Effect of land development and tree protection strategies on urban forest structure and composition in Surrey, British Columbia
Bibliographic record
Abstract
Land development is a significant source of urban tree canopy decline despite requirements to protect and replant trees after project completion. Using remote sensing data, as well as public records, we studied tree retention and protection choices during land development in Surrey B.C. between 2009 and 2017. We found that canopy sharply declined during development but rebounded slightly in following years. Forested lands experienced the most pronounced canopy loss, while agricultural lands had few trees to begin with. Additionally, post-development urban forests were more diverse, but had more non-native species. Previously forested lands offered the most opportunity for protecting large, culturally significant trees. However, current policy focuses on individual trees, resulting in missed opportunities for conservation, including conservation of soils on agricultural land. In addition, we highlight the role tree protection zone shape and size contributes to potential success of tree preservation especially on previously forested land. Land use affected the size and shape of protection zones, which can affect tree survival. Larger tree protection zones and those with a rounded shape reduced the edge effect, likely resulting in less stress on retained trees. These were common on forested lands, but tree protection zones often deviated from a round shape, exposing protected trees to greater stress from root severance and light exposure. Overall, our analysis revealed land development had a homogenizing effect on urban forest composition and structure reducing resilience to future disturbances. Post-development urban forests had greater species diversity, greater fragmentation, and more small stature trees. Furthermore, our findings suggest legislation may contribute to this homogenization, by limiting the scope of resources assessed for preservation. Finally, we suggest that holistic site assessments that occur before building footprints are finalized will likely lead to more sustainable development practices.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".