The growing number of species of concern in the Salish Sea suggests ecosystem decay is outpacing recovery
Bibliographic record
Abstract
Species of concern are native species, sub-species or ecologically significant units that warrant special attention to ensure their conservation. The number of species of concern within the Salish Sea is used by the US Environmental Protection Agency and Environment Canada as a transboundary ecosystem indicator (called "Marine Species at Risk"). Within the Salish Sea, four jurisdictions assess which species require special efforts to ensure protection and survival of the population: the Province of British Columbia, the State of Washington, the Canadian Federal Government, and the United States Federal Government. As of December 1, 2015, there were 125 species at risk in the Salish Sea. Between 2002 (when the list was first compiled) and 2008, the number of listed species grew at an average annual rate of 1% from 60 to 64. It then made a precipitous jump to 113 listed species in 2011 (an average annual growth rate of 15% for 3 years) and has since continued to grow at an average annual rate of 2.6%. Some of the increase seen can be attributed to better understanding of the number of fish, reptile, bird and mammal species known to use the Salish Sea, however most additions represent new listings due to concern about population declines. The number of species of concern provides a crude indicator of ecosystem health, permits cross checking of species of concern between jurisdictions, suggests where more research is needed to assess species status or causes of decline, and highlights where transboundary approaches could benefit species recovery. Assuming listing efforts have been consistent, the increasing number of species of concern within the Salish Sea over the last 13 years suggests ecosystem recovery efforts are being outpaced by ecosystem decay.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".