Urbanization as a driver of taxonomic, functional, and phylogenetic diversity losses in bird communities
Bibliographic record
Abstract
Urbanization is one of the most important threats to biodiversity worldwide, as it drives declines in species diversity, functional diversity, and phylogenetic diversity and increases functional redundancy among species. We estimated taxonomic, functional, and phylogenetic diversities, as well as the abundance of several functional groups, in bird communities from a town in east-central Argentina in 1985–1986 and 30 years after (2015–2016). In 1985–1986, we found that taxonomic diversity (abundance, species richness, and alpha diversity), functional richness, and basal phylogenetic diversity were negatively related to building cover, whereas terminal phylogenetic diversity showed a positive relationship with building cover. Moreover, the abundance of specialized functional groups (ground, aerial, and foliage insectivores; nectarivores/insectivores; ground/canopy and ground granivores) decreased with increased building cover, whereas the reverse pattern for the abundance of generalists (medium-sized/large and small omnivores) was found. In 2015–2016, by contrast, taxonomic, functional, and phylogenetic diversities were not related to building cover. Our results not only support the hypothesis that urbanization affects the potential number of ecosystem functions, but also that this relationship may change through time. Given the accelerated rate of urbanization worldwide, an integrative approach between different facets of biodiversity is promoted to gain insight into the response of bird communities in urban environments.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".