Bibliographic record
Abstract
ABSTRACT Through recent Decisions of the Convention on Biological Diversity (CBD), States have agreed to establish networks of Marine Protected Areas (MPAs), and that representativity is a necessary feature of the networks. There is extensive literature on the intent of these commitments and scientific guidance on network design. The guidance specifies that to have representativity captured in a network requires that a suitable biogeographical classification exists and that areas which ‘represent’ the biogeographical subdivisions are included. However, no operational guidance has been provided on how to determine that a subdivision is adequately ‘represented’ by a protected area. This paper looks at the management and conservation functions expected to be served by representative MPAs, including an ‘insurance policy’ function, a ‘benchmark’ or natural control function, and a ‘seed stock’ function. The scales at which marine ecological processes typically operate are reviewed, as a basis for determining the scales of MPAs needed to provide these functions. It is concluded that representative MPAs at the spatial scales of the interactions of key top predators and forage fish generally should ensure spatial scales large enough to give protection to the other processes as well. To ensure the key functions are served, the representative MPAs also should have sufficient protection that human pressures do not alter the characteristics of these ecological processes. Copyright © Her Majesty the Queen in Right of Canada 2011. Reproduced with the permission of the Minister of the Department of Fisheries and Oceans
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".