Urban tree diversity fosters bird insectivory despite a loss in bird diversity with urbanization
Bibliographic record
Abstract
• Urbanization reduces insectivorous bird specific richness and functional diversity. • Tree diversity within city increases bird insectivory. • Modeling intra-urban heterogeneity is essential to understand trophic interactions. Urbanization is one of the main drivers of biotic homogenization in bird communities worldwide. Yet, only a few studies have addressed its functional consequences on the top-down control birds exert on insect herbivores. We hypothesized that their inconsistent results reflect the overlooked heterogeneity of the urban habitat for birds, and in particular the distribution and diversity of urban trees. We monitored tree diversity, bird diversity, avian predation attempts on artificial prey, and the effect of bird exclusion on insect herbivory in 97 trees distributed among 24 urban experimental plots in the city of Montreal, Canada. We characterized urbanization levels through a combination of variables related to tree density, impervious surfaces, anthropic noise, and human population density. Bird diversity decreased with increasing urbanization, whereas the frequency of generalist synurbic species increased. We found no significant relationship between predation and urbanization or between predation and bird diversity. However, tree diversity was positively correlated with predation attempts on artificial prey, irrespective of bird diversity. We revealed a mismatch between the effects of urbanization on bird diversity and on the regulation service and unraveled the functional importance of tree diversity in shaping the avian predation function in urban ecosystems. Our study advocates for the consideration of intra-urban heterogeneity in the investigation of trophic cascades within cities.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".