Global macroecology of bird assemblages in urbanized and semi-natural ecosystems
Bibliographic record
Abstract
Aim Despite the increasing pace of urbanization, little is known about how this process affects biodiversity globally. We investigate macroecological patterns of bird assemblages in urbanized areas relative to semi-natural ecosystems. Location World-wide. Methods We use a database of quantitative bird surveys to compare key assemblage structure parameters for plots in urbanized and semi-natural ecosystems controlling for spatial autocorrelation and survey methodology. We use the term ‘urbanized’ instead of ‘urban’ ecosystems as many of the plots were not located in the centre of towns but in remnant habitat patches within conurbations. Results Some macroecological relationships were conserved in urbanized landscapes. Species–area, species–abundance and species–biomass relationships did not differ significantly between urbanized and non-urbanized environments. However, there were differences in the relationships between productivity and assemblage structure. In forests, species richness increased with productivity; in both forests and open habitats, the evenness of species abundances declined as productivity increased. Among urbanized plots, instead, both species richness and the evenness of species abundances were independent of variation in productivity. Main conclusions Remnant habitats within urbanized areas are subject to many ecological alterations, yet key macroecological patterns differ remarkably little in urbanized versus non-urbanized plots. Our results support the need for increased conservation activities in urbanized landscapes, particularly given the additional benefits of local experiences of biodiversity for the human population. With increasing urbanization world-wide, broad-scale efforts are needed to understand and manage the effects of this driver of change on biodiversity.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".