Aquatic ecosystems across boundaries: Significance of international agreements and cooperation
Bibliographic record
Abstract
Historically, international environmental agreements on shared transboundary waters have dealt with exploitation of natural resources like oil, minerals, forests, fisheries, shipping and trade. Presently the focus is on environmental issues relevant to conservation, restoration, protection, sustainability over-fishing, pollution, invasive species and climate change. Global assessment indicates a lack of international agreements between multiple users. A brief review of major conventions and agreements is offered with emphasis on the Great Lakes Water Quality Agreement on the North American Great Lakes and the European Water Framework Directive, since they appear to be ecologically sound and predominantly ecosystem-based. This article exemplifies the history behind these agreements with examples of environmental threats and consequences (eutrophication, pollution, invasive species and loss of biodiversity). It is concluded that such ecosystem-based agreements are essential for all large aquatic ecosystems shared by multiple users or countries for holistic and integrated management of aquatic resources.
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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".