Increased use of mud bottom by juvenile American lobsters (<i>Homarus americanus</i>) in Maces Bay and Seal Cove, Bay of Fundy, after three decades of population increases and predator declines
Bibliographic record
Abstract
In the Bay of Fundy, American lobster ( Homarus americanus) abundance has soared since the early 1990s, and predators have declined, either of which could have caused juvenile lobster populations in preferred hard-bottom habitat to expand onto less-protective mud bottom. To investigate whether juvenile lobsters have increased use of mud bottom, we used scuba surveys (1989–2021) in Maces Bay and Seal Cove, in the Bay of Fundy. Whereas the 1990s surveys found no juveniles on mud at either site (though they were present on hard bottom), in subsequent decades, juveniles inhabited mud burrows at densities of 0.00039 m–2 to 0.0081 m–2. In Maces Bay, mud occupancy occurred after juvenile density increases on hard bottom, but evidence was mixed as to whether increased competition within hard-bottom habitat drove this change. Concurrent cod, haddock, hake, and wolffish declines suggest reduced predation also increased occupancy and survival on mud. Although it supports low juvenile densities, mud habitat may contribute to recruitment given its prevalence, particularly as warming seas allow lobster recruitment into cooler, deeper water over mud bottom.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".