturists, has fulfilled that dream of breeding Red-legged Honeycreepers. Most of us would be happy with breeding them once, but Fred recorded a phenomenal success in rearing three nests of youngsters from the same pair. How did he realise this remarkable achievement? He accomplished this feat through diligence and perseverance, combined with total dedication and devotion to his birds and their welfare. Fred lives in Johannesburg, some 5600 feet (1800 metres) above sea-level. The winter nights can be freezing, but the dry sunny days quickly remove any frost - a completely different environment to that inhabited by Red-legged Honeycreepers in South America. While photographing and studying birds on a rainforest project in Colombia in 1991, I saw Red-legged Honeycreepers feeding in humid rainforest, at a height of only 330 feet (1800 metres) above sea level. Fred purchased his breeding pair in 1989. He spent a number of years moving them around from aviary to aviary, in the hopes that they would eventually settle down and breed. He tried various types of home-made nectars, supplied different fruits, persevered with live food, created planted aviaries, and experimented with nest sites - until finally, early in 1995, he accomplished the first breeding of his Red-legged Honeycreepers in a totally unexpected manner.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".