Interim Report of the Working Group on Introductions and Transfers of Marine Organisms (WGITMO). 7–9 March 2018, Madeira, Portugal
Bibliographic record
Abstract
The 44th meeting of the Working Group on Introductions and Transfers of Marine Organisms (WGITMO) was held in Caniçal, Madeira, Portugal, 7–9 March 2018. This meeting included a joint day with the Working Group on Ballast Water and Other Ship Vectors (WGBOSV). The meeting was hosted by João Canning-Clode (Portugal) and chaired by Cynthia McKenzie (Canada). The meeting was attended by 34 scientists, from 21 countries; six additional scientists participated in person, and five participated by webconference on the joint meeting day with WGBOSV. The objective of the meeting was to communicate new information and discuss several aspects of the introductions and transfers of marine organisms relevant to the six terms of reference for the working group. There was a particular focus in 2017 on ToRs a (detection and surveillance methods) and c (biofouling). This interim report for year two of the current cycle provides a summary of the 19 Na-tional Reports (reports attached in Annex 4), the 19 presentations provided by members and chair invited members in support of term of reference objectives (abstracts provided in Annex 5), discussions, achievements, limitations and recommendations. All Terms of Reference were discussed with this report structured so that each Term of Reference is dealt with in sequential order. The National Reports provide an overview of the priori-ties, findings, meetings and publications for each country. They also provide discussion points for methodologies, collaborations and knowledge gaps that need to be addressed by the group (ToR a) with discussions on potential new ToRs to be considered in 2019. In addition to national reports, two special sessions were held on: 1) Molecular tools for detection and monitoring (within ToR a); and 2) Marine invasive species screening tools (ToRs a&b - impact). The AquaNIS database continues to be updated (Appendix 6 for 2017 summary) and includes additional interactive tools. WGITMO considered two ToRs jointly with the Working Group on Ballast Water and Other Ship Vectors (WGBOSV): Examining biofouling as vector for the introduction and transfer of aquatic organisms on small boats and large ships; and Examining the effect of climate change on the establishment of aquatic species in the Arctic. The Groups ad-dressed a request for information on ship-mediated introductions of harmful algal bloom species in the Arctic from the Working Group on Harmful Algal Bloom Dynamics (WGHABD), and produced the preparatory document for an ICES VIEWPOINT on Eval-uating and Mitigating Introduction of Marine Non-native Species via Vessel Fouling. The ICES viewpoint was developed as a result of the theme session for the 2017 ICES ASC on bioinvasion trajectories and impacts in contrasting marine environments, orga-nized by WGITMO as a collaboration between ICES-PICES-CIESM. One of the recom-mendations from that session was to “prioritize investigation on one the most important non-native species transfer pathway – hull fouling and niche areas, both on commercial ships and recreational vessels, and through this contribute to IMO request for scientific information on use and effectiveness of IMO Biofouling guidelines globally”(Appendix 5 ASC Session report).\n
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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.112 | 0.060 |
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".