Gulf of Maine cod in 1861: historical analysis of fishery logbooks, with ecosystem implications
Bibliographic record
Abstract
Abstract Since 2000, virtually every major assessment of ocean policy has called for implementing an ecosystem approach to managing marine resources, yet crafting such an approach has proved difficult. Ecosystems today exhibit little of the abundance and complexity found in the past, and populations of over‐fished species have declined dramatically world‐wide, yet historical evidence has been difficult to assimilate into complex ecosystem models. Here, we look to the testimony of Gulf of Maine fishermen for insights on the abundance of Atlantic cod (Gadus morhua) and the environment that once supported such large numbers of them. Using logbook data from Frenchman’s Bay, Maine, and other New England communities at the time of the Civil War, we estimate cod landings in the Gulf of Maine in 1861, establish a population structure for cod at that time, and map the geographical distribution of fishing effort of a fleet that minimized risk and cut expenses by fishing inshore where cod and bait species were plentiful. Log entries list the pelagic and bottom‐dwelling invertebrate species these fishermen used for bait, when and how they acquired it, and what species they looked for in the water to signify the presence of cod. Ranked descriptions of both cod and bait abundance were found to be statistically significant indicators of cod catch. Frenchman’s Bay fishermen 140 years ago provided a minimum set of ecosystem requirements for abundant cod, conditions that may inform management plans aimed at restoring both the species and the Gulf of Maine marine ecosystem.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".