Historical knowledge, richness and relative representativeness of the avifauna of the largest native urban rainforest in the world
Bibliographic record
Abstract
Stretching for more than 10,000 ha in the Metropolitan Area of São Paulo, southeastern Brazil, Serra da Cantareira comprises the largest native urban rainforest in the World, harboring a rich and diverse Atlantic Forest avifauna. Despite its closeness to major urban areas, few bird surveys have been conducted there. In this article we present an updated compilation of all bird species recorded for Serra da Cantareira, including personal records from the authors. A total of 326 species have been recorded for Serra da Cantareira since 1901; of these, nine have not been sighted there for the last two decades. The number of bird species endemic to the Atlantic Forest is high (80), and seven of its species are globally threatened. According to multivariate analyses the species diversity at Serra da Cantareira is similar to other regions of the Atlantic Forest, such as Carlos Botelho and Intervales state parks, where the vegetation is also ombrophilous dense forest. We discuss local changes in the avifaunal composition over the last decades and suggest the incorporation of large forest remnants to the Cantareira State Park to mitigate the impact of the northern section of Rodoanel Mário Covas, a highway (SP-21) that will soon be operational and will negatively impact the biodiversity of Serra da Cantareira.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".