Top-down vs. bottom-up drivers of recruitment in a key marine invertebrate: investigating early life stages of snow crab
Bibliographic record
Abstract
Abstract Many snow crab fisheries have fluctuated widely over time in a quasi-cyclic way due to highly variable recruitment. The causes of this variability are still debated. Bottom-up processes related to climate variability may strongly affect growth and survival during early life, whereas top-down predator effects may be a major source of juvenile mortality. Moreover, intrinsic density-dependent processes, which have received much less attention, are hypothetically responsible for the cycles in recruitment. This study explored how climate, larval production, intercohort cannibalism and groundfish predation may have affected recruitment of early juvenile snow crab in the northwest Gulf of St Lawrence (eastern Canada) over a period of 23 years. Abundance of early juvenile snow crabs (2.5–22.9 mm in carapace width), representing the first 3 years of benthic life, came from an annual trawl survey and was used to determine cohort strength. Analyses revealed a cyclic pattern in abundance of 0+ crabs that may arise from cohort resonant effects. This pattern consisted of three recruitment pulses but was reduced to two pulses by age 2+, while the interannual variability of cohort strength was dampened. This reconfiguration of the earliest recruitment pattern was dictated primarily by bottom water temperature and cannibalism, which progressively overruled the pre-settlement factors of larval production and surface water temperature that best explained abundance of 0+ crabs. The results strongly suggest that bottom-up and density-dependent processes prevail over top-down control in setting the long-term trends and higher-frequency oscillations of snow crab early recruitment patterns.
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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 | 0.000 | 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".