Vancouver’s Batscape : Enhancing Urban Habitats for Our Winged Neighbours
Bibliographic record
Abstract
While bats provide numerous ecosystem services, urban populations of bats in Vancouver are increasingly threatened by habitat destruction, land fragmentation, and a lack of vegetation and prey to support their needs. Despite this, very little attention has been paid towards bridging existing ecological knowledge on bats towards local conservation policy. To better support the rich biodiversity of bats in Vancouver, this project was proposed by the City of Vancouver and CityStudio to identify bat-friendly vegetation and landscape features, and to assess the current bat habitat suitability of parks in the City of Vancouver. To accomplish these objectives, a literature review and expert interviews were first conducted to synthesize previous research and local knowledge. Subsequently, a geospatial multi-criteria evaluation was done to evaluate parks for bat habitat suitability. This was then ground truthed during site visits at select parks and supplemented by a statistical analysis of the restoration potential of parks for bat habitat suitability. As a result, 65 species of plants were identified to support bats in Vancouver, and 247 parks were ranked by bat habitat suitability and restoration potential. The highest scoring parks were generally large parks with established forests and stable freshwater bodies. Similarly, the parks with highest improvement potential were near other parks with water bodies and contained intermediate vegetational diversity. Deliverables for this project include this report, a bat-friendly landscape design guide pamphlet, and an interactive map of Vancouver’s parks by bat habitat suitability. This work can be used to guide policymakers at the City of Vancouver in strategically restoring public spaces for local bat species, building a more resilient ‘batscape’ for our critically important winged neighbours.
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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 | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".