Economic value of Greater Montreal's non‐market ecosystem services in a land use management and planning perspective
Bibliographic record
Abstract
Abstract The Greater Montreal (Quebec, Canada) area is currently re‐evaluating the future of its land use planning and development sector. One of the approaches being considered is the monetization of non‐market goods and services provided by biodiversity and ecosystems in this region. This is in the interest of providing decision makers and stakeholders a tool for quantification and comparison. Herein we analyzed land use cover in 2010 and applied benefit transfer using 103 monetary observations from 62 studies. The value measured for the 11 non‐market ecosystem services monetized for the Greater Montreal area reached $2.2 billion/year. More than three‐quarters of this total value is provided by the services of air quality regulation, recreation, and habitat for biodiversity. Ecosystems providing the highest non‐market values are urban forests, woodlands, and wetlands. We believe that the results of this ecosystem services value mapping could lead to better resource allocation and enable policy‐makers to design more effective land use policies in southern Quebec.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".