The ‘ecological character’ of wetlands: a foundational concept in the Ramsar Convention, yet still cause for debate 50 years later
Bibliographic record
Abstract
The Ramsar Convention text requires the Contracting Parties to respond to actual or potential changes in the ‘ecological character’ of their Ramsar Sites. After some years, the Convention’s obligations relating to the conservation of these sites and to the ‘wise use’ of wetlands in general came to be defined in terms of ‘maintaining’ this character. Defining and operationalising these concepts has been complex. This paper reviews the evolution of this, and the challenges that remain in relation to issues such as choosing an appropriate baseline condition to describe, the kinds of changes that warrant a response and situations of natural fluctuation or ‘regime shift’, where ‘maintaining’ ecological character may be an unduly static aim. The ‘character’ of wetlands nevertheless remains a valuably integrative concept, preserving something of the holistic vision developed 50 years ago by the Convention’s founders.
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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 | 0.015 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.029 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".