Report of Working Group 21 on Non-indigenous Aquatic Species
Bibliographic record
Abstract
Aquatic non-indigenous species (NIS) continue to threaten marine ecosystems, including seafood safety and security.To inform risk assessments predicting the likelihood and consequences of new invasions, it is critical to understand global NIS distributions, habitat tolerances/preferences, potential dispersal vectors and probable impacts related to new incursions.To this end, the NIS database developed by the North Pacific Marine Science Organization (PICES) Working Group on Non-Indigenous Aquatic Species (WG 21), with funding from the Ministry of Agriculture, Forestry and Fisheries (MAFF) of Japan through the Fisheries Agency of Japan, summarizes large-scale data which can be used by managers to develop monitoring programs for early detection or rapid response, and to make mitigation plans for higher-risk NIS to limit the impacts on native biodiversity, including commercially important species, and ecosystem structure and function.The Atlas of Non-indigenous Marine and Estuarine Species in the North Pacific, compiled through the activities of WG 21, synthesizes information from a variety of sources and can serve as a valuable resource for agencies and scientists tasked with managing and researching NIS in the North Pacific.Information included in the Atlas can help to identify and prioritize potential high-risk NIS and/or high-risk locations which can allow limited funding to be used effectively.The usefulness of the Atlas was illustrated most recently by the arrival of a large floating dock in Newport, Oregon, USA that had been set adrift by the 2011 Great East Japan Earthquake and tsunami -this document was consulted by experts to aid in the identification and ecological risk assessment of organisms attached to the dock.Another lasting outcome from activities of WG 21 has been increased awareness and collaboration on NIS issues broadly, especially between PICES member countries and with developing countries and international organizations like the Northwest Pacific Action Plan (NOWPAP) and the Intergovernmental Oceanographic Commission's Sub-Commission for the Western Pacific (WESTPAC), fostered through Rapid Assessment Surveys (RAS) and RAS demonstration workshops.Capacity building has better prepared researchers both within and beyond PICES to deal with emerging NIS issues and is critical to better understanding invasion dynamics and maintaining safe and productive marine ecosystems.Executive Summary viii PICES Scientific Report No. 48 Understanding Trends, Uncertainty and Responses of North Pacific Ecosystems) program and the North Pacific Ecosystem Status Report.Thus, at a minimum PICES should establish an expert group that can continue to exchange information on changing marine NIS dynamics via the WG 21 NIS database.A continued NIS expert group could explore how climate change will alter NIS distributions around the North Pacific, including probable changes in NIS vectors (e.g., new shipping routes, expanding trade).Further, a new expert group could address how PICES member countries have been affected by NIS and what community responses have occurred due to NIS incursions in the North Pacific, an element directly aligned with FUTURE.This information would help inform policy and management options within each PICES member country.WG 21 proposed several options for PICES' continued involvement in marine NIS issues, but the creation of an Advisory Panel on Aquatic Non-indigenous Species (AP-NIS) is the preferred option as it would allow continued progress on marine NIS issues, with the lowest resource commitment.This report summarizes the activities and accomplishments of WG 21 in fulfilment of its terms of reference, and recommends the establishment of an Advisory Panel on Non-indigenous Aquatic Species to continue work on NIS in the North Pacific.Section 1 Background
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.011 |
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".