Nature’s Value in the Salish Sea: the Ecosystem Services of the Salish Sea Basin
Bibliographic record
Abstract
The aquatic and terrestrial ecosystems of the Salish Sea basin provide vital fish and wildlife habitat, serve as a foundation for food production, employment, and outdoor recreation, improve water and air quality, and reduce natural disaster risks, such as flooding. This year, Earth Economics conducted a geospatial Ecosystem Services Valuation (ESV) of the nonmarket value provided by ecosystems throughout the basin, updating and expanding on Earth Economics 2010 report, “Valuing the Puget Sound Basin,” which estimated the value provided by the US portion of the basin—cited in the Seattle Times as recently as 2019. The availability of transnational 30m spatial data from the 2015 North American Land Change Monitoring System (NALCMS) allows an expansion of the earlier analysis to the entire basin. By contextualizing ecosystems by factors known to affect the productivity and value of ecosystem services (e.g., old growth, riparian zones, proximity to urban areas and agricultural lands, shellfish harvesting) nuances in the subsequent valuation literature can be more fully addressed. Benefit Transfer was used to estimate the value of ecosystem services provided each year by each landcover type. Each year, the Salish Sea Basin provides US$91 billion to US$153 billion in benefits, with the lands and waters within the U.S. providing an average of US$60 billion per year, and the Canadian side of the basin providing an average of US$56 billion per year. The purpose of this work was to promote better understanding of the economic and social benefits provided by the basin’s ecosystems, and to inform both domestic and foreign policies regarding cooperative management of ecologically important lands. The presentation will include demonstration of a dynamic web map that will be publicly available following the presentation.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".