The role of vacant lots in promoting avian species diversity and occupancy in a post-industrial city
Bibliographic record
Abstract
• Vacant land was associated with higher bird diversity in Detroit, while roads were associated with lower bird species diversity. • The occurrence of birds with specific habitat requirements was higher in areas with more vacant land in Detroit. • Other urban features, including roads, have an impact on the occurrence of birds in Detroit. • Vacant land management and rehabilitation should consider biodiversity and promotion of social justice, and also the role of surrounding roads. In deindustrialized cities, human population decline and building demolitions have created large quantities of vacant land. Land vacancy is a complex social issue but may create habitat that supports wildlife. We explored the relationship between vacant land and other features of the urban landscape and bird diversity and occupancy in Detroit, Michigan. Acoustic recordings were collected annually in June at 110 sites across 11 Detroit neighbourhoods from 2021 to 2024. At each site we manually scanned 28 min of the morning chorus on two days to identify bird species. We compared resulting metrics of species diversity and occupancy with annual spatial data on neighbourhood characteristics including vacancy, vegetation, buildings, and roads measured in 50 m and 100 m buffers around each recording site. Using a mixed-effects modelling approach, we found higher bird species diversity and richness at recording sites surrounded by greater proportions of vacant land (Shannon diversity, β vacantlots100m = 0.08, 95 % CI [0.04, 0.12]; bird species richness, IRR vacantlots100m = 1.08, 95 % CI [1.04, 1.12]). Using a spatial occupancy modelling approach, we found vacant land was associated with higher occurrence of four bird species. However, other urban features, especially roads, were also associated with bird species diversity and occupancy. Our results suggest vacant land can support higher bird diversity and occupancy in Detroit neighbourhoods, while road infrastructure, buildings, and vegetation also play a role. These findings have implications for land management in Detroit and other deindustrialized cities, where there is increasing pressure to determine how vacant land can be used to achieve positive ecological and social outcomes.
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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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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".