Urban avifauna diversity in Stellenbosch, South Africa, during the COVID-19 lockdown and observations of inner-city foraging behaviour
Bibliographic record
Abstract
In times of isolation or confinement, making regular natural history observations can not only represent a source of enjoyment, but generates insights into local avian ecology. Here we present an account of the urban bird diversity of Stellenbosch, South Africa, derived from daily observations of species presence collected during the initial two stages of the country’s nationwide COVID-19 lockdown period (66 days). A total of 38 bird species were observed during this time, including sightings of urban hunting behavior for birds of prey and greenspace foraging in general. The most commonly seen taxa were typical human-commensal species, including sparrows and doves. Many species were encountered far less frequently, with 21 of the 38 species being observed on less than 10 days. This was most notable for birds of prey (n = 6 species from Accipitriformes and Falconiformes) or African swifts (n = 2 species from Apodiformes), which were recorded only a few times for any given species. Our account provides some relatively niche information regarding the presence of birds from a single city block in South Africa and notes interesting observations of urban foraging behaviour, but also underscores the value of birdwatching during times of uncertainty.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".