Bibliographic record
Abstract
In the midst of several management failures, marine reserves are seen as a potential management tool to control overexploitation. In the literature, both modelling and empirical work have demonstrated that closing an area to fishing would lead to an increase in biomass and mean body size within the reserve. Benefits, in the form of increased catch, outside the reserves are sometimes shown using modelling, but the assessment of such benefits in nature is more difficult. Home range and migration rate of the targeted species are important factors to consider in the establishment of a reserve. A few cases convincingly point at the importance of the source of larvae and the direction and rate of dispersal. Reserves could also be used as a hedge against uncertainty and management mistakes by limiting fishing mortality. This study is intended to evaluate the possibility of using marine reserves to control fishing mortality for northern cod, a migrating fish. A simple dynamic pool model emphasized the importance of including stock recruitment relationship to properly assess reserves benefits. By protecting a part of the spawners, the system containing a reserve was more resilient than the control (no-reserve). However, these results were probably overly optimistic because the proportion of fish staying within the reserve was overestimated. An age- and spatially-structured model was then built to mimic the historical evolution of fishing and stock collapse of the northern cod, offshore Newfoundland. The model included four stocks, migrations, and range dynamics. Fishers were assumed to show hunting behaviour to various degree depending on the gear used. In the first version of the model had to increase catchability as cod biomass decreased. The second model used effort profiles based on documented qualitative and quantitative changes in fishing capacity and effort. In both cases, results showed that very large marine reserves (80%) by themselves could have hedge against mismanagement, while a 50% reserve would have only slowed the decrease of the cod population. The results also suggest that adding seasonal closures could help control fishing mortality although possible temporal effort displacement was not investigated. The principal benefits of seasonal closures would be to protect the spawning aggregations rather than controlling fishing mortality. Every management scenario that was efficient at controlling fishing mortality implied decreasing the catch before the stock started rebuilding. Marine reserves could be used as an additional management tool along with other measures limiting the range of action of the fishery. For example, banishment or severe restrictions on gears allowed in the fishery could limit the geographical range of the fishery and help control fishing mortality.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".