Top-down control of lobster in the Gulf of Maine: insights from local ecological knowledge and research surveys
Bibliographic record
Abstract
American lobster Homarus americanus landings in the Gulf of Maine have been steadily increasing since the 1980s. As a result, lobsters now support one of the most important fisheries in the USA and Canada. One hypothesis for this pattern is that lobsters have been released from predation as groundfish stocks declined, expanding both in abundance and habitat. Lobster habitat is typically rocky substrate of the inshore region, which is difficult to sample. Some long-term fisheries-independent abundance indices for lobsters and their predators are available for the Gulf of Maine in the USA, but not in Canada. To try and fill those research gaps, we designed a local ecological knowledge (LEK) survey. Semi-structured interviews of 42 fishermen in southwest Nova Scotia, Canada, revealed consistent trends of the depletion of large groundfish, particularly Atlantic cod Gadus morhua. Eighty-three percent of fishermen concluded this depletion was the main reason for an observed increase in lobster abundance. They also reported the expansion of lobsters to new habitats and depths. We further show that the proposed top-down control mechanism is independently supported by USA research trawl surveys, which revealed a negative correlation (p < 0.05) between the summed abundance indices of 5 groundfish predators of lobster and lobster abundance (kg tow -1 ) at time lags ranging from 0 to 9 yr. Survey-based diet data also corroborated direct observations by fishermen on lobster predation by groundfish. These results suggest that LEK may be a useful supplementary tool to investigate the ecosystem effects of fishing, particularly in data-poor situations.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".