From Site to Sea: Protecting Habitat Through an Integrated Response to the Invasive European Green Crab Across the Salish Sea
Bibliographic record
Abstract
Biological invasions are known to impact important nearshore habitats. Though European green crab, Carcinus maenas, has been periodically abundant in coastal embayments of Washington State and Vancouver island since the late 1990’s, range expansion into the Salish Sea in recent years has the potential for more destructive impacts and dynamics. In the Salish Sea, green crab pose a threat to essential eelgrass beds, tidal marshes, and mudflats. Management of green crab occurs at a regional scale, but control actions to mitigate impacts and protect habitats take place at the local (site) level. It can be a challenge to integrate place-based specific management needs across geographic scales and political jurisdictions and create a regional management framework sufficiently agile to respond to on-the-ground changes at meaningful timescales. This session will draw from several locally-based response efforts to the unfolding invasion of green crab in Washington and British Columbia. Panelists will highlight how knowledge transfer and collaboration can develop across multiple scales of management and can shift over time to build regional response capacity among institutions. This can enable a robust and responsive regional strategy, rooted in effective communication and data sharing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".