Opinions of University of Ibadan Residents on Impacts of Birds’ Activities on Tree Shade Management on Campus
Bibliographic record
Abstract
Trees play a crucial role in ecosystems, providing oxygen, carbon sequestration, and habitats for wildlife, including birds. In urban environments like the University of Ibadan, trees enhance aesthetics, regulate microclimates, and support biodiversity. However, bird activities such as nesting and feeding can impact tree health and shade quality, raising ecological and management concerns. Therefore, the study aimed at investigating the perception of the residents in the University of Ibadan about the impacts of birds’ activities on tree shade management. Using a stratified random sampling approach, a structured questionnaire was distributed to 102 respondents, including students, staff, and residents. Data were analysed in SPSS using descriptive statistics and chi-square test. Findings reveal that tree shading is the most valued benefit (83.3%), followed by oxygen provision (72.5%), air quality improvement (69.6%), and environmental temperature reduction (67.6%). While birds are recognized for their ecological roles, concerns over defoliation, crop depredation, and noise pollution persist. The study underscores the multifaceted roles of trees, with shading benefits being the most recognized, while their ecological functions, such as providing habitats for birds, receive varying levels of awareness. There is a strong appreciation for the ecological and recreational benefits of birds in the University of Ibadan, but there are also moderate concerns and perceived drawbacks, particularly in terms of personal interest and potential nuisances.
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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".